An improved ant-based routing protocol in Wireless Sensor Networks

Abstract

Routing in wireless sensor networks (WSNs) is very challenging due to their inherent characteristics of large scale, no global identification, dynamic topology, and very limited power, memory, and computational capacities for each sensor. Recent research on WSNs routing protocol has proved that data-centric technologies are needed for performing in-network aggregation of data to yield energy-efficient dissemination. As an effective distributed approach, ant colony optimization (ACO) algorithms have been introduced to the design of data-centric routing protocol and have got many achievements, but still have some shortcomings blocking their further application in the large scale WSNs. To overcome the flaws of conventional ant-based data-centric routing algorithms, we proposed an improved protocol by adding a new type of ant, search ant, to supply prior information to the following ants. Besides, we introduced the strategy of simulating global pheromone update to accelerate the convergence of our algorithm and defined a "retry" rule to avoid dead-lock of the protocol. All of these modifications made the routing protocol scalable, practicable and energy-conservative. Simulation results showed the great advantages of the new protocol