Prototyping a Scalable P-system-Inspired Dynamic Task Assignment Algorithm for a Centralized Heterogeneous Wireless Sensor Network

Abstract

The recent advancements in wireless communications, embedded processing and electronics have rendered wireless sensor networks (WSNs) an integral role in the development of smart environments and ubiquitous systems. In order to meet the ever-increasing market demands and to overcome the inherent resource-constrained nature of the constituent nodes, modern WSNs are enriched with multi-sensing nodes powered by multi-core processors. Regardless of the node type, the WSNs rely on task assignment algorithms to strategically allocate tasks to the nodes. However, our investigations reveal that a majority of task assignment algorithms are primarily designed for homogeneous WSNs. To this end, (1) the major factors influencing task assignment in a heterogeneous WSN are identified and discussed. (2) To overcome the shortcoming of the natural computing methods, a novel multi-criteria-based, nature-inspired, dynamic task assignment algorithm for centralized heterogeneous WSN inspired by the P-system has been proposed. In the proposed P-system, the nodes are mapped as cell components and the task assignment is achieved by executing the rules in a non-deterministic maximally parallel manner. Simulations were carried out by varying the criteria to achieve the desired application missions and compared with the benchmark methods. Investigation on energy, time, computational complexity, deadline missing ratio and scalability were carried out. The investigations revealed that the proposed algorithm was scalable and was able to attain the desired WSN application mission with lesser deadline missing ratio.