Abstract: Data propagation in wireless sensor networks can be performed either by hop-by-hop single transmissions or by multi-path broadcast of data. Although several energy-aware MAC layer protocols exist that operate very well in the case of single point-to-point transmissions, none is especially designed and suitable for multiple broadcast transmissions. The key idea of our protocols is the passive monitoring of local network conditions and the adaptation of the protocol operation accordingly. The main contribution of our adaptive method is to proactively avoid collisions by implicitly and early enough sensing the need for collision avoidance. Using the above ideas, we design, implement and evaluate three different, new strategies for proactive adaptation. We show, through a detailed and extended simulation evaluation, that our parameter-based family of protocols for multi-path data propagation significantly reduce the number of collisions and thus increase the rate of successful message delivery (to above 90%) by achieving satisfactory trade-offs with the average propagation delay. At the same time, our protocols are shown to be very energy efficient, in terms of the average energy dissipation per delivered message.
Abstract: This paper deals with early obstacles recognition in wireless sensor networks under various traffic
patterns. In the presence of obstacles, the efficiency of routing algorithms is increased by voluntarily avoiding some regions in the vicinity of obstacles, areas which we call dead-ends. In this paper, we first propose a fast convergent routing algorithm with proactive dead-end detection together with a formal definition and description of dead-ends. Secondly, we present a generalization of this algorithm which improves performances in all to many and all to all traffic patterns. In a third part we prove that this algorithm produces paths that are optimal up to a
constant factor of 2ð+1. In a fourth part we consider the reactive version of the algorithm which is an extension of a previously known early obstacle detection algorithm. Finally we give experimental results to illustrate the efficiency of our algorithms in different scenarios.