Swarm intelligence based data aggregation for intruder detection in wireless sensor networks

Abstract

Wireless Sensor Network in which nodes are mobile can be defined as MWSN (Mobile Wireless Sensor Networks). MWSNs are a budding field of research in contrast to their well-established ancestor. It consists of a variety of sensing elements deployed indiscriminately and at enormous scale. This can build a huge variety of redundant sensory information. Transmission of such redundant data saturates network resources and it additionally consumes nodes energy. Data aggregation is the process of reducing the amount of packets to be sent to sink to increase the life time of MWSN. Path and location of the nodes are changing frequently in mobile WSN. So Swarm intelligence (group behaviour) is needed for the communication as well as on data collection, Query publication and intrusion detection. To operate MWSNs in a secure way, intrusions should be detected before attackers can harm the network. Intrusion can also occur in multiple layers of MWSN so continuous investigation of aggregated data to be needed. Proposed work is for SIDI (Swarm Intelligence based Data aggregation for Intruder detection) raising the energy efficiency of a network. Simulation results indicate that this operation practically will increase the network lifetime.