Implementation of energy-efficent routing protocol within real time clustering wireless sensor networks

The lifetime of Wireless Sensor Network (WSN) is based on the energy of each sensor. Therefore, numerous routing protocols have been introduced such as SEP (Stable Election Protocol), LEACH (Low energy adaptive clustering hierarchy) and EAMMH (Energy Aware Multi-hop Multi-path Hierarchical routing protocol) to stable the lifetime of WSN by efficient utilization of energy of the sensors. In WSN networks data is collected and forwarded wirelessly to the base stations. Routing protocols in WSN provide an efficient path for multi-hop communication because the transmission range and battery power storage of nodes is limited. As nodes are usually deployed in remote areas so, they face challenges of long lifetime, network architecture, security issues, and network coverage. Many routing protocols have been developed to increase the efficiency of networks. Out of these clustering algorithms are the best choice to increase the lifetime of the nodes. Each protocol has its limitations in different scenarios. In this paper, we discussed and compared the performance of LEACH, EAMMH and SEP. SEP is an efficient algorithm due to its weighted cluster head (CH) selection method. Simulation results are obtained using MATLAB. Design metrics of energy consumption and network lifetime are under consideration in this research work.

A green clustering protocol for mobile sensor network using particle swarm optimization

The paper presents a novel algorithm called Modified End-to-End Secure Low Energy Adaptive Clustering Hierarchy (ME-LEACH) for extending the lifetime of Wireless Sensor Networks (WSNs).Energy constraints are a significant challenge in WSNs, and thus, efficient energy usage is essential for all activities within a WSN.Existing protocols have been introduced to address energy dissipation issues, such as the End-to-End Secure Low Energy Adaptive Clustering Hierarchy (E-LEACH) protocol, which is a hierarchical routing algorithm.However, E-LEACH suffers from high energy consumption as each Cluster Head (CH) directly sends data to the base station.In the proposed ME-LEACH method, a CH identifies the nearest CH and uses it as the next hop, forming a chain of CHs that serve as a path to the base station or sink.This approach aims to improve energy efficiency in WSNs and reduce energy dissipation during data transmission.The widespread applications of WSNs in various fields of science and technology highlight the significance of this research.

Wireless sensor networks (WSNs) consist of a large number of small, low data rate and inexpensive nodes that communicate in order to sense or control a physical phenomenon. The major difference between the WSN and the traditional wireless network is that sensors are very sensitive to energy consumption. Moreover, the performance of the sensor network applications highly depends on the lifetime of the network and we expect the lifetime of several months to several years. Thus, energy saving is crucial in designing long-lived wireless sensor networks. Many researchers have focused on developing energy efficient cluster based protocols for WSNs, but there has not been much research on event driven WSNs and, their focus is on continuous driven networks. In this paper, we propose a modified algorithm of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol which is a well known energy efficient clustering algorithm for WSNs. Our modified protocol called “Adaptive and Energy Efficient Clustering Algorithm for Event-Driven Application in Wireless Sensor Networks (AEEC)” is aimed at prolonging the lifetime of a sensor network by balancing energy usage of the nodes. AEEC makes the nodes with more residual energy have more chances to be selected as cluster head. Also, we use elector nodes which take the responsibility of collecting energy information of the nearest sensor nodes and selecting the cluster head. We compared the performance of our AEEC algorithm with the LEACH protocol using simulations .

Energy consumption is the main issue that researchers have dealt with to design any routing application. To design comprehensive reliable wireless sensors networks (WSNs), it is essential to consider node failure and energy constraint as inevitable phenomena. In this paper, a new method for optimal clustering is proposed, that accurately localizes sensors while minimizing their power consumption. It also splits the task of Cluster head between sensor nodes to send data to the base station (BS). The proposed scheme is based on K-means method to selected Cluster-Head. The selection of CH starts with the closest nodes to the centroid point. In the second step, we selected nodes with high power compared to its neighbors, after repeating this phenomenon until the energy of all the nodes is drained. This method can equilibrate the role of Cluster-Head between all the network sensors. Simulation results showed that our clustering mechanism seemed to effectively improve the network lifetime over Low Energy Adaptive Clustering Hierarchy (LEACH) and Energy efficient clustering algorithm for maximizing the lifetime of wireless sensor networks.

Wireless sensor networks (WSNs) are composed of an enormous number of smart sensor nodes that are usually battery-powered and considered to work for a long period. Application areas are several and diverse, such as the environmental field, health and military sector. The main gain of these intelligent devices is a large-scale utilization without any maintenance. These sensors do not need to attain an established infrastructure to transfer vital data to the study of the environment. Decreasing energy dissipation and increasing network lifetime in wireless sensor networks are major challenges in the design of routing protocols for smart sensor networks, the main reason why these days several works are concentrating in WSN's energy management.Clustering technique is one of the most popular techniques used to reduce energy ingesting in WSN and boost the whole network life extent. LEACH protocol was presented to minimize energy ingesting. In this paper, a new approach based on pure LEACH is suggested. To measure the performance of modified algorithm, simulation is used to compare its consumption to pure LEACH. Results show that the proposed algorithm lengthens network lifetime and thus diminishes power ingesting.

Wireless sensor networks (WSN) are a yield of advancement in information technology and the requirement of large-scale communication infrastructures. Routing of data via selected paths is a critical task in WSN as process need to be carried on under resource constraint situations. This route identification problem can be better handled by employing appropriate heuristic bio-inspired computational intelligence optimization method. The most frequently applied routing is hierarchical routing algorithm is Low Energy Adaptive Clustering Hierarchy (LEACH) algorithm which has limitations in identifying energy efficient inter and intra route communication, identification of number of cluster head (CH), an eminent node to communicate to CH and Base Station (BS), selection of CH, and computing residual energy level, etc. Hence, researchers are focusing on boosting the capability of LEACH clustering algorithm by applying heuristic bio-inspired computational intelligence optimization methods. The proposed work is an attempt in this direction through applying heuristic bio-inspired Grey Wolf Optimization algorithm (GWO) for improving the performance of LEACH algorithm. In this paper, focus is given to increase the overall network time by adapting two modifications to conventional algorithms (i) selection of vice cluster head (VCH) in addition to CH (VCH node will replace the CH when CH when CH node goes down due to unexpected reasons as sensor node work under critical and uninterruptable environments and (ii) selection of intra and inter relay nodes (intra relay node will enhance the life span during CH data gathering and inter relay node will further enhance the life span of CH by acting as a mediator between CH an BS). The Spyder-py3 tool is used to simulate the proposed algorithms, LEACH Binary Grey Wolf search based Optimization (LEACH-BGWO) and LEACH Discrete Grey Wolf search based Optimization (LEACH-DGWO) protocols. The proposed work is compared with cluster based LEACH algorithm, chain based power-efficient gathering in sensor information systems (PEGASIS) algorithm, bio-inspired GWO and Genetic Algorithm data Aggregation (GADA) LEACH protocols. The results prove that both proposed algorithms outperformed other conventional algorithms in terms of prolonged network lifespan and increased throughput. Among proposed algorithms LEACH-BGWO outperformed LEACH-DGWO

Wireless Sensor Networks (WSN) is an ever growing field owing to their extensive variety of applications. WSN have limited battery energy, consequently, an energy efficient routing protocol is of major concern. LEACH (Low Energy Adaptive Clustering Hierarchy) is one of the fundamental clustering protocols in WSN that provides high energy efficiency. Many protocols have been derived from LEACH which mostly address a single inherent challenge. Instead of focusing on a single parameter, combining independent techniques can compound gains in energy efficiency. This paper proposes Yet Another LEACH (YA-LEACH) which uses centralised cluster formation to ensure optimal clusters and allow Cluster Heads (CH) to extend operation into multiple rounds to achieve energy savings. Also, the proposed protocol will have an alternative (vice) CH that takes over when CH residual energy reaches a critically low level. The extended protocol was simulated on NS2 with results showing an improvement in network lifetime and overall data throughput.

Wireless sensor networks (WSN) play a key role in enabling wireless communication technology among several nodes to remotely communicate and exchange information. WSN consists of tiny sensor nodes equipped with battery, scattered in an area to gather information around an environment and send to data collection node known as sink or base station (BS). WSN have been widely used in various applications like agriculture, fire detection, health care and military and has become imperative necessity for future revolutionary area like UAV (unmanned aerial vehicles), IoT (Internet of things) and smart cities which employs large scale sensor nodes. However sensor nodes are limited to battery, memory, low computational power, resource and bandwidth. Continues sensing of events, makes node to drain its battery faster and goes dead fast. For resource constrained WSN, hierarchical cluster based approaches are considered as energy efficient and improves network performance for large scale WSN. Minimizing energy consumption and extending network lifetime are major challenging issues of WSN, clustering methods with optimized routing have offered solution to optimize energy utilization. To balance energy consumption and improve network lifetime many existing hierarchical clustering approaches have been proposed, however existing method does not consider rotation of cluster head (CH) and considers cluster head selection based on residual energy and distance parameter. In this paper we propose an improved energy efficient cluster tree (IEECT) based routing to improve energy efficiency of hierarchical cluster. IEECT considers modification of existing LEACH (Low energy adaptive clustering hierarchy) protocol to improved energy efficient LEACH by considering energy parameters like residual node energy and average network energy. IEECT accounts optimal number of cluster head (CH) and selection of CH is done using threshold value among sensor nodes. Proposed IEECT combines tree based routing and data aggregation scheme to maintain desirable quality of service. Simulation experiments are carried out by using network simulator. Performance of IEECT is evaluated in terms of PDR, delay, energy consumption, network lifetime and overhead.

In wireless sensor networks constructed from battery driven nodes, it is difficult to supply electric power to the nodes. Because of this, the power consumption must be reduced. To cope with this problem, clustering techniques have been proposed. EACLE is a method that uses a clustering technique. In EACLE, the route selection is executed independently after the CH (Cluster Head) selection. These two phase controls increase overheads and reduce the battery power, which leads to shorten the lifetime of wireless sensor networks. This paper proposes a novel routing and clustering method called PARC for wireless sensor networks that reduces these overheads by integrating the cluster selection phase and the route construction phase into a single phase. However, PARC has a following weak point that the batteries of CHs around the sink node are depleted earlier than the other nodes and the sink node cannot collect sensing data. This phenomenon is called a hot spot problem. In order to cope with this problem of PARC, we propose PARC+, which extends the CH selection method of PARC such as more nodes around the sink can be selected as a CH node. We evaluate our proposed methods by simulation experiments and show its effectiveness.

Wireless Sensor Network (WSN) is a self-configured network of light-weight nodes, that are used in many applications by sending their data through this network to a Base Station (BS), which in turn, delivers the data to its final destination. In WSN, the sensor node’s energy is usually limited, and thus, the overall power consumption of the network is a real challenge. Numerous methods have been proposed to overcome this challenge by improving the overall power consumption and thus, prolonging the lifetime of the network. Low Energy Adaptive Clustering Hierarchy (LEACH) protocol has been considered as a leading routing protocol in WSN, due to its low power consumption resultant from its cluster-based behavior. However, for dense networks, LEACH suffers from large burden over cluster head (CH), which might result in packet loss due to the induced congestion in the CH. In this paper, an improved algorithm based on LEACH is proposed to maximize the lifetime of WSN, by using another node to relieve CH’s burden. The routing path selection process is refined through selecting a new node that has the highest residual energy in each cluster to be an alternative gateway for the cluster head. Then, the routing path will be decided based on distance. This modified algorithm outperforms the original LEACH by 4.35% increase in the residual energy, which prolongs the network lifetime. However, there is a slight increase in the overhead ratio.

Wireless Sensor Networks (WSNs) allow a large area to be monitored with various sensors. WSNs, although useful, are subject to Black Hole attacks. Defenses against attacks typically require more energy which reduces WSN lifetime. This thesis proposes a novel approach to detect and recover from attacks using an improved version of Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. LEACH is an energy efficient protocol for groups of battery-operated computers with sensor components in WSNs. This protocol works by having a node become a cluster head responsible for sending data to a sink. The sink can be either an access point or base station. After a set time the cluster heads go back to being regular nodes and a completely new set of nodes become cluster heads. There are secure versions of LEACH such as S-LEACH and MS-LEACH that provide encryption, but LEACH and its encrypted variants do not secure against Black Hole attacks. Our proposed approach, referred to as Anomaly Report Cycling - Low Energy Adaptive Clustering Hierarchy (ARC-LEACH), aims to provide defense from Black Hole attacks while also providing low energy cost. ARC-LEACH does this by absorbing an attack. When an attack occurs, it rotates cluster heads to reestablish communication, then sending a message from the sink to coordinate all nodes against the malicious nodes. ARC-LEACH actively blocks malicious nodes while leveraging the resilience of LEACH by building up stronger resistance to attacks. ARC-LEACH provides more defense capability when under attack from multiple malicious nodes that would otherwise be defenseless by LEACH, with only a limited increase in power consumption. The prototype for ARC-LEACH is implemented to show feasibility of the proposed approach.

Among important issues in the current energy-efficient routing protocols for wireless sensor networks (WSNs) based on clustering approaches are how to determine the optimal number of clusters, how to generate clusters and how select cluster-heads to improve WSNs performance. These approaches aim to reduce energy consumption of the WSN nodes and to extend the network lifetime. This paper reviews and compares the performance of three clustering techniques for determining number of clusters: rule of thumb, elbow, and silhouette. Each of these techniques involves a distributed K-means approach to generate clusters. Moreover, we compare these three clustering methods with low energy adaptive clustering hierarchy (LEACH), Imp LEACH and MODLEACH in terms of network lifetime, energy consumption and the number of packets sent to the base station (BS). The results obtained indicate that rule of thumb method provides better performance compared to other clustering techniques in terms of energy consumption and network lifetime.

Routing Algorithm determines the optimal route to transmit data packet from source to destination. The nodes in wireless sensor networks (WSN) are devoid of abundant energy and hence energy efficiency is the vital benchmarks for data transmission in WSN. The basic importance of wireless sensor networks (WSN) in present scenario is to reduce the node energy consumption such that it improves the data transmission efficiency and reliability to extend entire network life time. In these respect, we need to search the optimal route for data transmission in WSN. Here an Improved Ant Colony Optimization (IACO) based energy efficient routing algorithm is proposed in WSN to solve the issue. The function of improved Low Energy Adaptive Clustering Hierarchy (LEACH) routing algorithm is to select cluster heads (CH) by considering residual energy and the distance in between the nodes. To balance the energy consumption between the nodes, residual energy is used as an energy control factor, which affects the network life time and enhances the data transmission efficiency. An ACO algorithm is applied to search the optimal path from the various available routes in between CH and sink for data transmission. Simulation results show that the proposed method Improved Ant Colony Optimization based Low Energy Adaptive Clustering Hierarchy (IACOLEACH) is found to yield better results over other conventional algorithms.

Wireless Sensor Networks (WSNs) is the vast area and developing very speedily now-a-days. This paper gives some of the major applications and critical limitations of WSNs like power and lifespan, communication bandwidth, memory size. Sensor nodes are working by node energy so the energy consumption is the essential issue in WSN. Routing in WSN consumes more energy than any other phase. Various routing techniques in WSNs are discussed and different routing protocols are illustrated. Low Energy Adaptive Clustering Hierarchy (LEACH) is one of the popular and feasible hierarchical clustering routing protocols in WSN. Working of LEACH is explained in brief. Furthermore, the descendants of LEACH e.g. LEACH-C (Centralized LEACH), LEACH-B (Balanced LEACH), LEACH-F, Multihop LEACH, MS-LEACH (Multihop and Single hop LEACH), MH-LEACH etc. are discussed in terms of the energy utilization. By analyzing the variants of LEACH, it is observed that the energy requirement in the cluster set up phase or data transmission phase is minimized to minimize the total energy consumption of the WSN. To elect the proper cluster head node, centralized approach is followed. Afterwards, data transmission will use the multihop communication technique. This will help to save some energy when base station is located far away from the cluster head node. Proposed protocol aims to decrease the energy overhead of the sensor nodes. The new approach is proposed entitled PV-LEACH which will save the energy consumption in cluster setup phase and also in data transmission phase of the conventional LEACH protocol. So, this will enhance the performance ratio in terms of energy consumption and life time of the sensor nodes.