Joint optimization of lossy compression and transport in wireless sensor networks

We consider the problem of joint data compression and transport of information in wireless sensor networks (WSN). WSN sources compress the data through a lossy compression scheme, which may be source-specific. This compressed data is then disseminated in a multi-hop fashion until it reaches the data collection point (the sink). The problem we study is to select a rate-distortion working point for the lossy compression scheme at each source node, while jointly assessing a routing path for the compressed information, under distortion and capacity constraints. This entails a multi-objective optimization problem that is here solved and discussed for two selected network scenarios, emphasizing the nontrivial interrelations that exist between the considered objectives, namely, total transport energy in the network and signal reconstruction quality at the sink.