HACH: Heuristic Algorithm for Clustering Hierarchy protocol in wireless sensor networks

Optimization of Clustering in Wireless Sensor Networks: Techniques and Protocols

Recently, Wireless Sensor Network (WSN) technology has emerged extensively. This began with the deployment of small-scale WSNs and progressed to that of larger-scale and Internet of Things-based WSNs, focusing more on energy conservation. Network clustering is one of the ways to improve the energy efficiency of WSNs. Network clustering is a process of partitioning nodes into several clusters before selecting some nodes, which are called the Cluster Heads (CHs). The role of the regular nodes in a clustered WSN is to sense the environment and transmit the sensed data to the selected head node; this CH gathers the data for onward forwarding to the Base Station. Advantages of clustering nodes in WSNs include high callability, reduced routing delay, and increased energy efficiency. This article presents a state-of-the-art review of the available optimization techniques, beginning with the fundamentals of clustering and followed by clustering process optimization, to classifying the existing clustering protocols in WSNs. The current clustering approaches are categorized into meta-heuristic, fuzzy logic, and hybrid based on the network organization and adopted clustering management techniques. To determine clustering protocols’ competency, we compared the features and parameters of the clustering and examined the objectives, benefits, and key features of various clustering optimization methods.

An IRGA-MACS Based Cluster-Head Selection Protocol for Wireless Sensor Networks

In a volatile environment, a substantial number of sensor nodes are extensively dispatched to track and detect changes in physical environment. Although sensor nodes have limited energy resources, so energy-efficient routing is a major concern in Wireless Sensor Networks (WSN) to extend the network’s lifespan. Recent research shows that less throughput, increased delay, and high execution time have been provided with high energy usage. A new mechanism called the IRGA-MACS is proposed to overcome these inherent problems. Firstly, the Improved Resampling Genetic Algorithm (IRGA) is used for the best Cluster Head (CH) selection. Secondly, to assess the shortest path among CHs and nodes, the Modified Ant Colony Optimization based Simulated Annealing (MACS) has been speculated to minimize the time consumption during the transmission. The results show that the proposed approaches attain the supreme goal of increasing the network lifetime compared to existing methods.

Optimization of Routing-Based Clustering Approaches in Wireless Sensor Network: Review and Open Research Issues

In today’s sensor network research, numerous technologies are used for the enhancement of earlier studies that focused on cost-effectiveness in addition to time-saving and novel approaches. This survey presents complete details about those earlier models and their research gaps. In general, clustering is focused on managing the energy factors in wireless sensor networks (WSNs). In this study, we primarily concentrated on multihop routing in a clustering environment. Our study was classified according to cluster-related parameters and properties and is subdivided into three approach categories: (1) parameter-based, (2) optimization-based, and (3) methodology-based. In the entire category, several techniques were identified, and the concept, parameters, advantages, and disadvantages are elaborated. Based on this attempt, we provide useful information to the audience to be used while they investigate their research ideas and to develop a novel model in order to overcome the drawbacks that are present in the WSN-based clustering models.

A Novel Energy-Efficient Clustering Protocol Using Two-Stage Genetic Algorithm for Improving the Lifetime of Wireless Sensor Networks

Wireless sensor networks (WSNs) are beginning to be deployed at an accelerated pace, and they have attracted significant attention in a broad spectrum of applications. WSNs encompass a large number of sensor nodes enabling a base station (BS) to sense and transmit data over the area where WSN is spread.

As most sensor nodes have a limited energy capacity and at the same time transmit critical information, enhancing the lifetime and the reliability of WSNs are essential factors in designing these networks. Among many approaches, clustering of sensor nodes has proved to be an effective method of reducing energy consumption and increasing lifetime of WSNs.

In this paper, a new energy-efficient clustering protocol is implemented using a two-step Genetic Algorithm (GA). In the first step of GA, cluster heads (CHs) are selected, and in the second step, cluster members are chosen based on their distance to the selected CHs. Compared to other clustering protocols, the lifetime of WSNs in the proposed clustering is improved. This improvement is the consequence of the fact that this clustering considers energy efficient parameters in clustering protocol.

Energy Efficient Routing in Wireless Sensor Networks: A Comprehensive Survey

Wireless Sensor Networks (WSNs) are among the most emerging technologies, thanks to their great capabilities and their ever growing range of applications. However, the lifetime of WSNs is extremely restricted due to the delimited energy capacity of their sensor nodes. This is why energy conservation is considered as the most important research concern for WSNs. Radio communication is the utmost energy consuming function in a WSN. Thus, energy efficient routing is necessitated to save energy and thus prolong the lifetime of WSNs. For this reason, numerous protocols for energy efficient routing in WSNs have been proposed. This article offers an analytical and up to date survey on the protocols of this kind. The classic and modern protocols presented are categorized, depending on i) how the network is structured, ii) how data are exchanged, iii) whether location information is or not used, and iv) whether Quality of Service (QoS) or multiple paths are or not supported. In each distinct category, protocols are both described and compared in terms of specific performance metrics, while their advantages and disadvantages are discussed. Finally, the study findings are discussed, concluding remarks are drawn, and open research issues are indicated.

Energy Efficient Techniques in Wireless Sensor Networks

Background:

Wireless Sensor Network (WSN) is a collection of tiny electromechanical nodes termed as sensors. Sensors are equipped with sensing unit, which is designed for application specific. When deployed either by planned or unplanned after deployment, sensor’s energy starts depleting due to various roles like sensing, communication and aggregation.

Method:

WSN is challenged with limited battery power. The aim is to enhance energy efficiency that leads to a prolonged lifetime of networks.

Results:

We have reviewed the patents related to energy efficiency in wireless sensor networks. This Paper presents the study of various energy efficient techniques, which can enhance the lifetime of sensor networks; it covers basics of WSN, their design, Classification, Communication in WSN and a survey of different techniques for effective utilization of sensor’s energy.

Conclusion:

Paper has emphasized on energy efficient clustering technique along with feature wise summary of existing clustering protocols.