Optimizing Energy-Latency Trade-off in Wireless Sensor Networks with Mobile Element

Recent research shows that significant energy saving can be achieved in wireless sensor networks by using mobile elements (MEs) capable of carrying data mechanically. Though ME can reduce the energy consumption at each sensor node, it increases the latency from the time the data is generated at a node to the time the base station receives it. To address this issue, we proposed a collection-based approach in which a subset of nodes served as the data collection points (CPs) that buffer data originated from sources and transfer to ME when it arrives. CPs shorten the trajectory of ME which can gather a large volume of data at a time, however, they also increase energy consumption of nodes to transmit data to them. There is a trade-off between the energy consumption of network and the length of trajectory of ME which is determined by the number of CPs. In this paper, we introduce a Probabilistic Path Selection (PPS) algorithm to reduce the data collection delay for stochastic event detection scenario. Furthermore, we develop a heuristic algorithm and extend to the more general case of combined ME and CPs selection to enable a flexible trade-off between energy consumption and data delivery latency. Our implementation and simulation results show nearly monotonic decrease of data delivery latency for greater limits on the energy consumption, and which is same on the contrary.