We propose a novel relay augmentation strategy for extending the lifetime of a certain class of wireless sensor networks. In this class sensors are located at fixed and pre-determined positions and all communication takes place via multi-hop paths in a fixed routing tree rooted at the base station. It is assumed that no accumulation of data takes place along the communication paths and that there is no restriction on where additional relays may be located. Under these assumptions the optimal extension of network lifetime is modelled as the Euclidean @math -bottleneck Steiner tree problem. Only two approximation algorithms for this NP-hard problem exist in the literature: a minimum spanning tree heuristic (MSTH) with performance ratio 2, and a probabilistic 3-regular hypergraph heuristic (3RHH) with performance ratio @math . We present a new iterative heuristic that incorporates MSTH and show via simulation that our algorithm performs better than MSTH in extending lifetime, and outperforms 3RHH in terms of efficiency.
In a sensor network, usually a large number of sensors transport data messages to a limited number of sinks. Due to this multipoint-to-point communications pattern in general homogeneous sensor networks, the closer a sensor to the sink, the quicker it will deplete its battery. This unbalanced energy depletion phenomenon has become the bottleneck problem to elongate the lifetime of sensor networks. In this paper, we consider the effects of joint relay node deployment and transmission power control on network lifetime. Contrary to the intuition the relay nodes considered are even simpler devices than the sensor nodes with limited capabilities. We show that the network lifetime can be extended significantly with the addition of relay nodes to the network. In addition, for the same expected network lifetime goal, the number of relay nodes required can be reduced by employing efficient transmission power control while leaving the network connectivity level unchanged. The solution suggests that it is sufficient to deploy relay nodes only with a specific probabilistic distribution rather than the specifying the exact places. Furthermore, the solution does not require any change on the protocols (such as routing) used in the network. In a typical sensor network, nodes around the sink consume more energy than those further away. It is not unusual that limited energy resources available at the nodes around the sink become the bottleneck which confines the performance of the whole network. In this letter, we firstly present our considered bottleneck zone in a general sensor network scenario. Then, the effect of the bottleneck zone on network performance is investigated by deducing performance bounds imposed by the energy resources available inside the bottleneck zone. In this letter, both the performance bound in terms of network lifetime and the performance bound in terms of information collection are explored. Finally, the ways by which network deployment variables may affect the performance bounds are analyzed.