PhD Bénédicte Mj Merle

MD, MSc Johanna M Colijn

PhD Audrey Cougnard-Grégoire

MSc Alexandra P M De Koning-Backus

MD Marie-Noëlle Delyfer

PhD Jessica C Kiefte-De Jong

PhD Magda Meester-Smoor

PhD Catherine Féart

PhD Timo Verzijden

MSc Cécilia Samieri

MD, PhD Oscar H Franco

PhD Jean- François Korobelnik

MD, PhD Caroline C W Klaver

PhD Cécile Delcourt

Bénédicte Mj

Timo Verzijden Msc

M J Bénédicte

PhD "lifelong exposure Merle

Mediterranean diet and incidence of advanced AMD: The EYE-RISK CONSORTIUM

Objective

To investigate associations of adherence to the Mediterranean diet (MeDi) with incidence of advanced AMD (the symptomatic form of AMD) in two European population-based prospective cohorts. Design Prospective cohorts: the Rotterdam Study I (RS-I) and the Alienor Study. Participants: 4 446 participants aged ≥55 years from RS-I (The Netherlands) and 550 French adults aged 73 years or older from Alienor Study with complete ophthalmologic and dietary data were included in the present study. Methods Examinations were performed approximately every 5 years over a 21-year period (1990 to 2011) in RS-I and every 2 years over a 4-year period (2006 to 2012) in Alienor Study.

Adherence to the MeDi was evaluated using a 9 component score based on intake of vegetables, fruits, legumes, cereals, fish, meat, dairy products, alcohol and the monounsaturated-to-saturated fatty acids ratio. Associations of incidence of AMD with MeDi were estimated using multivariate Cox proportional Hazard models.

Main outcomes measures

Incidence of advanced AMD based on retinal fundus photographs.

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Results

Among the 4 996 included participants, 155 developed advanced incident AMD (117 from RS-I and 38 from Alienor Study). The mean follow-up time was 9.9 years (range 0.6 to 21.7) in RS-I and 4.1 years (range 2.5 to 5.0) in Alienor Study.

Pooling data for both RS-I and Alienor study, participants with a high (6-9) MeDi score had a significantly reduced risk for incident advanced AMD compared to participants with a low (0-3) MeDi score in the fully-adjusted Cox model (HR, 0.59 [95% CI, 0.37-0.95], p for trend=0.04).

Conclusion

Pooling data from RS-I and Alienor, higher adherence to the MeDi was associated with a 41% reduced risk of incident advanced AMD. These findings support the role of a diet rich in healthful nutrient-rich foods such as fruits, vegetables, legumes and fish in the prevention of AMD.

INTRODUCTION

Age-related macular degeneration (AMD) is the leading cause of blindness in industrialized countries [START_REF] Lim | Age-related macular degeneration[END_REF] . This degenerative disease affects the central part of the retina, which is crucial for daily living tasks such as reading, driving and recognition of faces.

Worldwide, 196 million people will be affected by AMD in 2020, increasing to 288 million in 2040 [START_REF] Wong | Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis[END_REF] . Advanced forms of the disease (neovascular or atrophic AMD) associated with a deep visual impairment, are generally preceded by asymptomatic early stages. While no treatment is currently available for atrophic AMD, effective treatments are available for the neovascular form [START_REF] Rosenfeld | Ranibizumab for neovascular age-related macular degeneration[END_REF][START_REF] Heier | Intravitreal aflibercept (VEGF trap-eye) in wet agerelated macular degeneration[END_REF] . These treatments also incur major costs to society, with an estimated 2.3 billion dollars of Medicare claims in 2013 [START_REF] Erie | High Variation of Intravitreal Injection Rates and Medicare Anti-Vascular Endothelial Growth Factor Payments per Injection in the United States[END_REF] . The risk of developing AMD is jointly determined by age, individual genetic background and lifestyle [START_REF] Lim | Age-related macular degeneration[END_REF][START_REF] Sobrin | Nature and nurture-genes and environment-predict onset and progression of macular degeneration[END_REF] . Prevention strategies based on the modifiable risk factors of AMD may help decrease the major medical and social burden associated with AMD.

Epidemiological studies have observed a reduced risk of AMD associated with high consumption of antioxidants (lutein and zeaxanthin [START_REF] Seddon | Dietary carotenoids, vitamins A, C, and E, and advanced age-related macular degeneration. Eye Disease Case-Control Study Group[END_REF][START_REF] Mares-Perlman | Lutein and zeaxanthin in the diet and serum and their relation to age-related maculopathy in the third national health and nutrition examination survey[END_REF][START_REF] Delcourt | Plasma lutein and zeaxanthin and other carotenoids as modifiable risk factors for age-related maculopathy and cataract: the POLA Study[END_REF][10][START_REF] Ma | Lutein and zeaxanthin intake and the risk of age-related macular degeneration: a systematic review and meta-analysis[END_REF][START_REF] Van Leeuwen | Dietary intake of antioxidants and risk of age-related macular degeneration[END_REF] , fruits and vegetables rich in these nutrients), and omega-3 polyunsaturated fatty acids [START_REF] Mares-Perlman | Lutein and zeaxanthin in the diet and serum and their relation to age-related maculopathy in the third national health and nutrition examination survey[END_REF][START_REF] Delcourt | Plasma lutein and zeaxanthin and other carotenoids as modifiable risk factors for age-related maculopathy and cataract: the POLA Study[END_REF][START_REF] Seddon | Progression of age-related macular degeneration: association with dietary fat, transunsaturated fat, nuts, and fish intake[END_REF][START_REF] Seddon | Cigarette smoking, fish consumption, omega-3 fatty acid intake, and associations with age-related macular degeneration: the US Twin Study of Age-Related Macular Degeneration[END_REF][START_REF] Merle | Circulating omega-3 Fatty acids and neovascular age-related macular degeneration[END_REF] , provided by fish and nuts [START_REF] Seddon | Progression of age-related macular degeneration: association with dietary fat, transunsaturated fat, nuts, and fish intake[END_REF][START_REF] Seddon | Cigarette smoking, fish consumption, omega-3 fatty acid intake, and associations with age-related macular degeneration: the US Twin Study of Age-Related Macular Degeneration[END_REF][START_REF] Augood | Oily fish consumption, dietary docosahexaenoic acid and eicosapentaenoic acid intakes, and associations with neovascular age-related macular degeneration[END_REF][START_REF] Chong | Dietary omega-3 fatty acid and fish intake in the primary prevention of age-related macular degeneration: a systematic review and meta-analysis[END_REF] . However a single nutrient/food approach cannot capture the synergistic effects of food and nutrients consumed in combination in the diet. The Mediterranean diet (MeDi) is characterized by high consumption of plant foods and fish, low consumption of meat and dairy products, olive oil as the primary fat source and a moderate consumption of wine [START_REF] Willett | Mediterranean diet pyramid: a cultural model for healthy eating[END_REF] . Adherence to the MeDi has been linked to lower rates of mortality [START_REF] Trichopoulou | Diet and overall survival in elderly people[END_REF] , chronic diseases, stroke [START_REF] Estruch | Primary prevention of cardiovascular disease with a Mediterranean diet[END_REF] , cognitive decline 21 and recently to diabetic retinopathy [START_REF] Diaz-Lopez | Mediterranean Diet, Retinopathy, Nephropathy, and Microvascular Diabetes Complications: A Post Hoc Analysis of a Randomized Trial[END_REF] . Regarding AMD, very few studies are available to date [START_REF] Mares | Healthy lifestyles related to subsequent prevalence of age-related macular degeneration[END_REF][START_REF] Merle | Adherence to a Mediterranean diet, genetic susceptibility, and progression to advanced macular degeneration: a prospective cohort study[END_REF][START_REF] Hogg | Mediterranean Diet Score and Its Association with Age-Related Macular Degeneration: The European Eye Study[END_REF][START_REF] Nunes | Adherence to a mediterranean diet and its association with age-related macular degeneration. The Coimbra Eye Study-Report 4[END_REF][START_REF] Raimundo | Adherence to a Mediterranean diet, lifestyle and age-related macular degeneration: The Coimbra Eye Study -Report 3[END_REF] . In three

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population-based studies, it was associated with a lower prevalence of early AMD [START_REF] Mares | Healthy lifestyles related to subsequent prevalence of age-related macular degeneration[END_REF] , neovascular AMD [START_REF] Hogg | Mediterranean Diet Score and Its Association with Age-Related Macular Degeneration: The European Eye Study[END_REF] and any AMD [START_REF] Nunes | Adherence to a mediterranean diet and its association with age-related macular degeneration. The Coimbra Eye Study-Report 4[END_REF][START_REF] Raimundo | Adherence to a Mediterranean diet, lifestyle and age-related macular degeneration: The Coimbra Eye Study -Report 3[END_REF] , although dietary modifications due to AMD cannot be excluded in these cross-sectional studies. In a post-hoc analysis of a randomized clinical trial, the MeDi was associated with a lower incidence of advanced AMD [START_REF] Merle | Adherence to a Mediterranean diet, genetic susceptibility, and progression to advanced macular degeneration: a prospective cohort study[END_REF] , but the selected nature of the sample limits its generalizability. We therefore investigated the associations between MeDi and incidence of advanced AMD in a large sample from two population-based prospective studies.

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METHODS

Study population

The EYE-RISK project aims at identifying risk factors, molecular mechanisms and therapeutic approaches for AMD (http://www.eyerisk.eu/). It uses epidemiological data describing clinical phenotype, molecular genetics, lifestyle, nutrition and in-depth retinal imaging derived from existing European epidemiological cohorts to provide major insights needed for prevention and therapy of AMD. Within the EYE-RISK consortium, a unique harmonized database of individual data from 16 European epidemiological studies was constructed [START_REF] Colijn | Prevalence of Age-Related Macular Degeneration in Europe: The Past and the Future[END_REF] . Two prospective studies with appropriate data for the present analyses were available: the Rotterdam Study I 29 (RS-I) and the Alienor Study [START_REF] Delcourt | Nutrition and age-related eye diseases: the Alienor (Antioxydants, Lipides Essentiels, Nutrition et maladies OculaiRes) Study[END_REF] .

Rotterdam

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After pharmacologic mydriasis, 35° stereoscopic col or fundus photos of the macula (Topcon TRV-50VT; Topcon Optical Co., Tokyo, Japan) were taken in each of the first 3 visits, and 35° digital images (Topcon TRC 50EX) we re taken for the fourth and fifth visits [START_REF] Van Leeuwen | The risk and natural course of agerelated maculopathy: follow-up at 6 1/2 years in the Rotterdam study[END_REF] .

Alienor Study

At baseline (2006-2008), 963 participants aged 73 years or more were interviewed and had an ophthalmological examination [START_REF] Delcourt | Nutrition and age-related eye diseases: the Alienor (Antioxydants, Lipides Essentiels, Nutrition et maladies OculaiRes) Study[END_REF] The eye examinations took place in the Department of Ophthalmology of the University Hospital of Bordeaux. Two 45° non-mydriatic color r etinal photographs were taken using a high-resolution digital non-mydriatic retinograph (Topcon TRC-NW6S) [START_REF] Delcourt | Nutrition and age-related eye diseases: the Alienor (Antioxydants, Lipides Essentiels, Nutrition et maladies OculaiRes) Study[END_REF] . At the third visit (2011-2012), for participants who were not able to come to the hospital, the eye examination took place at home and 40° retinal phot ographs were taken using a digital non-mydriatic portable retinograph (Optomed Smartscope M5).

For both studies, all participants provided written informed consent in accordance with the Declaration of Helsinki to participate in the study.

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AMD classification

Retinal photographs of both eyes were graded by trained graders of each study and were interpreted according to a modification of the Wisconsin Age-Related System 32 for RS-I and according to the International Classification [START_REF] Bird | An international classification and grading system for age-related maculopathy and age-related macular degeneration. The International ARM Epidemiological Study Group[END_REF] for Alienor. All advanced AMD cases were adjudicated and confirmed by retina specialists of the corresponding study.

Phenotype harmonization was performed within the EYE-RISK Consortium [START_REF] Colijn | Prevalence of Age-Related Macular Degeneration in Europe: The Past and the Future[END_REF] .

Incidence

At each visit, each subject was classified according to the worst eye into one of the following exclusive groups: no AMD, early AMD, advanced AMD. Advanced AMD was defined by the presence of neovascular or atrophic AMD.

Neovascular AMD included serous or hemorrhagic detachment of the retinal pigment epithelium (RPE) or sensory retina, subretinal or sub-RPE hemorrhages, and fibrous scar tissue. Geographic atrophy was defined as a discrete area of retinal depigmentation, 175 µm in diameter or larger, characterized by a sharp border and the presence of visible choroidal vessels. Early AMD (in the absence of advanced AMD) was defined by the presence of (1) soft indistinct (≥125 µm, decreasing density from the center outward and fuzzy edges) / reticular drusen only or soft distinct drusen (≥63 µm, with uniform density and sharp edges) and pigmentary abnormalities or by (2) soft indistinct large drusen (≥125 µm, decreasing density from the center outward and fuzzy edges) / reticular drusen and pigmentary abnormalities (corresponding to grades 2 and 3

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of the Rotterdam Classification). No AMD was defined by the absence of early AMD and advanced AMD.

Incidence of advanced AMD was defined as the subject progressing from no or early AMD at baseline to advanced AMD (either neovascular or atrophic AMD) at any timepoint during the study period. The date of occurrence of advanced AMD was calculated as the midpoint of the interval between the last visit without advanced AMD and the first visit with advanced AMD. Follow-up ended at the date of occurrence of advanced AMD, or the date of the last gradable photograph. Subjects with advanced AMD or no gradable eyes at baseline were excluded from the analysis.

For the purpose of AMD subtype analysis, neovascular AMD comprised all subjects presenting some neovascular lesions, with or without coexisting atrophy. Atrophic AMD was defined as pure geographic atrophy (in the absence of neovascular AMD).

Dietary assessment

In RS-I, participants completed a checklist at home and had a face-to-face interview conducted by a trained dietitian at the research center using a 170-items validated semiquantitative food frequency questionnaire (FFQ) [START_REF] Klipstein-Grobusch | Dietary assessment in the elderly: validation of a semiquantitative food frequency questionnaire[END_REF] . The food items were converted into quantities consumed per day (g/day). By using the computerized Dutch Food Composition Table, these dietary data were converted to total energy intake (TEI) (kcal/day) and nutrient intakes (g/day) [START_REF] Klipstein-Grobusch | Dietary assessment in the elderly: validation of a semiquantitative food frequency questionnaire[END_REF] .

In Alienor, participants were visited at home by a specifically trained dietician who administered a 40-items validated FFQ and a 24-hour dietary recall [START_REF] Feart | Energy, macronutrient and fatty acid intake of French elderly community dwellers and association with socio-demographic characteristics: data from the Bordeaux sample of the Three-City Study[END_REF][START_REF] Samieri | Dietary patterns derived by hybrid clustering method in older people: association with cognition, mood, and self-rated health[END_REF] . The food items

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were converted into number of servings per day. The 24-hour recall was used to estimate nutrient intake (g/day) and TEI (kcal/day) and to compute the monounsaturated fatty acids (MUFAs) to saturated fatty acids (SFAs) ratio.

Adherence to the MeDi was assessed using the MeDi score developed by Trichopoulou et al [START_REF] Trichopoulou | Adherence to a Mediterranean diet and survival in a Greek population[END_REF] . This score including 9 components: vegetables, fruits, legumes, cereals, fish, meat, dairy products, alcohol and the MUFAs-to-SFAs ratio was applied to both studies.

The daily intake of each food/beverage group was calculated as quantity in g/day in RS-I and as the number of servings/day in Alienor. Participants with unreliable TEI were excluded (valid TEI range: women: 600-3200; men: 600-4200 kcal). For each component hypothesized to benefit health (vegetables, fruits, legumes, cereals and fish, MUFAs-to-SFAs ratio), 1 point was given if intake was above the sex-specific median values and zero otherwise. For components presumed to be detrimental to health (meat and dairy products), 1 point was given if intake was below the sex-specific median values and zero otherwise. For alcohol, 1 point was given for moderate consumption and zero otherwise (moderate consumption: women: 1-10; men: 5-15 g/day). Sexspecific median were calculated separately for each study. The total MeDi score was computed by adding the scores (0 or 1 point) for each component for each participant.

Scores ranged from 0 (non-adherence) to 9 (perfect adherence). Subjects were classified according to 3 categories of the MeDi score: low (0-3), medium (4-5), or high (6-9).

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Covariates Age (years), sex, education (primary, secondary, higher), smoking (never smoker, smoker <20 pack-years (PY), smoker ≥20 PY, PY=packs (20 cigarettes) smoked per day X years of smoking), multivitamins/minerals supplement use (Yes/No) were measured using self-reported questionnaires at baseline 30 38 for each study. Vascular risk factors included body mass index (BMI: weight (kg)/height (m²)), diabetes (treated or self-reported), hypertension (blood diastolic blood pressure ≥90mmHg or systolic blood pressure ≥140mmHg or treated or self-reported), and hypercholesterolemia (treated or self-reported). Complement Factor H (CFH) Y402H (rs1061170) and Age-Related Maculopathy Susceptibly 2 (ARMS2) A69S (rs10490924), the two main AMD-related SNPs were assessed in each study [START_REF] Ho | Reducing the genetic risk of age-related macular degeneration with dietary antioxidants, zinc, and omega-3 fatty acids: the Rotterdam study[END_REF][START_REF] Lambert | Genome-wide association study identifies variants at CLU and CR1 associated with Alzheimer's disease[END_REF] .

Statistical analysis

Subjects excluded from analyses were compared to those included using logistic regression model adjusted for age and sex for each characteristic separately. The same method was used to compare characteristics of subjects included between the two cohorts.

The associations of MeDi score with incidence of advanced AMD were analyzed using Cox proportional hazards models with delayed entry and age as a time scale, which allow for a better adjustment for age than the classical Cox models based on time from entry in the study [START_REF] Lamarca | Left-truncated data with age as time scale: an alternative for survival analysis in the elderly population[END_REF] . Model 1 was unadjusted and model 2 was adjusted for sex, AMD grade at baseline (no or early AMD), TEI (continuous), education, BMI, smoking, multivitamins/minerals supplement use, diabetes and hypercholesterolemia. Variables

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retained in model 2 were factors associated with incidence of AMD and/or with MeDi score, after adjustment for age and sex (p<0.10). For the pooled analysis, including data from both studies, models were further adjusted for the study (fixed study effect).

Low MeDi score was designated as the reference group. P-trend was calculated by using the median value of the MeDi score for each category. In all Cox models, the proportional hazard assumptions were tested.

Participants from RS-I and Alienor were different regarding some characteristics. To estimate the potential effect of these differences, interactions between study and each covariate were assessed and none was significant. Thus, as the proportional hazard assumptions were satisfied and there were no interactions, to account for differences between the two studies, all models combining both studies were adjusted for a fixed study effect.

Secondary analyses

We also assessed whether associations of MeDi score with incident advanced AMD

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RESULTS

Of the 7 146 participants at risk of developing advanced AMD, 1 337 had no follow-up data for both eyes. In addition, 813 were excluded due to missing/unreliable dietary data (Figure 1). Overall 4 996 (4 446 from RS-I and 550 from Alienor) participants free from advanced AMD at baseline with complete and reliable dietary data together with followup information were included in our analyses.

Among the 4 996 included participants, 155 developed advanced incident AMD (117 from RS-I and 38 from Alienor). The mean follow-up time was 9.9 years (range 0.6 to 21.7) in RS-I and 4.1 years (range 2.5 to 5.0) in Alienor.

In both studies, participants included in the analyses tended to be younger than those excluded (Table 1). In RS-I, after adjustment for age and sex, included participants tended to be more women, to have a higher education, to have a history of smoking and diabetes, a lower TEI, a higher MeDi score and to carry less often a CFH Y402H CC genotype than excluded participants. In Alienor, included participants were more likely to have a higher education, than excluded participants.

Participants from RS-I, tended to be younger, to have a lower education, to have a history of smoking, to have less hypertension and less hypercholesterolemia as well as a higher TEI, a lower adherence to the MeDi score and to have less early AMD than participants from Alienor. Also CFH Y402H polymorphism was slightly different between the two studies.

Participants from Alienor tented to have a higher median of consumption of vegetables, cereals and fish, whereas subjects from RS-I tented to have a higher median of

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consumption of dairy products. Consumption of fruits, legumes, meat and the MUFAs-to-SFAs ratio were similar (eTable 1).

For both studies, the incidence of advanced AMD was lower among subjects who had a high adherence to the MeDi score (Figure 2). The effect of MeDi is more noticeable among older people (85+), at higher risk of AMD, but as the proportional hazard assumption is respected, associations are considered similar among the different age groups.

In the unadjusted model, similar estimations were obtained in both studies, with a HR of 0.56 [95% CI 0.33 to 0.96] in RS-I and 0.48 [95% CI 0.18 to 1.26] in Alienor for participants with a high MeDi score, by comparison with a low MeDi score (Table 2).

When pooling both studies, a high MeDi score was significantly associated with a lower risk for incident advanced AMD (HR, 0.53 [95% CI, 0.33-0.84], p-trend=0.009). These associations remained similar and significant after further adjustment for sex, TEI, AMD grade at baseline, education, BMI, smoking, supplement use of multivitamins/minerals, diabetes and hypercholesterolemia, (HR, 0.59 [95%CI, 0.37-0.95], p-trend=0.04).

In secondary analyses, we further adjusted for CFH Y402H and ARMS2 genes and the HR remained unchanged (data not shown).

Interactions terms between MeDi and CFH Y402H and ARMS2 genes were not statistically significant (p for interaction=0.89 and 0.18, respectively, data not shown).

Adherence to MeDi score was not significantly associated with the risk for incident neovascular AMD neither in RS-I nor in Alienor or in the pooled analysis (Table 3). It was significantly associated with the risk for incident atrophic AMD in RS-I (HR=0.41, p-

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trend=0.046) but the association did not reach significance in Alienor (HR=0.52, p-trend=0.52). In the pooled data analysis, a higher MeDi score was significantly associated with a reduced risk for incident atrophic AMD (HR, 0.42 [95%CI, 0.20-0.90], p-trend=0.04).

We assessed whether the benefit of high adherence to the MeDi score was due to a specific component. Using the sex-specific median as cutoffs, no component was significantly associated with incidence of advanced AMD (eTable 2).

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DISCUSSION

High adherence to the MeDi was associated with a 41% reduced risk of incident advanced AMD in the pooled analysis. None of the nine components, including vegetables, fruits, legumes, cereals, fish, the MUFAs-to-SFAs ratio, meat, dairy products and alcohol consumption, was significantly associated with incidence of advanced AMD, highlighting the importance of assessing dietary patterns rather than single components.

In our studies, a high adherence to the MeDi was significantly associated with a reduced risk of incident atrophic AMD. A similar association was observed for neovascular AMD but did not reach statistical significance.

By evaluating the individual and the pooled associations of the adherence to the MeDi and incidence of advanced AMD in two well established and harmonized European population-based prospective cohorts, this study expands on prior studies, mainly crosssectional, case-control, and clinical trials on this topic. Visual impairment due to AMD could influence dietary practices; prospective studies, by assessing diet prior the onset of the disease, limits reverse causation. Thus, prospective design is more accurate and less biased than a cross-sectional or case-control design to evaluate the association between diet and AMD. In addition, although using a prospective design, clinical trials are limited by the selected nature of the sample. Results from population-based studies are more generalizable.

Our results are partially consistent with previous cross-sectional studies: the CAREDS study reported a lower prevalence of early AMD in American women with high adherence to the MeDi [START_REF] Mares | Healthy lifestyles related to subsequent prevalence of age-related macular degeneration[END_REF] , the Coimbra Study demonstrated a lower prevalence of any

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AMD in Portuguese participants who were having a high adherence to the MeDi [START_REF] Nunes | Adherence to a mediterranean diet and its association with age-related macular degeneration. The Coimbra Eye Study-Report 4[END_REF][START_REF] Raimundo | Adherence to a Mediterranean diet, lifestyle and age-related macular degeneration: The Coimbra Eye Study -Report 3[END_REF] and the European Eye Study (Eureye) showed a lower prevalence of neovascular AMD in subjects with a high MeDi score while atrophic AMD was not associated with MeDi score [START_REF] Hogg | Mediterranean Diet Score and Its Association with Age-Related Macular Degeneration: The European Eye Study[END_REF] . Our findings confirm the post-hoc analyses of the AREDS clinical trial. In this sample of American participants aged 55 to 80 years, a high MeDi score was associated with a 26% lower risk of progression to advanced AMD [START_REF] Merle | Adherence to a Mediterranean diet, genetic susceptibility, and progression to advanced macular degeneration: a prospective cohort study[END_REF] . The AREDS study also showed that fish and vegetable components were associated with a lower risk of progression to advanced AMD [START_REF] Merle | Adherence to a Mediterranean diet, genetic susceptibility, and progression to advanced macular degeneration: a prospective cohort study[END_REF] . Our results were in the same direction but did not reach the statistical significance when sex-specific median cutoffs were used. No significant interactions were observed between MeDi score and CFH Y402H and ARMS2 genes. Our findings report a significant association with advance AMD.

Regarding subtypes, only atrophic AMD was significantly associated with MeDi score.

For neovascular AMD even if the association was not statistically significant, the HRs were similar to those for atrophic AMD. These differences could be explained by a low number of incident cases. In the Eureye Study, the only study to show separate results for the two advanced forms of AMD, association was significant with neovascular AMD.

While in our studies this association with neovascular AMD was not statistically significant, HRs were similar to those for Eureye study.

Our results thus support public health efforts to emphasize adherence to the MeDi for everyone. The biological basis for the potential benefits of the MeDi is associated with a decrease in oxidative stress and inflammation, which are also involved in the pathophysiology of AMD [START_REF] Fung | Diet-quality scores and plasma concentrations of markers of inflammation and endothelial dysfunction[END_REF][START_REF] Dai | Association between adherence to the Mediterranean diet and oxidative stress[END_REF] .

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The PREDIMED study, a clinical trial among persons at high cardiovascular risk, showed that adhering to a MeDi reduced the incidence of major cardiovascular events [START_REF] Estruch | Primary prevention of cardiovascular disease with a Mediterranean diet[END_REF] .

Median consumptions were similar to the goals suggested by PREDIMED for vegetables (≥2 serving/d), fish (≥3 serving/w) and meat (<1 serving/d) in Alienor and for meat in RS--I. For both studies, median of fruits and legumes were below the goals of PREDIMED (≤3 serving/d) as well as median of vegetables, and fish in RS-I. Even though the medians in our study were lower for vegetables and fruits, the association with the MeDi score was significant, suggesting the importance of a global approach to prevent the development of AMD.

By showing a prospective association between AMD and MeDi, an energy-unrestricted diet mainly composed of nutrient-rich food, our study confirms the importance of dietary quality focused on healthful foods and dietary patterns rather than single nutrients or low-energy diet for AMD.

In observational studies, residual confounding is always a concern. In the present study, results were similar in the basic model (unadjusted model) and the fully-adjusted model (adjusted for sex, TEI, AMD grade at baseline, cardiovascular risk factors, educational level and dietary supplement use), suggesting that our results are not highly confounded. In the fully-adjusted model, association between MeDi and incidence of AMD seems to be weaker in RS-I. This could be explained by a lower statistical power due to a low incidence of participants developing advanced AMD combined to the increasing number of covariates compared to the unadjusted model. In addition, our findings are based on prospective follow-up, thereby limiting reverse causation.

However, only randomized clinical trials can prove the causal nature of the associations.

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Such randomized clinical trials testing dietary interventions have proven to be efficient in the prevention of stroke [START_REF] Estruch | Primary prevention of cardiovascular disease with a Mediterranean diet[END_REF] or diabetes [START_REF] Knowler | Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin[END_REF] , for instance, but none are available in the field of AMD.

Selection bias cannot be completely dismissed, as participants included in this analysis were different from non-participants in both RS-I and Alienor. Moreover, participants included from RS-I were different from those from Alienor regarding some sociodemographic and medical characteristics as well as follow-up time duration and frequency. Incidence rates of AMD were also higher in Alienor than in RS-I. These differences might be explained by the older age at baseline and a closer follow-up (every 2 years instead of 5 years in RS-I, with home examinations for participants unable to come to the hospital in Alienor but not in every RS-I follow-up visit), or by different incidence rates in France and the Netherlands.

The MeDi score uses cutoffs based on each study population and results can only be generalizable to similar populations. To calculate the MeDi score, we used validated FFQs for both studies, adapted to the specific dietary habits of each population (France and the Netherlands). As the FFQ in Alienor was a 40-items FFQ, we used the 24h recall to calculate the MUFAs-to-SFAs ratio and the TEI to increase the exactitude of their ascertainment, as previously published 21 . The distribution of the MeDi score was different between the two studies, participants from RS-I were less adherent. This result was expected in a North European population. MeDi and incidence of advanced AMD was similar in both cohorts. This association thus appears to be robust.

To strengthen our analyses, we excluded subjects with unusually high or low TEI and adjusted for several factors know to be related to MeDi and AMD. We used a well-known and validated score to assess diet and probable synergistic effects between nutrients and food groups. Our MeDi score was developed by using sex-specific thresholds according to each study to better account for differences between men and women and studies. Other strengths include a large sample from two well documented and dataharmonized population-based prospective cohorts in the framework of the European EYE-RISK project.

In conclusion, combined results from our two observational studies suggest that adopting an energy-unrestricted diet rich in healthful nutrient-rich foods such as fruits, vegetables, legumes and fish, and, reducing the unhealthful foods such as red and processed meats, savory and salty industrialized products may contribute to the prevention of AMD. b Cox proportional hazard model adjusted for sex, total energy intake, AMD grade at baseline, education, body mass index, smoking, supplement use of multivitamins/minerals, diabetes and hypercholesterolemia.

c Cox proportional hazard adjusted for sex, total energy intake, AMD grade at baseline, study, education, body mass index, smoking, supplement use of multivitamins/minerals, diabetes and hypercholesterolemia.

  Study I At baseline 7 983 eligible persons aged 55 years or older were interviewed and examined. Ophthalmological examinations and fundus photography were taken at each round starting in 1990-1993 (RS-I-1). Follow-up rounds were completed in 1993-1995 (RS-I-2), 1997-1999 (RS-I-3), 2002-2004 (RS-I-4) and 2009-2011 (RS-I-5). The RS has been approved by the Medical Ethics Committee of the Erasmus MC (registration number MEC 02.1015) and by the Dutch Ministry of Health, Welfare and Sport (Population Screening Act WBO, license number 1071272-159521-PG). The RS has been entered into the Netherlands National Trial Register (NTR; www.trialregister.nl) and into the WHO International Clinical Trials Registry Platform (ICTRP; www.who.int/ictrp/network/primary/en/) under shared catalogue number NTR6831.

  may be due to individual dietary components by examining associations between the individual components of the MeDi score and advanced AMD. Each component was introduced independently into model 2. In secondary analyses, CFH Y402H and ARMS2 A69S polymorphisms were added to model 2. Interactions between CFH Y402H and ARMS2 A69S polymorphisms and MeDi score were also analyzed. Interaction terms for the number of risk alleles and MeDi score were assessed separately for each genetic variant using model 2. All p-values representing a 2-tailed test of significance with M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT α=0.05 and SAS version 9.4 (SAS Institute Inc. Cary, NC, USA) was used for all 235 analyses.

  Despite these major differences in populations (different countries, different time periods, different generations and different diet habits) and methods (different follow-up M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT time and frequency, different dietary assessment methods), the association between

Figure 1 .

 1 Figure 1. Selection of participants for analyses.

Figure 2 .

 2 Figure 2. Incidence of advanced AMD according to adherence to Mediterranean Diet

c

  estimated using Cox proportional hazard model. d estimated using Cox proportional hazard model with additional adjustment for study.e Model 2, adjusted for sex, total energy intake, AMD grade at baseline, education, body mass index, smoking, supplement use of multivitamins/minerals, presence of diabetes and hypercholesterolemia.

  . Of these, 624 and 614 were reexamined at the

	second (2009-2010) and third (2011-2012) visits, respectively. The design has been
	approved by the Ethical Committee of Bordeaux (Comité de Protection des Personnes
	Sud-Ouest et Outre-Mer III) in May 2006 (http://www.alienor-study.com/langue-english-
	1.html).

Table 1 .

 1 Baseline characteristics of the Rotterdam Study I (RS-I) and the Alienor Study, according to participants included and excluded from analyses.

	Characteristics	Rotterdam Study I				Alienor Study
		Included a (n=4 446)	Excluded b (n=1 867)	P value	c	Included a (n=550)	Excluded b (n=283)	P value c	P value vs Alienor c RS-I
									for included
									subjects
		No. (%)			No. (%)
	Age, mean (SD), y
		66.9 (7.3)	73.4 (10.0) <0.0001 79.2 (4.2)	81.1 (4.3)	<0.0001	<0.0001
	Sex			0.006			0.61	0.08
	Men	1813 (40.8)	766 (41.0)			209 (38.0) 108 (38.2)
	Women	2633 (59.2) 1101 (59.0)			341 (62.0) 175 (61.8)
	Education	N=4426	N=1808	<0.0001		N=283	0.03	<0.0001
	Primary	2200 (49.7) 1151 (63.6)			301 (54.7) 180 (63.6)
	Secondary	1823 (41.2)	529 (29.3)			130 (23.7)	56 (19.8)
	Higher	403 (9.1)	128 (7.1)			119 (21.6)	47 (16.6)
	Smoking, pack-years	N=4131	N=1644	0.009	N=547	N=278	0.77	<0.0001
	Never smoker	1501 (36.3)	667 (40.6)			356 (65.1) 179 (64.4)
	<20	1173 (28.4)	413 (25.1)			95 (17.4)	51 (18.3)
	≥20	1457 (35.3)	564 (34.3)			96 (17.5)	48 (17.3)
	Multivitamin/mineral supplement use	N=4442	N=1867	0.11			N=281	0.32	0.05
	No	4070 (91.7) 1660 (88.9)			475 (86.4) 237 (84.3)
	Yes	370 (8.3)	207 (11.1)			75 (13.6)	44 (16.7)
	Body mass index, mean	N=4426	N=1775	0.26		N=542	N=274	0.87	0.17
	(SD), kg/m²
		26.3 (3.6)	26.2 (4.0)			26.0 (4.0)	25.9 (4.1)
	Diabetes	N=4444		0.003		N=281	0.33	0.63
	No	3941 (88.7) 1693 (90.7)			489 (88.9) 243 (86.5)
	Yes	503 (11.3)	174 (9.3)			61 (11.1)	38 (13.5)
	Hypertension			0.28			N=281	0.48	<0.0001
	No	1883 (42.3)	593 (31.8)			86 (15.6)	46 (16.4)
	Yes	2563 (57.7) 1274 (68.2)			464 (84.4) 235 (83.6)
	Hypercholesterolemia	N=4442		0.18			N=281	0.76	<0.0001
	No	4317 (97.2) 1837 (98.4)			275 (50.0) 146 (52.0)
	Yes	125 (2.8)	30 (1.6)			275 (50.0) 135 (48.0)
	CFH (rs1061170)	N=3972	N=1581	0.02		N=450	N=235	0.81	0.03
	TT	1649 (41.5)	632 (40.0)			212 (47.1) 101 (43.0)
	CT	1801 (45.3)	709 (44.8)			181 (40.2) 110 (46.8)
	CC	522 (13.2)	240 (15.2)			57 (12.7)	24 (10.2)
	ARMS2 (rs10490924)	N=3971	N=1582	0.16		N=450	N=235	0.12	0.11
	GG	2490 (62.7) 1028 (65.0)			309 (68.7) 145 (61.7)
	GT	1339 (33.7)	500 (31.6)			126 (28.0)	85 (36.2)

b Participants excluded from all analyses c p value from logistic regression adjusted for age and sex d p value from logistic regression adjusted for age, sex and total energy intake

Table 2 .

 2 Association between Mediterranean Diet (MeDi) score and incidence of advanced agerelated macular degeneration (AMD).

	Mediterranean Diet Score

a p for trend is calculated using the median value for each Mediterranean Diet score category.

b Model 1, unadjusted model.

Table 3 .

 3 Association between Mediterranean Diet score (MeDi) and incidence of advanced neovascular and atrophic age-related macular degeneration (AMD).

					Mediterranean Diet Score categories
			No. at risk for advanced AMD	No. incident cases	Low 0-3	Medium 4-5	High 6-9	P for trend a
	Neovascular AMD
	Rotterdam I HR (95% CI)	b	4104	68	Reference 0.87 (0.51-1.51) 1.03 (0.53-1.99)	0.91
	Alienor HR (95% CI)	b	538	18	Reference 0.80 (0.25-2.63) 0.75 (0.20-2.91)	0.65
	Overall HR (95% CI)	c	4642	86	Reference 0.78 (0.48-1.27) 0.88 (0.49-1.57)	0.64
	Atrophic AMD
	Rotterdam I HR (95% CI)	b	4104	52	Reference 0.61 (0.34-1.10) 0.41 (0.16-1.03)	0.046
	Alienor HR (95% CI)	b	538	21	Reference 1.08 (0.38-3.06) 0.52 (0.13-2.12)	0.52
	Overall HR (95% CI)	c	4642	73	Reference 0.70 (0.42-1.15) 0.42 (0.20-0.90)	0.04

a p for trend is calculated using the median value for each MeDi score category.

Funding EYE-RISK project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 634479. The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. The authors are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. Additionally, the ophthalmic research within the Rotterdam Study was supported by the following foundations: Oogfonds, Bartiméus Sonneheerdt Vereniging, Landelijke Stichting voor Blinden en Slechtzienden, Algemene Nederlandse Vereniging Ter Voorkoming Van Blindheid, Novartis Foundation and MaculaFonds that contributed through UitZicht (grants 2015-36 and 2016-19). The funding organizations had no role in the design or conduct of this research and provided unrestricted grants. The Alienor study is funded by Laboratoires Théa, Fondation Voir et Entendre, Retina France, Agence Nationale de la Recherche (ANR 2010-PRSP-011 VISA) and CNSA

M A N U S C R I P T A C C E P T E D ACCEPTED MANUSCRIPT

(Caisse Nationale pour la Solidarité et l'Autonomie). Laboratoires Théa participated in the design of the Alienor study, but none of the sponsors participated in the collection, management, statistical analysis and interpretation of the data, or in the preparation, review or approval of the present manuscript.

Competing financial interest of members of the EYE-RISK consortium:

Verena Arndt, Sebastian Bühren, Tanja Endermann and Markus Zumbansen are


Eduard Grigorescu
email: eduard@erg.abdn.ac.uk

Chamil Kulatunga
email: chamil@erg.abdn.ac.uk

Gorry Fairhurst

Nicolas Kuhn
email: nicolas.kuhn@telecom-bretagne.eu

Evaluation of Priority Scheduling and Flow Starvation for Thin Streams with FQ-CoDel

Keywords: Bufferbloat, AQM, Scheduling, CoDel, FQ-CoDel, Thin-streams, Flow Starvation I

Bufferbloat is the result of oversized buffers and induced high end-to-end latency experienced by applications across the Internet. This additional delay can adversely impact thin streams that frequently exchange small amounts of data, but have stringent latency requirements. Active Queue Management (AQM) techniques, such as Controlled Delay (CoDel), can control the queuing delay in a network device to ensure low latency by dropping packets to indicate incipient congestion. FlowQueue-CoDel (FQ-CoDel) is a scheduling scheme that creates one subqueue per flow and applies CoDel on each of them. FQ-CoDel features: (1) priority scheduling for low-rate traffic; (2) flow isolation; (3) queue management with CoDel. First, this paper fills a gap in the understanding of FQ-CoDel by analyzing what features are of interests for providing low latency for thin streams applications. Second, this paper provides the first analysis of the limits of the flow starvation mechanisms and show that FQ-CoDel is vulnerable to Denial of Service (DoS) attacks.

INTRODUCTION

Network devices require buffers to store bursts of incoming packets prior to forwarding. These buffers have traditionally implemented a FIFO/DropTail buffer policy, with passive queue management that drops packets only when a queue is full. While buffers are needed to achieve statistical multiplexing or to guarantee high bottleneck utilization when the available capacity fluctuates, excessive buffering can lead to large queues resulting in high network latency. This issue is known as Bufferbloat [START_REF] Gettys | Bufferbloat: Dark Buffers in the Internet[END_REF]. Although capacity between Internet core routers is often over-provisioned, this is rarely the case for access networks, using technologies such as ADSL, satellite and mobile broadband [START_REF] White | Active Queue Management in DOCSIS 3.X.Cable Modems[END_REF]. Latency has become a major issue in such access networks in the past decade where excessive queuing, affects application performance [START_REF] Leavitt | Network-Usage Changes Push Internet Traffic to the Edge[END_REF].

Active Queue Management (AQM) techniques, such as Random Early Detection (RED) [START_REF] Jacobson | Random Early Detection Gateways for Congestion Avoidance[END_REF], have been proposed for over a decade to appropriately manage the buffer by indicating impeding congestion to responsive transport protocols, to avoid building a standing queue. However, AQM schemes have been reported to be usually turned off, as they were hard to tune. More recent protocols, such as CoDel [START_REF] Nichols | Controlling Queue Delay[END_REF] or PIE [START_REF] Pan | PIE: A lightweight control scheme to address the bufferbloat problem[END_REF], have been designed to especially tackle the Bufferbloat, but with RED deployment issues in mind. Recent IETF work recommends the deployment of AQM as one solution to reduce latency [START_REF] Baker | AQM Recommendations Regarding Active Queue Management[END_REF]. On top of AQM schemes, scheduling algorithms, managing packet scheduling and isolation/capacity allocation among flows, can be introduced. As one example of a scheme that mixes both classes, FlowQueue-CoDel (FQ-CoDel) [START_REF] Hoeiland-Joergensen | [END_REF] is a scheduling scheme that features prioritization and flow isolation. FQ-CoDel creates one sub-queue per flow and applies CoDel on each of them. The awareness of the latency resulting from over-provisioned buffers has been accompanied by an increase in real-time applications such as Voice over Internet Protocol, gaming or financial trading applications. As one example, the latency experienced by gamers can directly impact the perceived value of the network service [START_REF] Claypool | Latency and player actions in online games[END_REF]. These thin streams applications generally send sparse streams of small time-critical packets [START_REF] Petlund | Improving latency for interactive, thin-stream applications over reliable transport[END_REF].

Since FQ-CoDel features a mechanism that prioritizes lowrate traffic, the benefits for the increasing number of thin streams that carry latency sensitive applications needs to be assessed. This paper fills the gap in research evaluating FQ-CODel when the traffic is a mix of thin streams and bulk flows and evaluates which part of FQ-CoDel (CoDel, prioritization, flow isolation) provides improvement. Because FQ-CoDel features flow prioritization, we also evaluate to what extent its flow starvation prevention mechanism works.

The remainder of this paper is organized as follows. Section II describes FQ-CoDel, by clearly identifying when each internal mechanism adds value. Section III presents the simulation setup used to assess the suitability of FQ-CoDel for carrying latency sensitive thin streams over a capacity limited path. Section IV discusses which part of FQ-CoDel might provide improvements in the queuing delay experienced by thin stream applications. Section V assesses the limits of the flow starvation prevention mechanism. Section VI concludes this work.

II. FLOWQUEUE-CODEL ALGORITHM

AQM algorithms seek to control network buffering level by sending messages to trigger transport congestion control, i.e., by early dropping/marking packets.

A. Over the Need for Flow Scheduling for Thin-Streams

AQM dropping techniques on their own may not be sufficient to satisfy the strict latency requirements for thin stream applications [START_REF] Mckenney | Stochastic Fairness Queuing[END_REF], [START_REF] Baker | AQM Recommendations Regarding Active Queue Management[END_REF]. Indeed, traffic such as file transfers or unresponsive constant rate streaming flows, with different time constraints, may share the bottleneck with thin streams. This would result in a non-negligible queuing delay experienced by the thin streams. Some form of flow isolation might be required to separate and protect the time sensitive small flows from larger and more aggressive flows. Scheduling algorithms can provide per-flow or per-class queuing to isolate traffic classes to guarantee the specific constraints of latency sensitive applications. As one example, if thin flows are assigned different subqueues to other flows, a scheduling scheme may protect the thin flows from the background traffic. This would avoid an increasing queuing delay for a latency sensitive application when the background flows build in a subqueue.

One simple isolation method is per-flow queuing [START_REF] Nabeshima | An Effective Queue Management Scheme for Data Communication[END_REF] in which each flow is deterministically assigned its own virtual sub-queue. However, this requires network devices to classify each flow, which can be difficult when dealing with traffic aggregates or when encryption is used. Each of the subqueues is served in a round-robin manner, improving fairness between flows [START_REF] Mckenney | Stochastic Fairness Queuing[END_REF]. A more complex example is Stochastic Fair Queuing (SFQ) [START_REF] Mckenney | Stochastic Fairness Queuing[END_REF] that provides a statistical alternative in the way the subqueues are served.

B. FlowQueue scheduling in FQ-CoDel

FQ-CoDel uses a modified Deficit Round Robin (DRR) scheduler. The default flow classifier of FQ-CoDel hashes incoming packets stochastically to a subqueue based on a 5tuple classifier -IP source and destination address, protocol, and port numbers. The scheduler of FQ-CoDel can be applied on any flow isolation technique and is not limited to a 5-tuple classifier. A byte-based scheduler, rather than a packet-based scheduler, is used to select the next packet for transmission.

The scheduling in FQ-CoDel is based on three lists of subqueues that are represented in Figure 1, the "new" list, the "old" list and the "empty state" list. In the rest of this subsection, we will detail how these lists are managed. We focus on how they can prevent flow starvation and how they prioritize some classes of traffic.

At initialization, FQ-CoDel creates a set of subqueues (by default 1024 subqueues), all are placed in the "empty state" list. When there is at least one byte of data that enters a subqueue, the subqueue is defined as active. This subqueue is initially placed in the "new" list, but may later be moved to the "old" list.

When a packet is enqueued, it is added at the end of the subqueue corresponding to the 5-tuple classifier: if the 5-tuple of this packet does not correspond to any list, it is added to an existing "empty list", which becomes a "new" list.

We describe here how the deficit is decreased and how the decision to dequeue data is taken:

• The scheduler first cycles through the "new" list of subqueues, allowing each subqueue to dequeue up to one "quantum" of packets and updating the deficit value. • For each subqueue, the scheduler checks the deficit. If the deficit becomes negative, the subqueue is moved to the end of the "old" list and its deficit is updated to the sum of the size of the quantum and the previous deficit.

• When a subqueue in the "new" list is found to be inactive (no packets in the buffer), it is placed at the end of the "old" list, and its deficit is re-initialized to the "quantum" size. • When the "new" list becomes empty, the scheduler examines the "old" list by repeating the algorithm used on the "new" list. When a subqueue from the "old" list becomes empty, it is removed.

C. Flow Starvation Prevention Mechanism in FQ-CoDel

When the deficit of a given queue, Q, becomes negative, it is moved to the end of the "old" list. This ensures that when FQ-CoDel loops over the "old" list, a subqueue that had been previously pushed to the end of the "old" list would be given the opportunity to transmit a quantum of data before Q. When a queue is empty, FQ-CoDel pushes the queue at the end of the "old" list. This feature, referred to as the Starvation Prevention Mechanism, is supposed to prevent starvation, providing some transmission opportunities for the flows already placed in the "old" list.

D. AQM in FQ-CoDel

Each subqueue is individually managed using the CoDel algorithm: FQ-CoDel classifies each packet, it timestamps the packet and appends it to the tail of the selected subqueue. CoDel controls the maximum size of each subqueue, using its default parameters: target delay of 5 ms and interval 100 ms. CoDel applies its control law and may discard at least one packet from the head of a scheduled subqueue if needed, before returning a packet for dequeuing (or no packet if the subqueue becomes empty). This should avoid buffer overflow and guarantee low queuing delay, if there are many flows and the scheduling introduces a non-negligible queuing delay.

III. EVALUATION TOOL SET FOR THE CAPACITY LIMITED NETWORK USE CASE

This section justifies our focus on the capacity-limited network use case. We also present the simulation tool set and the network topology used in our simulations.

A 10 Mbps (or higher speed) bottleneck that experiences congestion, has a transmission speed that is sufficiently low to result in negligible transmission delay, even for large packets, compared to the latency required by typical thin stream applications (approx. 1.2 ms for a packet of 1500 B sent at 10 Mbps). When the bottleneck has a smaller rate (e.g., the downlink of a rural access link operating at 1-2 Mbps or an uplink, operating at 1/10 of this speed), the packet transmission delay increases further (e.g., 12-6 ms for 1500 B packets). The cumulative effect of scheduling many competing flows can result in some flows becoming "choked". Because (1) the impact of the thin streams on the flow starvation of FQ-CoDel is exacerbating and (2) the latency sensitive applications would be more affected when there is no priority scheduling, we therefore focus on this use case.

Figure 2 presents the dumb-bell topology for our simulations in ns-2. The capacity of the bottleneck was 2 Mbps and the one-way-delay was 47.5 ms. The non-bottleneck links were configured with 1.25 ms one-way-delay and 100 Mbps capacity. The RTT of the network path was 100 ms. At node R1, the buffer size was set to twice the size of the Bandwidth-Delay Product (BDP) and either FQ-CoDel or CODel applied to the node. For other nodes, the queuing discipline was DropTail, with a buffer size of 300 packets.

IV. ANALYZING THE PERFORMANCE OF THIN STREAMS WITH FQ-CODEL

FQ-CoDel may be divided into different constituent mechanisms. There is one AQM scheme per subqueue, one priority scheme and a set of flow isolation techniques. If FQ-CoDel is to be used to support thin streams, it is important to assess which mechanism within FQ-CoDel is actually responsible for realizing any benefits observed.

A. The Benefits of Flow Isolation for Thin Streams

To support our evaluation, this subsection introduces a custom non-prioritization version of FQ-CoDel, FQ-CoDel Without Prioritization (FQ-CoDel WP). FQ-CoDel WP does not make the distinction between the "new" and "old" list and subqueues are created one after the other, while the scheduler still visits subqueues similar to SFQ. This is used to assess the benefits of the flow isolation for the thin streams applications.

This subsection compares the suitability of using FQ-CoDel WP, CoDel or SFQ to carry thin streams applications. The following traffic was considered: (1) 1 to 5 TCP bulk flows, using File Transfer Protocol (FTP) for the entire period of the simulation with a packet size of 1500 B. (2) 1 thin TCP with an inter-packet interval of 638 ms and a packet size of 100 B, which is representative of the traffic generated by the game Anarchy Online [START_REF] Petlund | TCP mechanisms for improving the user experience for time-dependent thin-stream applications[END_REF]. ( 1) and (2) used TCP New Reno with the SACK option and an initial window of 3 packets. Figure 3 shows the Cumulative Density Function (CDF) of the queuing delay experienced by the thin-stream flows, when the AQM is CoDel, SFQ or FQ-CoDel WP. With SFQ, the queuing delay increases as the level of network congestion increases (increasing number of TCP flows). For each TCP packet, the Round Robin scheduler of SFQ results in a 6 ms transmission time per packet (1550 B for a 2 Mbps bottleneck). As expected, a Round Robin scheduler that services a higher number of queues leads to increased queuing delay: we observe a linear increase of the queuing delay when the number of TCP flows increases. As an example, the thin stream subqueue will experience 5*6ms >= 30ms queuing delay with 5 bulk TCP flows before it has the opportunity to again be serviced.

With CoDel, the observed queuing delay is lower than with SFQ, whatever the number of TCP bulk flows. The early drops in CoDel tend to maintain a small queue that reduces the delay experienced by the thin stream flows. This queuing delay does significantly increase with the number of flows competing for queue space, as compared to SFQ.

With FQ-CoDel WP, the queuing delay experienced by the thin streams is lower than when using CoDel and lower than with SFQ. These results show that (1) dropping packets with CoDel enables a latency reduction; (2) flow isolation alone cannot reduce the queuing delay experience; (3) the performance of flow isolation techniques are sensitive to the traffic load. We can conclude that when FQ-CoDel features flow isolation, it results in lower queuing delay than with CoDel alone, showing that the flow isolation technique, along with CoDel drops, can offer the best of the two schemes.

B. The Importance of Thin Stream Prioritization and CoDel

In this subsection, we will explore the benefits of introducing prioritization in FQ-CoDel to reduce the queuing delay experienced by thin streams. We compare the performance of the default FQ-CoDel with "FQ-CoDel WP 100ms", which is a modified version of FQ-CoDel in which the target of CoDel is increased to 100 ms (instead of the default 5 ms) and prioritization is disabled. Therefore, the differences between FQ-CoDel WP 100ms and FQ-CoDel are The performance with FQ-CoDel WP 100ms shows that without prioritization and with CoDel less aggressive, the performance of this scheme is close to those of SFQ. The flow isolation of FQ-CoDel may reduce the latency (as shown in the previous section), but the CoDel part of the algorithm has a non-negligible benefit in reducing the queuing delay.

Also, if we compare the performance of FQ-CoDel and those of FQ-CoDel WP, shown respectively in Figure 4 and Figure 3, we see that the prioritization contributes in reducing the queuing delay experienced by the thin streams. FQ-CoDel provides lower queuing delay, for the traffic loads considered, whereas it is sensible to the traffic load with FQ-CoDel WP.

Therefore, based on the results presented in this subsection, we can conclude that the flow prioritization of FQ-CoDel provides a useful latency reduction and makes the queuing delay of the thin streams less sensible to the traffic load. We also confirm the conclusions of section IV-A, which are that the CoDel part of FQ-CoDel is essential to provide low latency in the context of capacity-limited networks.

C. Thin Stream with various inter-packet arrival times

Depending on the burst size and the frequency between bursts, when a second burst of packets reach the queue, the packets of the previous burst might still be in the "old" list, or they might have left the queue and the second burst would be prioritized. Flows with a different pattern of packet interarrival times but similar packet sizes can be treated differently.

We consider three cases of traffic generation: (1) 1 gaming flow, 1 TCP bulk flow and 1 VoIP flow; (2) 1 gaming flow, 1 TCP bulk flow and 5 VoIP flows; (3) 1 gaming flow, 5 TCP bulk flows and 1 VoIP flow. Both the VoIP and the gaming flows use TCP. The inter-packet arrival time for the VoIP flows is in 20-30 ms and in 600-1000 ms for the gaming flows. The packet size for both applications is on average 100 B. Results are shown in Figure 5.

With FQ-CoDel WP 100 ms and FQ-CoDel WP, the queuing delay for both voice and gaming flows increases in case (3), because of the high number of TCP flows, showing again the importance of CoDel coupled with isolation and prioritization. However, in cases ( 1) and ( 2), the load level is lower than in case (3), and we see a small gain of using the priority scheme of FQ-CoDel. With FQ-CoDel WP, we notice a small difference between gaming and voice flows this may be related to their different inter-packet arrival times, showing that the priority scheme of FQ-CoDel actually lets the AQM scheme reduce the queuing delay for applications with different inter-packet arrival times. The results presented in this subsection let us conclude that FQ-CoDel can deal with thin streams flows that have different inter-packet arrival times. We also highlighted that the prioritization mechanism seems to provide benefits. Another possible source of improvement might be the starvation prevention mechanism; we expect future work to evaluate this.

V. FLOW STARVATION AND FQ-CODEL

We discuss here the limits of the flow starvation prevention mechanism. The starvation prevention mechanism of FQ-CoDel is the following: FQ-CoDel would place an empty queue from the "new" list to the end of the "old" list. Also, if a queue is empty in the "old" list, it would be removed and considered as "new" when its packets reach the queue.

We assess the limits of the starvation prevention mechanism of FQ-CoDel. Under Denial of Service (DoS) attacks, FQ-CoDel scheduler may loop only over the "new" list, preventing the flow starvation mechanism to work. It is crucial therefore to assess the performance of the flow starvation mechanism when thin streams contribute a large proportion of the traffic compared to bottleneck capacity. A starvation prevention method that may prevent this issue from occurring. To verify the benefits of using this mechanism, we implemented FQ-CoDel Without its Starvation Prevention Mechanism (FQ-CoDel WSPM). FQ-CODel WSPM is a version of FQ-CoDel where starvation prevention is disabled, that is while looping over the "new" list, the algorithm would not move empty lists from the "new" list to the "old" list, but rather wait that the deficit for the list is negative.

The following traffic were considered: (1) 1 TCP bulk flows, using FTP for the entire period of the simulation with a packet size of 1500 B; (2) 5 to 45 thin unresponsive UDP flows with an inter-packet interval of 30 ms and a packet size of 100 B, which is representative of the traffic generated by a Skype session [START_REF] Petlund | TCP mechanisms for improving the user experience for time-dependent thin-stream applications[END_REF]. (1) used TCP New Reno with the SACK option enabled and an initial window of 3 packets.

Figure 6 presents the throughput achieved by the TCP flow as a function of the number of thin flows, with FQ-CoDel and with FQ-CoDel WSPM. When the number of thin streams is greater than 30, the TCP bulk flow becomes starved, both when using FQ-CoDel and with FQ-CoDel WSPM. This shows that unresponsive traffic can impact the performance, since the flow starvation prevention mechanism of FQ-CoDel is not sufficient to prevent the resulting congestion. The lack of a difference between FQ-CoDel with and without this mechanism highlights that it does not provide significant benefit when there is a high level of congestion. We finally consider the response to overload. An FQ-CoDel scheduler could be vulnerable to a Denial of Service (DoS) attack where traffic intentionally tries to disrupt normal operation, e.g., a large number of thin streams would be intentionally injected into the network bottleneck. This may cause the scheduler to become locked serving only flows in "new" list subqueues, leading to unwanted interactions between TCP flows and bursts of unresponsive flows that result in delay. For such a low capacity link, flows in the "old" list would barely receive an opportunity for transmission, and would become starved. CoDel would also drop queued packets from the old list. This suggests the need to design more sophisticated overload protection [START_REF] Baker | AQM Recommendations Regarding Active Queue Management[END_REF].

We note that other modern AQM algorithms, such as PIE, can also be combined with isolation methods [START_REF] Baker | AQM Recommendations Regarding Active Queue Management[END_REF] by introducing mechanisms similar to those described in this paper. The combined methods have been reported to support latency-sensitive thin-stream applications [START_REF] White | Active Queue Management in DOCSIS 3.X.Cable Modems[END_REF]. We leave exploration of the reasons behind the performance limits of the flow starvation prevention mechanism in capacity-limited networks as a part of our future work on this topic.

VI. CONCLUSION

This paper describes the operation of the various components mechanisms in FQ-CoDel and explores how thinstream applications can benefit from these mechanisms to reduce their experienced latency and mitigate the impact of sharing capacity with other types of network traffic. We measured that the flow isolation of FQ-CoDel is the main factor resulting in improved latency performance for thin flows over bottlenecks with limited bandwidth. Such isolation would be impossible with a traffic aggregate that it cannot dissect (e.g., when encrypted Virtual Private network tunnels are used). We identified that CoDel in FQ-CoDel can provide improvements for this specific traffic, this means that when a classifier cannot be used, low latency may still be guaranteed.

Flow prioritization has been introduced within FQ-CoDel to that favors low-rate traffic, or latency sensitive applications such as web traffic. Simulations have shown that this scheme provides a fair improvement of performance for thin stream traffic. We believe in general that deployed AQM algorithms should be made robust against overload and especially denial of service attacks, otherwise all the efforts spent in making the deployment of AQM a reality will be eroded. In the light of the results presented in this document, we encourage further research prior to deployment of the current version of FQ-CoDel. Other modern AQM algorithms, such as PIE, can also work in conjunction with isolation methods to better support latency-sensitive application. Therefore, we believe that more efforts should be spent on evaluating the performance of such hybrid mechanisms to support their large-scale deployment.

Figure 1 .

 1 Figure 1. FQ-CoDel State Machine

Figure. 2 .

 2 Figure. 2. Dumb-bell simulation topology

Figure 3 .

 3 Figure 3. CDF vs. Gaming Flow Queue Latency

( 1 )

 1 CoDel will allow more queuing in FQ-CoDel WP 100 ms and (2) the absence of prioritization in FQ-CoDel WP 100 ms.The traffic considered in this section is the same as in IV-A. Figure4presents the CDF of the queuing delay experienced by the thin streams for various numbers of TCP flows with FQ-CoDel or FQ-CoDel WP 100ms as an AQM.

Figure 4 .

 4 Figure 4. CDF vs. Game Flow Latency for FQ-CoDel (5 ms target delay) and non-prioritized FQ-CoDel WP (100ms target delay)

Figure 5 .

 5 Figure 5. Thin Flows Latency for prioritized and non-prioritized FQ-CoDel

Figure 6 .

 6 Figure 6. TCP Throughput with FQ-CoDel and with FQ-CoDel WSPM

ACKNOWLEDGEMENTS

This research was supported by the RCUK DE programme to the dot.rural Digital Economy Hub; EP/G066051/1 and part-funded by the European Community under its Seventh Framework Programme through the Reducing Internet Transport Latency (RITE) project (ICT-317700).