scholarly journals Comparison of Residual Energy-Based Clustering Algorithms for Wireless Sensor Network

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Asis Kumar Tripathy ◽  
Suchismita Chinara
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Architecture ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Awareness

Wireless sensor network swears an exceptional fine-grained interface between the virtual and physical worlds. The clustering algorithm is a kind of key technique used to reduce energy consumption. Many clustering, power management, and data dissemination protocols have been specifically designed for wireless sensor network (WSN) where energy awareness is an essential design issue. Each clustering algorithm is composed of three phases cluster head (CH) selection, the setup phase, and steady state phase. The hot point in these algorithms is the cluster head selection. The focus, however, has been given to the residual energy-based clustering protocols which might differ depending on the application and network architecture. In this paper, a survey of the state-of-the-art clustering techniques in WSNs has been compared to find the merits and demerits among themselves. It has been assumed that the sensor nodes are randomly distributed and are not mobile, the coordinates of the base station (BS) and the dimensions of the sensor field are known.

scholarly journals Clustering Algorithm for Energy- Efficient Wireless Sensor Network

2021 ◽  
Vol 12 (5) ◽  
pp. 877-884
Author(s):  
Asha Rawat, Dr. Mukesh Kalla
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Energy Efficient ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Packet Transmission ◽  
Wireless Sensor ◽  
Energy Efficient Clustering

Wireless networks data aggregation allows in-network processing, reduces packet transmission and data redundancy, and thus helps extend wireless sensor systems to the full duration of their lives. There have been many ways of dividing the network into clusters, collecting information from nodes and adding it to the base station, to extend wireless sensor network life. Certain cluster algorithms consider the residual energy of the nodes when selecting clusterheads and others regularly rotate the selection head of the cluster. However, we seldom investigate the network density or local distance. In this report we present an energy-efficient clustering algorithm that selects the best cluster heads of the system after dividing the network into clusters. The cluster head selection depends on the distance between the base station nodes and the remaining power of this approach.Each node's residual energy is compared to the node count. Our results show that the solution proposed more efficiently extends the life of the wireless sensor network. The algorithm prolongs the life and effectiveness of the Wireless Sensor Network.

scholarly journals TRACKING OF MOVING OBJECT IN WIRELESS SENSOR NETWORK

2015 ◽  
pp. 42-47
Author(s):  
D. CHARANYA ◽  
G. V. UMA
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Base Station ◽  
Moving Object ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Current Location

A Wireless Sensor Network is a collection of sensor nodes distributed into a network to monitor the environmental conditions and send the sensed data to the Base Station. Wireless Sensor Network is one of the rapidly developing area in which energy consumption is the most important aspect to be considered while tracking, monitoring, reporting and visualization of data. An Energy Efficient Prediction-based Clustering algorithm is proposed to track the moving object in wireless sensor network. This algorithm reduces the number of hops between transmitter and receiver nodes and also the number of transmitted packets. In this method, the sensor nodes are statically placed and clustered using LEACH-R algorithm. The Prediction based clustering algorithm is applied where few nodes are selected for tracking which uses the prediction mechanism to predict the next location of the moving object. The Current Location of the target is found using Trilateration algorithm. The Current Location or Predicted Location is sent to active Cluster Head from the leader node or the other node. Based on which node send the message to the Cluster Head, the Predicted or Current Location will be sent to the base station. In real time, the proposed work is applicable in traffic tracking and vehicle tracking. The experiment is carried out using Network Stimulator-2 environment. Simulation result shows that the proposed algorithm gives a better performance and reduces the energy consumption.

scholarly journals HYBRID APPROACH USING MOBILE SINK AND FUZZY LOGIC FOR REGION BASED CLUSTERING IN WSN

2017 ◽  
Vol 16 (5) ◽  
pp. 6933-6944
Author(s):  
Amneet Kaur ◽  
Harpreet Kaur
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Clustering Algorithm ◽  
Research Work ◽  
Hybrid Approach ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Fuzzy Variables

Wireless sensor network has revolutionized the way computing and software services are delivered to the clients on demand. Wireless sensor network is very important to the mankind. It consist of number of sensor called nodes and a base station. Nodes collect data and send to the base station. There are number of nodes which send data at a time. So, number of problems are occurred. So, far this nodes are divided into cluster then a cluster head will be formed. WSN is a battery powered system. When the battery is died no data send or received. So when all nodes participate for sending and receiving data then system is died earlier. Our research work proposed a new method for cluster head selection having less computational complexity. It was also found that the modified approach has improved performance to that of the other clustering approaches. The network area is divided into same sized small–small regions. Sensor nodes are randomly deployed in each predefined sub-area. Each region will have its region head (RH) and multiple member nodes. The member nodes in a specific region will send the data to the RH. RH within the region will be elected by distributed mechanism and will be based on fuzzy variables. It was found that the proposed algorithm gives a much improved network lifetime as compared to existing work. Based on our model, transmission tuning algorithm for cluster-based WSNs has been proposed to balance the load among cluster heads that fall in different regions. This algorithm is applied prior to a cluster algorithm to improve the performance of the clustering algorithm without affecting the performance of individual sensor nodes.

scholarly journals An Enhanced Clustering Method for Extending Sensing Lifetime of Wireless Sensor Network

2021 ◽  
pp. 67-82
Author(s):  
Yakubu Abdul-Wahab Nawusu ◽  
Alhassan Abdul-Barik ◽  
Salifu Abdul-Mumin
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Performance ◽  
Rank Order ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Cluster Heads ◽  
Heterogeneous Wireless Sensor Network

Extending the lifetime of a wireless sensor network is vital in ensuring continuous monitoring functions in a target environment. Many techniques have appeared that seek to achieve such prolonged sensing gains. Clustering and improved selection of cluster heads play essential roles in the performance of sensor network functions. Cluster head in a hierarchical arrangement is responsible for transmitting aggregated data from member nodes to a base station for further user-specific data processing and analysis. Minimising the quick dissipation of cluster heads energy requires a careful choice of network factors when selecting a cluster head to prolong the lifetime of a wireless sensor network. In this work, we propose a multi-criteria cluster head selection technique to extend the sensing lifetime of a heterogeneous wireless sensor network. The proposed protocol incorporates residual energy, distance, and node density in selecting a cluster head. Each factor is assigned a weight using the Rank Order Centroid based on its relative importance. Several simulation tests using MATLAB 7.5.0 (R2007b) reveal improved network lifetime and other network performance indicators, including stability and throughput, compared with popular protocols such as LEACH and the SEP. The proposed scheme will be beneficial in applications requiring reliable and stable data sensing and transmission functions.

scholarly journals A NOVEL APPROACH OF CLUSTERING FOR ENHANCED LIFETIME IN WIRELESS SENSOR NETWORK

2017 ◽  
Vol 16 (7) ◽  
pp. 7031-7039
Author(s):  
Chamanpreet Kaur ◽  
Vikramjit Singh
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Power Level ◽  
Research Work ◽  
Cluster Head ◽  
Mobile Node ◽  
Separation Distance ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor

Wireless sensor network has revolutionized the way computing and software services are delivered to the clients on demand. Our research work proposed a new method for cluster head selection having less computational complexity. It was also found that the modified approach has improved performance to that of the other clustering approaches. The cluster head election mechanism will include various parameters like maximum residual energy of a node, minimum separation distance and minimum distance to the mobile node. Each CH will create a TDMA schedule for the member nodes to transmit the data. Nodes will have various level of power for signal amplification. The three levels of power are used for amplifying the signal. As the member node will send only its own data to the cluster head, the power level of the member node is set to low. The cluster head will send the data of the whole cluster to the mobile node, therefore the power level of the cluster head is set to medium. High power level is used for mobile node which will send the data of the complete sector to the base station. Using low energy level for intra cluster transmissions (within the cluster) with respect to cluster head to mobile node transmission leads in saving much amount of energy. Moreover, multi-power levels also reduce the packet drop ratio, collisions and/ or interference for other signals. It was found that the proposed algorithm gives a much improved network lifetime as compared to existing work. Based on our model, multiple experiments have been conducted using different values of initial energy.

scholarly journals An improved cluster formation process in wireless sensor network to decrease energy consumption

2020 ◽  
Author(s):  
Hamid Reza Farahzadi ◽  
Mostafa Langarizadeh ◽  
Mohammad Mirhosseini ◽  
Seyed Ali Fatemi Aghda
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Information Transfer ◽  
Cluster Head ◽  
High Energy ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Death Time

AbstractWireless sensor network has special features and many applications, which have attracted attention of many scientists. High energy consumption of these networks, as a drawback, can be reduced by a hierarchical routing algorithm. The proposed algorithm is based on the Low Energy Adaptive Clustering Hierarchy (LEACH) and Quadrant Cluster based LEACH (Q-LEACH) protocols. To reduce energy consumption and provide a more appropriate coverage, the network was divided into several regions and clusters were formed within each region. In selecting the cluster head (CH) in each round, the amount of residual energy and the distance from the center of each node were calculated by the base station (including the location and residual energy of each node) for all living nodes in each region. In this regard, the node with the largest value had the highest priority to be selected as the CH in each network region. The base station calculates the CH due to the lack of energy constraints and is also responsible for informing it throughout the network, which reduces the load consumption and tasks of nodes in the network. The information transfer steps in this protocol are similar to the LEACH protocol stages. To better evaluate the results, the proposed method was implemented with LEACH LEACH-SWDN, and Q-LEACH protocols using MATLAB software. The results showed better performance of the proposed method in network lifetime, first node death time, and the last node death time.

scholarly journals Trust-Aware and Low Energy Consumption Security Topology Protocol of Wireless Sensor Network

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Zuo Chen ◽  
Min He ◽  
Wei Liang ◽  
Kai Chen
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Low Energy ◽  
Wireless Sensor ◽  
Trust Value ◽  
Low Energy Consumption

Wireless sensor network (WSN) is a kind of distributed and self-organizing networks, in which the sensor nodes have limited communication bandwidth, memory, and limited energy. The topology construction of this network is usually vulnerable when attacked by malicious nodes. Besides, excessive energy consumption is a problem that can not be ignored. Therefore, this paper proposes a secure topology protocol of WSN which is trust-aware and of low energy consumption, called TLES. The TLES considers the trust value as an important factor affecting the behavior of node. In detail, the TLES would take trust value, residual energy of the nodes, and node density into consideration when selecting cluster head nodes. Then, TLES constructs these cluster head nodes by choosing the next hop node according to distance to base station (BS), nodes’ degrees, and residual energy, so as to establish a safe, reliable, and energy saving network. Experimental results show that the algorithm can effectively isolate the malicious node in the network and reduce the consumption of energy of the whole network.

scholarly journals Two Level Intrusion Detection Mechanism For Context and Trust in Wireless Sensor Network

2020 ◽  
Vol 8 (6) ◽  
pp. 65-71
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Intrusion Detection ◽  
Sensor Network ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Trust Evaluation

21st century is considered as the era of communication, and Wireless Sensor Networks (WSN) have assumed an extremely essential job in the correspondence period. A wireless sensor network is defined as a homogeneous or heterogeneous system contains a large number of sensors, namely called nodes used to monitor different environments in cooperatives. WSN is composed of sensor nodes (S.N.), base stations (B.S.), and cluster head (C.H.). The popularity of wireless sensor networks has been increased day by day exponentially because of its wide scope of utilizations. The applications of wireless sensor networks are air traffic control, healthcare systems, home services, military services, industrial & building automation, network communications, VAN, etc. Thus the wide range of applications attracts attackers. To secure from different types of attacks, mainly intruder, intrusion detection based on dynamic state context and hierarchical trust in WSNs (IDSHT) is proposed. The trust evaluation is carried out in hierarchical way. The trust of sensor nodes is evaluated by cluster head (C.H.), whereas the trust of the cluster head is evaluated by a neighbor cluster head or base station. Hence the content trust, honest trust, and interactive trust are put forward by combining direct evaluation and feedback based evaluation in the fixed hop range. In this way, the complexity of trust management is carried in a hierarchical manner, and trust evaluation overhead is minimized.

PROCEDURE OF SELECTING A CLUSTER HEAD NODE IN A WIRELESS SENSOR NETWORK USING FUZZY LOGIC

2018 ◽  
pp. 81-89
Author(s):  
Ekaterina Andreevna Evstifeeva ◽  
Valeriy Dmitrievich Semeykin
Keyword(s):  
Fuzzy Logic ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Power Efficiency ◽  
Cluster Head ◽  
Residual Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Head Node ◽  
Input Parameters

Clustering, as one of the energy-efficient approaches, is widely used in wireless sensor networks. This method is based on creating clusters and selecting cluster head nodes in a wireless sensor network. Clustering saves network energy because data transfer is restricted between multiple nodes. Thus, clustering is provided between several nodes, and the service life of the wireless sensor network can be extended. Since the parent cluster node interacts with other nodes of the network, a node with a high level of residual energy must be selected to perform this role. When the energy level of the selected cluster head node becomes lower than the threshold value, then the re-election of this node takes place. It should be noted that multiple patterns of choosing cluster head nodes built using various parameters (residual node energy, distance from the base station to a node, distance between the head node and a cluster member, the number and proximity of neighboring nodes, etc.) lacked for a factor of energy consumption, i.e. how many times nodes communicated to each other. To cope with the problem, this paper presents a prognostic algorithm for selecting a cluster head node using fuzzy logic. This algorithm suggests using a number of input parameters, such as the residual energy of the node, the proximity of neighboring nodes, and the centralization of the node in the cluster. The proposed algorithm has been implemented using the software package MATLAB Fuzzy Logic Toolbox. The simulation results prove the advantages of the proposed technique; application of the input parameters mentioned above helps select optimal cluster head nodes in a wireless sensor network, which increases power efficiency of a wireless sensor network.

Enhanced Auxiliary Cluster Head Selection Routing Algorithm in Wireless Sensor Networks

2019 ◽  
Vol 12 ◽  
Author(s):  
Gaurav Kumar Nigam ◽  
Chetna Dabas
Keyword(s):  
Wireless Sensor Networks ◽  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Cluster Head ◽  
Base Station ◽  
Energy Utilization ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Cluster Head Selection

Background & Objective: Wireless sensor networks are made up of huge amount of less powered small sensor nodes that can audit the surroundings, collect meaningful data, and send it base station. Various energy management plans that pursue to lengthen the endurance of overall network has been proposed over the years, but energy conservation remains the major challenge as the sensor nodes have finite battery and low computational capabilities. Cluster based routing is the most fitting system to help for burden adjusting, adaptation to internal failure, and solid correspondence to draw out execution parameters of wireless sensor network. Low energy adaptive clustering hierarchy is an efficient clustering based hierarchical protocol that is used to enhance the lifetime of sensor nodes in wireless sensor network. It has some basic flaws that need to be overwhelmed in order to reduce the energy utilization and inflating the nodes lifetime. Methods : In this paper, an effective auxiliary cluster head selection is used to propose a new enhanced GC-LEACH algorithm in order to minimize the energy utilization and prolonged the lifespan of wireless sensor network. Results & Conclusion: Simulation is performed in NS-2 and the outcomes show that the GC-LEACH outperforms conventional LEACH and its existing versions in the context of frequent cluster head rotation in various rounds, number of data packets collected at base station, as well as reduces the energy consumption 14% - 19% and prolongs the system lifetime 8% - 15%.

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