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This paper introduces a cluster-based routing scheme for mobile sink-based Wireless Sensor Networks (WSNs) operating in obstacle-prone environments. The approach combines an optimized HEED algorithm for adaptive cluster formation with the D* Lite path planning algorithm for obstacle avoidance. The proposed hybrid routing protocol incorporates directional forwarding and angle-based sector routing, along with energy balancing and mobility tracking, demonstrating improved performance over LEACH and HEED in packet delivery ratio, packet loss ratio, and network lifetime.
Navigate obstacle-laden wireless sensor networks more efficiently with a new routing scheme that boosts packet delivery to 98.5% and extends network life.
Wireless Sensor Networks (WSNs) have become the fundamental technologies in a number of critical applications like environmental mapping, military observation and disaster relief. Nonetheless, physical obstacle cost, energy limits, and dynamic topologies used in the real-world environment have massive impacts on routing performance and network life. The purpose of this paper is to suggest a more powerful and enhanced cluster-based routing scheme that is suitable to be applied to the mobile sink-based WSN in obstacle-prone environment. The suggested approach unites an optimized HEED algorithm of the adaptive cluster development and path planning algorithm D* Lite (avoiding obstacles navigation of sink direction). A hybrid routing protocol that is triple obstacle aware (because it is directionally aware due to directional forwarding and angle aware due to angle based sector routing) is implemented and facilitated by energy balanced and mobility tracking mechanisms in place. It was found by simulation that the model that was proposed behaved better than conventional protocols like LEACH and HEED in most of the important performance parameters. It attains a best case packet delivery ratio of 98.5%, the average packet loss ratio as 1.5% and the lifetime of the network up to 1800 rounds in full energy scenario. Moreover, the model consumes fewer amount of energy per round and accomplishes low average end-to-end delay of 120ms in sparse deployments. The routing plan shows a high level of reliability of data, energy management and capability to resist environmental adversities. The results support the practical use of the model in real-time usage in which data integrity and long-term functionality are critical. This combination of adaptive mobility management and object avoidance renders the proposed solution being very much applicable to dynamic or mission critical WSN applications.
