Abstract

The contemporary wireless sensor applications employ a Heterogeneous Wireless Sensor Network (HeWSN) to achieve its multi-objective missions. Modern wireless nodes constituting the HeWSN are more versatile in terms of its capabilities, functionalities, and applications. Assigning tasks in a dynamic HeWSN environment are challenging due to its inherent heterogeneous properties and capabilities. The investigation of existing task assignment algorithms reveals (i) the majority of the existing task assignment algorithms were designed for the homogeneous environment, (ii) most of the nature-inspired algorithms were built for centralized architecture. Scheduling tasks by existing task assignment algorithms lead to underutilization of resources as well as to the rapid depletion of network resources. To this end, a novel, distributed, heterogeneous task assignment algorithm adhering the modern sensors capabilities, functionalities and sensor application to attain sustainable computing is required. Based on the investigation, Tissue P-System inspired task assignment algorithm for the distributed heterogeneous WSN has been modelled. The experimental analyses of the proposed method have been self-evaluated as well as compared with the corresponding recent benchmark algorithms under various conditions and its performance metrics are analysed.

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