Collaborative broadcasting and compression in cluster-based wireless sensor networks
Achieving energy efficiency to prolong the network lifetime is an important design criterion for wireless sensor networks. In this article, we propose a novel approach that exploits the broadcast nature of the wireless medium for energy conservation in spatially correlated wireless sensor networks. Since wireless transmission is inherently broadcast, when one sensor node transmits, other nodes in its coverage area can receive the transmitted data. When data collected by different sensors are correlated, each sensor can utilize the data it overhears from other sensors to compress its own data and conserve energy in its own transmissions. We apply this idea to a class of cluster-based wireless sensor networks in which each sensing node transmits collected data directly to its cluster head using time division multiple access ( TDMA). We formulate the problem in which sensors in each cluster collaborate their transmitting, receiving, and compressing activities to optimize their lifetimes. We show that this lifetime optimization problem can be solved by a sequence of linear programming problems. We also propose a heuristic scheme which has low complexity and achieves near optimal performance. Important characteristics of wireless sensor networks such as node startup cost and packet loss due to transmission errors are also considered. Numerical results show that by exploiting the broadcast nature of the wireless medium, our control schemes achieve significant improvement in the sensors' lifetimes.
clustering sensor networks design spatial correlation lifetime optimization performance algorithms data gathering broadcast communications data compression