Yinxue Shi

Minghao Yang

Ruizhi Sun

Goal-driven Workflow Generation based on AI planning

Keywords: goal-driven, pattern oriented, HTN planning, workflow generation

The success of an enterprise heavily depends on its ability to respond to changes in its environment in an effective and dynamic way. To cope with emerging business trends, automatic workflow generation provides a significant competitive advantage .This paper presents a goal-driven workflow generation, which is pattern-oriented and knowledge-based. First, a process pattern is proposed as a vehicle for knowledge representation. Then, a heuristic intelligent planning algorithm is deployed to construct a workflow automatically according to the goal specified by the users and the business context.

Introduction

Process-driven workflow systems are used to configure and control structured business processes from which well-defined workflow models and instances can be derived [START_REF] Joeris | Defining flexible workflow execution behaviors[END_REF][START_REF] Vander Aalst | Case handling: A new paradigm for business process support[END_REF]. Because all information needed in the execution stage is specified, this method is also called full-ahead plan [START_REF] Yong | Pattern-Oriented Workflow Generation and Optimization[END_REF]. However, since most business environments are complicated and changeable, it is difficult for users to know all the details for defining the process specification. And the process definitions often need to be modified during execution for the unexpected and developmental change in the business processes being modeled and the deviations from the prescribed process model at runtime [START_REF] Rinderle | Correctness criteria for dynamic changes in workflow systems: A survey[END_REF].

Obviously, the traditional "full-ahead" [START_REF] Shaohua | A Pattern-Oriented Planning Approach for Grid Workflow Generation[END_REF][START_REF] Shaohua | Knowledge Modeling and Optimization in Pattern-Oriented Workflow Generation[END_REF] workflow scheduling can't meet the complex and flexible enterprise. Automating the workflow generation process as much as possible is the main point. Ideally, the user just need to specify what they want the workflow to achieve (instead of how to achieve it) and what the constraint is. The workflow management system should then be able to generate an appropriate workflow and execute it successfully.

Presently, some research has focused on the workflow system that integrates AI planning techniques for automatic workflow construction or workflow generation. This method applying AI planning to dynamic workflow creation sacrifices the advanced features: Firstly, high availability is possible by enabling users to represent the workflows at an abstract level without needing to worry about the particulars of the target execution systems. Secondly, robustness is possible by generating a replaceable process when exception occurs. Because when the failure happens, realtime planning will find a new resolution to deal with the exception. But high scalability is required for the present planning algorithms usually limit to a specific application domain. Pegasus [START_REF] Joeris | Defining flexible workflow execution behaviors[END_REF][START_REF] Kee | Pegasus on the Virtual Grid: A Case Study of Workflow Planning over Captive Resources[END_REF] is a typical example which uses AI planning to workflow system in Grid environment.

Our work is different from the current practices in two aspects: the first is that a new workflow modeling method based on a pattern is proposed to specify a goaldriven workflow correctly. The second is that we adopt the heuristic evaluation algorithm and pattern-oriented HTN planning algorithm to knowledge representation and workflow planning, which enables the use of domain heuristics in problem solving and automatic workflow composition thus speeding up the planning process and improving the planner's performance. And it will lead a more effective way of exception handling and workflow simulation.

2

Goal-Driven Workflow Usually, process-driven workflow functions well in a small-scale, centralized, homogeneous environment.

Goal-Driven Workflow

Goal-Driven Workflow is a more flexible workflow, where the boundary between workflow build-time and run-time is eliminated. Instead of defining a workflow process in advance, users just specify a goal and then workflow management system (WFMS) will, with or without users' intervention, decompose it into some sub-tasks according to the resources and knowledge possessed and fulfill the coordination and scheduling function necessary to achieve the specified goal. The decomposition procedure can be executed several times on the fly, making it possible to tolerate and/or adapt to the changes and exceptions encountered during the execution time [START_REF] Jinlei | Workflow Management in Grid Era: From Process-Driven Paradigm to a Goal-Driven One[END_REF].

Goal-Driven is more applicable in large-scale, distributed and heterogeneous environment. The users don't need to know the detail of process. They just need to describe what to be achieved.

Process-Driven Workflow vs. Goal-Driven Workflow

Table1 shows the differences between Process-Driven workflow and Goal-Driven workflow. Goal-Driven workflow has more advantages in real applications.

Goal-Driven Workflow Generation

Process Pattern

Patterns originally come from architectural domain to describe a problem which occurs over and over again in our environment, and then describes the workflow solutions to that problem, in such a way that you can use this solution a million times over [START_REF] Alexander | A Pattern Language[END_REF].

Similarly, Process Pattern refers to the experiences and knowledge within business domain. It comprises three parts----Goal, Context and Solution which described as a triad:

Process Pattern = <Goal, Context, Solution> (1)
Goal describes the target of business, whose properties include id, name and domain. Context describes the condition, whose properties include relevant data, positive factors and negative factors. Solution gives the guideline or solution to reach the business goal. For the same goal, different context or scenario leads to different solutions. And each goal can be decomposed into several sub-goals .In the same way, sub-goal has its appropriate process pattern. When modeling, the business process will be divided into a serious of process segments which can be represented with process pattern. All of these patterns are saved as knowledge. Once the user input the goal, workflow generation process starts. Then AI planner constructs a planning tree composed with patterns which are selected through goal matching and pattern matching. Continually, all of these tree nodes are arranged into a whole process definition according to the connection between patterns. Finally, the Execution Engine maps the identified process steps to the physical services and coordinates their execution.

AI planning

HTN Planning

In HTN planning a planning problem is represented by sets of tasks (task networks). Methods decompose non-primitive tasks into sub-tasks until a level of primitive tasks is reached, which can be solved by operators [START_REF] Kutluhan | UMCP: A Sound and Complete Procedure for Hierarchical Task-Network Planning[END_REF]. HTN planning decomposes highlevel tasks into simpler ones until eventually all tasks have been decomposed into actions. This feature makes HTN planning a promising means to realize Goal-Driven workflow generation. Because the Goal-driven workflow generation is based on process pattern, which can describe knowledge at different levels of abstraction resolved to various levels of detail.

As illustrated in the last section, Goal-Driven workflow generation allow userdefined process segments which named Process Pattern, and then use AI planner automatically to search appropriate patterns and auto-assembly to form the segments to a complete solution for the goal. A Heuristic intelligent planning algorithm is deployed to complete automatic workflow generation.

Heuristic Intelligent Planning Algorithm

Once user input the Goal and Context information from the human computer interface, heuristic intelligent planning module starts. The system finds the best solutions through goal matching, context matching and pattern matching. And then automatically assemble the process fragments into a complete workflow process. Fig. 3 shows the flow chart of the intelligent planning algorithm.

Fig. 3. Heuristic Intelligent Planning Algorithm

As shown in Fig. 3, HTN planning algorithm is described as follows:

Step 1: Input a planning problem G

Step 2: If G contains only primitive tasks, then return the result

Step 3: Choose a goal task g in G in depth-first search traversal method

Step 4: Choose an expansion for g, using the heuristic evaluation algorithm

Step 5: Replace g with the expansion Go to step 2 HTN planning decomposes tasks until a plan consists only of primitive tasks. Expanding each non-primitive task (step 3-5) is done by choosing an appropriate reduction, which specifies one possible way of accomplishing that task. Reductions are stored as solutions or process, which associate non-primitive tasks or goals with task networks. In step 3, we have adopted a depth-first traversal method to expand the nodes to form a final complete solution. The algorithm is sound because a heuristic evaluation algorithm is used in the step 4.

The heuristic evaluation algorithm is an artificial neural network algorithm optimized by genetic algorithm.

Artificial Neural Networks (ANNs) are computational tools that have found extensive utilization in solving many complex real-world problems.

The attractiveness of ANNs comes from their remarkable information processing characteristics pertinent mainly to nonlinearity, high parallelism, fault and noise tolerance, and learning and generalization capabilities [START_REF] Basheer | Artificial neural networks: fundamentals, computing, design, and application[END_REF].

Artificial Neural Network algorithm is a kind of human brain simulation of the physical structure. That is to say, it uses computer methods to simulate the human brain from physical structure to make the system intelligent. Among the ANN models, multi-layer feed-forward neural network model is the most widely used model and often be trained by use of back-propagation learning algorithm (BP algorithm for short) . BP algorithm has the advantage of simple and plastic, but the BP algorithm is gradient-based method, which slow the convergence rate, and often affected by the local minima problem. Genetic Algorithm can get out of this predicament.

The following is the description of the heuristic evaluation algorithm:

Step1

Remarks and Related Works

Heuristic Intelligent Planning we proposed in this paper is based on application-level knowledge .It can be extended to solve the general business problems. Since a Goal has many solutions, it is very important to choose the best one. Heuristic evaluation algorithm helps the user to choose an optimal implementation. Heuristic evaluation algorithm based on Genetic algorithm is a machine learning algorithm. It capture the experience gained during process planning and execution so as to enrich pattern library. And it can reduce the costs of business knowledge. Pegasus [START_REF] Deelman | Pegasus: a Framework for Mapping Complex Scientific Workflows onto Distributed Systems[END_REF][START_REF] Kee | Pegasus on the Virtual Grid: A Case Study of Workflow Planning over Captive Resources[END_REF] uses heuristic to search for an effective operator of the semiordered set in order to convert the current state to the target state. However, its planner and knowledge used for planning are tightly bound to a specific application domain. In our work, explicit knowledge representation (process patterns) is deployed to make workflow planner domain-independent.

The optimization method for process pattern proposed by Zhang Shaohua is based on the artificial neural network. As mentioned above, slow convergence and local minimum is a problem. We use the artificial neural network algorithm optimized by genetic algorithm to get out of this trouble.

Conclusion

Compared with process-driven workflow, goal-driven workflow generation based not on proprietary process definition frameworks, but on accepted ideas of how people actually work. And because the AI planning techniques had been integrated with workflow construction, goal-driven workflow generation enhanced the flexibility and adaptability of workflow system. In this paper, a new workflow modeling method based on the process pattern is proposed to specify a goal-driven workflow correctly. This approach simplifies the logic and verification of the standard model, since process pattern is easier to understand and less complex to build. To avoid the users' intervention, a heuristic intelligent planning algorithm based on AI planning and genetic algorithm is deployed in this paper to generate workflow automatically. It provided a lightweight, efficient and cost-effective way to introduce knowledge into workflow composition.

Our future work will concentrate on the following topics. The first one is to investigate algorithms to refine the undetermined elements during execution. The second one is to investigate re-planning algorithm and trace back method to handle the exception .The last one is to perfect machine learning algorithm to capture the experience gained during process planning and execution so as to enrich domain knowledge.

Fig. 1 .Fig. 2 .

 12 Fig. 1. Process Pattern in XML

2.1 Process-Driven Workflow

	Process-Driven Workflow largely takes the decision-making responsibility for the
	flow of documents, information and tasks out of the hands of the user, leaving it to an
	automated business process rules engine [4].
	Process-Driven Workflow is a pre-defined workflow .Where the user should
	* Understand and control the processes in detail.
	* Identify the metrics and objectives for the key processes.
	* Model and automate key business processes.
	* Identify the participants who are involved in the process.
	* Innovate continuously to keep pace with business change.

Table 1 .

 1 Process-Driven Workflow vs. Goal-Driven Workflow.

		Process-Driven Workflow	Goal-Driven workflow
	style	full-ahead workflow	automatic construction, dynamic
	application	special application domain	domain independent
	definition	user based(understand the detail)	knowledge based
	robustness	low	high
	cost	low cost, multiple invest	single invest, knowledge maintenance

  : Use Genetic Algorithm to train Artificial Neural Network weights with reasonable cases set up by experts and spread the signal Step 2: end the training if errors meet the condition and jump to Step6 Step3: the training error back-propagation Step4: modify network weights based on the results of the error back-propagation and jump to Step 2 Step5: save the network weight and put it into use In step1, the Genetic Algorithm was used to train ANN weights.

	The procedure
	includes:
	Step 1: randomly generate initial population
	Step 2: access and sort the initial population
	Step 3: cross-operating
	Step 4: assess and sort population pairs
	Step5: choose the best stocks of the NUM as a new parent population form Father
	and Son
	Step 6: carry out mutation operation
	Step 7: end if meet the training requirements and save the best results, otherwise,
	jump to Step 3


Sylvain Schwartz

Gilles Feugnet

Evguenii Lariontsev

Jean-Paul Pocholle

Oscillation regimes of a solid-state ring laser with active beat note stabilization : from a chaotic device to a ring laser gyroscope

Keywords: numbers: 42.65.Sf, 42.62.Eh, 06.30.Gv, 42.55.Rz

We report experimental and theoretical study of a rotating diode-pumped Nd-YAG ring laser with active beat note stabilization. Our experimental setup is described in the usual Maxwell-Bloch formalism. We analytically derive a stability condition and some frequency response characteristics for the solid-state ring laser gyroscope, illustrating the important role of mode coupling effects on the dynamics of such a device. Experimental data are presented and compared with the theory on the basis of realistic laser parameters, showing a very good agreement. Our results illustrate the duality between the very rich non linear dynamics of the diode-pumped solid-state ring laser (including chaotic behavior) and the possibility to obtain a very stable beat note, resulting in a potentially new kind of rotation sensor.

INTRODUCTION

Interest in ring lasers developed almost simultaneously with the invention of laser itself [START_REF] Rosenthal | [END_REF]2,3,4,5]. Intensive work on this device has been motivated both by fundamental aspects (especially in the field of non linear dynamics, phase transitions, instabilities and chaos [6,7,8,9,10,11,12,13,14,15]) and by practical applications (amongst which are the ring laser gyroscope [16,[START_REF] Aronowitz | Laser applications[END_REF][START_REF] Chow | [END_REF] and the single-frequency unidirectional ring laser [19,20,21]). The recent achievement of active beat note stabilization in a diode-pumped Nd-YAG ring laser [22] revived interest for homogeneously broadened (e.g. solid-state) ring lasers, although this kind of device had already been extensively studied (see for example [23,24,25,26]). In particular, the experiment described in [22] provides both a simple tool for the study of mode coupling in a resonant macroscopic quantum device such as a toroidal superfluid [27], and a potentially new kind of ring laser gyroscope involving only standard optical components and no gaseous medium.

It is well known in the field of homogeneously broadened ring lasers (see references above) that the dynamics of these devices is mainly ruled by two sources of coupling between the counterpropagating fields, one being due to the backscattering of light by the cold cavity elements and the other being due to the spatially non uniform saturation of the gain (or 'population inversion grating'). It is also well known that the latter coupling tends to destabilize bidirectional emission [START_REF] Siegman | Lasers[END_REF], thus preventing beat note existence and rotation sensing. Although it is not possible, for a solid-state ring laser, to suppress this coupling in the same way as in the case of a gas ring laser gyroscope (because of the absence of Doppler gainbroadening), it has been demonstrated in [22], following the pioneer work of [START_REF] Dotsenko | [END_REF], that it was however possible to circumvent it by using an additional stabilizing coupling.

The aim of this paper is to show how fine control of these mode coupling effects can turn the diode-pumped solid-state ring laser, which has intrinsically a very rich and non linear dynamics, into a stable ring laser gyroscope.

The semi-classical model we use for the description of our device, including active beat note stabilization, is quickly described in Sec. II. We then present, in Sec. III, an experimental overview of the oscillation regimes of the diode-pumped Nd-YAG ring laser. We show in particular that our data are in good agreement both with previous experimental observations using lamp-pumped solidstate ring lasers and with theoretical predictions from the literature. In Sec. IV, we study both theoretically and experimentally the possibility of stabilizing the beat note. Sec. V deals with the frequency response of the solid-state ring laser gyroscope obtained when the stability condition derived in Sec. IV is fulfilled. We finally conclude the article in Sec. VI.

SEMI-CLASSICAL MODEL

The dynamics of the rotating solid-state ring laser, including the additional stabilizing coupling, can be satisfactorily described using the typical semi-classical approach [30].

For the laser electric field inside the ring cavity, obeying Maxwell equations, we make the plane wave, uniform field and slowly-varying envelope approximations. In particular, all the transverse effects and also the longitudinal (i.e. axial) effects due to the spatial distribution of the laser components will be neglected. We furthermore assume one single identical longitudinal mode in each direction (this approximation is not valid when the laser is at rest, as will be discussed in next section) and the same (linear) polarization state e, resulting in the following expression for the electric field E : E(x, t) = Re Ẽ1 (t)e i(ωct-kx) + Ẽ2 (t)e i(ωct+kx) e ,

where k = 2π/λ is the mean spatial frequency associated with the longitudinal coordinate x and ω c is the mean angular frequency of the emitted modes.

The laser cavity is described, in the framework of Maxwell theory, by a polarization P due to the active medium, a dielectric constant ε and a fictitious conductivity κ, those parameters being related to the total cavity loss per time unit γ through the relation γ = κ/ε and to the frequency ω c through the relation ω c = k/ √ µ 0 ε, where µ 0 is the magnetic permeability of vacuum. In accordance with the uniform field approximation, the quantities κ and ε are supposed to be independent of the longitudinal coordinate x. However, their possible modulation at the spatial frequency 2k, although being usually very small, has to be taken into account for a correct description of the coupling induced by the cold cavity elements [31]. In order to avoid unnecessary complexity, we will use the same notation for the local and mean values of those parameters.

Starting from the typical Maxwell wave equation (using the rationalized MKSA system of units [START_REF] Jackson | Classical Electrodynamics[END_REF]) :

∂ 2 E ∂t 2 + κ ε ∂E ∂t + k 2 µ 0 ε E = - 1 ε ∂ 2 P ∂t 2 , (1)
we make a projection on the cavity emission modes, i.e. we multiply equation ( 1) by exp(±ikx) and integrate with respect to x along the cavity perimeter. Taking also into account the rotation of the ring laser and the additional stabilizing coupling, we obtain the following equations of evolution for the slowly-varying amplitudes Ẽ1 and Ẽ2 :

d Ẽ1,2 dt = - γ 1,2 2 Ẽ1,2 + i m1,2 2 Ẽ2,1 +(-1) 1,2 iΩ 2 Ẽ1,2 + ω c P1,2 2iε ,
where γ 1 and γ 2 are the counterpropagating modes loss coefficients, and where m1,2 are the cold cavity coupling coefficients, defined as :

m1,2 = - ω c εL L 0 ε(x) - iκ(x) ω c e -2i(-1) 1,2 kx dx , (2)
L being the cavity length. The rotation-induced angular frequency non-reciprocity Ω is given by the Sagnac formula Ω = 8πA θ/(λL op ), A being the area enclosed by the cavity, L op the cavity optical length and θ the rotation speed. We have also introduced the spatial harmonics of the complex amplitude of the gain medium polarization P1,2 , defined by :

P1,2 = 1 L L 0 e • Pe -i[ωct+(-1) 1,2 kx] dx .
It can be seen, on the mode equations, that the laser dynamics is mainly ruled by three different sources of coupling between the counterpropagating fields.

• The coupling induced by the cold cavity (i.e. in the absence of gain), represented by the coefficients m1,2 ; as can be deduced from expression (2), such a coupling can result for example from localized losses or from a step of refractive index ; it is wellknown in the field of gas ring laser gyroscopes that this coupling is responsible for a frequency synchronization between the counterpropagating modes at low rotation speeds, resulting in a zone of nonsensitivity usually called the "dead zone" [34] ;

• The coupling induced by the active medium, represented by the coefficients P1,2 , whose expression as a function of the electric field will be derived further in this section, in the framework of the dipolar coupling theory in quantum mechanics ;

• The additional coupling introduced in order to stabilize the beat note, which consists, for the counterpropagating modes, of different loss coefficients γ 1,2 , whose mean value γ is constant and whose difference is proportional to the difference between the intensities of the counterpropagating modes :

γ 1 -γ 2 = aK(| Ẽ1 | 2 -| Ẽ2 | 2 ) , (3)
where a is the saturation parameter (such that a| Ẽ1,2 | 2 is dimensionless, see further) and K is a constant chosen to be positive, such that the mode with the higher intensity gets the higher loss coefficient ; this coupling, first suggested by [START_REF] Dotsenko | [END_REF], has been successfully implemented on a diode-pumped Nd-YAG ring laser [22].

In order to calculate the polarization of the gain medium, we describe the diode-pumped Nd-YAG crystal as system of two-level atoms. In accordance with the uniform field approximation, we consider the gain medium and the optical pumping power to be homogeneously distributed. The gain medium is then fully described by a complex coherence term ρ ab and two real population terms ρ aa and ρ bb , a and b referring respectively to the lower and the upper level of the laser transition, whose frequency will be designated as ω ab . Due to the very short relaxation time of the lower level of the 1.064 µm emission line of the Nd-YAG, we will moreover assume ρ aa = 0. In this formalism, the macroscopic polarization is given by P = 2dn 0 ℜe(ρ ab ) e where d is a real number characterizing the dipolar coupling and n 0 is the atomic density per volume unit. The temporal evolution of ρ ab and ρ bb is ruled by the Bloch equations with adiabatic elimination of the polarization term ρ ab (this is made possible because the coherence damping time T 2 is much smaller than the population inversion relaxation rate T 1 and than the electric field decay time inside the cavity 1/γ). Introducing the population inversion density function N = n 0 ρ ab , we obtain : ωct+kx) ,

n 0 ρ ab = iN dT 2 2 (1 + iδ) Ẽ1 (t)e i(ωct-kx) + Ẽ2 (t)e i(
where δ = T 2 (ω c -ω ab ) is the cavity detuning, that will be neglected in our analysis since it is usually much smaller than unity (typically δ 10 -2 ). Defining the spatial average N 0 and 2k-harmonics N 1,2 of the population inversion density as :

N 0 = 1 L L 0 N dx and N 1,2 = 1 L L 0
N e 2i(-1) 2,1 kx dx leads to the following expression :

P1,2 = ia T 1 (N 0 Ẽ1,2 + N 1,2 Ẽ2,1 ) ,
where a is the saturation parameter [START_REF]The saturation parameter a is defined by a = T1T2d 2 -2 /(1 + δ 2 ), while the emission cross-section σ reads σ = aµ0Lc ω/(LopT1)[END_REF]. The total mean gain is proportional to N 0 , while N 1 = N * 2 represents the effects of the population inversion grating.

The complete self-consistent equations describing the evolution of the counterpropagating modes eventually read :

d Ẽ1,2 dt = (-1) 1,2 aK 2 (| Ẽ1 | 2 -| Ẽ2 | 2 ) + iΩ 2 Ẽ1,2 - γ 2 Ẽ1,2 + i m1,2 2 Ẽ2,1 + σL 2T Ẽ1,2 N 0 + Ẽ2,1 N 1,2 (4)
where σ is the emission cross section [START_REF]The saturation parameter a is defined by a = T1T2d 2 -2 /(1 + δ 2 ), while the emission cross-section σ reads σ = aµ0Lc ω/(LopT1)[END_REF]. Concerning the evolution of the population inversion density function N (x, t), it is ruled by the following equation (obtained from Bloch equations in the secular approximation) :

∂N ∂t = W - N T 1 - aN 2T 1 Ẽ1 e -ikx + Ẽ2 e ikx 2 , (5)
where W is the pumping rate, and where the second and the third terms stand respectively for the spontaneous and the stimulated emissions. Throughout this paper, we shall assume the following value for the population inversion lifetime : T 1 = 200 µs. Equations ( 4) and ( 5) will be the starting point for the theoretical description of the dynamics of the solid-state ring laser with active beat note stabilization in the next sections.

Because of its strongly non linear dynamics, the diodepumped Nd-YAG ring laser exhibits a broad variety of oscillation regimes. We report in this section an experimental overview of these regimes, and we discuss for each case the agreement with previously published data (mainly theoretical studies and experiments with lamppumped Nd-YAG ring lasers).

Estimation of the relevant laser parameters

The device we used for our experimental investigations is similar to the one described in reference [22]. It is made of an approximately 30-cm long stable ring cavity containing a 2.5-cm long Nd-YAG rod placed inside a solenoid. One of the four cavity mirrors is polarizing and a skew-rhombus geometry is used, with a very small non-planarity angle (typically 10 -2 rad). The Nd-YAG rod is optically pumped by a 808 nm pigtailed laser diode, and laser emission occurs at 1.064 µm. In order to create the additional stabilizing coupling, the current inside the solenoid (and consequently the difference of losses between the counterpropagating modes) is kept proportional to the difference between the intensities of the counterpropagating modes by an electronic feedback loop, ensuring condition (3). The whole device is placed on a turntable.

In order to make comparisons between theory and experiment, it is useful to estimate the typical parameters of our experimental configuration. Those parameters are mainly the mean loss coefficient γ, the backscattering coefficients m1,2 and the gain of the feedback loop K (plus the relative excess of pumping power above threshold η, which is easily deduced from the current inside the pump laser diode).

The loss coefficient can be precisely estimated in a class-B laser thanks to the presence, in the noise spectrum, of relaxation oscillations at the following frequency [35] :

f r = ω r 2π = 1 2π γη T 1 with η = W -W th W th , (6)
W th being the pump power density at laser threshold. The measurement of this frequency as a function of η leads to an estimation of the loss coefficient γ, as shown on Fig. 1. We obtained the experimental value γ ≃ 21.5 10 6 s -1 , which corresponds, for a 30-cm long cavity, to intensity round trip losses approximately equal to 2.3%. The backscattering coefficient is more difficult to measure than the loss coefficient. However, an estimate can be obtained by following the same argument as in the case of gas ring lasers [START_REF] Aronowitz | Laser applications[END_REF]. For this, we first assume, for symmetry reasons, that m1 and m2 have the same modulus m, i.e. we write : m1,2 = me i(-1) 2,1 θ1,2 with m > 0 .

Then, we make both hypothesis that the coupling described by m1,2 is mainly due to the fraction of light scattered by the YAG crystal in the solid angle of the couterpropagating beam and that such a scattering is mainly isotropic. In particular, we neglect the backscattering induced by the cavity mirrors as compared to the backscattering induced by the crystal. We furthermore assume that all the losses induced in the YAG crystal are due to diffusion, not absorbtion (this is justified by the fact that the lower level of the laser transition has a very short relaxation time, typically a few tens of nanoseconds). This leads to the following expression for m :

m = c L op λ √ b πw ,
where b represents the intensity losses corresponding to one pass through the YAG crystal (typically b = 0.7% for a 25-mm long rod) and w is the waist of the emitted modes (typically 500 µm). We obtain m ≃ 5.2 10 4 rad/s, which corresponds to a few tens of ppm per round trip. Although this method is only a cursory estimate (and cannot predict in particular any value for θ 1 and θ 2 ), we will see further in this paper that it provides at least the correct order of magnitude for m.

The strength of the stabilizing coupling K is fully determined by the laser geometry (non-planarity, characteristics of the solenoid) and by the design of the electronic feedback loop. A good stabilizing effect has been obtained with K ≃ 10 7 s -1 , which we will use as a reference value in the next sections.

We will see further in this paper alternate possibilities to estimate some of the relevant laser parameters (more precisely γ, m and θ 1,2 ), based on the study of the laser oscillation regimes.

s deg/ 75 - = θ 1 s deg/ 0 = θ 1 s deg/ 75 + = θ 1

Oscillation regimes in the absence of beat note stabilization

We first consider the possible oscillation regimes of the "plain" diode-pumped Nd-YAG ring laser, i.e. in the absence of additional coupling (K = 0).

In the absence of rotation, and when such a laser is operated slightly above threshold (η ≃ 0.2), we observe a stable stationary bidirectional regime, as reported on fig. 2 (case θ = 0). The occurrence of such a regime may seem at first sight surprising, since the analytical condition for the stability of the bidirectional stationary regime, which reads [23] :

m sin θ 1 -θ 2 2 > γη 3 , (7)
is obviously not fulfilled with the values of the laser parameters estimated previously. However, it has been shown in [36] that the stability condition for the bidirectional stationary regime is weaker when the existence of many longitudinal modes is accounted. Indeed, experimental measurements with an optical spectrum analyzer showed the existence of many (typically 3 or 4 per direction) longitudinal modes in the laser at rest, which may explain the fact that we observe a stable bidirectional emission even if condition ( 7) is not fulfilled. It is worth noting that the laser becomes single-mode in each direction when it is rotated above a critical speed (typically a few deg/s), ensuring in this case the validity of the theoretical description presented in Sec. II.

For faster rotations (typically above 70 deg/s), the laser turns to a unidirectional stationary emission regime, which has been theoretically studied in [START_REF] Dotsenko | Fedorovich[END_REF]. The stability condition for the stationary regime corresponding to | Ẽ1 | 2 ≪ | Ẽ2 | 2 reads θ sin(θ 1 -θ 2 ) < 0, while the stability condition for the opposite case (| Ẽ1 | 2 ≫ | Ẽ2 | 2 ) reads θ sin(θ 1 -θ 2 ) > 0. In particular, the direction of emission depends in this case on the direction of rotation, something which we did observe experimentally, as shown on fig. 2. Note that references [23] and [START_REF] Dotsenko | Fedorovich[END_REF] predict a ratio of 3 between the intensity of the dominant mode in the unidirectional regime and the intensity of both modes in the bidirectional regime, while the ratio we measured was only about 1.4. Again, this difference might be explained by the fact that the single-mode hypothesis, which is used in the theoretical description of references [23] and [START_REF] Dotsenko | Fedorovich[END_REF], is not valid when θ = 0.

In addition to those stationary regimes, a periodic (permanent) regime in which the two counterpropagating modes oscillate in phase opposition can occur, as reported on fig. 3. This regime, sometimes called 'selfmodulation of the first kind', has been described in [38] under the following hypothesis :

|θ 1 -θ 2 | ≪ 1 , γη ≪ m and |Ω| ≪ m . (8)
It comes out from the theoretical analysis that such a regime can give rise to beat note when the frequency non-reciprocity |Ω| obeys the inequality Ω 1 < |Ω| < Ω 2 , with :

Ω 1,2 = γ ′ aB 4|θ 1 -θ 2 | + (-1) 2,1 2
γ ′ aB 2|θ 1 -θ 2 | 2 -4m 2 (9)
where γ ′ = γ -m|θ 1 -θ 2 |/2 and aB/2 = η + 1 -γ/γ ′ . The numerical simulations we present on fig. 4 show very good agreement with expression (9). When realistic experimental parameters are used, numerical simulations show that the laser behavior is qualitatively similar, although conditions (8) are not fulfilled anymore. In particular, the zone of natural beat note occurrence is still present. However, we could not observe experimentally a beat note signal that was naturally stable over a reasonably long period, and to our knowledge such an observation has never been reported in the literature. This is probably due to the weak stability of this regime over external perturbations (e.g. mechanical noise).

Another periodic regime, typical of solid-state ring lasers, is presented on fig. 5. It consists in a periodic switch between both unidirectional regimes, with a period approximately equal to T 1 , and is sometimes called 'self-modulation regime of the second kind'. This regime, which had already been observed on lamp-pumped solidstate ring lasers [23], can be described theoretically [24] if one accounts for the existence of a second line in the emission spectrum of the Nd-YAG (something which is generally neglected invoking thermal equilibrium in the crystal due to phonon interactions [39]). Although it is in principle not necessary, we had in practice to modulate one of the laser parameters (namely the pump power) to observe this regime.

Because of the presence of strong non-linearities in the solid-state ring laser, periodic modulation of one of the parameters can also lead to chaotic behavior, as shown on fig. 6. Such a regime turns the solid-state ring laser into a convenient experimental tool for the study of dynamic chaos (see for example reference [9]). Preliminary numerical simulations and experimental work, not reported in this paper, have also shown the possibility of measuring the Sagnac frequency in the spectrum of the signal obtained by superposing both emitted modes when the laser is in the chaotic regime. This would present the major advantage of suppressing mode coupling effects, thus improving the quality of the gyroscopic response. However, some questions about this technique, like for example the problem of stabilizing the chaotic regime, are still not fully answered at the moment.

When the laser is rotating not too fast (typically | θ| 10 deg/s), we observe a beat note signal, whose frequency is proportional to the rotation speed but much smaller (about 100 times) than the theoretical Sagnac frequency (see fig. 7). We believe this 'anomalous scale factor' regime can be theoretically described if one accounts for the non-zero relaxation time of the lower level of the laser transition (this time constant, which is typically on the order of a few tens of nanoseconds, is usually assumed to be equal to zero although it is comparable with the photon lifetime inside the cavity 1/γ ≃ 50 ns). The establishment of an absorption grating is likely to give rise to a low frequency beat signal [START_REF] Klochan | [END_REF].

The broad variety of oscillation regimes we observed for the rotating diode-pumped solid-state ring laser illustrates the richness and the intrinsic non linear characteristics of its dynamics. However, although many of those regimes do depend on the speed of rotation of the device, none of them exists for a sufficiently broad range of parameters nor is stable enough to provide a satisfactorily way to use the diode-pumped solid-state ring laser as a rotation sensor. This observation has been the starting point for our theoretical and experimental work about beat note stabilization, which will be described in the next sections.

STABILIZATION OF THE BEAT NOTE : THEORETICAL AND EXPERIMENTAL STUDY

We now turn to the study of the diode-pumped solidstate ring laser with active beat note stabilization, i.e. we assume condition (3) is fulfilled, with K > 0. The aim of this section is to show, both theoretically and experimentally, that under these conditions the beat regime exists and is stable provided the rotation speed is high enough.

Theoretical study

We use as a starting point for this study equations ( 4) and (5). It is more convenient for analytical calculation to define new (real) variables as :

Y = | Ẽ1 | 2 + | Ẽ2 | 2 , X = | Ẽ1 | 2 -| Ẽ2 | 2 , Φ = arg( Ẽ2 ) -arg( Ẽ1 ) . (10)
We study the beat regime in the limit of high rotation speeds, i.e. we assume :

|Ω| ≫ m and |Ω| ≫ ω r . (11)
Under these conditions, the laser parameters in the beat regime have the following expression :

     Y (t) = B(t) + y M (t) with |y M | ≪ B , X(t) = C(t) + x M (t) with |C| , |x M | ≪ B , Φ(t) -Ωt = Φ 0 (t) + Φ M (t) with |Φ 0 | , |Φ M | ≪ 1 ,
where the functions x M , y M and Φ M are supposed to oscillate at a frequency close to Ω, while B, C and Φ 0 are supposed to be slowly varying with respect to 1/|Ω|. The phase origin is chosen such that Φ 0 (0) = 0.

The spatial harmonics of the population inversion density N 0 and N 1 can be calculated in this regime, keeping only the lowest order terms in the expressions for Y /B, X/B and Φ -Ωt and solving equation (5). We obtain :

N 0 = W T 1 - aB 2 N th , N 1 = - aBN th 4 1 + iΩT 1 1 + Ω 2 T 2 1 e -iΩt ,
where N th = T 1 W th is the population inversion density at threshold. Integrating equation (4) using the same approximation leads to :

                 y M = m Ω B 2 -C 2 sin Ωt + θ 1 + θ 2 2 sin θ 2 -θ 1 2 x M = m Ω B 2 -C 2 cos Ωt + θ 1 + θ 2 2 cos θ 2 -θ 1 2 Φ M = m Ω B -C B + C cos Ωt + θ 1 + θ 2 2 sin θ 2 -θ 1 2 (12)
Inserting those expressions in equation ( 4) up to the first order and then averaging over a few periods of 1/|Ω|, we obtain the following equations for the slowly varying functions B and C :

       Ċ = dC + Bm 2 2Ω sin(θ 1 -θ 2 ) - aKBC 2 , Ḃ = dB + Cm 2 4Ω sin(θ 1 -θ 2 ) - σl 4T N seuil aB 2 1 + Ω 2 T 2 1 -aKC 2 ,
where d is defined by d = σlN 0 /T -γ. In the stationary regime, we obtain aB ≃ 2η, 2d = γη/(1 + Ω 2 T 2 1 ) and :

aC = 2m 2 sin(θ 1 -θ 2 ) Ω 2K - γ 1 + Ω 2 T 2 1 -1 .
The initial hypothesis |C| , |x M | , |y M | ≪ B are selfconsistently fulfilled in the high rotation speed limit defined previously. To study the stability of this solution, we assume a small perturbation (δB, δC) exp(µt) and look for the possible values for µ. We find the following three solutions µ 1,2,3 :

µ 1,2 = - 1 2T 1 ± iω r and µ 3 = γη/2 1 + Ω 2 T 2 1 -Kη .
The first two solutions correspond to damped oscillations at the angular frequency ω r , while the third solution determines wether or not the beat regime will be stable, the stability condition µ 3 < 0 reading :

2K > γ 1 + Ω 2 T 2 1 . (13)
Physically, this condition expresses the fact that for the beat regime to be stable, the additional stabilizing coupling (left term) has to be stronger that the destabilizing coupling due to the population inversion grating (right term). It is a remarkable fact that whatever the stabilizing coupling strength is (provided it is non-zero and positive), the beat note will always be stable for sufficiently high rotation speeds. This is due to the fact that all the intrinsic coupling go to zero when the rotation speed increases, while the external stabilizing coupling strength remains constant whatever the rotation speed is [22].

Experimental achievement

When the additional stabilizing coupling is turned on, the beat regime occurs for rotation speeds higher than ≃ 10 deg/s. The observation, with two close detectors, of two modulated signals in phase quadrature (fig. 8) is an undisputable signature of the beat note (as opposed to just intensity modulations), and gives the additional information of the direction of the rotation.

Experimental study of the intensities of the counterpropagating modes in the beat regime allows to measure the parameter θ 1 -θ 2 . As a matter of fact, it comes out from equations (12) that the relative phase between the modulated parts of E 2 1 = (X +Y )/2 and E 2 2 = (Y -X)/2 is given by π+θ 1 -θ 2 . For our experimental configuration, we obtained the following measurement :

θ 1 -θ 2 ≃ π/20.
The measured value of the beat frequency as a function of the Sagnac non-reciprocity Ω is reported on fig. 9. A very good agreement with the ideal Sagnac line is observed for high values of |Ω|. The frequency response becomes non-linear when the rotation speed decreases, and finally disappears when | θ| 10 deg/s.

It is worth noting that the zone corresponding to the absence of beat note around Ω = 0 is not a lock-in zone as in the case of gas ring laser gyroscopes, but rather a zone of self-modulation of the first kind with an average value of the phase difference equal to zero. It is also worth noting that the condition for the occurrence of the natural beat note regime, as described in the previous section, is with our parameters weaker than the validity condition (11). The size of the zone of insensitivity to rotation is thus determined by the condition of occurrence for the natural beat regime, rather than by condition (13).

FREQUENCY RESPONSE OF THE DIODE-PUMPED ND-YAG RING LASER GYROSCOPE

A typical frequency response curve for the solid-state ring laser is shown on fig. 9. The difference between the beat frequency and the ideal Sagnac frequency can be expressed analytically provided it is much smaller than the absolute value of the beat frequency. For this, we derive from equation ( 4) the following equation for Φ :

Φ = Ω - Y √ Y 2 -X 2 σL T ℑm(N 1 e iΦ ) - m 2 Y -X Y + X cos(Φ + θ 1 ) - Y + X Y -X cos(Φ + θ 2 ) .
Using for the beat regime the definition given previously, we obtain, in the limit

Φ0 = m 2 cos(θ 1 -θ 2 ) 2Ω + γη 2ΩT 1 .
The beat frequency Φ is thus finally given by :

Φ = Ω + m 2 cos(θ 1 -θ 2 ) 2Ω + ω 2 r 2Ω . (14)
As can be seen on this equation, the two sources of deviation from the ideal Sagnac line are the coupling through backscattering on the cold cavity elements and the coupling induced by the population inversion grating. The linear dependance of the beat frequency on the pumping rate η has been checked experimentally, as reported on fig. 10. We deduce from the line slope another measurement for the loss parameter, namely γ ≃ 19.3 10 6 s -1 . This value is in good agreement with the measurement performed on the relaxation frequency (γ ≃ 21.5 10 6 s -1 , see Fig. 1). The difference can be attributed to the analytical approximations made in deriving expression (14).

The value of the extrapolated beat frequency at η = 0 (offset) provides a measurement of the parameter m. Considering the fact that cos(θ 1 -θ 2 ) ≃ 1 (see Sec. IV), we obtain with this technique m ≃ 11 10 4 rad/s, which is twice the value estimated in Sec. III. This difference might be due in particular to the fact that we have neglected in Sec. III the effect of diffusion on crystal edges and on cavity mirrors.

As can be seen on Fig. 9, the solid-state ring laser has a characteristic response curve "above" the ideal Sagnac line, while the typically admitted frequency response curve for the gas ring laser gyroscope is rather "below" the ideal Sagnac line (Fig. 11). The first reason for this is that the typically admitted picture for the frequency response curve of the gas ring laser is not always true : it has been shown [42] that when the coupling induced by the cold cavity elements was dissipative (i.e. when |θ 1 -θ 2 | ≪ 1), the frequency response curve was above the ideal Sagnac line, at least in the limit of fast rotations. This result is in agreement with equation (14). The second reason is that the deviation induced by the population inversion grating, which is not present in the gas ring laser gyroscope, is always positive and often dominates the former coupling, resulting in typical frequency response curves "above" the ideal Sagnac line.

CONCLUSION

We have studied in this paper the dynamics of a diodepumped solid-state ring laser with active beat note stabilization. We have shown in particular that amongst a broad variety of oscillation regimes, including chaotic behavior, a stable rotation sensitive regime can occur thanks to fine mode coupling control. Focusing on this regime, we have derived theoretically its stability condition and its frequency response under rotation. We have also studied this regime experimentally, showing a very good quantitative agreement with our theoretical predictions.

Applications for this work range from the study of nonlinear systems with periodic boundary conditions (including other fields than optics, e.g. superfluidity [22]) to optical gyroscopes. In the latter case, the performances will depend on the possibility of reducing the strength of the coupling induced by backscattering and by the population inversion grating. Some techniques to improve these performances will be presented in future publications.

2 Figure 1 :

 21 Figure 1: (Color online) Square of the relaxation frequency as a function of the pumping rate (data obtained from the electronic Fourier transform of the laser intensity). The linear dependance is in agreement with equation (6), and leads (for T1 ≃ 200µs) to the estimated value γ ≃ 21.5 10 6 s -1 .

Figure 2 :

 2 Figure 2: Experimental observation of the stationary regimes of the solid-state ring laser. When the laser is at rest ( θ = 0), the bidirectional regime is observed. When the laser is rotating at ±75 deg/s, unidirectional operation occurs, the direction of emission depending on the sign of θ. The horizontal time scale is 5 µs/div, while the vertical scale is arbitrary.

Figure 3 :

 3 Figure 3: Experimental observation of the self-modulation regime of the first kind. The counterpropagating modes oscillate in phase opposition, with a frequency close to 27 kHz. The horizontal time scale is 50 µs/div, while the vertical scale is arbitrary.

Figure 4 :

 4 Figure 4: (Color online) Numerically computed angular beat frequency as a function of the Sagnac non-reciprocity Ω, using the following laser parameters : γ = 2 10 6 s -1 , m = 10 6 rad/s, θ1 -θ2 = π/78 and η = 0.1. The continuous line corresponds to the ideal Sagnac response. With those parameters, equation (9) predicts the following values for the boundaries of the beat note zones : Ω1 = 0.24 10 6 rad/s and Ω2 = 4.2 10 6 rad/s, which is in good agreement with this simulation. Integrating step : 3 ns. Integrating time : 7 ms. The plotted values are obtained by averaging the time signals between 5 ms and 7 ms.

Figure 5 :

 5 Figure 5: Experimental observation of the self-modulation regime of the second kind. The measured switching frequency is about 3.7 kHz. The horizontal time scale is 100 µs/div, while the vertical scale is arbitrary.

Figure 6 :

 6 Figure 6: Experimental observation of the chaotic behavior of the diode-pumped solid-state ring laser. This regime has been obtained by periodic modulation of the pump power at a frequency close to the relaxation frequency fr. The horizontal time scale is 100 µs/div, while the vertical scale is arbitrary.

Figure 7 :

 7 Figure 7: (Color online) Measured beat frequency as a function of the rotation rate in the regime of 'anomalous scale factor'. The estimated line slope is about 20 Hz/(deg/s), which is about 100 times smaller than the Sagnac scale factor, about 2 kHz/(deg/s).

Figure 8 :

 8 Figure 8: Experimental observation of two sinusoidal signals in phase quadrature with two close detectors, which is the signature of the beat note. The direction of the measured rotation can be deduced from the relative position of the two signals. Only the AC components of the signals are shown on this figure.

Figure 9 :

 9 Figure 9: (Color online) Experimental frequency response curve of the solid-state ring laser gyroscope, i.e. beat frequency as a function of rotation speed. The line corresponds to the ideal (theoretical) frequency response curve.

Figure 10 :

 10 Figure 10: (Color online) Experimental dependance of the beat frequency of the solid-state ring laser gyroscope on the pumping rate for a fixed rotation speed ( θ = 190 deg/s, corresponding to Ω = 8.25 10 5 rad/s). The line results from a linear fit of the data.

  |x M | ≪ B, |y M | ≪ B, |C| ≪ B and |Φ M | ≪ 1, the following equation for Φ 0 (after averaging over a few periods of 1/|Ω|) :

Figure 11 :

 11 Figure 11: (Color online) Graph illustrating the typically admitted shape for the frequency response curve of the gas ring laser gyroscope, as compared to the frequency response curve of our Nd-YAG ring laser gyroscope. The first curve is "below" the ideal Sagnac line, while the second is "above".

The authors thank Thales Aerospace for constant support. They are also very grateful to Alain Aspect and Philippe Bouyer for fruitful discussions, and to Michèle Leduc and the French-Russian GDRE Lasers and Optoelectronics for their contribution to the support of the visits of one of them (E.L.) in France. They also thank Franois Gutty, Francis Grabisch and Maxence Rebut for their help in numerical simulations and experiments.


Xiandi Zhang
email: zhangxd@nercita.org.cn

Feng Yang

Zhongqiang Liu

Zhenzhi Wang
email: wangky@nercita.org.cn

Kaiyi Wang

Research and Application of Data Security for Mobile Devices

Keywords: Mobile devices, data transmission, security, XML encryption, SSL protocol

Mobile devices have been increasingly become important tools for the information system application in agriculture, but the safe problem that follow also results in risks of economy lose. Considering above problems and combining the application of an agriculture chain logistics management system, a series of jobs have been done. This paper presents a data security solution which encrypts the configuration files to protect sensitive information and uses SSL protocol to protect the network transmission security. At present, this solution has been modular integrated with the agriculture chain logistics management system. This paper also provides reference for data security problems of other mobile devices.

Introduction

Due to the flexible and customizable feature, wireless mobile devices agree with the special requirements of the agriculture application, such as wide region and poor infrastructure condition. Therefore, related application based on wireless mobile devices will become the development direction of agricultural information system. However, the smallness and portable characteristics also cause the security problems of the sensitive data seem more outstanding. Moreover, the wireless mobile devices currently send data by GPRS while GPRS at this stage need to transmit information via public network. So, the data security in the process of passing data through network faces crucial threat. Data security during transmission of mobile devices application has become an urgent problem to be solved. Aiming at these problems and according to the practical requirement, this paper proposed a set of data security solution. This solution has been applied to an agriculture chain logistics management system. The effectiveness has been demonstrated.

Introduction of the agriculture chain logistics management system

The system is composed of client-side and server-side, which communicate data via GPRS. The client-side system running on mobile devices integrates agricultural material reservation, acceptance of the goods, returned goods, sales record and price acquisition. These five modules implement basic business requirement of agricultural material chain stores. The server-side system also integrates these five modules to ensure that the business functions can be completed in the case of client-side system failure. In addition, the server-side system provides inquiry and statistics to each module. Basic data management module of the server-side system makes a uniform management on basic information of agricultural material. These basic information can be transmitted to client-side to support the client-side system operation. And server's IP address, data transmission URL, system username and password are stored in the system configuration module of client-side system.

In the system, there are two significant data security risks as below:

a. Loss of mobile devices may compromise business data and sensitive information which is stored in the devices. People who intercepted above information would spread trade secrets or attack servers.

b. Data interception during transmission will pose a threat to confidentiality,interity and availability of data.If the hackesrs tampered,disguised, replayed the data or made the server deny the data from client-sides,the agricultural material sellers would sustain a great loss. b. SSL protocol to protect data security during the process of network connection.

SSL handshake protocol will automatically perform exchanging keys and symmetrical encrypt to prevent the safety hazards after the transmission attacking.

Above both security modules have been established in the agriculture chain logistics management system. To meet the needs of flexible application on other systems, lots of jobs have also been done to reduce the coupling degree. This solution, though, has certain pertinence; it covers most of the basic security requirement of mobile devices. Superadded the modular development, this solution has a general significance for other applications.

Configuration files encryption

The system configuration files are XML format, so we mainly study XML encryption.

The biggest difference between XML encryption and conventional encryption is the introduction of the concept of encryption granularity; you can encrypt the whole document, the document element or document element content. After encryption the whole element is replaced with an element named <EncryptedData>. The element contains information with encryption or decryption information, encrypted data and encrypted data references, etc.. The <EncryptedData> element is the core element in the syntax. Not only does its cipherdata child contain the encrypted data, but it's also the element that replaces the encrypted element, or serves as the new document root.

When encrypting an XML element or element content the <EncryptedData> element replaces the element or content (respectively) in the encrypted version of the XML document [START_REF] Jiangyong | Safe Data Exchange Based on XML Encryption[END_REF] .

Encrypt the xml using a combination of asymmetric and symmetric encryption requires a symmetric session key to encrypt the data and an asymmetric key to protect the session key. Both the encrypted session key and the encrypted data are stored together in the xml document. The public asymmetric key is used to encrypt the session key while the private asymmetric key is used to decrypt the key [START_REF] Kui | Research and implementation of encryption method based on XML[END_REF] .

SSL

Short for Secure Sockets Layer, a protocol developed by Netscape for transmitting private documents via the Internet. SSL uses a cryptographic system that uses two keys to encrypt data a public key known to everyone and a private or secret key known only to the recipient of the message. Both Netscape Navigator and Internet

Explorer support SSL, and many Web sites use the protocol to obtain confidential user information, such as credit card numbers. By convention, URLs that require an SSL connection start with https: instead of http:. The primary goal of the SSL Protocol is to provide privacy and reliability between two communicating applications. The protocol is composed of two layers. At the lowest level, layered on top of some reliable transport protocol (e.g. [TCP]), is the SSL Record Protocol. The SSL Record Protocol is used for encapsulation of various higher level protocols. One such encapsulated protocol, the SSL Handshake Protocol, allows the server and client to authenticate each other and to negotiate an encryption algorithm and cryptographic keys before the application protocol transmits or receives its first byte of data. One advantage of SSL is that it is application protocol independent. A higher level protocol can layer on top of the SSL Protocol transparently.

Fig. 3. SSL Protocol

The SSL Handshake Protocol is one of the defined higher level clients of the SSL Record Protocol. This protocol is used to negotiate the secure attributes of a session.

Handshake messages are supplied to the SSL Record Layer, where they are encapsulated within one or more SSLPlaintext structures, which are processed and transmitted as specified by the current active session state [12][13][14] . c. The client uses some of the information sent by the server to authenticate the server (see Server Authentication for details). If the server cannot be authenticated, the user is warned of the problem and informed that an encrypted and authenticated connection cannot be established.

d. Using all data generated in the handshake so far, the client (with the cooperation of the server, depending on the cipher being used) creates the premaster secret for the session, encrypts it with the server's public key, and sends the encrypted premaster secret to the server.

e. If the server has requested client authentication (an optional step in the handshake), the client also signs another piece of data that is unique to this handshake and known by both the client and server. In this case the client sends both the signed data and the client's own certificate to the server along with the encrypted premaster secret.

f. If the server has requested client authentication, the server attempts to authenticate the client (see Client Authentication for details). If the client cannot be authenticated, the session is terminated. If the client can be successfully authenticated, the server uses its private key to decrypt the premaster secret, then performs a series of steps (which the client also performs, starting from the same premaster secret) to generate the master secret.

g. Both the client and the server use the master secret to generate the session keys, which are symmetric keys used to encrypt and decrypt information exchanged during the SSL session and to verify its integrity--that is, to detect any changes in the data between the time it was sent and the time it is received over the SSL connection.

h. The client sends a message to the server informing it that future messages from the client will be encrypted with the session key. It then sends a separate (encrypted) message indicating that the client portion of the handshake is finished.

i.

The server sends a message to the client informing it that future messages from the server will be encrypted with the session key. It then sends a separate (encrypted) message indicating that the server portion of the handshake is finished.

j.

The SSL handshake is now complete, and the SSL session has begun. The client and the server use the session keys to encrypt and decrypt the data they send to each other and to validate its integrity. [12][13][14] 6. Implementation of secure data transfer solution

Encrypting configure file

We encrypted the key of symmetric encryption algorithm using asymmetric algorithm on configure file, to ensure the security of key exchange, then we make encryption and decryption on file data using symmetric encryption algorithm, which is the recommended method of XML encryption specification. In the process of configure file encrypting,firstly public key and private key pair was generated and saved into security key container,secondly one single session key was generated by AES algorithm, by which XML document element was Encrypted,thirdly AES session key was Encrypted using RSA public key, finally the encrypted AES session key and encrypted XML data was saved to new element of <EncryptedData> in XML The sever side will return handshake status to judge if success of Handshake  Data Transfer

After the success of handshake,we can make secure data transfer. In axTLS, we use the function of read() and write() to accomplish read and white operations of socket

Conclusions

In this article,we introduced a secure data transfer solution of moving equipment using XML encryption and SSL protocol, and implemented it in Agriculture Chain Logistics Management System. In the practice, the solution satisfied the security requirement of data transfer in system, in which the server side is in Myeclipse framework and client side is in .NET3.5 framework. We believe as the moving equipment in agriculture becomes more and more Diversity,the data transfer security problem will drawn wide attention.

Fig. 1 .Fig. 2 .

 12 Fig. 1. Agriculture Chain Logistics Management System Structure

Fig. 4 .

 4 Fig. 4. Handshake protocol

  int axTLSj::SSLCTX::read ( SSL ssl, finishes between client and server, Dispose() function should be called to release SSL resources. void axTLSj::SSLCTX::dispose () [inline]

Acknowledgements. This research is funded by the Support of Science and Technology Project of the State, Programmed award No. 2008BADA0B02.


Wenqin Cao

Haiyan Zhu

Supply Chain Integration Based on Core Manufacturing Enterprise

Keywords: Supply chain (SC), Integration, Logistics, Core manufacturing enterprise

System integration solutions and model of supply chain are proposed based on core manufacturing companies, combining the actual operation of the supply chain process of a motor enterprise. The operation of the supply chain is discussed from the supplier integration, internal integration, and customer integration. The process integration is studied from the logistics integration, information flow integration and capital flow integration. Strategic decision management corresponding to cultural integration, separately discuss from the development strategic integration, concept integration and management integration.

Introduction

China is becoming a center of world manufacture, which is a good opportunity for the Chinese manufacturers [START_REF] Adewole | Developing a strategic framework for efficient and effective optimization of information in the supply chains of the UK clothing manufacturing industry; Supply Chain Management[END_REF]. The paper responses to the urgent needs of manufacturing enterprises, combining with personal experiences of K Company (a medium car manufacturer) integration, which is for manufacturing company's supply chain management [START_REF] Saad | An investigation of supply chain performance measurement in the Indian automotive sector[END_REF][START_REF] Phallapa Petison | Dynamics of the manufacturer -supplier relationships in emerging markets[END_REF]. The core manufacturer in the supply chain plays leading role in the integration process, relying on the superiority of their own capital, technology and brand to influence and integrate the upstream and downstream businesses from strategic level to plan and control layer [START_REF] Lewis | Improving the inter-organizational supply chain through optimization of information flows[END_REF][START_REF] Fischer | A global concept -Virtual companies[END_REF].

Prerequisite of the core manufacturing supply chain integration

For supply chain integration, the core manufacturing enterprise should have certain conditions to play leading role in the supply chain integration. Core business must have at least the following three conditions [START_REF] Fawcett | Developing logistics capability to improve the performance of international operations[END_REF].

1). Perfect internal management information system. Business should have enterprise resource planning system Etc. to grasp all kinds of raw materials, semi finished goods inventory and shipments in order to promptly respond to market; should have good customer relationship management system to respond customer needs and personalized service. Therefore, the core business should have a more complete internal management information system to integrate internal resources and companies.

2). Smooth and efficient business processes. The business can achieve effective interface between the upstream and downstream enterprises with smooth and efficient business process. So business in the supply chain business process integration should be preceded by rationalization, optimization and reconstruction, the establishment of efficient standardization of business norms.

3). A sound management system and operating specifications. Different enterprise has different business processes and operations, which make a lot of inconvenience in communication. The core business should establish a unified management and operating standards, and information systems integration standards.

Contents and methods of supply chain integration

Based on core manufacturing companies, supply chain integration will be divided by the executive level into the strategic level integration, planning and control layer integration, basic layer integration. Strategic level integration includes development strategic integration, concept integration, management integration; planning and control layer includes logistics integration, process integration, information integration and capital flow integration; basic layer integration includes supplier integration, internal integration and customer integration. Integration model is shown in Figure 1. 1、Internal Integration: Good internal integration is successful experience for other businesses in supply chain. Internal integration is divided into two levels: the internal process and information integration, organizational integration [START_REF] Daugherty | Leveraging logistics/distribution capabilities: the effect of logistics service on marketshare[END_REF].

1) The internal process and information integration: Business should identify and optimize core business processes, establish standard operation procedures to improve the speed and quality of processes. Internal information of core business should be integrated by process to respond to market changes and customer demands.

2) Organizational integration: Organizational integration should enable organizational design, structure and operation to meet the system objectives, and establish process-oriented management mode. Distributed logistics should be unified and integrated with procurement to set up an integrated logistics system, whose all logistics-related functions are unified.

2、Supplier integration Core business should have a good supplier management system, optimize supply chain structure from the number of suppliers, quality and other aspects in the global integration.

In the implementation of supplier integration process, business can start from the following areas.

1) Establish strategic partnership with key suppliers. Establishment of strategic partnership can strengthen procurement, and timely meet the needs of the supply chain to reduce supply chain inventories through JIT purchasing. At the same time, the core business should integrate design and research capabilities of supplier to build collaborative design relationship with strategic cooperation partners.

2) Establish information sharing mechanisms with key strategic partners. Sharing information of production planning, production information, inventory information, demand forecast information with key suppliers can reduce information distortion.

3) The supplier selection and management scope expand to supplier's supplier. Integration from the source of supply chain can ensure reliable raw materials, which can boost the competitiveness of suppliers and enhance the whole supply chain competitiveness.

4) Integration outsourcing service provider. Outsourcing service helps companies to use resources and capacity that they don't have. So the selection and integration of outsourcing service providers should be more emphasis on its core competence and the integration degree of supply chain, so that outsourcing service providers can better enhance the supply chain's competitive advantage and flexibility.

3、Customer integration: Customer integration includes enterprises in the entire distribution chain node (wholesalers, distributors, retailers and ultimately customers) integration. Selection of various vendors according to established evaluation index is to expand the sales network, optimize the distribution chain structure to reach distribution chain's labor clear (including the sale of product categories, covering the area, etc.). Three main aspects are for clients to integrate [START_REF] Nagurney | supply chain network equilibrium model[END_REF].

1) To provide management and technical support for the distributor, to establish a unified application system to real-time master distributor sales information; to form a strategic alliance with dealers to design distribution channels.

2) To establish partnerships with major customers to provide personalized products and services; to establish an effective customer feedback mechanism to keep abreast of changing customer needs and requirements; to share market information, sales information, demand forecast information, inventory information, production planning information with major customers.

3) To reduce the level of distribution channels, combining retail channels of distribution and online. Online sales are an important sales channel development trends, which can save investment costs.

Planning and control layer integration -process integration

Supply Chain business process is an independent design, which is lack of effective convergence and required to integrate accordingly, such as the sale of a business process is another company's procurement process [START_REF] Chopra | Supply Chain Management: Strategy, Planning, and Operation[END_REF]. Based on all aspects of supply chain business process optimization among the basic implementation strategy, the core processes should be optimized to improve the efficiency of the whole supply chain and value creation capabilities.

Process integration should be based on the process management idea, whose three levels are process specification, and process optimization and process Reengineering. The supply chain core processes has different expression form by different classification, where are expressed by logistics, information flow and cash flow.

In the operation of the supply chain, the process of manufacturing resource materials or products, finished in different position or performance over time is known as logistics; the information of the production and marketing performance for the material in three main areas of change and shift is known as information flows; the costs associated with material value-added data is known as cash flow.

1、Logistics Integration: Internal production and logistics integration can improve their ability to optimize the allocation of resources; supply chain logistics integration can enhance the use of external resources to gain competitive advantages. Logistics integration also can improve time response, gain competitive advantage. Logistics integration ultimate aim is to meet customer demand, gain the fastest way the lowest cost to deliver products and services to customers.

Internal logistics integration refers to the integration of enterprise procurement, distribution, manufacturing, logistics, to achieve the integrated operation of the system, and upstream suppliers and downstream customers connected. Supply chain logistics integration concerns integration of logistics operations group, the wider and deeper level to improve the operation of the logistics system performance. Integration of logistics includes two levels of integration, logistics information and logistics facilities [START_REF] Hao | The effect of logistics capabilities on firm performance: customer-focused versus information-focused capabilities[END_REF].

1) Logistics Information Integration. Related logistics information system is a bridge in the transfer logistics information, whose related information systems include inventory management information systems, distribution systems, data exchange and transmission systems, electronic financial transactions systems, retail point-of-systems and so on. Effective integration of information systems can increase the interface function; improve information sharing and the logistics efficiency of the system.

2) Logistics facilities integration. Core enterprise should overall plan infrastructure

Figure 1 The integration model of supply chain 3 . 1 .

 131 Figure 1 The integration model of supply chain

of supply chain, to make full use of co-members' infrastructure, such as distribution centers and warehouses. The establishment of efficient supply chain distribution system can reduce duplication of investment and increase resource utilization. Channel design and network analysis, optimization of supply chain manufacturing plants, distribution centers, distribution centers, warehouses and other infrastructure facilities, location and number are to make the entire supply chain logistics system more rational.

2、Information Integration. Information integration is an important level of supply chain integration, which decides the success of supply chain integration. Core business should integrate internal information to make the full internal information sharing between the different functions of application, so that the different departments can in a timely manner, quickly and accurately respond to changes in the market coordination to meet customer needs.

Supply chain systems integration with internet on the basis of internal information can increase the visibility levels of whole supply chain information, forecast and plan production with suppliers, customers to achieve reasonable allocation of the supply chain resources, timely and effective from order to delivery. Information integration approach can be integrated by IT technology integration and the relationship between two channels.

3、Financial flows integration. Integration of financial flows mainly includes integration of each node's credit, payment, accounts, receivable accounts payable and other aspects. An effective corporate credit tracking system and a unified method of payment should be established to enhance the utilization rate of capital turnover. Supply chain logistics, financial flow, information flow are accompanied, which constitute the entire value stream as shown in Figure 2.

Strategic level integration cultural integration

Cultural integration is the highest level of supply chain integration, which can be divided into internal cultural integration and partner cultural integration. Within the enterprise, cultural integration should further highlight the characteristics of enterprises, namely the outstanding business value, business spirit, corporate style, business sense of service. The cultural integration of the supply chain is to create a unified culture, or each node integration between corporate culture and enhance supply chain cohesion and competitiveness. For the whole supply chain, cultural integration is mainly from the development strategy, ideas and management models.

Conclusions

This research based on the core manufacturer's supply chain management, with value-added process procurement, manufacturing and sales as line, provide reference model of supply chain integration and its implementation measures to integrate resource.


Yuling Shi

Zhongyi Wang

Xu Liu

Dongjie Zhao

Lan Huang

A Web-based monitoring system as a measurement tool in greenhouses using wireless sensor networks

Keywords: monitoring system, WSNs, GPRS modules, received signal strength indicator, link quality indicator

In this work, we propose a Web-based monitoring system using wireless sensor networks (WSNs) to measure plant parameters and environmental factors in greenhouses. To detect and send these variables, e.g. leaf temperature, air humidity, a ZigBee-based WSN collects data, which is transmitted by GPRS modules and the Internet to a central computer, and all information, including the dynamic topology of WSNs, can be published via the Web. The system provides flexible configuration options for sensor nodes and transport downlink commands, i.e. sensors can be added or removed flexibly in a node without changing the hardware interface and data center service software. Also, the variance of the received signal strength indicator(RSSI) and link quality indicator (LQI) under different distributions of the growing plants was considered to estimate the network link quality to ensure reliable data transmission in the WSNs. Experiments show that the system is reliable, flexible, convenient, and provides good real-time and scalability characteristics.

Introduction

When using a conventional wire-based automatic monitoring system in a greenhouse, an increased number of measurement points can dramatically increase the complexity and cost of the system. It should also be possible to change the location of the measurement points easily to meet different measurement needs, which depend on the particular plant, on possible changes in the external weather or the greenhouse structure, and on the plant placement in the greenhouse.

In recent years, wireless sensor networks (WSNs) have been used in several agriculture applications, e.g. regional and on-farm agriculture projects for irrigation [START_REF] Pierce | Regional and on-farm wireless sensor networks for agricultural systems in Eastern Washington[END_REF][START_REF] Camilli | From wireless sensors to field mapping: anatomy of an application for precision agriculture[END_REF] . Vivoni and Camilli [START_REF] Vivoni | Real-time streaming of environmental field data[END_REF] developed a wireless prototype system to acquire, store, display and transmit real-time, geo-referenced environmental data between multiple field teams and remote locations. Mahan and Wanjura [START_REF] Mahan | Upchurch, Design and Construction of aWireless Infrared Thermometry System[END_REF] cooperated with a private company to develop a wireless, infrared thermometer system for in-field data collection. The system consisted of infrared sensors, programmable logic controllers and low power radio transceivers to collect data in the field and transmit it to a remote receiver outside the field. However, there has been little research into web-based WSNs for measurement of plant and environmental variables in greenhouses, and particularly to investigate the influence of plant growth on radio wave propagation in the WSNs. Also, there remains an engineering issue that requires further study to provide flexible configuration options for sensor nodes and transmit downlink commands to set up new parameters for nodes online during addition or removal of sensors without changing the interface and software.

From an engineering perspective, there remain many difficulties and challenges in measuring plant variables in the field or the greenhouse using WSNs. Our objective was to develop WSN hardware and software to provide functions for acquiring realtime measured data from the Internet, and displaying the RSSI and topology of the WSNs dynamically, and also for transmitting downlink commands to sensor nodes.

Remote monitoring system design and overall structural framework

To explore the issues with the deployment of such a monitoring network related to plant growth in the greenhouse, Web-based remote sensing network architecture is depicted in Fig. 1. The system consisted of a ZigBee-based tree-topology WSN with 20 sensor nodes to obtain plant or environmental variables, e.g. leaf temperature, stem sap flow, temperature or humidity, plus 5 router nodes, and 1 coordinator node (sink node) deployed in the greenhouse, a GPRS module connected with the coordinator via the RS-232 serial port to transmit the received data to the remote monitoring center, and a web-based management sub-system for users to acquire and analyze the data via the Internet. To meet special applications of the system, the system can send commands to the wireless network to re-configure the node channel and set the sampling frequency.

Sensor Node

The sensor node functional module is shown in Fig. 2. Each sensor node can provide 8 analog channels with 14-bit resolution and multiple I/O channels, and therefore we can simultaneously connect up to 8 analog sensors and configure the channels flexibly. A node can access any sensor data without changing the hardware circuit and interface, simply using the upper flexible configuration. At the same time, all the network nodes send LQI and RSSI values to the coordinator for future operations by the data center. Sensor nodes collect the sensors' data periodically according to commands from the control center, and then send the data to the coordinator node. The coordinator node is connected with the GPRS DTU to send the data to the remote data center via the Internet.

System software design

Network Management Software based on Z-stack

The network application was written in C and designed to run on a CC2430 system-on-chip (SoC) solution specifically tailored for IEEE 802.15.4 and ZigBee applications. The code for each node was based on the Z-Stack supported by an Operating System Abstraction Layer (OSAL). OSAL is an event driven non-real-time operating system (for a detailed description see the documentation of Texas Instruments [START_REF]Z-Stack OS Abstraction Layer API F8W[END_REF] , Inc.). The components of the Z-Stack are implemented as separate tasks and information is passed inside the stack using the OSAL messaging system.

Using a tree-topology WSN, a coordinator is responsible for initiating and maintaining the network. After joining the network, the sensor nodes obtained 16-bit short network addresses, which identified data from each sensor node. Since the low LQI and RSSI indicated higher packet losses, we acquired LQI and RSSI to estimate performance for the WSN. In the Z-stack, LQI can be directly read from the receiving data packet, and assuming the structure is defined as pkt, then the LQI = pkt-> Link Quality; the RSSI value was not directly allocated in the structure, and thus we need to read it from the underlying protocol stack, and then the application layer calls.

Monitoring Center Program Design

The monitoring center software was developed to receive and transmit TCP protocol packets, which communicated with GPRS terminals. Using a CAsyncsocket class provided by Visual C++, the software easily achieved socket communications. After data reception, the received data is stored in the database. According to the actual needs of the project, data centers permit users to conduct these operations, e.g. setting the acquisition cycle, selecting each channel for each node to be connected to the sensors, and transporting the downlink commands to the corresponding nodes in the network, and then sensor nodes periodically call the corresponding function based on the commands.

Web data release

As mentioned above, a method to view the data easily via a Web browser is very important. Here, data representation challenges arise when dealing with wireless sensors. First, the data must be packaged by the wireless sensor node and sent in an understandable manner over the WSN. The data must be interpreted by a computer that stores or displays the data, which includes the network addresses of nodes, the collected sensor data, and the RSSI and LQI values and power consumption. To make the data accessible by a large range of applications, efforts should be made to determine the best structures for storing the data in databases.

The client browser running on the Web page is based on a. Net framework development, development tools, mainly Visual Studio 2008, and SQL Server 2005. The web page is shown in Fig. 3.

This Web page includes five main functions: real-time data, historical data, network topology and node deployment management, and user management. The real-time data module allows users to view real-time data from each sensor node; the historical data module allows the user to select the time range for acquiring data. Also, the network topology and deployment management functions permit the user to check the status of the network and the actual deployment of nodes, so that the user can see whether the need to replace batteries or re-deploy the nodes following the growth of the crops is indicated.

Results and discussion

To verify the proposed system, we conducted experiments both in the laboratory and the greenhouse. In the first stage, a small ZigBee network with several nodes was deployed to collect data from SHT11 and infrared temperature sensors, in the light upper plane, and to add analog channel selection in the transformer, and experimental testing is conducted to verify the proposed hardware and software solutions. In the second stage, the WSN was deployed in the greenhouse to assess system performance, e.g. range, robustness and flexibility. Fig. 4 depicts the experimental setup in the greenhouse.

Fig.4. Image of device in the greenhouse

As shown in Fig. 5, we sent transport downlink commands from the remote server to nodes in the WSN, with a new configuration table for obtaining sensor data from the greenhouse. Fig. 6 shows real-time data via the browser. When considering the deployment of wireless multi-hop networks in the greenhouse, we must evaluate basic performance parameters such as radio performance (e.g., received signal strength, coverage ranges and link failure probability) with growth of crops. RSSI and LQI are important indicators of the measurement for link quality. In this experiment, the RSSI value versus the change of distance and obstacles is depicted in Fig. 7, indicating that obstacles had a major impact on link quality.

Fig.7. RSSI Measurement

Also, the network nodes periodically upload their own network information and data collected, including topology information to the data center stored in the database. The data in the database dynamically updates every hour, and when the client queries the topology, the web server then searches the database and displays the network topology in the browser. The client can see which node has left the network because of energy depletion and other reasons via the topology view, and then can add new nodes and re-deploy nodes as needed, as shown in Fig. 8.

Conclusions

The application of the WSN as a measurement tool in broad ranges for monitoring environmental and plant parameters has the obvious advantages of faster deployment, unlimited installation flexibility for sensors, and better mobility than wired networks. Thus, the Web-based system has realized the display of the network topology, and the sensor data from the nodes. RSSI and LQI were important performance indicators for data transmission, and the system was able to obtain RSSI and LQI values with the growth of crops in the greenhouse. Also, the system offers flexibility, i.e. it is customizable in terms of replacing sensors to enable variations such as the type of sampling channel and the sampling frequency used.

Fig. 1 .

 1 Fig. 1. Overall system architecture of the web-based remote sensing network

Fig. 3 .

 3 Fig.3. Web data release

Fig. 5 .

 5 Fig.5. Channel configuration of each node by monitor center

Fig. 6 .

 6 Fig.6. Real-time data displays via the web

Fig. 8 .

 8 Fig.8. Network topology

Acknowledgments

. This research was supported by the National High Technology Research and Development Program of China (863 Program, Grant 2008AA10Z201; Grant 2006AA10Z202).