Energy Efficient Clustering Scheme Research Articles

TEDDEEC: Threshold enhanced developed distributed energy-efficient clustering for heterogeneous wireless sensor networks

Wireless Sensor Networks (WSNs) comprise of vast number of arbitrarily conveyed energy required sensor nodes. Sensor nodes have capacity to sense and send detected information to Base Station (BS). Detecting and in addition transmitting information towards BS require more energy. In WSNs, sparing energy and developing network lifetime are awesome difficulties. Clustering is a key method used to enhance energy utilization in WSNs. Among two types of network; Homogeneous and Heterogeneous, the later has demonstrated to be significantly more essential in upgrading the network lifetime and making the network a great deal more energy adjusted with fitting probabilistic cluster head choice. In this paper, a novel clustering based routing protocol called Threshold Enhanced Developed Distributed Energy Efficient Clustering scheme (TEDDEEC) for heterogeneous WSNs is proposed. This method depends on more efficient selection of Cluster Heads (CH) for the rounds. Simulation is carried out for different proportion of normal and advanced nodes. Simulation results demonstrate that this proposed scheme accomplishes longer lifetime, stability period and more effective messages to BS than Enhanced Developed Distributed Energy Efficient Clustering scheme (EDDEEC) in heterogeneous situations.

A Novel Topology-scale-adaptive and Energy-efficient Clustering Scheme for Energy Sustainable Large-Scale SWIPT-enabled WSNs

A Novel Topology-scale-adaptive and Energy-efficient Clustering Scheme for Energy Sustainable Large-Scale SWIPT-enabled WSNs

Metaheuristic algorithm for energy efficient clustering scheme in wireless sensor networks

The utilization of wireless sensor networks (WSNs), which combine sensing, communication, and computation in an intelligent environment. The use of energy becomes the primary obstacle for sensor nodes to overcome. Clustering and routing algorithms are promising ways to fix the issue and prolong the network's effectiveness. The availability of restricted energy resources is the most significant challenge in WSNs. In this paper, we propose an energy-efficient clustering scheme integrated with a particle swarm optimization method called PSO-EECS for wireless sensor networks to raise energy efficiency while simultaneously increasing the lifetime of sensor nodes. The predominant concern being addressed in this paper is the selection of a Cluster Head (CH), which helps gather, aggregate and forward the data from the cluster-based routing paradigm. PSO-EECS algorithm is used to optimize the fitness parameters for CH selection, which include the energy ratio, distance considerations, node density, load balancing, and the Network's average energy, among other things. The simulation results reveal that the proposed technique offers a considerable improvement in network stability and operation time compared to the currently used approaches. Compared to the PSOGSA, GAPSOH, and ABE-DE protocol, simulation findings demonstrate that PSO-EECS enhances stability by 95.4%, 34.8%, and 29.2%, respectively.

A Review Paper on Energy Efficient Clustering Schemes for WSN Assisted IOT Networks

“Abstract”:WSNs have seen a large improvement in their applications in recent years. WSNs are self-organized, non- wired networks that monitor ambient conditions such as temperature, tension, motion, audio, vibration, or contaminants and transmit data. Because of its sensor-based working standards, the WSN is becoming a common topic among numerous investigators. Clustering is a method used in WSNs to extend network lifecycle & provide more effective operating processes. Clustering is a topology management method that can gather nodes to boost efficiency of the network by controlling resources and distributing duties between many nodes in an adequate way. It divides a sensing field into clusters where cluster's sensor node can be appointed as cluster head. The cluster-dependent routing protocol is a very energy-efficient technique of choosing and relaying information to the CH. Optimized clustering could save a significant amount of energy in the system. This review examines a variety of energy-efficient clustering methods utilized in the wireless sensor area. Keywords: WSN, Energy Efficiency, Clustering, Cluster Head, Clustering protocols.

Cluster Head Selection and Multipath Routing Based Energy Efficient Wireless Sensor Network

The Wireless Sensor Network (WSN) is a network of Sensor Nodes (SN) which adopt radio signals for communication amongst themselves. There is an increase in the prominence of WSN adaptability to emerging applications like the Internet of Things (IoT) and Cyber-Physical Systems (CPS). Data security, detection of faults, management of energy, collection and distribution of data, network protocol, network coverage, mobility of nodes, and network heterogeneity are some of the issues confronted by WSNs. There is not much published information on issues related to node mobility and management of energy at the time of aggregation of data. Towards the goal of boosting the mobility-based WSNs’ network performance and energy, data aggregation protocols such as the presently-used Mobility Low-Energy Adaptive Clustering Hierarchy (LEACH-M) and Energy Efficient Heterogeneous Clustered (EEHC) scheme have been examined in this work. A novel Artificial Bee Colony (ABC) algorithm is proposed in this work for effective election of CHs and multipath routing in WSNs so as to enable effective data transfer to the Base Station (BS) with least energy utilization. There is avoidance of the local optima problem at the time of solution space search in this proposed technique. Experimentations have been conducted on a large WSN network that has issues with mobility of nodes.

A greedy energy efficient clustering scheme based reinforcement learning for WSNs

A greedy energy efficient clustering scheme based reinforcement learning for WSNs

ENERGY AWARE ROUTING FOR WIRELESS SENSOR NETWORKS

Wireless sensor networks are used in improving conditions in the practical field and real life which lead researchers and developers to further research it and work into improving this field. These networks consist of sensor nodes that can help acquire data and information about temperature and pressure dependent on the environment of the location which are sent from. After all that, we are bounded by a really important factor which can determine everything which is Energy. Since sensor nodes send data and information to web applications, they need an energy source to operate. Their main energy source is their batteries which offer limited source of energy. Hence, various protocols are introduced to help in many parameters of a wireless sensor network such as increasing lifetime and decreasing consumption of energy, in other words, increasing the Energy Efficiency (EF). In this paper, we evaluate consumption of average energy for various protocols used in this context after each complete logical round for these protocols, such as Energy Efficient Clustering Scheme and Stable Election Protocol. Finally, we used Matlab tool to generate results which indicate that the protocol used in this paper is efficient and reliable.

Energy efficient clustering and topology management scheme for wireless sensor networks

Energy efficient clustering and topology management scheme for wireless sensor networks

Energy Efficient Clustering for Certificate Revocation Scheme in Mobile Ad-Hoc Network

Mobile ad hoc networks (MANETs) have a wide range of uses because of their dynamic topologies and simplicity of processing. Inferable from the autonomous and dynamic behavior of mobile nodes, the topology of a MANET frequently changes and is inclined to different attacks. So, we present certificate revocation which is an efficient scheme is for security enhancement in MANET. This certificate revocation scheme is used to revoke the certificate of malicious nodes in the network. However, the accuracy and speed of the certificate revocation are further to be improved. By considering these issues along with the energy efficiency of the network, an energy-efficient clustering scheme is presented for certificate revocation in MANET. For cluster head (CH) selection, an opposition based cat swarm optimization algorithm (OCSOA) is proposed. This selected CH participates in quick certificate revocation and also supports to recover the falsely accused nodes in the network. Simulation results show that the performance of the proposed cluster-based certificate revocation outperforms existing voting and non-voting based certificate revocation in terms of delivery ratio, throughput, energy consumption, and network lifetime.

Clustering-cum-Handover Management Scheme for improved Internet access in high-density mobile wireless environments

The accessibility of ubiquitous communication services from various wireless technologies has become essential in the current Internet of everything (IoE) era. It is crucial for mobile users residing in densely populated areas to get the provision of uninterrupted connectivity and seamless services. To this end, this paper provides a mechanism for uninterrupted connectivity to a maximum number of users with the available resources. We propose a master/slave model in a 4G-Wi-Fi integrated network. Our novel Clustering-cum-Handover Management Scheme (CHMS) for dynamic cluster management together with the handover management in high density mobile wireless environment dispenses the unrestricted movement without connectivity loss and quality sacrifice. The dynamically configured clustering protocol of CHMS provides reduced cluster formation overhead and balances the load between cluster heads. To make smart selections, a distance-based energy-efficient clustering scheme is proposed for calculating the chances of a mobile device to become a cluster head. The seamless handover mechanism of CHMS manages the mobility of both the cluster head and cluster member while considering the limited energy of devices. It also achieves high network throughput and reduced end-to-end delay during handovers. Furthermore, our evaluation shows that CHMS provides application-specific quality of service even in highly dense wireless environments.

A Survey on Energy-Efficient Strategies in Static Wireless Sensor Networks

A comprehensive analysis on the energy-efficient strategy in static Wireless Sensor Networks (WSNs) that are not equipped with any energy harvesting modules is conducted in this article. First, a novel generic mathematical definition of Energy Efficiency (EE) is proposed, which takes the acquisition rate of valid data, the total energy consumption, and the network lifetime of WSNs into consideration simultaneously. To the best of our knowledge, this is the first time that the EE of WSNs is mathematically defined. The energy consumption characteristics of each individual sensor node and the whole network are expounded at length. Accordingly, the concepts concerning EE, namely the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective, are proposed. Subsequently, the relevant energy-efficient strategies proposed from 2002 to 2019 are tracked and reviewed. Specifically, they respectively are classified into five categories: the Energy-Efficient Media Access Control protocol, the Mobile Node Assistance Scheme, the Energy-Efficient Clustering Scheme, the Energy-Efficient Routing Scheme, and the Compressive Sensing--based Scheme. A detailed elaboration on both of the basic principle and the evolution of them is made. Finally, further analysis on the categories is made and the related conclusion is drawn. To be specific, the interdependence among them, the relationships between each of them, and the Energy-Efficient Means, the Energy-Efficient Tier, and the Energy-Efficient Perspective are analyzed in detail. In addition, the specific applicable scenarios for each of them and the relevant statistical analysis are detailed. The proportion and the number of citations for each category are illustrated by the statistical chart. In addition, the existing opportunities and challenges facing WSNs in the context of the new computing paradigm and the feasible direction concerning EE in the future are pointed out.

Scalable Energy Efficient Hexagonal Heterogeneous Broad Transmission Distance Protocol in WSN-IoT Networks

In this paper hexagonal heterogeneous broad transmission distance protocol (HEXA-HTBTDP) is introduced and scalability analysis is performed in the context of internet-of-things (IoTs). A two-dimensional (2-D) hexagonal field is taken for the random deployment of sensor nodes which will be beneficial in the recently emerging integrated wireless sensor network-internet-of-things (WSN-IoTs). This technology opens new horizons for the cellular and mobile communications. With the growing demand for an efficient utilization of resources at present, it is a challenging task to develop clustering protocols which support wirelessly connected heterogeneous sensor nodes. They exist either independently or embedded within devices in the network. With a common objective of achieving energy efficiency, reliable communication, connectivity and coverage of network field, scalability is analyzed by varying the number of nodes and their initial energies. Two-level energy heterogeneity is adopted in the form of normal and advanced nodes. HEXA-HTBTDP is compared with hexagonal field versions of classical protocols viz. hexagonal stable election protocol (HEXA-SEP) and hexagonal energy efficient heterogeneous clustered scheme (HEXA-EEHC). Benchmarking parameters used for the comparison of results are stability period, network lifetime, instability period, residual energy and energy variance. The hexagonal field will expand the current scenario of clustering for the achievement of quality of service (QoS) and quality of user experience (QoE) in real time WSN-IoT systems.

Energy consumption and network connectivity based on Novel-LEACH-POS protocol networks

Wireless sensor network (WSN) is used for a large number of sensor nodes and energy efficiency is important to constrained resources in wireless sensor networks. Wireless sensors networks use multiple approaches such as data cycling, energy optimal scheduling and energy aware routing to reduce energy consumption throughout the network. Energy awareness is an essential design for WSNs hence, data broadcasting protocols, routing and power management are specially designed to meet their requirements. The past decade was mitigating the issues of energy dissipation to ensure energy efficient routing and clustering. To address these issues, a novel idea is presented where the energy efficiency will incorporate the selection mechanism of nodes. In Wireless Sensor Networks, path routing for nodes is a difficult and tricky task. It is a crucial role to increase the stability and network lifetime. The LEACH Protocol is a measured level of the sensor networks lifetime by pairing the node energy consumption. Simulation results show that protocol outperform its routing protocols Low Energy Adaptive Clustering Hierarchy (LEACH) and Novel-LEACH in terms of network connectivity and power consumption. Also, a new energy efficient clustering scheme for WSNs with the use of Particle Swarm Optimization (PSO) is proposed. The clustering algorithm is implemented with the goal of concurrently minimizing the intra-cluster distance along with optimizing the usage of network energy.

Improved Enhanced Distributed Energy Efficient Clustering (iE-DEEC) Scheme for heterogeneous Wireless Sensor Network

Wireless Sensor Networks (WSNs) contain thousands of sensor nodes which are capable of conveying sensed and captured data from any deployment area to another well –resourced node called the Base station for analysis. Due to the ability of the sensor nodes to relay data from one place to the other, they are found applicable in several areas such as environmental monitoring, military surveillance and home intelligence. The operation of the heterogeneous routing algorithm, E-DEEC (Enhanced Distributed Energy-Efficient Clustering) for heterogeneous networks has been observed carefully. The E-DEEC scheme improved the DEEC algorithm by introducing other nodes called supernodes. It was realized that E-DEEC did not consider the proximity of the advanced nodes to the Base station in its election probabilities. This compelled the supernodes with higher residual energy but far from the Base station to dissipate a large amount of energy in conveying their reports to the Base station. In this research work, an improved heterogeneous algorithm, iE-DEEC, is proposed. The new scheme considered the distance of supernodes and the average distance of the nodes to the Base station (BS) in selecting the cluster heads (CHs). Also, different amplification energy levels have been implemented in this protocol to minimize the energy consumption during the communication between the CHs and BS and also between inter and intra cluster communication. MatLab 2017a was used for simulation to evaluate the performance of the new scheme and the existing protocol. The simulation results showed that the proposed protocol performed better than E-DEEC in terms of throughputs, residual energy and network lifetime.

Energy efficient scalability of three level hexagonal heterogeneous broad transmission distance protocol (3L‐HEXA‐HTBTDP) for WSN‐IoT networks

SummaryMultilevel heterogeneity is the present demand of wireless sensor networks as well as internet‐of‐things for balanced energy consumption of the network systems. In this paper, three level hexagonal heterogeneous broad transmission distance protocol (3L‐HEXA‐HTBTDP) is introduced for increasing the energy efficiency of the network. Normal, advanced, and superadvanced sensor nodes in a hexagonal field represent three level heterogeneity. These nodes are elected as cluster heads (CHs) on the basis of new thresholds, thus transferring the collected data to the base station. The protocol is beneficial in cellular communication and web‐of‐things applications to fulfill the high energy requirements of the wireless systems. The scalability is done here for perceiving the differences in the application of proposed algorithm 3L‐HEXA‐HTBTDP on different number of sensor nodes with variable values of initial energies. This is a promising approach to achieve reliable communication, coverage, and connectivity among sensor nodes of the hexagonal field. The scheme is evaluated through exhaustive simulation using Matlab. It is compared with the previous approaches of clustering implemented on the hexagonal field. Different performance parameters like alive node metrics, stability period, network lifetime, residual energy, and variance of energy are used for benchmarking the results of 3L‐HEXA‐HTBTDP with three level hexagonal stable election protocol (3L‐HEXA‐SEP) and three level hexagonal energy efficient heterogeneous clustered scheme (3L‐HEXA‐EEHC). In general, it is observed that the proposed 3L‐HEXA‐HTBTDP outperforms other existing protocols.

An Energy Efficient and Load Balancing Clustering Scheme for Wireless Sensor Network (WSN) Based on Distributed Approach

One of the most critical problem and challenging in Wireless Sensor Networks (WSNs) is to reduce energy consumption in order to prolong network lifetime of WSNs. Clustering technique is one of the techniques which have been used to provide energy efficiency.. However Most of clustering schemes select the cluster head either randomly without considered important parameters or based on centralized approach by utilizing the base station which can affect the network scalability. In addition, single hop communication is used by CHs to forward their sensed data to the CH which lead to increases energy consumption of CHs in large scale network. Therefore in this paper clustering scheme is proposed based on distributed approach, different parameters are consider for cluster head selection and also for multi-hop communication. Results shows that the proposed scheme have better performance in term of energy consumption and number of alive sensor nodes

Energy Efficient Clustering of Statistically Distributed Heterogeneous Wireless Sensor Networks for Internet-of-Things

This paper shows the effect of random as well as six statistical distributions on heterogeneous wireless sensor network (WSN) for internet-ofthings (IoTs). The distribution of sensor nodes in a WSN reflects the significant variation occurring in the lifetime performance of network operation. Novel models of heterogeneous clustering permit the sensor nodes to communicate with different devices of the future WSN-IoT systems in a unique fashion. Different statistical distributions viz. Random, Exponential, Chi-Square, Weibull, Gamma, Gaussian and Beta on heterogeneous broad transmission distance protocol (HT-BTDP) are used here for observing the changes in the performance parameters such as network lifetime, residual energy and energy variance. The strategies are validated on the basis of simulation and compared with various distributions on the classical protocols like stable election protocol (SEP) and energy efficient heterogeneous clustered (EEHC) scheme also.

Energy Efficient Clustering Scheme (EECS) for Wireless Sensor Network with Mobile Sink

The participants in the Wireless Sensor Network (WSN) are highly resource constraint in nature. The clustering approach in the WSN supports a large-scale monitoring with ease to the user. The node near the sink depletes the energy, forming energy holes in the network. The mobility of the sink creates a major challenge in reliable and energy efficient data communication towards the sink. Hence, a new energy efficient routing protocol is needed to serve the use of networks with a mobile sink. The primary objective of the proposed work is to enhance the lifetime of the network and to increase the packet delivered to mobile sink in the network. The residual energy of the node, distance, and the data overhead are taken into account for selection of cluster head in this proposed Energy Efficient Clustering Scheme (EECS). The waiting time of the mobile sink is estimated. Based on the mobility model, the role of the sensor node is realized as finite state machine and the state transition is realized through Markov model. The proposed EECS algorithm is also been compared with Modified-Low Energy Adaptive Clustering Hierarchy (MOD-LEACH) and Gateway-based Energy-Aware multi-hop Routing protocol algorithms (M-GEAR). The proposed EECS algorithm outperforms the MOD-LEACH algorithm by 1.78 times in terms of lifetime and 1.103 times in terms of throughput. The EECS algorithm promotes unequal clustering by avoiding the energy hole and the HOT SPOT issues.

Hybrid Multihop Partition-Based Clustering Routing Protocol for WSNs

Wireless sensor networks (WSNs) have great potential in the application of partition parameter observation; however, the high correlation with applications makes WSNs working in specific environments require specific work patterns. In this article, a hybrid multihop partition-based clustering (HMPBC) routing protocol is proposed, which can fit a specific environment, meet interests and needs, balance network load, and prolong the network lifetime. In HMPBC, both the single-chain structure within cluster and the cluster heads selection depending on residual energy are operated by self-organization, and the region minimum spanning tree structure among clusters is established by the base station. The proposed protocol is simulated in MATLAB with the network model of 200m $\times$ 200m 400 nodes. Simulation results show that HMPBC has 33.31 and 39.70 longer lifetime, smaller fluctuations of average energy consumption of each node per round, and more precise measurement of zone parameters than LEACH-MLOR and the energy efficient hybrid multihop clustering scheme.

English

English