Wireless devices now hold multiple radio interfaces, allowing to switch from one network to another according to required connectivity and related quality. Still, the selection of the best radio interface for a specific connection is under the responsibility of the end-user in most cases. Integrated multi-radio network management so as to improve the overall performance of the network(s) up to the software application layer, has led to a number of research efforts over the last few years. However, several challenges remain due to the inherent complexity of the problem. This paper specifically concentrates on the comprehensive analysis of energy-efficient multi-radio networking for pervasive computing. Building upon the service oriented architectural style, we consider pervasive networks of software services, which are deployed on the various networked nodes. The issue is then to optimize the energetic performance of the pervasive network through careful selection of the radio link over which service access should be realized for each such access. By considering the most common wireless interfaces in use today (Bluetooth, WiFi and GPRS), we introduce a formal model of service-oriented multi-radio networks. The proposed model enables characterizing the optimal network configuration in terms of energetic performance, which is shown to be a NP-hard problem and thus requires adequate approximation.

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The massive deployment of mobile networks together with the emergence of powerful portable devices has given rise to pervasive computing environments. In such environments, mobile users may discover and access services offered in surrounding networks using Service Discovery Protocols (SDPs). However, several SDPs are currently in use, each one designed for a specific target network architecture and setting. As a result, in today's multi-radio networking environment, SDPs do not equally suit each radio interface. In order to provide effective service discovery in multi-radio networks, the most resource-efficient radio interface should be chosen with respect to two main criteria: the adequacy of the interface against the SDP to be used, and energy saving, which is crucial for battery-powered devices. Toward this goal, this article assesses how to effectively take advantage of the multiple radio interfaces now embedded within wireless devices with respect to energy consumption, from the standpoint of service discovery and access. It further investigates the adequacy of legacy SDPs with the various networks, so as to classify the most appropriate networks for each SDP. Exploitation of these results is finally investigated with the description of an energy-efficient algorithm for SDP-based context sensing in a multi-radio pervasive environment.

Abstract. This paper proposes a new multi-objective genetic algorithm, called GAME, to solve constrained optimization problems. GAME uses an elitist archive, but it ranks the population in several Pareto fronts. Then, three types of fitness assignment methods are defined: the fitness of individuals depends on the front they belong to. The crowding distance is also used to preserve diversity. Selection is based on two steps: a Pareto front is first selected, before choosing an individual among the solutions it contains. The probability to choose a given front is computed using three parameters which are tuned using the design of experiments. The influence of the number of Pareto fronts is studied experimentally. Finally GAME's performance is assessed and compared with three other algorithms according to the conditions of the CEC 2009 competition.

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