Balancing message delivery latency and network lifetime through an integrated model for clustering and routing in Wireless Sensor Networks

One common approach to extend Wireless Sensors Networks (WSN) lifetime is to use mobile sinks to gather sensed information through the network, avoiding that sensor nodes spend their limited energy in relaying other nodes’ messages to the sinks. Such approach, however, tends to significantly increase message delivery latency. On the other hand, it is widely recognized that the optimization of any Quality of Service parameter in WSN, message delivery latency included, must always be conducted bearing in mind the implied impact in the network lifetime. In this paper, we introduce a network model to seek for a good solution for this inherent multi-objective optimization problem. In our approach, optimization algorithms are used to define optimal (or near-optimal) density control policies, sensors clustering and sink routes to collect sensed data. We deal with the multi-objective nature of the design in WSN by explicitly minimizing message delivery latency and by imposing topology constraints that help to reduce energy consumption. Our proposal differs from most studies in the literature by the integrated way in which we tackle clustering and routing decisions. Various metaheuristic based heuristics that solve the integrated problem were incorporated into a dynamic simulation environment. Through extensive simulation experiments, we compared our approach to others in the literature, in terms of Quality of Service parameters. Our results indicate that the integrated model proposed here compares favorably to other approaches, allowing a good balance among conflicting parameters like message delivery latency, network lifetime and rate of messages received.