Nora M Dempsey

Arnaud Walther

Frederic May

Dominique Givord

Kirill Khlopkov

Oliver Gutfleisch

High performance hard magnetic NdFeB thick

Keywords: numbers: 75, 50, Vv, 75, 70, -i

come

NdFeB thin films with excellent hard magnetic properties have been prepared by sputtering 1 and Pulsed Laser Deposition. 2 Out-of-plane texture was induced by depositing the films onto heated substrates in both 1-step (directly crystallized) 1,2 and 2-step (crystallized during a post-deposition anneal) 3,4,5 processes. Thick films (≥5 µm) of such high performance hard magnetic materials have potential applications in magnetic MEMS (Micro Electro Mechanical Systems). 6 Their integration into MEMS requires the use of preparation techniques which can produce high deposition rates over large areas. In addition, the use of substrates which are compatible with today's MEMS technology (i.e. Si) is necessary for the exploitation of such materials. So far, the only group which has reported the successful growth of textured NdFeB thick films by high rate sputtering (≈30 µm/h) used metallic substrates. 3 in this letter, we report on the preparation and analysis of 5µm thick NdFeB films deposited on 100 mm Si substrates using high rate sputtering. The film's magnetic properties compare with those of high-quality sintered NdFeB magnets. {Ta (100 nm) / NdFeB(5 µm) / Ta (100 nm)} films were deposited onto (001) oriented Si substrates (diameter = 100 mm) at a rate of 18 µm/hour by triode sputtering of square targets of surface area 100 mm x 100 mm (note that the film thickness is reduced to 4 µm at the edge of the 100 mm wafer). The nominal composition of the NdFeB target was Nd 16.8 Fe 74.7 BB 8.5 .

During deposition, the substrate was either "cold" (no power to substrate heater, though the substrate temperature gradually rises during deposition, eventually reaching a temperature of about 230°C) or fixed at a temperature in the range 300 -500°C. Full wafers were annealed at 750°C for 10 minutes. Structural characterization was carried out using high resolution Scanning Electron Microscopy (LEO Gemini 1530, equipped with In-Lens and Quadrant Back Scattering (QBSD) detectors as well as Energy Dispersive X-ray Analyzer (EDX)) and

x-ray diffraction (Co radiation). For cross-sectional imaging, the samples were simply fractured while for plane-view imaging they were lightly polished to remove the Ta capping layer. Room temperature magnetic properties were characterized with a Vibrating Sample Magnetometer.

In the as-deposited state, films prepared at T sub ≤ 450°C appear to be amorphous (no xray diffraction peaks are resolved and the films are magnetically soft) while the films deposited at 500°C are crystallized (appearance of Nd 2 Fe 14 B xrd peaks and an out-of-plane coercivity of 0.3T) (data not shown). Structural and magnetic properties of the annealed samples are compiled in figure 1. The samples' fractured cross-sections, observed with an inlens detector, are shown in column 1. Films deposited at substrate temperatures up to 450°C have an equiaxed granular microstructure, in stark contrast with films deposited at 500°C, which have a columnar structure with individual grains traversing the entire film thickness of 5µm (note that in the as-deposited state, no grain structure is observed up to 450°C while a columnar structure exists in films deposited at 500°C, however it is less distinct than in the annealed state). Inter-granular fracture is predominant and many grain surfaces have a peculiar sponge like aspect due to the presence of small spherical holes (φ = 10-50 nm), the density of which decreases with increasing deposition temperature. Such holes were already identified in films prepared by a two-step process. 3,4 Kapitanov et al. suggested that they may be due to the segregation of trapped Ar during the post-deposition annealing process. 3 The samples' polished plane-view sections, imaged with a Quadrant Back Scattering Detector, are shown in column 2. While electron backscattered diffraction analysis (not shown) identifies the grey grains in these plane-view images as Nd 2 Fe 14 B, no diffraction patterns could be obtained on the large dark zones observed. EDX analysis indicates that the films have an overall Fe:Nd atomic ratio of 6.1, which is slightly lower than the value of 7 for Nd 2 Fe 14 B, indicating that any significant quantity of additional phases should be Nd-rich and thus show a brighter contrast compared with Nd 2 Fe 14 B grains in the QBSD images. TEM analysis (imaging, EELS and EDX) indicates that these dark zones are in fact holes. [START_REF] Khlopkov | Handbook of Magnetic Materials[END_REF] The holes show a wide distribution in size, and except for the "cold" deposited sample, the size of the largest holes is comparable to that of the Nd 2 Fe 14 B grains. Very few holes are observed in the films deposited at 500°C, and these are significantly smaller that the average diameter of the Nd 2 Fe 14 B columnar grains. These large irregular shaped holes appear to be specific to our preparation procedure. Their size depends on the surface area of the annealed sample as well as the annealing conditions (heating rates). We attribute their formation to concurrent grain growth and volume change upon crystallization (a 10% increase in density has been reported upon crystallization of amorphous RE-TM films). 8 The direct crystallization of films deposited at 500°C explains the near absence of such holes in these films.

Refinement of the Nd 2 Fe 14 B grain size with increasing deposition temperature up to 450°C is observed, with the average grain size decreasing from a value of the order of 800 nm for the sample deposited on a "cold" substrate to a value of the order of 200 nm for the sample deposited at 450°C. This indicates that the density of Nd 2 Fe 14 B nucleation sites increases with substrate temperature. It is likely that these nucleation sites are responsible for the development of texture in the films, the exact nature of the nucleation sites remaining to be established (a study of films in their as-deposited state is underway). The change to a columnar structure for a deposition temperature of 500°C is attributed to the direct crystallization of Nd 2 Fe 14 B during deposition under growth conditions favorable to columnar grain formation. Though all films show out-of-plane crystallographic c-axis texture, a progressive increase in the degree of texture with increasing deposition temperature is evidenced by a significant sharpening of the (006) x-ray diffraction pole figures shown in the third column of figure 1.

Correspondingly, an increase in out-of-plane magnetic anisotropy is clearly identified in the fourth column, in which in-plane and out-of-plane hysteresis curves are compared. Though other authors attributed the anisotropic magnetic nature of films produced by such a two-step procedure to the development of a columnar grain structure, 4 we clearly demonstrate that such a columnar structure is not necessary. The variation of remanence, coercivity and energy product with deposition temperature are plotted in figure 2. While the remanence increases with deposition temperature, due to the increase in out-of-plane texture, the coercivity varies little (µ 0 H c ≈1.6 T). This is in contrast to bulk NdFeB samples, in which easy-axis coercivity tends to be reduced as texture is increased. [START_REF] Khlopkov | [END_REF] The maximum energy product (400 kJ/m 3 ) which was achieved for the films deposited at 500°C is comparable to that of high-quality sintered magnets. 10 All films show a two-stage initial magnetization behavior in the out-of-plane measurements with a first stage of high susceptibility in low fields (<0.2T) followed by a second low susceptibility stage. The relative contribution of the former decreases with increasing deposition temperature up to 450°C, and then rises again for a deposition temperature of 500°C. We attribute this 2-stage behavior to the presence of both multi-domain (high susceptibility) and single-domain (low susceptibility) Nd 2 Fe 14 B grains. [START_REF] Givord | RE-Fe Permanent Magnets[END_REF] The influence of deposition temperature on the relative contribution of each population to the sample's magnetization is directly related to its influence on grain size. The switch from single to multi-domain state should occur at the critical single domain particle size, which for Nd 2 Fe 14 B is estimated to be 300 nm. [START_REF] Livingston | [END_REF] This agrees with the experimental observation that the biggest change in the relative contribution of low and high susceptibility behavior occurs between 300°C and 400°C, when the average grain size is refined from above to below 300 nm. The rise in multi-domain behavior in the film deposited at 500°C may be explained by an increase in grain volume owing to the shift from equiaxed to columnar grains which traverse the entire film. An alternative explanation for the low susceptibility stage would be domain wall pinning. However, the irregular shaped holes present in our films are much too large to act as pinning sites (to be effective, defects should be of a size comparable to the domain wall width, which for Nd 2 Fe 14 B is estimated to be 5 nm), [START_REF]The structuring of these films for integration into prototype micro-systems is being studied in collaboration with CEA-LETI (Grenoble) within the ANR "Nanomag2" project[END_REF] while the density of nanometer sized spherical pores which could act as efficient pinning sites decreases as the low susceptibility contribution increases.

In addition to the anomalous magnetic volume effect (Invar effect), Kapitanov et al. demonstrated that the thermal expansion curves of NdFeB films produced by such a two step procedure display an expansion anomaly during crystallization of the Nd 2 Fe 14 B phase. 3 Owing to this, separated their films from their metallic substrates, prior to annealing them in small pieces. In this study, where the post-deposition annealing was carried out on the entire 100 mm wafer, it was found that the central region (diameter ≈ 30 mm) of all films has a tendency to peel off during annealing (note that all results presented above were for sections of film which remained tightly adhered to the Si substrate). We attribute this effect to a combination of three factors: the above mentioned expansion anomaly during crystallization, differential thermal expansion of the magnetic layer and the substrate and to a degradation of the Si -Ta interface caused by diffusion during the high temperature annealing step. [START_REF] Khlopkov | Handbook of Magnetic Materials[END_REF] This peel off is not necessarily problematic since the out of plane magnetization of the films is optimally exploited in structured objects of which the lateral dimensions are of the order of the film thickness. No peel off occurs in Ta (100 nm)/ NdFeB (5µm) / Ta (100 nm) films deposited through a mask with mm sized holes or onto pre-patterned 100 mm wafers which have topographic relief (trench motifs with individual trenches of depth 5 µm with trench/wall widths on the scale of 5-100 µm). [START_REF] Givord | RE-Fe Permanent Magnets[END_REF] We have recently produced mechanically intact 50 µm thick films on 100 mm Si wafers by depositing through the same mask and using a 1-step procedure in which the films are directly deposited in the crystalline state.

We have studied the structural and magnetic properties of thick NdFeB films deposited on Si substrates. Though the best textured films have a columnar structure, such a structure is not necessary for magnetic anisotropy. The development of texture in films produced using a two step. The optimum films produced have magnetic properties (µ 0 M r = 1.4 T, µ 0 H c = 1.6 T and (BH) max ≈ 400 kJ/m 3 ) which are comparable to those of the best sintered bulk NdFeB magnets. The combination of high sputtering rates, large sputtering surfaces, microtechnology compatible substrates and excellent magnetic properties are very promising for the integration of hard magnetic materials into MEMS. This work was carried out in the framework of the ANR "Nanaomag2" project. The authors would like to thank N. Kornilov for his invaluable contribution to the triode sputtering activity at Institut Néel. K. Khlopkov is grateful for financial support from the DFG (SFB 463). FIG. 2. Remanence µ 0 M r , coercivity µ 0 H c and estimated maximum energy product (BH) max as a function of deposition temperature (note all films were annealed at 750°C for 10 minutes).

FIG. 1 .

 1 FIG. 1. Comparison of the evolution in structural and magnetic properties of NdFeB films as a function of deposition temperature (note all films were annealed at 750°C for 10 minutes). Column 1 : Fractured cross sections imaged with an in-lens detector Column 2 : Polished plane views imaged in QBSD mode Column 3 : XRD pole figure of (006) diffraction peak of Nd 2 Fe 14 B Column 4 : In-plane (ip) and out-of-plane (oop) hystersis loops and the initial oop magnetization curves (oop loops were corrected with a demagnetization factor N = 1 ).


A Walther

K Khlopkov

O Gutfleisch

D Givord

N M Dempsey
email: nora.dempsey@grenoble.cnrs.fr

Evolution of magnetic and microstructural properties of thick sputtered NdFeB films with processing temperature

Ta (100 nm) / NdFeB (5 µm) / Ta (100 nm) films have been deposited onto Si substrates using triode sputtering (deposition rate ~ 18 µm/h). A 2-step procedure was used : deposition at temperatures up to 400°C followed by ex-situ annealing at higher temperatures. Postdeposition annealing temperatures above 650°C are needed to develop high values of coercivity. The duration of the annealing time is more critical in anisotropic samples deposited onto heated substrates than in isotropic samples deposited at lower temperatures.

For a given set of annealing conditions (750°C/ 10'), high heating rates (≥ 2000°C / h ) favour high coercivity in both isotropic and anisotropic films. The shape and size of Nd 2 Fe 14 B grains depend strongly on the heating rate.

Introduction

NdFeB thin films with excellent hard magnetic properties have been deposited by RF sputtering [1], magnetron sputtering [2] and Pulsed Laser Deposition [3]. Thick films of such high performance hard magnetic materials have potential applications in magnetic MEMS (Micro Electro Mechanical Systems) [4]. High quality NdFeB thick films (≤ 300 µm) have been prepared by high rate triode sputtering [5]. These authors were the first to report that outof-plane texture can be developed in NdFeB films by a 2-step procedure: deposition at a temperature below the crystallization temperature followed by a high temperature postdeposition anneal. While samples deposited at room temperature were magnetically isotropic, samples deposited at higher temperatures were anisotropic and the degree of texture was found to increase with substrate temperature [5]. We have studied the evolution in both magnetic and microstructural properties in 5 µm thick films, produced using such a 2-step procedure, as a function of substrate temperature [6]. In this study, the influence of postdeposition annealing conditions on the magnetic and microstructural properties of NdFeB films deposited under different conditions is assessed.

Experiment

A Nd 16.8 Fe 74.7 BB 8.5 target was triode sputtered in an Ar plasma at a power of 1000 W. 5 µm thick NdFeB layers, with 100 nm thick Ta buffer and capping layers, were deposited at a rate of 18µm/h onto Si. The substrate was either not furnace heated (we label this "cold" deposition, although the substrate temperature rose to 230 °C during deposition) or maintained at a fixed temperature of 400 °C. Samples were then annealed ex-situ in a vacuum of 10 mbar. The heating rate, annealing temperature and annealing time were varied.

-5

Magnetic properties were measured at 300 K with an Oxford VSM. Microstructures were investigated with a high resolution LEO FEG SEM (GEMINI 1530).

Results and discussion

Annealing treatments at different temperatures have been carried out on "cold" deposited NdFeB films. These samples were rapidly heated (from room temperature to the annealing temperature in approximately 40 seconds) and maintained at the annealing temperature for 10 minutes. Such films do not show any preferential texture and their in-plane hysteresis loops are compared in figure 1. The highest coercivity (µ 0 H c = 1.95 T) was obtained for the maximum annealing temperature (850 °C). Note that coercivity is significantly increased between the annealing temperatures of 650 °C and 675 °C. Considering that the x-ray diffraction peaks of Nd 2 Fe 14 B are clearly resolved for all samples (data not shown), we tentatively attribute this large increase in coercivity to the redistribution of a Nd-rich intergranular phase leading to a more homogeneous and complete covering, and thus better decoupling, of the Nd 2 Fe 14 B grains.

The influence of annealing time was assessed on both the "cold" and hot deposited films.

Samples were rapidly heated to 750 °C and annealed for times of 0 to 60 minutes. "Cold" deposited films show high coercivity even for the shortest annealing time and the coercivity varies little over the time scale studied, though a slight decrease is observed for the longest annealing time of 60 minutes (figure 2a). On the contrary, the coercivity of hot deposited films, which show high crystallographic texture (c-axis perpendicular to the film plane), increases significantly with annealing time (figure 2b). In this case, a maximum coercivity of 1.7 T was achieved for the longest annealing time.

The influence of heating rate was also assessed. Both hot and "cold" deposited films were annealed at 750 °C for 10 minutes with heating rates of 500 °C/h, 1000 °C/h, 2000 °C/h and a rapid heating (RT to annealing temperature in 40 seconds, i.e. 65000 °C/h) as used above. For both film types, magnetic properties are strongly dependent on the heating rate and a fast heating rate promotes the development of coercivity. However, differences can be noticed between the behaviour of "cold" deposited (figure 3(a)) and hot deposited films (figure 3(b)). Whereas, for "cold" deposited films, a heating rate of 1000°C/h yields the same magnetic properties as for 500°C/h, coercivity is higher for the faster heating rate in hot deposited films.

Moreover, contrary to "cold" deposited films, annealing at 2000°C/h yields a slightly higher coercivity than a rapid heating of hot deposited ones.

The shape and size of the Nd 2 Fe 14 B grains are found to depend strongly on the heating rate for both film types. While rapidly heated films have equiaxed grains throughout the film thickness, films heated at slower rates have a mixed structure, with columnar grains in the lower film section and equiaxed grains in the upper film section (figure 4).

Plane view images of the top of the films show that the equiaxed grains in the films heated at slow rates are much larger than those formed in the rapidly heated films (figure 5). In our previous study, it was shown that both the size and shape of Nd 2 Fe 14 B grains depend strongly on the substrate temperature during deposition, and a surprising result was that samples with very different grain sizes (in the range 0.1 -1 µm) and shapes (equiaxed vs columnar) had very similar values of coercivity [6]. Thus, the difference in the size and shape of grains in samples heated at different rates is not sufficient to explain the differences in coercivities observed. These differences may be due to differences in the distribution of a Nd-rich intergranular phase and secondary phases. TEM studies are now underway.

Conclusion

5µm thick NdFeB films have been deposited at a deposition rate of 18 µm/h and excellent hard magnetic properties were achieved (µ 0 H c ≤ 1.95T) following post-deposition annealing.

Films deposited onto heated substrates are highly textured. The threshold temperature for developing coercivity is higher than the crystallization temperature of the Nd 2 Fe 14 B phase and is in the range of the eutectic melting temperature of the Nd-rich intergranular phase. For the post-deposition annealing conditions studied, high heating rates favour high coercivity.

Figure 1 :

 1 Figure 1 : In-plane VSM measurements of Si/Ta/NdFeB(5µm)/Ta films "cold" deposited and subsequently annealed at different temperatures for 10 minutes (inset : coercivity vs annealing temperature).

Figure 2 :

 2 Figure 2 : VSM measurements of Si/Ta/NdFeB(5µm)/Ta films deposited "cold" ((a), in-plane loops) and at 400°C ((b) out-of-plane loops non corrected for demagnetisation), and subsequently annealed at 750 °C for different times.

Figure 3 :

 3 Figure 3 : VSM measurements of Si/Ta/NdFeB(5µm)/Ta layers deposited "cold" ((a), in-plane loops) or at 400°C ((b), out-of-plane loops, non corrected for demagnetisation) and annealed at 750 °C for 10 min with different heating rates.

Figure 4 :

 4 Figure 4 : SEM cross sectional view (in-lens detector) of the fracture surface of "cold" deposited NdFeB films annealed at 750 °C for 10' with a rapid heating rate (left) and a heating rate of 1000 °C/h (right).

Figure 5 :

 5 Figure 5 : SEM plane view (QBSD detector) of polished surfaces of "cold" deposited NdFeB films annealed at 750 °C for 10' with a rapid heating rate (left) and a heating rate of 1000 °C/h (right). The white contrast is attributed to a Nd-rich phase.


Marie-Axelle Granié

Thierry Brenac

Florence Huguenin-Richard

Thierry Saint-Gérand

Mohand Medjkane

Elisa Maitre

Jean-Francois Peytavin

Florent Varet

Cécile Coquelet

Pedestrian adolescents: mobility and safety at secondary school in France

teaching and research institutions in France or abroad, or from public or private research centers.

PEDESTRIAN ADOLESCENTS: MOBILITY AND SAFETY AT SECONDARY

SCHOOL IN FRANCE Marie-Axelle Granié 1 , Thierry Brenac 1 , Florence Huguenin-Richard 2 , Thierry Saint-Gérand 3 , Mohand Medjkane 3 , Elisa Maître 1 , Jean-François Peytavin 1 , Florent Varet 4 , Cécile Coquelet 1 .

1 IFSTTAR-TS2-LMA, France 2 University of Paris Sorbonne, France 3 University of Caen, France 4 Aix-Marseille University, France

The road crash peak among children is around 11-12 years-old in France, as in many industrialized countries, at the time of entry in secondary school. The reasons why this vulnerability increases while the skills involved should have improved are not clear. By linking two fields of analysis of road safety (fine spatial analysis of crashes and depth analysis of behaviors and psychosocial factors), our project aimed to finely identify the mobility and pedestrian accident involvement of the 10-15 years old and specify geographical, psychological and sociological determinants of both variables. A study of accident processes among pedestrians aged 10-15 years over France for the period 2002-2011 was conducted, based on the national accident file and on a sample of accident police reports. It was completed in the field of study of the Lille region (France) by the spatial analysis of local accident data (including the identification of accident scenarios) and the mobility of 10-15 years, using data from the 2006 household travel survey. Two field surveys were then conducted. A first survey among 2500 junior high school students has identified the fine mobility practices and their socio-spatial determinants. It also explored the demographic and psychological variables (age, gender roles, perceptions of social norms, risks, rules, level of supervision) explaining the reported pedestrian risky behaviors. A second survey among 300 junior high school students focused on their perceptions of known and unknown walking environments. It enabled to draw up a sensible mapping of their actual walking environment and a qualitative analysis of the elements using to judge the pleasantness and safety and characterize their representations of positive or negative actual and virtual travels as pedestrian. The results allow a better understanding of the phenomena and processes involved in the accident of pedestrian adolescents and to identify measures needed to overcome this problem.

Keywords: Pedestrian, adolescents, safety, mobility


Luis M Camarinha-Matos

Hamideh Afsarmanesh
email: h.afsarmanesh@uva.nl

Collaborative Systems for Smart Environments: Trends and Challenges

Keywords: Smart Environments, Collaborative Networks, Cyber-Physical Systems

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Smart environments represent a fast growing area which is often presented as an evolution of the notion of pervasive or ubiquitous computing, initially suggested by Mark Weiser [START_REF] Weiser | The computer of the twenty-first century[END_REF] as "a physical world that is richly and invisibly interwoven with sensors, actuators, displays, and computational elements, embedded seamlessly in the everyday objects of our lives, and connected through a continuous network". From this notion, smart environments emerge as "small worlds that are able to acquire and apply knowledge about the environment and its inhabitants in order to improve their experience in that environment" [START_REF] Cook | How smart are our environments? An updated look at the state of the art[END_REF]. Similar to pervasive computing, in smart environments there is the idea of a physical environment interwoven with a network of devices and systems, sensors and actuators. But now with a more explicit purposeusing technology to improve the life or comfort of its inhabitants.

Examples of smart environments include: closed spaces with relatively welldefined boundaries, such as home, office, or car, and open spaces such as streets, bridges, parking lots, or smart cities [START_REF] Augusto | Intelligent Environments: a manifesto[END_REF]. The relevance of this area can be illustrated by the growing number of applications in domains such as health monitoring, elderly care provision, transportation and logistics, entertainment, environment monitoring, smart homes, smart offices, and smart shop floors, etc.

In technical terms, smart environments result from the convergence of a variety of contributions including sensor networks, pervasive and mobile computing, robotics, miniaturization of hardware components with embedded processing power, reliable wireless network protocols, increased automation associated to everyday devices such as home appliances, natural human-computer interfaces, artificial intelligence, middleware platforms, etc. In fact, this is clearly an area that is leveraged by multidisciplinary contributions.

When systems involved in smart environments grow and involve large number of entities (hundreds, thousands, or millions), flat organizational structures are not sufficient to support effective management. Therefore we also need to address the organization of such entities in "communities" and "societies" within the "ecosystems" of cyber-physical artefacts. Within such organizational structures collaboration among artefacts can then support the creation and provision of composed value-added services, by service developers. Such environments and associated services are opening new grounds for business opportunities, which typically require the collaboration of multiple stakeholders, and also challenge the positioning of enterprises in society, leading to new concepts such as sensing enterprise. Collective awareness then also becomes a necessary property of such systems. Furthermore, some artefacts have a nomadic characteristic, i.e. they move between spaces (e.g. gadgets or sensors carried by the human user or by other moving objects), which in turn raises the issues of artefact discovery, acceptance (by the "visited" ecosystem), definition of roles, access policies (addressing security and safety), pro-active promotion of services, and system dynamics. In this context, data/service interoperability assumes a fundamental role.

Additionally, people are increasingly surrounded by and depend on a fast growing collection of gadgets and other smart objects in their daily lives. These artefacts in turn have gradually changed people's habitat and extended their sensorial and acting capabilities. User acceptability is therefore the base criterion for the design of any such systems, in the context in which users' expectations increase as the technology evolves. Another important criterion for designing such systems is the trustworthiness of the components and the composed systems, which is mainly associated to the notions of reliability, risk, privacy, and security. Furthermore, with the trend towards more personal data being available through the cloud, monitoring and understanding "what people will accept" in exchange of higher value services, becomes relevant. On the other hand, smarter decision making and higher levels of autonomy is required from systems, in order to neither "overload" the humans with excess of information, nor requiring constant input, e.g. "pressing buttons" to interact with the cyber-physical world, considering the real-time access to a large number of devices.

In this context, collaborative networks can play a significant role in a number of areas facilitating the design and development of complex smart environments. Although already identified by various authors [START_REF] Cook | How smart are our environments? An updated look at the state of the art[END_REF], [START_REF] Augusto | Intelligent Environments: a manifesto[END_REF], such collaborative perspective is so far only briefly touched by current developments.

This introductory text aims at giving a brief overview of the area and its challenges, particularly from the collaborative networks perspective, contributing to identify further research directions.

Related Areas

A number of different partially overlapping related paradigms have been introduced in recent years, among which the Ambient Intelligence (AmI), Ambient Assisted Living (AAL), and Sensing Enterprises can be named. These paradigms address environments supported through the collaboration among human actors, intelligent agents, and smart devices.

Different aspects of the above paradigms are further addressed by related work in several technology-based areas, including the Cyber Physical Systems (CPS), Internet of Things (IoT), Internet of Events, Sensing Networks, etc.

As an outcome of these research and development directions, a number of advanced areas of application have emerged illustrating substantial impact in improving the quality of life in societies, as exemplified by the Smart Cities, Smart Homes, and a number of Intelligent Infrastructures such as those manifested as Intelligent Transportation Systems and Smart Grid, etc.

Related paradigms

Ambient Intelligence (AmI):

A paradigm that represents electronic-enhanced environments, which are sensitive and responsive to the presence of people [START_REF] Cook | Ambient intelligence: Technologies, applications, and opportunities[END_REF], considering their needs, habits, and even emotions. The notion is similar to smart environment, but perhaps with more emphasis on human-computer interaction, context awareness, and provision of intelligent services.

A number of characteristics are usually presented to identify AmI systems, including: context awareness, personalization (tailored to the needs of each individual), acting anticipatory (anticipating the needs of individuals), adaptive (coping with the changing needs of individuals), ubiquitous (integrated in our everyday environments), and transparent (making computers disappear in the background) [START_REF] Cook | Ambient intelligence: Technologies, applications, and opportunities[END_REF], [START_REF] Acampora | A Survey on Ambient Intelligence in Health Care[END_REF].

Many application examples can be found in the areas of healthcare and elderly care [START_REF] Acampora | A Survey on Ambient Intelligence in Health Care[END_REF], but references in other sectors can also be found [START_REF] Cook | Ambient intelligence: Technologies, applications, and opportunities[END_REF], [START_REF] Kerner | Ambient Intelligence as One of the Key ICT factors for Energy Efficiency in Buildings[END_REF], e.g. in smart homes, intelligent transportation, rescue / crisis management, education, workplaces, energy management, etc. The convergence between AmI and social computing is attracting growing interest [START_REF] Mckenna | Social Interactions with Wireless Grids: Conceptualizing the 21 st Century Ambient Information[END_REF], namely with the new interaction facilities offered by mobile computing and wireless networks.

Ambient Assisted Living (AAL):

AAL is a paradigm widely used in Europe representing a kind of AmI that provides safe and adapted environments for people with specific needs, allowing them to live more independently [START_REF]Ambient Assisted Living -Catalog of Projects[END_REF]. Most developments in AAL are focused on assisting elderly [START_REF] Camarinha-Matos | Care Services Ecosystem for Ambient Assisted Living[END_REF], [START_REF] Sun | Promises and Challenges of Ambient Assisted Living Systems[END_REF], namely to help them live independently in their home environments. Most efforts in the last decade have been focused on transferring the dependence from human assistance to assistive devices [START_REF] Van Den Broek | AALIANCE Ambient Assisted Living Roadmap[END_REF]. But even earlier works such as the TeleCARE project [START_REF] Camarinha-Matos | TeleCARE: Collaborative virtual elderly care support communities[END_REF], [START_REF] Afsarmanesh | Management of Federated Information in Tele-assistance Environments[END_REF], pointed out the need for a collaborative systems approach to AAL, both at the infrastructure level (collaborating multi-agent systems) and social computing level (virtual communities).

In fact, the realization that a pure technological perspective also has the negative effect of reducing the social connections of the assisted people has triggered other efforts to combine the basic technological assistive aspects with social computing [START_REF] Sun | Promises and Challenges of Ambient Assisted Living Systems[END_REF]. Furthermore, provision of integrated care and assistance services require the involvement and collaboration of multiple stakeholders. This led to a shift in the AAL developments, from a device and infrastructure focus, to a care ecosystem [START_REF] Rosas | Development of an Ecosystem for Ambient Assisted Living[END_REF], [START_REF] Camarinha-Matos | Active Aging with Collaborative Networks[END_REF]. Such perspective is well represented in the BRAID roadmap for ICT and ageing [START_REF] Camarinha-Matos | A comprehensive research roadmap for ICT and ageing[END_REF] and recent development initiatives such as the AAL4ALL project [START_REF] Camarinha-Matos | Care Services Ecosystem for Ambient Assisted Living[END_REF], [START_REF] Sun | Promises and Challenges of Ambient Assisted Living Systems[END_REF].

Sensing enterprise: A paradigm introduced by the FInES (Future Internet Enterprise Systems) cluster of projects [START_REF] Fines | Embarking on New Orientations Towards Horizon[END_REF] to refer to an enterprise making decisions by using multi-dimensional information captured through physical and virtual objects in its environment, and providing added value information to enhance its global context awareness. In other words, this notion particularly focuses on enriching enterprises' context awareness through intelligent, interconnected, and interoperable smart components and devices that power enterprise systems, making them responsive to events in real time and aiming at reaching seamless transformation of (raw) data to (tailored) information and (experienced) knowledge [START_REF] Thoma | Linked Services for Enabling Interoperability in the Sensing Enterprise[END_REF].

Related supporting technologies

Cyber-Physical Systems (CPS):

Engineered systems that are built from and depend upon the synergy of computational and physical components [START_REF] Nfs | Cyber-Physical Systems (CPS)[END_REF]. Numerous projects (e.g. AMADEOS, CASAGRAS2, CONET, GAMBAS, SCUBA, COMPASS, DANSE, DYMASOS, to name a few), have addressed the development of communication middleware systems to support seamless and trustworthy interoperation of heterogeneous subsystems and artefacts, new programming paradigms to support adaptive applications, methods to deal with real-time requirements, and management of devices with critical constraints such as energy, computing and communication capabilities. Many successful developments have been focused on vertical use cases, while those solutions prove to be difficult to generalize and scale up. The cost-effective engineering of larger CPSs, coping with an evolving nature and ensuring added-value to their users, remains a challenge. [START_REF]Vision and Challenges for Realising the Internet of Things[END_REF]. In this context, a "thing" is understood either as a real/physical or digital/virtual entity that exists and moves in space and time and is capable of being identified [START_REF] Camarinha-Matos | Contributing to the Internet of Things[END_REF]. Large classes of the objects that are connectable to Internet constitute (smart) sensors and (smart) devices, able to provide status information, thus an important technological enabler for smart environments. IoT is in fact a way to materialize the vision of a technology that becomes invisibly embedded in our natural surroundings, but present themselves whenever we need them.

Internet of Things (IoT): A term representing "a dynamic global network infrastructure with self-configuring capabilities based on standard and interoperable communication protocols where physical and virtual "things" have identities, physical attributes, and virtual personalities, and use intelligent interfaces, and are seamlessly integrated into the information network"

There has been quite some discussion on the relationship between Cyber-Physical Systems and Internet of Things. For some authors the two terms carry some "geographical bias", being CPS more popular in the USA, while IoT is more prevalent in Europe and Japan. Others refer to CPS as being originated in the embedded systems community, while IoT comes from the area of Internet computing. These are certainly limited perspectives, and other authors try to relate the two concepts in terms of their focus [START_REF] Camarinha-Matos | Contributing to the Internet of Things[END_REF], [START_REF] Jeschke | Everything 4.0? -Drivers and Challenges of Cyber Physical Systems[END_REF]. In any case, there is a growing convergence between the two areas since CPSs are becoming more Internet-based and complex CPSs / complex Systems-of-Systems increasingly combine open systems with closed and semi-closed ecosystems.

Internet of Events:

Although it is less popular than IoT, it corresponds to a perspective of the IoT that puts the emphasis on time dependency and discrete events handling [START_REF] Ortner | Temporal and Modal Logic Based Event Languages for the Development of Reactive Application Systems[END_REF]. As such, events modeling and management, time critical reactivity, and process modeling and supervision are the relevant issues here.

Sensor Networks: Being implicit in all the above areas, sensor networks are a fundamental component of any smart environment which relies first and foremost on sensory data acquired from multiple sensors in distributed locations of physical environments. One of the most relevant topics in this area is the wireless sensor networks which typically comprise large numbers of spatially distributed autonomous sensors that have limited computing, communication, and energy autonomy capabilities. In this context, collaboration appears as a way to cope with those limitations, leading to the emergence of the notion of collaborative sensor networks. Examples of collaboration in such networks include [START_REF] Li | Collaborative wireless sensor networks: A survey[END_REF]: collaboration in localization, energy awareness and collaboration to reduce energy consumption and extend system's lifetime, collaborative sensing and perception, collaboration in sending messages through different paths in response to security threats, self-adapting routing, covering "sensing holes" resulting from inactive nodes, etc.

Closely related to the increase in the sensing capabilities, the term big data has become popular. It refers to massive data sets and stream computing that due to their large size and complexity are beyond the capabilities of traditional databases and software techniques. The expansion of sensing capabilities, sensor networks, smart devices, and other sources, generating huge amounts of data, motivates the importance of this topic. Interest in big data has emerged in science, business, security, and many other areas [START_REF] Fines | Embarking on New Orientations Towards Horizon[END_REF]. Context awareness or collective awareness, supporting intelligent services for smart environments, may require the adoption of techniques being developed for big data.

Advanced application areas

Smart Home: Sometimes also known as home automation, are smart environments at home that rely on networked technologies to provide inhabitants with better comfort and security [START_REF] Allameh | Smart Home as a smart real estate: a state of the art review[END_REF], [START_REF] Alam | A Review of Smart Homes-Past, Present, and Future[END_REF]. Typical functions include monitoring and control of lighting, temperature and ventilation, home access security, entertainment, control of home appliances, etc.

Although home automation technologies have been around for the last thirty years, for a while, their developments evolved in isolated niches. Recent efforts are focusing on integrated solutions and the possibility of integrating different artefacts in a technology-agnostic manner, as aimed by initiatives such as openHAB [START_REF] Openhab | openHAB Open Source Automation Server[END_REF], FHEM [START_REF] Fhem | FHEM Home Automation Sever[END_REF], or openRemote [START_REF] Openremote | openRemote Open Source Automation Platform[END_REF]. In recent years there has been a growing attention devoted to energy awareness systems and energy efficiency, an opportunity to integrate smart home and smart grid technologies [START_REF] Gharavi | Smart Grid: The Electric Energy System of the Future[END_REF]. Developments in Internet of Things, natural user interfaces, wireless sensor networks, and service robotics are also adding new dimensions to this area [START_REF] Neßelrath | A Gesture Based System for Context -Sensitive Interaction with Smart Homes[END_REF], [START_REF] Borja | Integration of service robots in the smart home by means of UPnP: A surveillance robot case study[END_REF].

Smart Cities:

The concept of smart city has been gaining increasing importance in the research and policy making agendas, with many initiatives being promoted worldwide. And yet, the concept is not precisely defined, corresponding to different visions for different communities and stakeholders, also with variants according to geographical origin. A high level notion is that a smart city must be "able to optimise the use and exploitation of both tangible (e.g. transport infrastructures, energy distribution networks, natural resources) and intangible assets (e.g. human capital, intellectual capital of companies, and organisational capital in public administration bodies)" [START_REF] Neirotti | Current trends in Smart City initiatives: Some stylised facts[END_REF]. The results of an operational definition in this direction is presented in [START_REF] Giffinger | Smart cities ranking: an effective instrument for the positioning of the cities?[END_REF] that was applied to evaluate the degree of smartness of 70 medium-sized European cities, includes six dimensions of analysis: (i) "smart mobility", (ii) "smart environment", (iii) "smart governance" (iv) "smart economy", (v) "smart people", (vi) "smart living".

From an ICT focus, smart cities are characterized by pervasive computing and extensive sensing and information integration capabilities, in the various urban sectors, to help cities make better use of their resources. Implicit in all pilot initiatives towards building smart cities, is the need to engage and promote collaboration among multiple stakeholders, both public institutions and private organizations, as well as citizens. As such, collaborative networks can bring a fundamental contribution to this domain. As many projects are still at the level of building the base infrastructures, collaborative networks are not yet explicitly visible but undoubtedly they are a must when progressing towards providing integrated services.

Intelligent Infrastructures: are infrastructures that use computing and communication technologies, sensors, and other networked devices, to deliver relevant real-time data to their operators in order to optimize their use, minimize costs and prevent failures [START_REF] García-Murillo | The paradox of intelligent infrastructures[END_REF], as well as proving higher-level services to their users.

One example is given by the Intelligent Transport Systems, which are leading to the progressive introduction of new technologies based on electronics, sensorial systems, and communication and information technologies. For instance, road management policies, based on user-paying models, and the increasing concerns about traffic safety, establish requirements for a new family of emergent business services. A promising direction aims at offering new comprehensive service contracts integrating multiple possibilities of access to public transport systems, parking areas, subscription to innovative insurance policies, etc. [START_REF] Osório | A collaborative case study: The extended "ViaVerde" toll payment system[END_REF], [START_REF] Weber | ICT-enabled system innovations in public services: Experiences from intelligent transport systems[END_REF]. Another challenge is the development of collaborative eco-driving environments, focused on effective support of integrated services targeting transportation energy efficiency, costs saving, and improvement of safety in mobility.

Another example is the Smart Grid, or smart energy grid, which represents a move from a centralized, energy producer-controlled network to one less centralized and more consumer-interactive. Initially, it corresponds to an overlay of the energy distribution grid with an information and (smart) metering system [START_REF] Fon | Smart Grid Communications: Overview of Research Challenges, Solutions, and Standardization Activities[END_REF], [START_REF] Farhangi | A Road Map to Integration: Perspectives on Smart Grid Development[END_REF]. In the current stage, most efforts are very focused on infrastructure aspects. However, establishing a truly smart grid requires the participation of a large number of stakeholders, including producers, transmission and distribution operators, regulators, policymakers, and consumers. Thus, a next challenge is to adopt proper organizational models, governance structures, and to develop advanced tools to support collaboration among these players [START_REF] Camarinha-Matos | The Role of Collaborative Networks in Sustainability[END_REF].

Some Technical Challenges

Earlier developments of smart environments, often led by specific application needs, contributed to the identification of key technical challenges and preliminary evaluation of promising solutions, some of which were briefly mentioned above. The urge to develop more advanced environments for diversified application domains raises various critical challenges, including:

Modeling approaches and collaboration needs

Modeling is a fundamental part of the development of future smart environments. Although various modeling approaches have been used, a number of aspects need to be further addressed, including:

-How to represent objects / devices in the cyberspace. Two main approaches have been used: agents and service orientation. The first one is particularly appealing when modeling objects / subsystems with some level of autonomy and reasoning capabilities. In practical terms, this approach can be well supported by existing multi-agent platforms when focusing local, well-confined environments. When addressing larger physical environments, agent platforms have some limitations. Modeling devices through the services they provide is another common approach, which is not constrained by geographical limits, but does not properly encapsulate all relevant aspects of the object being modelled. Efforts to combine the two paradigms, as exemplified by the service entity notion [START_REF] Franco | Modeling extended manufacturing processes with service-oriented entities[END_REF], can be a good direction. Furthermore, when dealing with physical systems, it is also relevant to model events and pro-activity of devices / sub-systems [START_REF] Cardoso | Pro-Active Service Ecosystem Framework[END_REF]. -How to discover the objects / devices and their functionalities. Independently of the modeling approach, it is necessary to provide registry and discovery mechanisms that also cope with the nomadic and volatile nature of some devices. For instance, devices / entities can "appear and disappear" from the cyber-space, or evolve over time. Associated to this aspect, it is necessary to also model access rights, which are closely related to the ownership of devices / subsystems and the business models available within the smart environment. -Organizational structures. Besides the individual components, it is also necessary to model the organizational structures present in the environment. Particularly, it is necessary to model the various categories of networked entities and their organizational structures, e.g. devices, sensors, machines, enterprises/organizations, and human actors, covering both their functional and behavioral characteristics, as well as their specificities, e.g. mobility and evolution perspectives in this environment. -Business services modeling. In a complex smart environment, some of the services offered to its inhabitants are likely to be jointly provided by various stakeholders.

Dealing with the complexity arising from the large and increasing number of artefacts and subsystems constituting smart environments, and the inherent dynamism involved in such environments, suggest organizing them around different "spaces", constituting certain "communities" or "ecosystems" and "societies" of artefacts. Within such organizational structures collaboration among artefacts and subsystems is a requirement for the creation and provision of composed value-added services for the benefit of the environment inhabitants. To support value-added service creation, mechanisms are required for registering and sharing service components within service-developers communities, as well as supporting these developers with discovery and integration of such component services. As such, collaborative networks concepts need to be applied to various levels, including: (i) giving an organizational scope to the structure of the smart environment and supporting collaboration among artefacts and subsystems, (ii) supporting the multiple stakeholders that participate in the building and operation of the smart environment, (iii) providing a framework for interaction between users and environment services, and (iv) coping with the communities of users and their organizational structures.

Other technical aspects

Human-systems interaction. In order to effectively improve life/comfort of inhabitants of the smart environments, new and advanced forms of interaction with users need to be considered. For instance, natural user interfaces and augmented reality, benefiting from well-proven techniques (e.g. from the gaming industry) are likely to play a relevant role here. In this area, it is also necessary to further handle a number of other aspects, such as: dealing with the "excess of information" that comes from large variety of sources, reducing the effort of users having to deal with many different interfaces, capturing user experience to adjust the systems to the user's life style and preferences, etc.

Technological artefacts in smart environments are gradually changing people's habitat, while extending people's sensorial and acting capabilities in these environments. Therefore, the challenge is not only to consider the human in the loop when designing systems, rather the fact that the systems shall be human-centric. On the other hand, users can have a growing influence on the smart environments innovation process, namely through social networks, forums, blogs, rating systems, and similar mechanisms, which raises the importance of the concept of co-innovation in this area.

Risks and security.

As the environments become increasingly permeated by technology and networked infrastructures, and their inhabitants become more dependent on such technology, the issue of trustworthiness of the components and systems, which is associated to the notions of reliability, risk, privacy, and security, assumes critical relevance. Therefore, the definition of environment-level trustworthiness indicators and their monitoring mechanisms, combined with recovery procedures contributing to system's resilience, need to be developed.

Furthermore, when smart environments are addressed as societies of artefacts and sub-systems, it is important to study and manage their emergent behaviors. Some behavioral patterns are "healthy" in the sense that they are aligned with the environment's purpose, generating value to the human inhabitants, while others are "faulty", due to either malfunctioning or cyber-attacks. Systems resilience is then a desired property, calling for new indicators of "system's health" and associated monitoring and diagnosis functionalities.

Technological basis. Smart environments involve a large diversity and increasing quantity of devices and infrastructures with different life cycles. In this context, interoperability and scalability are rather critical issues. The nomadic nature of many devices / gadgets that may enter / leave the environment also poses strong interoperability requirements. Therefore, the ability to easily integrate different artefacts in a technology agnostic manner remains a fundamental goal [START_REF] Openhab | openHAB Open Source Automation Server[END_REF], [START_REF] Fhem | FHEM Home Automation Sever[END_REF], [START_REF] Openremote | openRemote Open Source Automation Platform[END_REF].

Technological developments need to also deal with the peculiarities of devices regarding their constraints on energy, communication range, computational power, memory capacity, etc., for which collaborative approaches can also provide ways to overcome individual limitations. Early examples in this direction can be found in the approaches to implement energy aware collaborative sensor networks [START_REF] Li | Collaborative wireless sensor networks: A survey[END_REF].

Bridges to other fields. The growing availability of cloud computing resources can provide a solution to the constraints of some devices in widely distributed smart environments and thus a close link between the two areas needs to be explored.

Being smart environments potential sources of large volumes of data, a close link with the developments in big data / data science may open opportunities for the creation of new advanced business services.

Engineering methods

While current engineering techniques have been good enough to deliver small-scale smart environments, they appear rather limited when addressing complex systems requiring a convergence of different technologies and knowledge areas [START_REF] Broy | Challenges in Engineering Cyber-Physical Systems[END_REF]. As smart-environments constitute cyber-physical systems, traditional approaches used in a single discipline, e.g. software engineering, or product engineering, are not sufficient.

Furthermore, effective smart environments need to be considered as sociotechnical systems. As such, besides technological developments, the design of these systems needs to also consider other elements, e.g. people, processes, organizational structures, culture, and surrounding environment.

In terms of system operation, besides the typical maintenance activities involved in traditional product engineering and software engineering, new dimensions have to be considered due to the heterogeneity, diversity, and possible autonomy of components, and interaction between different "communities / ecosystems" (e.g. home environment and external environments). Moreover, smart environments are not designed and built at once rather they gradually grow and/or evolve. For instance, in a smart home environment, new artefacts are incrementally added and/or existing artefacts are from time to time replaced by new ones.

Engineering methods need to be user-centric and also take into account the requirements of scalability and dynamism, multi-stakeholder collaboration and trustworthiness certification, maintenance and evolution, and support for user involvement in co-innovation processes.

Concluding Remarks

The convergence of developments in several basic technologies -e.g. sensors, devices, networking / pervasive computing -enabled good progress on the materialization of the smart environments paradigm, as already illustrated by several application cases.

As new cases emerge and new applications are devised, complexity increases and thus new conceptual, technological, and methodological approaches are needed. In this context, collaborative networks can bring an important contribution to the next generation of smart environments.

Particularly when moving from smart to intelligent environments, increasingly involving components / sub-systems with higher levels of autonomy and decisionmaking capability, looking at these systems from a collaborative networks lens facilitates architectural design and planning governance principles.

Acknowledgments. This work was funded in part by the European Commission through the GloNet project (FP7 programme).


John Fitzgerald
email: john.fitzgerald@ncl.ac.uk

Jeremy Bryans
email: jeremy.bryans@ncl.ac.uk

Peter Gorm Larsen

Hansen Salim
email: h.salim@ncl.ac.uk

Collaborative Systems of Systems Need Collaborative Design

Keywords: Collaborative Systems of Systems, Cyber-Physical Systems, Formal Methods, Model-based Systems Engineering

Advances in smart devices and networks are enabling convergence between systems of systems and cyber-physical systems in which computing elements interact closely with the physical environment. The development and maintenance of such systems should be inherently collaborative, crossing boundaries of constituent system ownership as well as semantic differences between engineering notations and disciplines. We present instances of modelbased methods and tools that aim to bridge these gaps. Using a case study from smart grid control, we discuss the challenges in realising collaborative systems of systems that merit the reliance placed on them.

Introduction

In areas as diverse as intelligent manufacturing or traffic control, advances in devices and networks are providing the basis of Cyber-Physical Systems (CPSs) that have potential to improve the quality of life of individuals and civic society. Such systems are assemblies of smart objects and pre-existing systems, many of them influenced by, and capable of influencing their physical environment. CPSs have potential to make spaces such as homes, factories and offices, smarter, more energy-efficient and comfortable because of the capacity to control their environment by making interventions in response to real-time data from internal and external sources.

In CPSs, the tight coupling of computing with the physical world found in embedded systems meets the independence, autonomy, heterogeneity and scale of Systems of Systems (SoSs). Although CPS technology is making significant progress, barriers to innovation remain, particularly the lack of modelling languages, tools, and associated foundations that support engineering of CPSs that are open and dynamic and yet dependable [START_REF] Broy | Engineering cyber-physical systems: Challenges and Foundations[END_REF][START_REF] Lee | CPS Foundations[END_REF].

In this paper, we focus on the need to support the collaboration that is inherent in the engineering of SoSs and CPSs. This includes collaboration between the owners and operators of otherwise independent constituent systems, and between the engineering disciplines involved in the design of a system in which computing elements interact with the physical world. We reflect on our experience in developing modelling frameworks for both SoSs and embedded systems, and consider whether together they hold out promise for supporting the design of trustworthy CPSs. In Section 2, we review the characteristics of SoSs that make their model-based design and maintenance a challenge, and discuss the realisation of a formal contract-based approach to model-based design of SoSs in the COMPASS project. In Section 3, we look to CPSs, discussing the implementation of cross-disciplinary co-modelling in Crescendo 1 . In Section 4, we present an illustrative example of co-modelling of a smart grid CPS. This leads to a brief discussion in Section 5 of the potential for bringing the technologies for SoS and co-modelling together.

Collaborative Modelling for SoSs

SoSs are composed of independent Constituent Systems (CSs) that are brought together in order to deliver a new service that the individual constituents could not offer separately. Classical examples include accident response as a result of collaboration between emergency services, or the delivery of an urban transport system composed of multiple providers.

Collaborative systems bring geographically dispersed teams together, supporting communication, coordination and cooperation [START_REF] Bafoutsou | Review and Functional Classification of Collaborative Systems[END_REF], and are a significant enabling technology in both the creation and the operation of SoSs. In fact, a growing match between SoS and the discipline of collaborative networks has been noted [START_REF] Camarinha-Matos | Taxonomy of Collaborative Networks Forms, Final Report of FInES Task Force of Collaborative Networks and SOCOLNET -Society of Collaborative Networks[END_REF]. The characteristics of SoSs induce requirements on the collaborative engineering processes and systems used in their design. We briefly consider some of the more important characteristics below.

Challenges of Model-based SoS Engineering

A SoS provides new emergent behaviour resulting from collaboration between constituent systems. However, unexpected emergence frequently has negative consequences [START_REF] Calder | Feature Interaction: A Critical Review and Considered Forecast[END_REF], and a comprehensive approach to engineering SoSs must include provision to verify both the existence of positive emergent behaviour and the limits of unexpected and undesirable emergence.

Constituent systems are frequently autonomous in the sense that their behaviour is governed by their own goals rather than those imposed by the environment. Nevertheless, the reliance placed on the SoS's emergent behaviour necessitates an approach allowing constituents to offer behavioural guarantees to one another, sufficient to guarantee global SoS-level properties.

Constituent systems are independently operated, and would continue to function successfully if detached from the SoS. They are therefore likely to have much information about their day-to-day operation that is commercially sensitive. A collaborative engineering process should not require the exposure of this information. The guarantees required of a constituent system should not overly constrain its behaviour, but allow it freedom in deciding how to meet those guarantees. The ability to handle abstraction is therefore an important part of collaborative design.

In summary, model-based SoS engineering must support collaboration while allowing for constituent system autonomy and independence, and yet supplying sufficient information to permit verification of emergence [START_REF] Bryans | Maintaining Emergence in Systems of Systems Integration: a Contractual Approach using SysML[END_REF].

Collaborative SoS Engineering: the COMPASS approach

In previous work, we proposed formal model-based methods for describing SoSs in terms of the interfaces offered by the constituent systems, with each interface defined contractually in terms of the assumptions it makes and the guarantees that it offers when those assumptions are satisfied [START_REF] Fitzgerald | A Formal Model-Based Approach to Engineering Systems-of-Systems[END_REF]. In the COMPASS project2 , this approach has been realised in a modelling language (the COMPASS Modelling Language, CML [START_REF] Woodcock | Features of CML: a Formal Modelling Language for Systems of Systems[END_REF]) that allows description of data, functionality and communication over an architectural model of the SoS given in SysML3 . CML's semantic basis is extensible [START_REF] Woodcock | Engineering UToPiA -Formal Semantics for CML[END_REF], making it possible to verify emergence by a range of techniques including simulation, model checking and proof, while the contractual approach permits the description of constituents without over-constraining each system's internals [START_REF] Fitzgerald | Foundations for Model-based Engineering of Systems of Systems[END_REF].

While a model-based approach based on contractual specification can be realised and supported by tools, the practical challenges of SoS engineering necessitate a further strengthening of tool support. To a large degree, SoS engineering depends on collaboration between integrators and owners of constituent systems. How can collaborators exchange information, agree on interfaces, prevent misunderstandings and ensure consensus, particularly when confidentiality may limit the extent to which collaborators permit access to interface specifications of their respective systems?

The need to support collaboration while respecting confidentiality is inherent in SoS engineering. Supporting it requires a step beyond beyond the kinds of Integrated Development Environment (IDE) developed for formal modelling and programming languages towards Collaborative Development Environments (CDEs) enabling negotiation and information hiding [START_REF] Whitehead | Collaboration in Software Engineering: A Roadmap[END_REF].

In COMPASS, tool support for model-based SoS engineering is based on the Symphony platform which integrates architectural and systems modelling tools based on SysML with CML (Fig. 1). In order to support collaborative development and (re-) negotiation of constituent system contractual interfaces, the framework has been extended with the concept of a collaboration group. Such a group is a collection of stakeholders (typically constituent system owners and integrators) who agree protocols for the development and evolution of interfaces developed for the SoS in question (Fig. 2), [START_REF] Nielsen | Collaborative Formal Modeling of System of Systems[END_REF]. Within the collaboration group, rules govern the exposure of model data and the iterative convergence on a mutually satisfactory set of reliances and guarantees. The analytic tools available in the COMPASS tool set are thus able to allow exploration and verification of alternative shared strategies, SoS architectures and allocations of responsibility to constituents. This contract-based approach has enabled the development of architectural models and modelling profiles for SoSs, and enabled the analysis of emergent behaviour in applications such as content-streaming networks [START_REF] Bryans | Maintaining Emergence in Systems of Systems Integration: a Contractual Approach using SysML[END_REF].

Co-modelling of Cyber-Physical Systems

Our work on collaborative development of SoS models has focussed on the computing systems. However, CPSs demand semantically heterogeneous models. For example, there is a need to be able to allow developers to work together onelectromechanical and control elements most conveniently described in terms of Continuous Time (CT), as well as Discrete Event (DE) models of computing phenomena.

In our recent work, rather than developing a common hybrid modelling notation, we have sought to develop a common semantic basis allowing DE and CT models to be presented in established notations that would be familiar to engineers from different disciplines, but interfacing these (and their simulation environments), so that models can be developed and evaluated together in a common harness, rather than entirely separately (in a concurrent development process) or sequentially [START_REF]Collaborative Design for Embedded Systems: Co-modelling and Co-simulation[END_REF]. The resulting collaborative modelling (co-modelling) approach allows for DE and CT models in different notations (in our case VDM and 20-sim respectively) to be subjected to simulation in their own well-established simulation environments, but coordinated by a co-simulation engine (Fig. 3). The data and design parameters exchanged between the harnessed simulations are defined as a contract and the sequence of events and external inputs that are to take place during a co-simulation are termed a scenario. The co-modelling approach allows the systematic exploration of both cyber and physical aspects of a system's design space. An example of this is considered below.

Example: Co-modelling of a Smart Grid

A smart grid uses digital technology to enable responsive and adaptive management of electricity generation, storage and consumption [START_REF] Gellings | The Smart Grid: Enabling Energy Efficiency and Demand Response[END_REF]. Data gathered from sensors on the grid enables forecasting, monitoring and response, including autonomous compensation for sensed failures. A smart grid is a CPS because of its computational integration with physical processes and has SoS characteristics through the integration of multiple constituent systems such as power generation and distribution facilities that may be independently owned and managed. A fault in such a system can have a marked impact. For example, a software defect was identified as a significant factor in the US Northeast Blackout of 2003 [START_REF]Canada Power System Outage Task Force[END_REF].

To illustrate the co-modelling approach, consider a simple network containing two generators servicing domestic, industrial and hospital customers via a transmission system. Fig. 4 shows a CT model of the network developed in the 20-sim tool using notations and methods familiar to electrical and control engineers. The physical system is represented by multiple elements represented by icons, connected with lines that indicate power flow. Each icon stands for a system of differential equations describing the CT behaviour of the corresponding element. Generators are modelled as modulated voltage sources producing output that is stepped up by transformers for transmission, before being stepped down for consumers (represented by resistors). The "S" units are current sensors and switches. Under normal circumstances, Houses 1-6 are powered from Generator 2, and the other consumers from Generator 1. The Control Center (CC) represents the link, via the co-modelling contract, to the DE model of the control logic that reads the sensors and operates the switches. Space does not permit the description of the DE controller model, but this is represented in terms of data and functionality at an abstract level using VDM -a notation that has markedly greater abstraction than conventional programming languages, but the elements of which are familiar to software engineers. We model a fault by defining a resistance unit that can be set to a low or high value under control from the DE side via its scenario (patterns for modelling CT and DEside faults have been presented in [START_REF]Collaborative Design for Embedded Systems: Co-modelling and Co-simulation[END_REF]). Error detection and recovery is largely enabled by the sensed on current resulting from the sensors deployed along the smart grid. Careful design is required in the cyber-side part of the system, which must store and analyse collected sensor data.

In order to model and analyse the effects on the system as a whole of faults and attacks, it is important to be able to model defective or malicious behavior in both DE and CT formalisms. For example, a physical sensor defect naturally modelled in a CT formalism can result in corrupt data analysis that is best described in the DE formalism. Going in the opposite direction, cyber faults and attacks, such as defective data transmission or SQL injection, are naturally modelled using a DE formalism, but their physical CT-side consequences are of real concern.

Co-modelling allows the specification of cyber-side faults and attacks in a notation suited for the purpose. For example, we can model a cyber-side fault in which sensor data is not read for a fixed period by a conditional in the DE controller model:

if time < 5E9 or time > 22E9 then updateSensordata();
In fact, when we combine this with the model of a physical fault introduced above, we observe the loss of the capacity to recover from the physical fault modelled CTside. Since the database is not updated with the real-time sensor reading, the control centre (DE algorithm) uses the last data entry, and believes that things are running normally. Thus we are able to model the combination of DE-side and CT-side behaviours that might individually be tolerable but lead to emergent system-level failure. For example, in other studies, we have demonstrated power spikes resulting from a cyber-side attack that changes sensor values.

This ability to model and co-simulate collaboratively across discipline boundaries allows diverse teams of engineers to explore models rapidly in the early phases of their construction, in order to select optimal fault-tolerant designs.

Conclusions

We have examined the modelling of SoSs and simple CPSs. In the former, it is apparent that support for collaboration entails support for abstraction at constituent system interfaces, and a contractual approach has potential here. In the latter case, we have demonstrated the value of modelling techniques that allow the collaborative exploration of cyber-side and physical-side faults and attacks, and the consequences that they have in combination on the delivery of the overall system's emergent behaviour.

We would argue that the combination of co-modelling and a contractual approach to the modelling of interfaces of constituent systems has the potential for significant impact in engineering collaborative CPSs, although many challenges to fully realising this vision remain. A successful approach that permits the verification of emergent behaviour requires semantic support for multiple modelling paradigms. Our experience suggests that this should not supplant established formalisms, but should allow tool-level integration. Extensibility of semantic frameworks is important here, and COMPASS' UTP-based semantic framework is a first step.

We have examined only DE and CT formalisms, but one can imagine needing to integrate formalisms that support the description of features that are important to many CPSs, including the description of human behaviour, stochastic behaviour, and abstractions such as mobility and spatial characteristics. The integration of such modelling frameworks and appropriate tool support form a significant challenge.

Finally, our work has been motivated by dependability in the technical sense, but designing systems that command the less tangible property of trust from citizens demands more radical approaches, and the possibility of human-centred design of SoSs and CPSs remains an open and intriguing area for potential research.

Figure 1 :

 1 Figure 1: COMPASS tool support for formal contract-based SoS modelling

Figure 2 :

 2 Figure 2: Enabling collaboration in Symphony

Figure 3 :

 3 Figure 3: Collaborative simulation across disciplinary boundaries

Figure 4 :

 4 Figure 4: Smart grid CT model

http://cresendotool.org

http://www.compass-research.eu

http://www.omgsysml.org

Acknowledgements. The work reported here has been supported by the EU FP7 projects COMPASS (Grant 287829) and DESTECS (Grant 248134), and by the EPSRC Platform Grant on Trustworthy Ambient Systems (EP/J008133/1). We are grateful to our many colleagues in all three project teams.