Hybrid Ant Algorithm Based Query Processing with Multiagents in Sensor Networks

The wireless sensor networks are usually deployed in various application-specific contexts, which can be treated as distributed databases with big data. The event-involved query responses can be obtained by issuing query requests to this kind of database. However, the constraints of the energy and delay have had a great impact on the operation of wireless sensor networks. How to design the query-involved network model and the corresponding query processing algorithms is extremely challenging. This work investigates query processing problem in resource-constrained wireless sensor networks with the two-tier architecture and multiple query agents, where the multiple nodes of query agents are configured in the networks and the corresponding source cluster-heads send collected events to only one optimum query agent. To reduce the energy consumption and shorten the delivery delay, an efficient query processing algorithm inspired by the swarm intelligence of ants is proposed, which takes advantage of the beneficial clustering and routing emerging in a hybrid self-organized way from the positive interaction of ants. The experimental results demonstrated that the proposed algorithm can deliver collected events to the optimum query agents efficiently. Not only is the energy cost reduced but also the delivery delay is shortened significantly when transmitting the named events to the appropriate query agents.