Abstract
Wireless Sensor Networks (WSNs) is the base for many critical applications where a large number of nodes are deployed in the monitored field. Those nodes suffer from limited processing capabilities as well as energy. They are also required to live for a long time; sensors send their data to the sink node through multi-hop routing. The sink node is responsible for making the appropriate decision based on the received data. This shows how critical the information fusion process at the sink node. Such fusion is affected by the quality of the collected information from the deployed sensors. In addition, information handling in the WSN is also affected by environmental conditions, sensors energy, and data reliability, which play important roles in the eminence of information fusion. This paper introduces an efficient environment-aware fusion-based reliable routing algorithm named E3AF. The algorithm takes different parameters into consideration, including environmental metrics, energy consumption balance among sensor nodes, and network and data reliability. The algorithm models the environment to allow the routing algorithm to avoid going through areas marked dangerous. The paper formulates the problem into an optimization problem, which is structured as an Integer Linear programming (ILP) to help grasp and obtain the optimum solution. Furthermore, the paper presents swarm intelligence as a heuristic algorithm when the optimal solution is not possible. In comparison to EFMRP, some of the used equations were corrected, and more realistic conditions and constraints were added. With extensive experiments, the proposed algorithm is evaluated and proved its efficiency.
Highlights
Wireless Sensor Networks (WSNs) are composed of tiny devices with limited capabilities and battery-powered devices called sensors whose primary goal is information fusion
As given by Eq (1) inspired from [2], the scenario is as follows: We look at the value of the environmental data acquired by the sensor nodes for certain environmental factor f, and we check at the normal operation range (EDfL, EDfH ), if it is equivalent, this means that the performance of node i would be not affected by the environmental factor f and the environmental impact metric EDfi (t) is set to 1
E3AF BASED SOLUTION This section deals with the Ant Colony Optimization (ACO) technique as a second solution that we have developed to solve the environment-aware routing problem
Summary
Wireless Sensor Networks (WSNs) are composed of tiny devices with limited capabilities and battery-powered devices called sensors whose primary goal is information fusion. The shortest path causes the depletion of energy sources of sensor nodes in the area surrounding the sink node at a higher rate as compared to the other nodes and subsequently causing unbalanced energy consumption; this is addressed as an energy hole problem [5] This problem has a negative impact on the network lifetime and the successful packet delivery to the sink, and it hinders the performance and the proper information fusion of WSNs [5]. Aware and Reliable Data Reporting Algorithm for Object Tracking in WSNs and Real-Time Energy Reliable Traffic-Aware Routing for Industrial Wireless Sensor Network, with the main goal of reducing the total cost of communications and ensuring compliance with the overall delay at all times Such researches focus on problems related to routing attempting to boost energy efficiency, reliability, and realtime communication without recognizing the consequences of environmental influence, which would be vulnerable to potential environmental changes in chosen routes.
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