A branch and price algorithm for the minimum power multicasting problem in wireless sensor networks

The Minimum Power Multicast Problem arises in wireless sensor networks and consists in assigning a transmission power to each node of a network in such a way that the total power consumption over the network is minimized, while a source node is connected to a set of destination nodes, toward which a message has to be sent periodically. A new mixed integer programming model for the problem, based on paths, is presented. A practical exact algorithm based on column generation and branch and price is derived from this model. A comparison with state-of-the-art exact methods is presented, and it is shown that the new approach compares favorably to other algorithms when the number of destination nodes is moderate. Under this condition, the proposed method is able to solve previously unmanageable instance

Letters

www.elsevier.com/locate/dsw A branch and bound algorithm for the robust shortest path problem with interval data

Ant Colony System for a Dynamic Vehicle Routing Problem

An aboundant literature on vehicle routing problems is available. However, most of the work deals with static problems, where all data are known in advance, i.e. before the optimization has started. The technological advances of the last few years give rise to a new class of problems, namely the dynamic vehicle routing problems, where new orders are received as time progresses and must be dynamically incorporated into an evolving schedule. In this paper a dynamic vehicle routing problem is examined and a solving strategy, based on the Ant Colony System paradigm, is proposed. Some new public domain benchmark problems are defined, and the algorithm we propose is tested on them. Finally, the method we present is applied to a realistic case study, set up in the city of Lugano (Switzerland

Algorithm Engineering in Robust Optimization

Robust optimization is a young and emerging field of research having received a considerable increase of interest over the last decade. In this paper, we argue that the the algorithm engineering methodology fits very well to the field of robust optimization and yields a rewarding new perspective on both the current state of research and open research directions. To this end we go through the algorithm engineering cycle of design and analysis of concepts, development and implementation of algorithms, and theoretical and experimental evaluation. We show that many ideas of algorithm engineering have already been applied in publications on robust optimization. Most work on robust optimization is devoted to analysis of the concepts and the development of algorithms, some papers deal with the evaluation of a particular concept in case studies, and work on comparison of concepts just starts. What is still a drawback in many papers on robustness is the missing link to include the results of the experiments again in the design

The sound of communication in underwater acoustic sensor networks: (Position paper)

Underwater environments have never been much of a constraint to the rich animal life they support at all depths of our seas and oceans. Indeed, nature has taken advantage of this environment to develop a rich variety of efficient communication strategies through evolutionary change and adaptation. The wealth of knowledge to be discovered will continue to dazzle and fascinate the world. For underwater sensor network communication, acoustic signalling is the preferred choice for designers because sound propagation is the most efficient when compared to other forms, like thermal, light, and electromagnetic. It is within this acoustic environment that researchers have to innovate and develop new ideas and methodologies so as to advance the state-of-the-art. In this paper, several fundamental issues and connections are discussed that arise in the study of underwater wireless sensor networks. A variety of ideas and solutions for further research is proposed and fundamental issues in topology control, directional underwater transducers, and monitoring and surveillance are disc

A topology control approach for utilizing multiple channels in multi-radio wireless mesh networks

We consider the channel assignment problem in a multi-radio wireless mesh network that involves assigning channels to radio interfaces for achieving efficient channel utilization. We present a graph-theoretic formulation of the channel assignment guided by a novel topology control perspective, and show that the resulting optimization problem is NP-complete. We also present an ILP formulation that is used for obtaining a lower bound for the optimum. We then develop a new greedy heuristic channel assignment algorithm (termed CLICA) for finding connected, low interference topologies by utilizing multiple channels. Our evaluations show that the proposed CLICA algorithm exhibits similar behavior and comparable performance relative to the optimum bound with respect to interference and capacity measures. Moreover, our extensive simulation studies show that it can provide a large reduction in interference even with a small number of radios per node, which in turn leads to significant gains in both link layer and multihop performance in 802.11-based multi-radio mesh networks