Particle Swarm Optimized Enhanced Distributed Energy Efficient Clustering (EDEEC-PSO) Protocol for WSN (original) (raw)
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Journal of Information Technology Management (JITM), 2023
Wireless Sensor Networks (WSNs) have been employed in various real-time applications and addressed fundamental issues, such as limited power resources and network life. Several sensor nodes in a WSN monitor the actual world and relay discovered data to base stations. The biggest issue with WSN is that the sensors have a limited lifetime and use much electricity to relay data to the base station. This paper proposes an improved PSO-based Enhanced Distributed Energy Efficient Clustering (EDEEC) algorithm to extend the network's life and reduce power consumption. Clustering is the process of forming groups of sensor nodes. The cluster aims to improve the network's scalability, energy efficiency, and other characteristics. The particle swarm optimization algorithm is modified to obtain energyefficient WSNs. The assessment is based on the essential WSN characteristics, including network lifetime and energy efficiency (power consumption). Compared to LEACH, HEED, and DEEC, our proposed IPSO-EDEEC uses less energy.
International journal of engineering research and technology, 2018
Heterogeneous wireless sensor network (WSN) consists sensor nodes with different computing power and sensing range. Compared with homogeneous Wireless sensor network, deployment and topology management are more complex in heterogeneous WSN. Many routing protocols have been suggested in this regard for achieving energy efficiency and prolonging the lifetime of WSN in heterogeneous scenarios. However, every protocol doesn't fit in this criteria, because in heterogeneous WSN all sensor nodes have a dissimilar energy level and capacity to sense element is different as compare to homogeneous WSN where all the nodes in a network have the same energy level and having same sensing capacity. In this paper, we test Distributed Energy-Efficient Clustering (DEEC), Developed DEEC (DDEEC), Enhanced DEEC (EDEEC) and Threshold DEEC (TDEEC) under several different scenarios containing high level heterogeneity to low level heterogeneity in order to conclude the behavior of those heterogeneous protocols.
Energy-Efficient Heterogeneous Optimization Routing Protocol for Wireless Sensor Network
Instrumentation mesure meĢtrologie, 2020
A wide range of applications include in Wireless Sensor Networks (WSNs), and it is being used extensively in data collection specifically to process the mission-critical tasks. The implementation of routing protocols of energy-efficient (EE) is one of the significant challenging jobs of Sensor Networks (MC-SSN) and Mission Critical Sensors. In hierarchical routing protocols, higher EE can reach when compared to the flat routing protocols. The network's scheduling process doesn't support enhanced balanced Energyefficient network-integrated super-heterogeneous (E-BEENISH), which discusses earlier. An Energy. Energy efficient Time scheduling based particle swarm optimization unequal fault tolerance clustering protocol (EE-TDMA-PSO-UFC) is proposed in this paper. Based on the distance parameter, an efficient cluster head (CH) is selected in this protocol. Owing to the unexpected failure of MCH (Master Cluster Head), an additional "CH" is chosen that is termed as Surrogate cluster head (SCH) for the restoration of network's connectivity in the protocol of PSO-UFC. Based on TDMA (Time Division Multiple Access) protocols, the consumption of Energy. Energy is reduced with the allocation of timeslots during transmission of data. Using the technique of EE-TDMA-PSOUFC, the network's lifespan improves than CEEC and E-BEENISH protocols according to the assessment of simulation results.
International Journal of Intelligent Systems Design and Computing, 2018
Power and resource limitations of the sensor nodes, the possibility of packet loss and delay are the requirements should be considered while designing routing protocol for the wireless sensor network. To meet and achieve these requirements, several routing techniques have been proposed. Clustering-based routing protocol puts a network structure to satisfy energy efficiency, stability and scalability of the network. In such protocols, the network is organised into clusters in which one node will be selected as a cluster head for the cluster. Selecting cluster head and forming the clusters are the key issues in these protocols, as a result, many routing protocols-based clustering have been proposed. With the objective of solving of these issues, reducing the energy consumption and extending the lifetime of the network, in this paper, energy efficiency-based clustering and particle swarm optimisation (EECPSO) method is proposed. EECPSO performance is evaluated and justified through extensive analysis, comparison and implementation. The results show that the proposed method is highly efficient and effective in term of balancing the consumption of energy and prolonging network lifetime.
Engineering Applications of Artificial Intelligence, 2014
Energy efficient clustering and routing are two well known optimization problems which have been studied widely to extend lifetime of wireless sensor networks (WSNs). This paper presents Linear/ Nonlinear Programming (LP/NLP) formulations of these problems followed by two proposed algorithms for the same based on particle swarm optimization (PSO). The routing algorithm is developed with an efficient particle encoding scheme and multi-objective fitness function. The clustering algorithm is presented by considering energy conservation of the nodes through load balancing. The proposed algorithms are experimented extensively and the results are compared with the existing algorithms to demonstrate their superiority in terms of network life, energy consumption, dead sensor nodes and delivery of total data packets to the base station.
ArXiv, 2014
Wireless sensor networks are composed of low cost and extremely power constrained sensor nodes which are scattered over a region forming self organized networks, making energy consumption a crucial design issue. Thus, finite network lifetime is widely regarded as a fundamental performance bottleneck. These networks are used for various applications such as field monitoring, home automation, medical data collection or surveillance. Research has shown that clustering sensor nodes is an efficient method to manage energy consumption for prolonging the network lifetime. Presence of heterogeneity enhances the lifetime and reliability in network. In this paper, we present the distributed and energy efficient clustering protocols which follow the thoughts of Distributed Energy Efficient Clustering protocol. Objective of our work is to analyze that how these extended routing protocols work in order to optimize network lifetime and how routing protocols are improved. We emphasizes on issues e...
Wireless Sensor Networks (WSNs) consist of large number of randomly deployed energy constrained sensor nodes. Sensor nodes have ability to sense and send sensed data to Base Station (BS). Sensing as well as transmitting data towards BS require high energy. In WSNs, saving energy and extending network lifetime are great challenges. Clustering is a key technique used to optimize energy consumption in WSNs. In this paper, we propose a novel clustering based routing technique: Enhanced Developed Distributed Energy Efficient Clustering scheme (EDDEEC) for heterogeneous WSNs. Our technique is based on changing dynamically and with more efficiency the Cluster Head (CH) election probability. Simulation results show that our proposed protocol achieves longer lifetime, stability period and more effective messages to BS than Distributed Energy Efficient Clustering (DEEC), Developed DEEC (DDEEC) and Enhanced DEEC (EDEEC) in heterogeneous environments.
A Review on Energy Efficient Clustering Protocol of Heterogeneous Wireless Sensor Network
International Journal of Engineering and Technology, 2017
Today is the era of information technology, collect the information and use it for required application with technology support. Sensor nodes operating remotely are the popular approach for today's researcher for collecting real time information. But, facing difficulty due to constraints of energy resource for long life monitoring. So there is high need to have energy efficient communication scheme for the betterment of sensor network communication. Clustering protocol is the best option in designing routing protocol for Wireless Sensor Network (WSN). Though we have option of heterogeneity, Clustering approach enhances the energy efficiency of WSN by systematically sharing the load and hence prolongs the lifetime of the network. Most of the researchers achieve energy efficient approach in WSN, by adding different level high energy nodes and use clustering approach to prolong the lifetime of WSN. There are lots of efforts put in reality by researchers for the development of energy efficient schemes with WSN. This paper explored the contribution of different clustering scheme reported in published literature in the three sections as Clustering algorithm basic and its different attributes, suggested Cluster head selection criteria, literature survey and the identified gaps found in published material. The main aim of this paper is to present basic considered in designing clustering algorithm and metrics available for validation.
A Review on Energy Efficient Clustering Protocols of Heterogeneous Wireless Sensor Network
Today is the era of information technology, collect the information and use it for required application with technology support. Sensor nodes operating remotely are the popular approach for today's researcher for collecting real time information. But, facing difficulty due to constraints of energy resource for long life monitoring. So there is high need to have energy efficient communication scheme for the betterment of sensor network communication. Clustering protocol is the best option in designing routing protocol for Wireless Sensor Network (WSN). Though we have option of heterogeneity, Clustering approach enhances the energy efficiency of WSN by systematically sharing the load and hence prolongs the lifetime of the network. Most of the researchers achieve energy efficient approach in WSN, by adding different level high energy nodes and use clustering approach to prolong the lifetime of WSN. There are lots of efforts put in reality by researchers for the development of energy efficient schemes with WSN. This paper explored the contribution of different clustering scheme reported in published literature in the three sections as Clustering algorithm basic and its different attributes, suggested Cluster head selection criteria, literature survey and the identified gaps found in published material. The main aim of this paper is to present basic considered in designing clustering algorithm and metrics available for validation. Summary: CH are selected based on residual energy and it is to be at the central position of cluster .The node with minimum value of energy will be TCH for next round and the node with highest RE is CH for next round, also have the provisioning of sleep period. BS is at the outside the network. 23
Energy-Aware Clustering for Wireless Sensor Networks using Particle Swarm Optimization
2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications, 2007
Wireless sensor networks (WSNs) are mainly characterized by their limited and non-replenishable energy supply. Hence, the need for energy efficient infrastructure is becoming increasingly more important since it impacts upon the network operational lifetime. Sensor node clustering is one of the techniques that can expand the lifespan of the whole network through data aggregation at the cluster head. In this paper, we present an energy-aware clustering for wireless sensor networks using Particle Swarm Optimization (PSO) algorithm which is implemented at the base station. We define a new cost function, with the objective of simultaneously minimizing the intra-cluster distance and optimizing the energy consumption of the network. The performance of our protocol is compared with the well known cluster-based protocol developed for WSNs, LEACH (Low-Energy Adaptive Clustering Hierarchy) and LEACH-C, the later being an improved version of LEACH. Simulation results demonstrate that our proposed protocol can achieve better network lifetime and data delivery at the base station over its comparatives.