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Rapid growth in the domain of Internet of Things (IoT) leads to massive deployment of sensors and therefore the need to develop automatically reconfigurable complex wireless sensor network. Software defined networking (SDN) is a promising and widely adopted technique to automatic reconfigure the wireless sensor network. In SDN, control nodes are dynamically selected (to activate the functioning of the sensor network) in order to assign the tasks to other nodes and for routing data packets to control server. For residual energy of sensor nodes, and transmission distance among sensor nodes, the problem of control node selection has been formulated as an NP-hard problem. Usually, smart sensing devices of IoT suffers from low battery which are not frequently rechargeable. Therefore, an energy efficient routing mechanism is required to operate software defined wireless sensor network (SDWSN). In this paper, a green routing algorithm using fork and join adaptive particle swarm optimization (FJAPSO) is proposed to maximize the lifetime of sensor network. FJAPSO acts at two levels for auto optimization: optimal number of control nodes and optimal clustering of control nodes. Experimental results evidenced that FJAPSO outperforms other state of the art and significantly maximizes the lifetime of the sensor network.
Kumar et al. (Thu,) studied this question.