Maximum lifetime data aggregation in distributed intelligent robot network based on ACO

Providing multimedia traffic support in distributed intelligent robot network (DIRN) as a kind of wireless sensor and actor network (WSAN) is addressed. Since multimedia traffic has stringent bounds on end-to-end delay resource reservation for transmitting such traffic has to be done. The existing methods used for multimedia traffic provide inefficient utilization of network resources and affect call acceptance and drop ratio of multimedia traffic severely. Hence a data aggregation scheme based on ant optimization algorithm using bionic swarm intelligence for supporting multimedia traffic is proposed to overcome those limitations and to help reduce the traffic to the sink node in turn reducing the power consumption of intermediate node. Lifetime maximization can balance the traffic across the network so as to avoid overwhelming the bottleneck nodes. Key issues and configurations are discussed and studied, such as influence of location of aggregation point, impact of network shape and balance based energy-efficient methods. Extensive simulations are done to assess the performance of the scheme under varying network condition for carrying multimedia traffic. A practical implementation with real DIRN has been carried out to validate the enhanced efficiency, stability and accuracy of the proposed algorithm, which is proved to lead to longer network lifetime in comparison to other traditional data aggregation schemes such as Minimum Energy Gathering Algorithm (MEGA) for supporting multimedia traffic in real time.