A Learning Algorithm for Energy-Efficient Routing of Prioritized Messages in Wireless Sensor Networks
Energy is a valuable resource in wireless sensor networks since it constitutes a limiting factor for the network lifetime. In order to make an efficient use of its own energy resources, each node in the network should be aware of the energy resources at other nodes, which can be relevant to the success of their routing decisions. The proposal of this paper is twofold:(i)to design a routing algorithm based on learning patterns using geographic information and (ii) to focus on the cut down in energy consumption. We show that by exploiting local information from the signals detected at each node, sensor nodes can learn to route messages in order to improve the communication performance of the overall network and minimize the need of coordination or signalling protocols among nodes. Moreover, if messages are prioritized by some importance parameter, the overall importance of the successfully transmitted messages can be drastically improved. Experimental results highlight that our algorithm achieves a good performance in terms of successful delivery rate and maximizes the importance of the received messages.