An adaptive routing algorithm using dynamic TTL for data aggregation in Wireless Sensor Network

Abstract

Wireless Sensor Networks (WSNs) are event driven networks that usually use overlapping paths from events to maximize the data aggregation. But this will weaken ability of WSNs instead of improving the network lifetime. There should be a tradeoff between data aggregation maximization and energy balance. In this paper a novel adaptive algorithm for data aggregation is proposed. The algorithm maximizes the data aggregation points by building and updating hop-tree with shortest paths based on events and nodes local states, which can maximize data aggregation according to data correlation, well balance node energy consumption and route data in a reliable way. The algorithm maximizes the possible data aggregation points by building and updating a Hop-Tree. For building and maintaining Hop-Tree the local state of nodes is considered to gain better data aggregation in wireless sensor networks. Finding best path for forwarding aggregated data Time-To-Live (TTL) mechanism is used to limit the Hop-Tree update range to avoid over-overlapping of paths according to the correlation of events. It designs a path that balance the data load on the nodes of Hop-Tree to further balance the energy consumption. Performance evaluation results shows that our algorithm can maximize the possible data aggregation while balance the energy consumption among nodes.