Energy Efficiency In WSN Research Articles

An efficient Analysis of the Fusion of Statistical-Centred Clustering and Machine Learning for WSN Energy Efficiency

Recently, wireless sensor networks on several challenging topics have piqued researchers’ attention. Maximising a network's lifetime requires just the right combination of cluster size and number of nodes. Data transmission from nodes to cluster leaders is energy intensive, even for a modest number of clusters. If there are several clusters, many leaders will be chosen, and many nodes will rely on long-distance transmission to communicate with the home base. Therefore, in order to maximise efficiency, it is necessary to strike a balance between these two factors. WSN's major challenge is improving its energy efficiency. This is because their energy consumption defines their lifespan, and it is difficult, if not impossible, to recharge their batteries. Therefore, it is crucial to develop algorithms that consume as little energy as possible in order to maximise the network's potential. The perfect clusters are essential for the longevity of the network. Therefore, an algorithm called statistical centre energy efficient clustering approach (SEECA) is presented to increase the network's lifetime while decreasing its energy consumption. The experimental findings show that the proposed methodology SCEECA outperforms the LEACH method by a wide margin, with gains of 32% in Residual energy, 16% in Network Lifetime, and 12% in Throughput.

SSFSCE: Design of a Sleep Scheduling based Fan Shaped Clustering Model to enhance working Energy Efficiency of WSN

To enhance energy level in WSN is a research requirement, which assists in improving their lifetime over a series of communications. To achieve this target, a various variety of clustering & sleep scheduling models are discussed by researchers. Most of these models deploy static clustering & sleep scheduling operations, which limits their applicability & scalability levels. Moreover, dynamic clustering & scheduling models are highly complex, which reduces temporal QoS performance under real-time use cases. In order to reduce the probability of these issues, this text discusses design of the proposed Sleep Scheduling based Fan Shaped Clustering Model to enhance working Energy Efficiency of WSN. The proposed model initially deploys a Grey Wolf Optimization (GWO) Method for dynamic sleep scheduling via temporal performance analysis. The GWO Method models a fitness function that combines temporal usage levels, temporal Quality of Service (QoS), and temporal energy levels. Based on this modelling process, nodes were categorized into wake & sleep nodes, which were further clustered via destination-aware Fan Shaped Clustering (FSC), that assisted in improving QoS performance under multiple scenarios. The FSC Model was combined with a QoS-aware routing model, that assisted in selection of routing paths that can achieve low delay, high throughput, and high packet delivery with higher energy efficiency levels. Efficiency of the model was tested on node & network conditions, and its QoS performance was checked in terms of communication delay, consumption of energy, level of throughput, and Packet Delivery Ratio (PDR) levels. On the basis of these comparative evaluations, it is observed that the new proposed model is able to enhance end-to-end delay by 8.5%, reduce level of energy by 15.5%, while increasing throughput by 8.3%, and PDR by 1.5%, thus making it useful for a different real-time conditions.

A mathematical optimization of the lifetime of the wireless sensor network using ML- based energy dependent clustering and tiered routing algorithm

Significant research work is being done in the field of WSN and standardization of many aspects is being looked into. The most well-known procedures for optimising energy in WSNs are using hierarchical topology. LEACH is a hierarchical topology which was introduced initially and served as the basis for achieving energy efficiency in WSN. However, LEACH has certain limitations which has led to a lot of research in improving the conventional LEACH performance. The current study is based on the use of certain algorithms and strategy to enhance the performance of the conventional LEACH protocol. By focusing on parameters such as cluster head formation, energy expenditure in transmission etc., the performance such as throughput and network life may be extended using this enhanced LEACH.

Analysis of Algorithms to Control the Congestion by Improve Energy Efficiency in WSN

Congestion is a major significant challenge in WSNs because it directly impacts energy efficiency and the network lifetime of sensor nodes in the network. This paper aims to analyze the different congestion control or avoidance routing protocols performances in WSNs with their drawbacks for identifying the upcoming scope of congestion-aware routing protocols in WSNs. This article proposed an adaptive queuing system with the WPDDRC called a proficient control (PRC) algorithm to tackle this issue. In this algorithm, two independent virtual queues are considered single physical length (lines), which accumulate the input packets from every child's node depending on the source's traffic significance and priority. A Proficient Rate Control (PRC) technique develops using traffic type priority and virtual queue conditions. Here, a PRC with fair bandwidth allocation (PRC-FBA) technique is compared and analyzed. It must handle the congestion due to the mix of RT and Non-RT (NRT) packets effectively in network.

Throughput Analysis of EERP Protocol

Abstract: Grouping techniques in WSN for Energy effectiveness has been tended to by different specialists because of promising upgrades in the exhibitions. The Energy utilization despite everything has an open door for development regarding multifaceted nature decrease, decrease in Energy utilization and lifetime of the system. The work introduced in this paper contributes a novel methodology for Energy efficiency in WSN. The throughput and packet delivery comparative analysis is performed in which EERP outperforms the LEACH protocol. Keywords: LEACH, WSN, K-medoid, clustering, routing

Impact of Network Topology on Energy Efficiency in WSN

<p class="0abstractCxSpFirst"><span lang="EN-US">Wireless communication network has a significant success in scientific and industrial communities. Due to its various advantages, this technology is considered as a key element in current network architectures. It represents the architecture that allows to group a large number of sensors to collect information about a physical process in different environments. The gathered data is transmitted to base station which communicates the information to the end user.</span></p><p class="0abstractCxSpFirst">Several protocols are proposed for WSNs routing, by considering the limited capacities of sensor nodes according to a specific topology that allows to organize the nodes within the network. However, the performance of each routing protocol mainly depends on the application requirements and its results in terms of the lifetime of WSN and satisfaction of objectives defined.</p><p class="0abstractCxSpLast"><span lang="EN-US">According of the structure of WSN, the routing techniques can be divided in three types hierarchical, location-based flat routing. This paper, present the different routing techniques in WSN, based on the organization of nodes in sensor area. We focus specially to study the three types, cluster-based, chain-based and location-based routing techniques. These techniques will be simulated in order to compared their performances with our protocol Location-Based LEACH (LOC-LEACH).</span></p>

RETRACTED ARTICLE: Denaturalized cluster organization based improving energy constraints using relay link chain routing protocol in wireless sensor network

Energy constraints is an important for routing standards in cooperative transmission to make a better communication on wireless medium. The WSN broadcast communication leads Loss of energy, broken link, non-relay network issues because of cooperative network does not make efficient routing standards. Most of the energy efficient schemas possess the network wide broadcast protocol (NWBP) to oppose the challenges in WSN. To improve the energy efficiency in WSN, we propose a denaturalized cluster organization to form the centralized cluster head (DNC-CCH) communication on route head to make the transmission without sleeping nodes on networks have the on state available node from source to destination. In Addition by improving energy constraints using relay link chain routing protocol (RLCRP) in wireless sensor network make an relay on routing to choose the non-sleeping cluster nodes relies the neighbor discourse supposed to the delay routing propagation. This select the closest relay links to make the continues link on really transmission with aggregate data from source to destination with improved energy. Also this consider the neighboring senders to improve the lifespan of the network nodes to make energy efficient routing standards and life time of WSN cooperative communication.

Balanced wireless sensor networks with energy efficient bees swarm–harmony Search–Hill Climbing mechanism

SummaryWireless sensor networks (WSNs) are widely employed in various sectors, which include health care, military, automotive, and manufacturing sectors. Most of these applications use WSN with certain limitations in terms of its computational power, storage capability, and energy supply. Among this, energy supply is considered to be a major limitation for these sectors. Therefore, prolonging the lifetime of the network by improving the energy efficiency in WSN is a common objective in many types of research. In this research, the WSN energy efficiency is improved using the data aggregation clustering technique by balancing the energy consumption among the sensor nodes. To balance the energy consumption, an efficient selection of cluster heads is required with faster convergence and an improved search pattern. In accomplishing this, a hybrid architecture that combines Bees Swarm Optimization (BSO) with Harmony Search Algorithm (HSA) is used. The combination of both BSO and HSA tends to achieve premature convergence that leads to poor selection of cluster head. Hence, to increase the optimal and faster convergence, the proposed system uses the Hill Climbing algorithm to reach the optimal solution with faster convergence in a shorter computational time. The experiments are conducted with various node densities between the proposed and existing methods. The result shows that the proposed method is active in improving the search capability in effectively finding the cluster heads for improved routing paths.

Improving Energy Efficiency in Internet of Things using Artificial Bee Colony Algorithm

Background: With the advent of IoT, the deployment of batteries with a limited lifetime in remote areas is a major concern. In certain conditions, the network lifetime gets restricted due to limited battery constraints. Subsequently, the collaborative approaches for key facilities to reduce the constraint demands of the current security protocols. Objective: This work covers and combines a wide range of concepts linked by IoT based on security and energy efficiency. Specifically, this study examines the WSN energy efficiency problem among IoT devices and security for the management of threats in IoT through collaborative approaches and finally outlines the future. The concept of energy-efficient key protocols which clearly cover heterogeneous IoT communications among peers with different resources has been developed. Because of the low capacity of sensor nodes, the energy efficiency in WSNs has been an important concern. Methods: In this paper, we present an algorithm for Artificial Bee Colony (ABC) which reviews security and energy consumption to discuss their constraints in the IoT scenarios. Results: The results of a detailed experimental assessment are analyzed in terms of communication cost, energy consumption and security, which prove the relevance of a proposed ABC approach and a key establishment. Conclusion: The validation of DTLS-ABC consists of designing an inter-node cooperation trust model for the creation of a trusted community of elements that are mutually supportive. Initial attempts to design the key methods for management are appropriate individual IoT devices. This gives the system designers, an option that considers the question of scalability.

Energy Proficient Hybrid Secure Scheme for Wireless Sensor Networks

One way hash chain with a new key indicating the performance of the node as well to isolate malicious nodes from the network. Public key cryptography is derived using elliptical curve cryptography (ECC) have couple of key for decryption and encryption. Public key cryptography provides protection and verification using numerous algorithms. In addition secret session key is generated for secured data transmission and improve energy efficiency in WSN. Advanced encryption standard (AES) is applied for message cipher text once the key validation process gets finished. Energy proficient hybrid secure scheme (EPHSS) is proposed to provide secured and energy efficient data transmissions in WSN. To utilise the node energy in a proper way node clustering process is carried out. Clustering process efficiently reduces unnecessary energy wastage during node communication. Graded co-prime keys are generated for public and private keys, also encrypting functions are performed for providing security mechanisms. This mechanism improves security measures and simultaneously reduces energy consumption among nodes. The route should be undetectable by malicious nodes and the data should not be lacerate by the opponent node even it gets to know the public key. Identifying private key component [B, n] is difficult for malevolent; thus building it computationally infeasible for discovering decryption type at receiver side. Simulation presentations of the networks are analysed by network simulator tool. Efficiency of the proposed scheme is computed by taking delivery rates of packets which results in 18% better than the conventional ECCSAS scheme.

A New Cluster Head Selection Technique based on Remaining Energy of Each Node for Energy Efficiency in WSN

A New Cluster Head Selection Technique based on Remaining Energy of Each Node for Energy Efficiency in WSN

Efficient data aggregation with node clustering and extreme learning machine for WSN

Wireless sensor network is effective for data aggregation and transmission in IoT environment. Here, the sensor data often contain a significant amount of noises or redundancy exists, and thus, the data are aggregated to extract meaningful information and reduce the transmission cost. In this paper, a novel data aggregation scheme is proposed based on clustering of the nodes and extreme learning machine (ELM) which efficiently reduces redundant and erroneous data. Mahalanobis distance-based radial basis function is applied to the projection stage of the ELM to reduce the instability of the training process. Kalman filter is also used to filter the data at each sensor node before transmitted to the cluster head. Computer simulation with real datasets shows that the proposed scheme consistently outperforms the existing schemes in terms of clustering accuracy of the data and energy efficiency of WSN.

Improvement in LEACH Protocol for Energy Efficiency

Clustering methods in WSN for the sake of energy efficiency has been addressed by various researchers due to promising improvements in the performances. The energy consumption still possesses an opportunity for improvement in terms of complexity reduction, reduction in energy consumption and lifetime of the network. The work presented in this paper contributes a novel strategy for energy efficiency in WSN. This work consists of clustering technique using K-medoid, ANFIS and optimized ANFIS using firefly. The simulation analysis shows significant improvement in performance in terms of residual energy and energy consumption parameters along with number of dead and alive nodes with respect to number of iterations. The proposed method outperforms compared to basic LEACH protocol.

Hybrid FruitFly Optimization Algorithm and Wavelet Neural Network for Energy Efficiency in WSN

Hybrid FruitFly Optimization Algorithm and Wavelet Neural Network for Energy Efficiency in WSN

Agent Based Energy Efficiency in WSN

Agent Based Energy Efficiency in WSN

EELEACH Clustering Approach to Improve Energy Efficiency in WSN

Background: Wireless sensor network is self-organizing which consists of a large number of sensor nodes and one sink node according to recent patents. The most important characteristics of such a network are the restricted resources like battery power, consumption capacity and consumption range. Energy consumption is one of the important issues in the wireless sensor network and the challenge is to prolong the network lifespan. Objective: The objective of the proposed approach is to balance a consumption of energy at member node as well as head node of cluster during the data transmission stage and to improve energy efficiency and lifespan of the network. Methods: The aim of an energy efficient clustering method to deal with the homogenous distribution and deployment of tree structure is performed. The performance of network is enhanced by electing head node with data to the node with greater cluster rate and having lowest distance from sink node. The member node sends their data to the head node which forwards their data to the node with greater weight rate which is sent to the sink node in an energy balancing way. Results: A performance analysis of existing approach as LEACH and proposed approach as EELEACH is undertaken by considering different metrics such as energy consumption successful data delivery, throughput, routing overhead, packet delivery fraction and delay ratio. Conclusion: From result analysis, the proposed system as EELEACH shows successful data delivery, throughput, routing overhead, packet delivery fraction and delay ratio. Hence, the low energy consumption improved lifespan of the network and better data transfer rate.

Review on LEACH (Low Energy Adaptive Clustering Hierarchy) Protocol for Enhancing Energy Efficiency of WSN

Review on LEACH (Low Energy Adaptive Clustering Hierarchy) Protocol for Enhancing Energy Efficiency of WSN

Multi-level Structured Tree based Routing for Energy Efficiency in WSN

The manuscript should contain an abstract. The abstract should be self-contained and citation-free and should not exceed 200 words. The abstract should state the purpose, approach, results and conclusions of the work. The author should assume that the reader has some knowledge of the subject but has not read the paper. Thus, the abstract should be intelligible and complete in it-self (no numerical references); it should not cite figures, tables, or sections of the paper. The abstract should be written using third person instead of first person.

Improving energy utilization using multi hop data aggregation with node switching in wireless sensor network

The WSNs contain several miniature models that have some abilities of perception, communication and computation. For WSNs various energy-efficient relaying schemes have been designed, in which clustering is specifically the most useful relay-based sensor network which requires scalability of more than 1000 nodes. Different cluster-based protocols have been present by examiners in current years that improve the network lifetime. Among these, a self-organizing protocol is Low Energy Adaptive Clustering Hierarchy (LEACH) which can utilize a distributed and cluster formation algorithm. This work deals with an innovative technique which can improve packet delivery and energy efficiency in WSN. This work proposed has been grouped broadly into new Node Switching Multi Hop LEACH that makes use of an average randomization of network energy where the selection of nodes which have a higher average of energy when round is complete. The protocol that is proposed for an improved saving of energy, the Load Balanced Inter Cluster Network Switching Multi Hop LEACH has been proposed. The techniques that have been proposed are compared with Multi Hop LEACH.

Analysis of Energy Efficiency in WSN by Considering SHM Application

The Wireless Sensor Network is composed of a significant number of autonomous nodes deployed in an extensive or remote area. In WSN, the sensor nodes have a limited transmission range, processing speed and storage capabilities as well as their energy resources are also limited. In WSN all nodes are not directly connected. The primary objective for all kind of WSN is to enhance and optimize the network lifetime i.e. to minimize the energy consumption in the WSN. There are lots of applications of WSN out of which this research paper focuses upon the Structural Health Monitoring application in which 50 Meter bridge has been taken as a test application for the simulation purpose.