LEACH Algorithm Research Articles

Symmetric Algorithm for Detection of Coverage Hole in Wireless Sensor Network

For the problems of traditional overburden hole detection methods, such as overtime, low accuracy and high running cost, etc. A multi factor reliable coverage hole detection method based on LEACH algorithm is proposed. Based on the analysis of the QoS architecture of wireless sensor networks and the research of representative network layer symmetry protocols, a symmetric network model is constructed according to the selection of gateway performance parameters, gateway selection criterion function and symmetry criterion, and a symmetric criterion design and optimization strategy is given. It uses this strategy to improve LEACH algorithm in three aspects. Two reliability optimization factors are added to the similarity calculation of coverage hole detection, which are node intrusion optimization factor and multipath transmission optimization factor respectively. Multipath transmission optimization factor is used in data transmission. In hostile environments, in order to avoid a large number of malicious nodes interfering with real data, the data containing noise should be filtered and processed. Then, the similarity is calculated by multi-path transmission optimization factor, and the coverage holes of wireless sensor networks are detected by weighted average. The experimental results show that the proposed method takes less time to detect the covering holes, which has higher detection accuracy and lower operation cost.

Performance analysis of two layer leach algorithm based on area partition (tl-leach-p) for wsn

Currently, much research has been done to develop routing algorithms to improve the lifetime of sensors from Wireless Sensor Network (WSN). Routing protocols based on the network structure can be classified into two categories: flat protocols and hierarchical protocols. One of the most popular hierarchical protocols is the Low Energy Adaptive Clustering Hierarchy (LEACH) algorithm. However, LEACH routing has a high packet loss in a busy network. This research propose Two Layer LEACH based on area Partition (TL-LEACH-P) routing algorithm based on the LEACH routing algorithm where the cave layer is done to prioritize the node that can become Cluster Head to decrease energy consumption. LEACH and TL-LEACH-P algorithms are simulated using MATLAB. The results show that the TL-LEACH-P algorithm has a better performance of 60% reaching LEACH in terms of network lifetime. The TL-LEACH-P algorithm has a 50% increase in the round where 50% of the nodes are dead from LEACH. Best TL-LEACH-P algorithm performance is when the k cluster value = 5. And best performance for LEACH algorithm is when the k cluster value = 15.

An efficient intelligent data fusion algorithm for wireless sensor network

Abstract Wireless sensor network (WSN) are usually restricted by assembled batteries which are difficult to recharge, therefore saving network energy is crucial for WSN. For increasing the survival time of the network, an efficient intelligent data fusion algorithm named GAPSOBP is put forward which integrating BP neural network, genetic algorithm and particle swarm optimization algorithm reasonably. In GAPSOBP, wireless sensors are analogy to neurons in the neural network. Data collected by sensors is extracted by BP neural network, and then combined with clustering routing to fuse extra data, thus reducing data volume sent to base station or sink node. Simulation results show that GAPSOBP is superior than LEACH and PSOBP algorithms in terms of energy consumption and network lifetime.

The Effects of Physical and Mac Parameters on the Routing by Cross-Layers Interaction Approach

Wireless sensor networks (WSN) are an ad hoc network consisting of miniaturized autonomous sensors that communicate with each other over a radio link. In this paper, the authors' contribution is a cross-layer approach. To achieve this approach, the authors proposed in the first part an improvement of LEACH algorithm named WEIGHTED_LEACH. This algorithm is an enhancement of LEACH by inserting novel factors in the threshold equation in order to choose the best node to be CH by competitiveness strategy. In the second part, the authors propose a new adaptable cross-layer design realized by proposed algorithm and AODV protocol with cross layer interaction algorithm. This is an improvement by the control of data fusion in the network using multi-hop routing based on weight metric deducts from relative parameters of node such RSSI, SINR, residual energy, and distance. A comparative analysis between WEIGHTED_LEACH and LEACH, shown for different configurations the efficiency of the proposition in terms of energy saving and life time of WSN cluster, are evaluate under the NS2 simulator.

On-Chip Embedded Debugging System Based on Leach Algorithm Parameter on Detection of Wireless Sensor Networks

Leach (low energy adaptive clustering hierarchy) algorithm is a self-clustering topology algorithm. Its execution process is cyclical. Each cycle is divided into two phases: cluster building phase and stable data communication phase. In the stage of cluster building, the adjacent nodes cluster dynamically and randomly generate cluster heads. In the data communication phase, the nodes in the cluster send the data to the cluster head, and the cluster head performs data fusion and sends the results to the aggregation node. Because the cluster head needs to complete data fusion, communication with the convergence node and other works, the energy consumption is large. Leach algorithm can ensure that each node acts as cluster head with equal probability, so that the nodes in the network consume energy relatively evenly. The basic idea of Leach algorithm is to randomly select cluster head nodes in a circular way. It evenly distributes the energy load of the whole network to each sensor node in the network. It can reduce network energy consumption and improve network life cycle. Leach repeatedly performs cluster refactoring during its operation. This paper studies the parameter detection of wireless sensor network based on Leach algorithm on the on-chip embedded debugging system. Because the classical low-power adaptive clustering layered protocol (Leach) has the problem of energy imbalance and short node life cycle, this paper uses embedded debugging technology based on Leach algorithm and the residual energy and position of nodes in wireless sensor networks were tested for research. This Leach algorithm uses the concept of wheel. Each round consists of two phases: initialization and stabilization. In the initialization stage, each node generates a random number between 0 and 1. If the random number generated by a node is less than the set threshold T (n), the node publishes a message that it is a cluster head. Through the research on the parameter detection, the simulation results show that the research in this paper has good feasibility and rationality.

Energy-efficient clustering algorithm for a WSN with a distributed structure

In this study, a new center-oriented clustering (CCP) algorithm that provides self-clustering of a network by using a method similar to the center-biased clustering method of the k-means algorithm is presented and differs from the literature in this respect. The proposed algorithm is compared with low-energy adaptive clustering hierarchy (Leach) because it uses similar techniques, as it aims to self-organize irregularly distributed networks. In the experimental study, CCP and Leach algorithms were run in randomly generated network models and the algorithms were compared in terms of the total amount of energy remaining in the network and the number of surviving nodes. The algorithms were run on 15 different wireless sensor network (WSN) models, each of which was irregularly distributed with 100 nodes, and the amount of energy remaining in the network after each trial was recorded and averaged. As a result, it was observed that the energy in the network was 9.4% more efficient in the CCP algorithm. In addition, when the number of surviving nodes was considered, it was observed that an average of 28.3 nodes in the CCP algorithm and 18 nodes in the Leach algorithm survived.

Fastest adaptive estimation algorithms for topological structure errors in smart grid networks

Compared with traditional wired networks, wireless sensor networks(WSN) have the characteristics of low cost and rapid deployment, and also guarantee the same level of fault tolerance as wired networks. The WSN can also monitor the operating status of the power grid in real time, collect physical information such as related parameters, and provide more comprehensive and complete power grid operation data as a reference basis for smart grid operation and related management personnel, and complete the diagnosis, monitoring and power statistics of smart grid equipment The rapid construction of the data communication network has become a key technology to effectively solve the problems of difficult optimization management and high cost and economic benefits in the smart grid. This paper discusses the application of WSNs in smart grids from two aspects. Firstly, construct a WSN topology that complies with the smart grid architecture, and establish a real-time routing mechanism that meets the requirements of smart distribution network communication reliability; secondly, propose a fastest adaptive algorithm for the fault of the WSN topology in the smart grid . The proposed adaptive routing mechanism has certain advantages in node energy consumption, which reduces energy consumption by nearly 4% compared to the directional diffusion method and the LEACH algorithm. Therefore, the algorithm is more suitable for the adaptation of WSN topology, and the method can Improve the life cycle of sensor nodes and networks.

EE-LEACH: Energy Enhancement in LEACH to Improve Network Life Time of Homogeneous Wireless Sensor Network

Purpose ”“ In the recent scenario, there are various issues related to wireless sensor networks such as clustering, routing, packet loss, network strength. The core functionality of primarily wireless sensor networks is sensor nodes that are randomly scattered over a specific area. The sensor senses the data and sends it to the base station. Energy consumption is an important issue in wireless sensor networks. Clustering and cluster head selection is an important method used to extend the lifetime of wireless sensor networks. The main goal of this research article is to reduce energy consumption using a clustering process such as CH determination, cluster formation, and data dissemination.
 
 Methodology/approach/design ”“ The simulation in this paper was finished utilizing MATLAB programming methodology and the proposed technique is contrasted with the LEACH and MOD-LEACH protocols.
 
 Findings ”“ The simulation results of this research show that the energy consumption and dead node ratio are improved of wireless sensor networks as compared to the LEACH and MOD-LEACH algorithms.
 
 Originality/value ”“ In the wireless sensor network there are various constraints energy is one of them. In order to solve this problem use CH selection algorithms to reduce energy consumption and consequently increase network lifetime.

Multi‐path unequal clustering protocol based on ant colony algorithm in wireless sensor networks

For the requirement of low power consumption in wireless sensor networks, from the point of view of prolonging the life cycle of the whole network and improving the utilisation rate of the network, this study proposes a LEACH-EA protocol based on LEACH algorithm. In order to increase the probability of being elected as a cluster head node so that more nodes in the network can share the transmission energy equally, the residual energy factor and the influence factor of node distance are added to the cluster head election threshold. Considering the energy loss of single-hop transmission and the limitation of single-hop transmission on the maximum transmission distance of equipment, the ant colony algorithm is used to find the optimal transmission path for nodes iteratively. Finally, by comparing with LEACH, MODLEACH, LEACH-GA, simulation experiments show that LEACH-EA protocol has significantly improved in network life cycle, total network data transmission and cluster head number. The network utilisation rate of LEACH-EA is 431.3, 135.7 and 38.6% higher than the other three algorithms, respectively.

LOW-POWER AND LOSSY NETWORKS OF WIRELESS SENSOR NETWORKS WITH PROTOCOLS ALGORITHM COMPARISON

This research focuses on the energy efficiency needed by sensor nodes in the network architecture i.e, LEACH, HEED, LEACH-TLCH and PEGASIS according to the Routing Protocol Low Power and Lossy Network (RPL) pattern. In this research compared all algorithms based on the number of different sensor nodes. In this research, there is no focus on the type of sensor used but rests on the conclusions of the total results of the Overall energy (Avg_Energy) on clustering with the most appropriate networking strategy. In this research, 20, 50 and 100 nodes were tested in the HEED, LEACH, LEACH-TLCH and PEGASIS Algorithms respectively. furthermore, from the results of testing the total Power (mW) sensor obtained from the sum of 4 components of the Power Sensor node, i.e, CPU Power, Power LPM, Power TX (Transmitter) and Power Rx (Receiver), concludes the Power Consumption sensor node is affected by the number of nodes found on the Sensor Node Network Architecture, the lowest Power Consumption is the LEACH Algorithm Protocol with a total of 2,038 mW at 100 nodes, while the highest Power Consumption is LEACH-TLCH Protocol Algorithm 4,851 mW with 100 nodes followed by PEGASIS with total Consumption 4.31 mW. accordingly the simulation, At the lowest sensor node in this experiment, which is 20 nodes, LEACH produces the lowest total Power of 1.21 mW, while the highest is PEGASIS 1,361 mW. At the number of 50 nodes, the lowest is HEED with a power consumption of 1,558 mW, this result is only 0.046 mW with the LEACH Algorithm Protocol which is 1,604 mW. Furthermore, by building the right sensor network (WSN) it will support IoT networks with long sensor lifetime.

Optimal Number of Cluster Heads in Wireless Sensors Networks Based on LEACH

The Wireless Sensor Network (WSN) has been one of the leading research fields of wireless networks, particularly in recent year. Sensors are randomly positioned in the region, every node senses the surroundings and sends the data collected to the cluster head (CH), which aggregates and transmits obtained information to the Base Station (BS). A non-rechargeable battery is included on each WSN node. The sensor energy and network life extension of WSN are the most important considerations in the academia and industry. And thus, many routing protocols have been proposed to solve this issue, one of these is LEACH, the early protocol that introduced the clustering idea to extend the life of the WSN. LEACH is affected by the number of heads of the Clusters as it is randomly selected, and this has an impact on network lifetime, furthermore, the nodes are randomly joined in each cluster, this means that some of the cluster heads work more than others with fewer cluster nodes. In this paper, it is proposed an algorithm Maximum Optimal Number of Cluster Heads (MONCH) to identify the optimum cluster heads in WSN and to find which is the nearest one to BS and helps to integrate nodes with the most appropriate cluster. The results show improved energy consumption performance for the LEACH algorithm.

Routing Algorithm based on Clustering for Increasing the Lifetime of Sensor Networks by Using Meta-Heuristic Bee Algorithms

Background: Nowadays, the use of wireless sensor networks is developing rapidly. these networks are applicable in many fields, including military, medical, and environment. these networks use hundreds or thousands of cheap sensor nodes with low power-low and low energy to perform large tasks. These networks have limitations that can lead to inefficiency or not cost - effective. Among these limitations, consumption of energy and issues related to the lifetime of the network. One of the solutions that can assist the load balancing between sensor nodes, increased scalability, improving energy consumption and consequently, increasing network lifetime, clustering of sensor nodes and placing a suitable cluster head in all clusters. Choosing the right cluster head, significantly reduces energy consumption in the network and increases network lifetime. Objective: The purpose of this paper is to increase network lifetime by using the efficient clustering algorithm, which is used in Meta-heuristic bee colony to select the cluster head. Simulation of this paper is performed by MATLB software and the proposed method is compared with LEACH and GACR approaches. Conclusion: The simulation findings in this study show that the intended study has remarkably increased the length of the network lifetime by LEACH and GACR algorithms. Due to the limitation of energy in the wireless sensor network such solutions and using Meta-heuristic algorithms can give rise a remarkable increasing in network lifetime.

An improved spatial-temporal correlation algorithm combined with compressed sensing and LEACH protocol in WSNs

The energy of the sensor network nodes is limited, in order to save the energy consumption of the sensor nodes, a compressed sensing method based on the spatial-temporal correlation of nodes is proposed. The LEACH algorithm is used to cluster the network nodes and select the cluster head. Then, the cluster head node is sampled by the compressed sensing theory. The sampled data is passed to the remote sink node through multi-hop routing. Finally, at the sink node, the OMP algorithm can be used to recover the original signal from a small amount of data transmitted by the cluster head nodes. The simulation results show that the method can effectively reduce the amount of data transmission and save the energy consumption of nodes and prolong the lifetime of the wireless sensor network.

A Probability-Based Clustering Algorithm with CH Election for Expanding WSN Life Span

Clustering achieves energy efficiency and scalable performance in wireless sensor networks (WSNs). A cluster is formed by several sensors nodes, and one of them is elected as Cluster-head (CH). A CH collects information from the cluster members and sends aggregated data to the base station or another CH. This article proposes a new clustering algorithm (EMESISC) that is based on each node's probability of becoming a CH. This node's probability depends on its residual energy, buffer length, and received signal power. We compared EMESISC with LEACH algorithm. Simulation results showed that EMESISC is superior to LEACH.

Improvement of LEACH Algorithm Based on Inter-Cluster Ring Routing Strategy

Wireless Sensor Network (Wireless Sensor Network, WSN) is a self-organizing network formed by a large number of wireless sensor nodes through radio communication [1]. The sensor nodes in the network cooperate with each other to monitor and collect the object information in the observation area, and the information is transmitted to the users who need this information after data fusion processing. It is often deployed in harsh environments, such as oceans, deep forests, and deserts. At the same time, the sensor nodes in the network are powered by batteries [2]. These external factors make it impossible to replace batteries manually. Therefore, energy is an important resource for wireless sensor networks [3]. In this paper, aiming at the problems of LEACH inter-cluster communication, from the perspective of energy saving, an improved strategy using inter-cluster ring routing is proposed. This strategy first abstracts all sensor nodes into a ring system model during the network topology formation stage. In the data transmission stage, a ring transmission strategy is adopted, and nodes on the ring are used to randomly and evenly undertake data transmission tasks, so the imbalance of energy consumption of sensor nodes can be effectively reduced. Simulation experiments show that this strategy can extend the network life cycle to a certain extent.

Lifetime and Energy Efficiency Improvement Techniques for Hierarchical Networks

The detection points are the detection points in the space of network. The properties of detection points include cost effective materials and longer battery capacity. WSN can span variety of applications like sensing of data related to environment entities, detection of enemy vehicles. Lifetime ratio defines the efficiency of the WSN network operation. There are multiple techniques which can help in improvement of Network Lifetime (NL) spanning from transmission nature, data connections, formation of System and time scheduling. This paper provides the analysis of how energy consumption happens and its effect on lifetime ratio. LEACH and CHEF algorithms responsible for hierarchical kind of routing are discussed in detail with simulation results. The parameters used for comparison includes delay, hops, consumption of energy. Non-Hole detection points, Hole detection points, Non-Hole to Hole Ratio, residual energy, routing overhead and throughput.

Energy Reckoning Distance Based Clustering for Spectrum Aware Cognitive Radio Wireless Sensor Networks

Implementing cognitive radio sensor nodes in wireless sensor networks introduced a smart combination called cognitive radio sensor network (CRSN) which creates new challenges in the design of network topology. Conserving the nodes energy helps to extend the lifetime of the network. This stands as an important criterion while designing any algorithm. In order to achieve the same, two important criteria are to be considered – the communicating distance between the nodes or node to base station and proper spectrum sharing technique. In the proposed work, Energy Reckoning Distance-Based Clustering (ERDBC) algorithm, both the criterion is taken into consideration and designed in order to increase the lifetime of a cognitive radio sensor network. In the ERDBC algorithm, the whole network area is divided into three regions according to the distance and the cluster heads are elected based on energy, distance and common channel creates a greater impact on retaining the nodes energy. Also, implementing multi-hop routing using proper spectrum sharing technique helps to avoid data collision and retransmission thereby; the energy consumption of the nodes are reduced to a greater extent. The performance of the proposed ERDBC algorithm is measured on the basis of residual energy, throughput, channel usage, first node death, last node death, and network lifetime, and compared with the already existing LEACH, CogLEACH, LEAUCH and CEED algorithms. Thus the network lifetime of the proposed ERDBC algorithm is 78.18% more than LEACH, 73.6% more than CogLEACH, 29.88% more than CEED and 17.98% more than LEAUCH algorithms.

An Improved Leach Algorithm Based on Wireless Sensor Networks

In our current generation, wireless sensor network is much in use and has become quintessential. With wide improvement of technology and the various ranges developed in communication and in other aspects, this document mainly focuses on the LEACH algorithm (Adaptive Low Energy Hierarchy) and the second most important methodology used is the SEP (stable election protocol). We have discovered improvements in energy efficiency by comparing our results with these two algorithms and the sensor mortality rate is reduced to a greater extent. This research proposes an improved computation algorithm method for the calculation of LEACH clustering, by considering the importance of the cluster heads and the sensor nodes present, T (n) is reorganisedrecommendinga procedure that focuses on reducing the energy consumption. The combined rate of information is found by allowing cluster heads to gather information before it is sent to base station. This improved computation algorithmwill be able to increase vital utilisation of networks and increase sensor life.

An Enhanced Cluster Head Selection of LEACH Based on Power Consumption and Density of Sensor Nodes in Wireless Sensor Networks

The cluster head of LEACH algorithm was selected randomly in WSNs. It effects the distribution of clusters for the shadowing effect of obstruction in real scenarios. The network consumption is increased because of poor communication between nodes. A new selection method is presented to solve those problems in this paper. The logarithmic function is adopted to eliminate the shadowing effect of obstruction. The most suitable cluster is sorted out because the density of nodes is defined as the new threshold value. Simulation results show that the performances of new algorithm are obviously better than LEACH, ALEACH and Kost-LEACH algorithms. Compared with classical algorithms, the nodes utilization could enhance more than 2.0%, average energy consumption of the nodes is reduced by 9.1 J at least, and the probability of nodes failure to join the cluster could be decreased great than 3.7%.

Healing Coverage Holes for Big Data Collection in Large-Scale Wireless Sensor Networks

The quality of service is severely degraded by coverage holes in wireless sensor networks. This paper focuses on the coverage hole healing (CHH) problem for big data collection in a large-scale wireless sensor network (LS-WSN) where the LS-WSN containing both static sensors and mobile sensors with the topology control of LEACH algorithm. Meanwhile, the data volume transmitted by each sensor node may be inconsistent. Specifically, the target of the CHH problem is to find an optimal subset of mobile nodes from all mobile nodes while maximizing the transmission times (TT) that all dispatched mobile nodes can transmit in their lifetime. Hence, from the data-centric perspective, we propose a greedy healing algorithm (GHA) via the greedy-based heuristic strategy with low computational complexity to solve this CHH problem. Simulation results show that the proposed GHA can efficiently heal the coverage holes which significantly prolongs the network lifetime and observably enhances the quality of service (QoS) of WSNs while increasing the TT, transmitted data volume (TDV) and average residual energy of all dispatched mobile nodes.