Affiliations: [a] Department of CSE, JNTUK, Kakinada, AP, India | [b] PVP Siddhartha Institute of Technology, Kanuru, Vijayawada, AP, India | [c] Krishna University, Machilipatnam, AP, India
Correspondence:
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Corresponding author: T. Santhi Sri, Department of CSE, JNTUK, Kakinada, AP, India. E-mail: sri_santhi2003@yahoo.com.
Abstract: Mobility awareness and energy efficiency have been considered as the two irreplaceable enhancement issues in Mobile Ad Hoc Networks (MANETs) where nodes navigate erratically toward any path with limited battery life, bringing about incessant change in topology. These constraints are generally concentrated to build the lifetime of such systems. The research work proposes Clustering with Chicken swarm based Energy Efficient (CCEE) algorithm to take care of the advanced issues for useful dynamic data transmission alongside Adaptive Position Update based Geographic Routing (APUGR) protocol. The race of cluster heads deals with mobility and remaining vitality and additionally, the level of availability for choosing nodes to fill in as cluster head set out toward longer duration of time. The cluster formation is exhibited by taking multi-objective fitness work utilizing chicken swarm enhancement. APUGR progressively changes the frequency of position refreshes, in light of the mobility dynamics of the nodes and the sending designs in the system. It depends on two basic standards: (i) nodes whose developments are harder to foresee refresh their positions all the more as often as possible and the other way round, (ii) nodes nearer to broadcasting ways refresh their positions all the more oftentimes and the other way round. In light of this routing, the data transmission from source to end user is extremely viable. The recreation comes about to demonstrate that the execution of CCEE achieves preferred outcomes, which are analyzed over existing energy efficient algorithms plot as far as load balancing factor, throughput, inter packet delivery ratio, average end-to-end delay and power consumption by using NS2 simulations.
Keywords: Adhoc network, load balancing, mobility, energy consumption, Clustering based Energy Efficient (CCEE), Adaptive Position Update based Geographic Routing (APUGR), chicken swarm optimization
