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CLUSTER HEAD SELECTION ALGORITHMS FOR ENHANCED ENERGY EFFICIENCY IN WIRELESS SENSOR NETWORKS: A SYSTEMATIC LITERATURE REVIEW
(International Journal of Computer Science and Engineering Survey (IJCSES), 2022-06) Mwangi, Peter Maina; Ndia, John Gichuki; Muketha, Geoffrey Muchiri
The extension of the sensor node's life span is an essential requirement in a Wireless Sensor Network. Cluster head selection algorithms undertake the task of cluster head election and rotation among nodes, and this has significant effects on the network's energy consumption. The objective of this paper is to analyze existing cluster head selection algorithms and the parameters they implement to enhance energy efficiency. To achieve this objective, systematic literature review methodology was used. Relevant papers were extracted from major academic databases Elsevier, Springer, Wiley, IEEE, ACM Digital Library, Citeseer Library, and preprints posted on arXiv. The results show that there are many existing Cluster Head Selection Algorithms and they are categorized as deterministic, adaptive and hybrid. These algorithms use different parameters to elect Cluster Heads. In future the researchers should derive more parameters that can be used to elect cluster heads to improve on energy consumption.
An Extended Low-Energy Adaptive Clustering Hierarchy Routing Protocol for Efficient Energy Consumption in Wireless Sensor Networks
(International Journal of Research in Advent Technology, 2024-06) Mwangi, Peter Maina; Ndia, John Gichuki; Muketha, Geoffrey Muchiri
In wireless sensor networks (WSNs), a primary objective is to extend the lifespan of sensor nodes. Cluster head selection algorithms play a crucial role in electing and rotating cluster heads among nodes, significantly impacting the network's energy utilization. Over the years, various energy-efficient routing protocols have been developed to reduce energy consumption and thereby prolong the network's lifespan. Current energy-efficient routing protocols, such as HEED, TEEN, APTEEN, SHPER, and LEACH, have not fully addressed the challenge of energy consumption in WSNs. LEACH, which stands for Low Energy Adaptive Clustering Hierarchy, is a well-known clustering protocol designed for energy-efficient data gathering in WSNs. However, the processes of selecting cluster heads and the effectiveness of data aggregation in the basic form of LEACH can be complex. This study aims to develop an extended version of the Low Energy Adaptive Clustering Hierarchy routing protocol that employs an extended K-Means Cluster Head Selection Algorithm to choose cluster heads more effectively. The developed protocol is intended to enhance the longevity of WSNs. A quantitative approach has been utilized to measure performance by simulating various routing protocols. To demonstrate the advantages of the proposed protocol, we compared it against previous protocols using several metrics, including residual node energy, packet delivery ratio, throughput, network longevity, average energy consumption, and the number of live and dead nodes. The results indicate that the proposed protocol outperforms existing protocols, such as LEACH and SEP.
A Systematic Literature Review of Routing Protocols in Wireless Sensor Networks: Current Trends and Future Directions
(International Journal of Research in Advent Technology, 2024-12) Mwangi, Peter Maina
Wireless Sensor Networks (WSNs) have emerged as a key technology in various applications, ranging from environmental monitoring to healthcare and industrial automation. Efficient data communication among sensor nodes is essential for the success of WSNs, and routing protocols play a critical role in determining the overall network performance. This review aims to comprehensively analyze and synthesize the existing literature on routing protocols in WSNs, highlighting their strengths, weaknesses, and applications. The review also aims to highlight various performance indicators (metrics) used by researchers to evaluate the performance of routing protocols in WSN, emerging trends that may influence the future design of routing protocols in WSN, and security concerns in WSN routing protocols. To attain this goal, a systematic literature review process was employed based on Barbara Kitchenham's original guidelines (2007). Relevant papers were retrieved from major academic databases such as Elsevier, Springer, Wiley, IEEE, and the ACM Digital Library, as well as preprints posted on arXiv. The findings demonstrate that various existing routing protocols have been created throughout time and are classified as data-centric, location-based, mobility-based, multi-path-based, heterogeneity-based, and hierarchical routing protocols. The routing protocols in WSNs vary depending on the application and network architecture. The paper also focuses on the performance criteria used to evaluate them, their pros, limitations, areas of applications, emerging trends in WSN, and security challenges. The future of WSN routing protocols is moving toward intelligent, adaptive, and robust protocols that can serve larger, more complex networks
AN EXTENDED K-MEANS CLUSTER HEAD SELECTION ALGORITHM FOR EFFICIENT ENERGY CONSUMPTION IN WIRELESS SENSOR NETWORKS
(International Journal of Network Security & Its Applications (IJNSA), 2023-05) Mwangi, Peter Maina; Ndia, John Gichuki; Muketha, Geoffrey Muchiri
Effective use of sensor nodes’ batteries in wireless sensor networks is critical since the batteries are difficult to recharge or replace. This is closely connected to the networks’ lifespan since once the battery is used up, the node is no longer useful. The entire network will not function if 60 to 80% of the nodes in it have completely depleted their energy. In order to minimize energy usage and sustain the network for a long time, many cluster head selection algorithms have been developed. However, the existing cluster head selection algorithms such as K-Means, particle swarm selection optimization (PSO), Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Fuzzy C-Means (FCM) cluster head election algorithm have not fully reduced the issue of energy usage in WSN. The objective of this paper was to develop an extended K Mean Cluster Head selection(CHS) algorithm that uses remaining energy, distance between node and base station, distance between nodes and neighbour nodes, node density, node degree Maximum Cluster size, received signal strength indicator (RSSI) and Signal to Noise Ratio. The algorithm developed was used to enhance the lifespan of WSNs. The performance of the simulated variants of LEACH routing protocols is measured and evaluated using the quantitative research methodology. Utilizing residual node energy, packet delivery ratio, throughput, network longevity, average energy usage, and the number of live and dead node, the suggested approach is contrasted to previous approaches. From the study we observed that the proposed approach outperforms existing actual LEACH, Mod-LEACH and TSILEACH approaches.
Machine Learning Load Balancing Techniques in Cloud Computing: A Review
(International Journal of Computer Applications Technology and Research, 2022) Muchori, Juliet Gathoni; Mwangi, Peter Maina
Load balancing (LB) is the process of distributing the workload fairly across the servers within the cloud environment or within distributed computing resources. Workload includes processor load, network traffic and storage burden. LB’s main goal is to spread the computational burden across the cloud servers to ensure optimal utilization of the server resources. Cloud computing (CC) is a rapidly growing field of computing that provides computing resources as a product over the internet. This paper focuses on the issues within Cloud Load Balancing (LB) that have attracted research interest. The paper also mainly focused on uncovering machine learning models used in LB techniques. The most common algorithms in the reviewed papers included Linear Regression, Random Forest classifier (RF) Artificial Neural Network (ANN), Convolutional Neural Network (CNN) and Long-Short Term Memory- Recurrent Neural Network (LSTM -RNN). The criteria for LB technique was identified through performance metrics like throughput, response time, migration time, fault tolerance and power saving. The paper adjourns by identifying research gaps found in the reviewed literature.