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EEMOR: Energy Efficient Metaheuristic Opportunistic Routing Protocol for WSNs
Soni Chaurasia and Kamal Kumar
Wireless sensor networks (WSNs) sense the data from the physical region and transmit the data to the Base station (BS) or sink. It is a self-organizing network with a limited battery. Due to limited energy, the network’s lifetime is one of the most critical issues in WSNs and mandates the use of an energy-efficient routing protocol in WSNs. Their many routing algorithms optimize this goal. But in real-time applications, network overload and coverage factors affect the performance of routing schemes in a complex way. The meta-heuristic based opportunistic routing algorithms present an alternative to correct these trade-offs. The meta-heuristic decision-making approach involves local nodes to perform the computation, and the BS receives the results of analyses or decisions. This paper presents a recently researched idea and proposes a situation-based novel Energy Efficient Meta-heuristic Opportunistic Routing protocol for WSNs (EEMOR). Dragonfly (DA) meta-heuristic is exploited for route optimization besides addressing energy concerns primarily. EEMOR’s route searching is modelled as a transition from an initial state to any desired state in terms of residual energy, node density and distance. It selects the optimal forwarders using a Meta-heuristic Function (MHF) or an Energy Level Matrix (ELM). EEMOR performance is compared with other routing protocols on essential parameters such as Packet delivery ratio (PDR), Message success rate (MSR), through-put and Average Energy Consumption (AEC). The experiments of the proposed work exhibit improved performance in relevant parameters such as PDR (99%), MSR (200 bits/s), Throughput (896 kbps) and AEC (26 J). The simulation results show that the EEMOR considerably outperforms its competitive techniques in terms of energy efficiency.
Keywords: WSN, meta-heuristic, opportunistic routing, energy efficient, optimal forwarders
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