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IFIP Networking 2018, Zürich, SUISSE, 14-/05/2018 - 16/05/2018; International audience; Orchestrating network and computing resources in Mobile Edge Computing (MEC) is an important item in the networking research agenda. In this paper, we propose a novel algorithmic approach to solve the problem of dynamically assigning base stations to MEC facilities, while taking into consideration multiple time-periods, and computing load switching and access latency costs. In particular, leveraging on an existing state of the art on mobile data analytics, we propose a methodology to integrate arbitrary time-period aggregation methods into a network optimization framework. We notably apply simple consecutive time period aggregation and agglomerative hierarchical clustering. Even if the aggregation and optimization methods represent techniques which are different in nature, and whose aim is partially overlapping, we show that they can be integrated in an efficient way. By simulation on real mobile cellular datasets, we show that, thanks to the clustering, we can scale with the number of time-periods considered, that our approach largely outperforms the case without time-period aggregations in terms of MEC access latency, and at which extent the use of clustering and time aggregation affects computing time and solution quality.

International audience; The real-time detection of crowded spots in access networks is considered nowadays a necessary step in the evolution of mobile cellular networks as it can be of great benefit for many use-cases. On the one hand, a dynamic positioning of contents and computing resources in the most crowded regions can lower connection latency and data loss and can allow us to have a seamless service provided for the users, without performance degradation across the network. On the other hand, a dynamic resource allocation among access points taking into account their loads can enhance the user's quality of service and indeed network performances. In this context, using real mobile data traces from a cellular network operator in France, provided us with a temporal and spatial analysis of user content consumption habits in different French Metropolitan areas (Paris, Lyon and Nice). Furthermore, we put to use a real-time crowded spot estimator computed using two user mobility metrics, using a linear regression approach. Evaluating our estimator against more than one million user databases from a major French network operator, it appears to be an excellent crowd detection solution of cellular and backhauling network management. We show that its error count definitely decreases with the cell load, and it becomes very small for reasonable crowded spot load reaching S. Hoteit Ecole d'ingénieurs du numérique ISEP 2 Sahar Hoteit et al. upper thresholds. We also show that our crowded spot estimator is time and city-independent as it shows a stable behavior for different times of the day and for different cities with different topographies. Furthermore, compared to another crowded spot estimator from the literature, we show that our proposed estimator offers more suitable and accurate results in terms of crowded spot estimation for the three selected areas.

International audience; Major interest is currently given to the integration of clusters of virtualization servers, also referred to as 'cloudlets' or 'edge clouds', into the access network to allow higher performance and reliability in the access to mobile edge computing services. We tackle the edge cloud network design problem for mobile access networks. The model is such that the virtual machines (VMs) are associated with mobile users and are allocated to cloudlets. Designing an edge cloud network implies first determining where to install cloudlet facilities among the available sites, then assigning sets of access points, such as base stations to cloudlets, while supporting VM orchestration and considering partial user mobility information, as well as the satisfaction of service-level agreements. We present link-path formulations supported by heuristics to compute solutions in reasonable time. We qualify the advantage in considering mobility for both users and VMs as up to 20% less users not satisfied in their SLA with a little increase of opened facilities. We compare two VM mobility modes, bulk and live migration, as a function of mobile cloud service requirements, determining that a high preference should be given to live migration, while bulk migrations seem to be a feasible alternative on delay-stringent tiny-disk services, such as augmented reality support, and only with further relaxation on network constraints.

International audience; Major interest is currently given to the integration of clusters of virtualization servers, also referred to as `cloudlets', into the access network to allow higher performance and reliability in the access to mobile cloud services. We tackle the cloudlet network design problem for mobile access networks. The model is such that virtual machines are associated with mobile users and are allocated to cloudlets. Designing a cloudlet network implies first determining where to install cloudlet facilities among the available sites, then assigning sets of access points such as base-stations to cloudlets, while supporting virtual machine migrations and taking into account partial user mobility information, as well as the satisfaction of service-level agreements. We present link-path formulations supported by heuristics to compute solutions in reasonable time. We qualify the advantage in considering mobility for both users and virtual machines as up to 40% less cloudlet facilities to install and 40% less virtual machine migrations to execute. We compare two migration modes, bulk and live migration, as a function of mobile cloud service requirements, determining that a high preference should be given to bulk migrations for delay-stringent services such as augmented reality support, while for applications with less stringent delay requirements, live migration appears as largely preferable.

A new small automobile, the Fiat Strada, was designed and tested to suit the special needs of the American driver. Outlined by the author are those needs, as they have shaped the American car and as they are perceived by his company. Characteristics of small cars offered on the American market in recent decades by his firm are described and analyzed. Also described is the process of designing, road-testing and clinic-testing a new small car destined for the American market.

This work addresses a multi agent allocation problem in which multiple departments compete for shares of a company budget. Each department has its own portfolio of projects with given expected profits and costs and selects an optimal subset of its projects consuming its assigned budget share. Besides considering the total profit of the company a central decision maker should also take fairness issues into account. Thus, we introduce an equity criterion based on maximin fairness. The resulting trade-off between total profit and fairness indicators is studied in this contribution. To this purpose a bicriteria ILP model is presented where one of the objectives is the maximization of the overall profit and the other is the maximization of the minimum budget allocated to one of the departments. We perform an experimental analysis showing a nearly perfect linear anticorrelation between profit and fairness index values.