Computer
Hayder I. Mutar; Muna M. Jawad
Abstract
Wireless Sensor Networks (WSNs) have become the most cost- effective monitoring solution due to their low cost, despite their major drawback of limited power due to dependence on batteries. Each Sensor Node (SN) is clustered in a particular location and forms a network by self-organizing. They often ...
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Wireless Sensor Networks (WSNs) have become the most cost- effective monitoring solution due to their low cost, despite their major drawback of limited power due to dependence on batteries. Each Sensor Node (SN) is clustered in a particular location and forms a network by self-organizing. They often operate in some of the world's most unusual or dangerous conditions. Networking errors, memory and processor limitations, and energy constraints all pose problems for WSN developers. Many problems in WSNs are expressed as multivariate optimization problems that are solved using biologically inspired techniques. Particle swarm optimization (PSO) is an easy, algorithmically sound, and robust optimization technique. It has been used to address problems like Clustering, data routing, Cluster Head (CH) collection, and data collecting in WSNs. This paper presents a brief analysis of WSN studies in which the PSO algorithm was used as the primary or secondary algorithm for enhancing lifespan of WSNs, focusing on results that show energy efficiency in the sensors, extending the network's life.
Sarah Ammar Rafea; Abdulkareem Abdulrahman Kadhim
Volume 19, Issue 1 , January 2019, , Page 71-81
Abstract
Internet of Things (IoT) enables things to have connectivity throughthe internet. The number of things is growing fast and has to be uniquelyidentified through the Internet to communicate with other things. In WirelessSensor Networks (WSNs) each node can be considered as a thing. WSN noderesources are ...
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Internet of Things (IoT) enables things to have connectivity throughthe internet. The number of things is growing fast and has to be uniquelyidentified through the Internet to communicate with other things. In WirelessSensor Networks (WSNs) each node can be considered as a thing. WSN noderesources are very limited due to the need to communicate using low power andusually through unreliable links. Such limitations need an energy efficientrouting protocol. WSN is considered as a type of Low power and LossyNetwork (LLN). The routing protocol for low power and lossy network (RPL)is being adopted for LLN and has been standardized to enable connectivity ofWSN over IoT. RPL constricted a topology similar to tree topology. Nodes inRPL optimized its path using an objective function (OF). OF depends ondifferent node/link metrics in the optimization process. In this paper, an EnergyThreshold RPL (ETRPL) protocol is proposed. ETRPL depends on a newobjective function to enhance energy consumption of RPL protocol by takinginto account the remaining energy of the preferred parent node. ETRPL isimplemented using Cooja simulator. The results show that ETRPL provides anincrease in the remaining energy of at least 87.4% for a small area with highnumber of nodes. ETRPL also performed better with regards to Time Delay,Packet Reception Ratio, and the number of dead nodes in a small area. For alarge area, the performance is not encouraging. Thus the proposed ETRPLprotocol is useful for IoT networks with relatively small areas.
