scholarly journals Unequal clustering in wireless sensor network: a review

2021 ◽  
Vol 22 (1) ◽  
pp. 419
Author(s):  
Khalid Waleed Al-ani ◽  
Fairuz Bin Abdullah ◽  
Salman Yossuf
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Energy Hole ◽  
Node Location ◽  
Energy Hole Problem

<p><span>In recent time, the applications' diversity of wireless sensor network (WSN) attracts many researchers. WSN comprises of many sensor nodes with limited battery power. Therefore, energy consumption should be controlled to the optimum. Clustering is an efficient solution for energy management in WSN, but clustering does not consider the sink node location. It will cause the energy hole problem in multi-hop routing. Energy hole problem was solved by unequal clustering. A review of various unequal clustering mechanisms is presented in this paper. The comparison between the various mechanisms was based on cluster head election process, cluster properties, simulation parameters and energy efficiency to highlight a more efficient and scalable unequal clustering algorithm for </span>WSN.</p>

scholarly journals E-FUCA: enhancement in fuzzy unequal clustering and routing for sustainable wireless sensor network

2021 ◽  
Author(s):  
Pawan Singh Mehra
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Cluster Head ◽  
Average Energy ◽  
Base Station ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Energy Hole ◽  
Intelligent Decision ◽  
Improved Performance

AbstractWith huge cheap micro-sensing devices deployed, wireless sensor network (WSN) gathers information from the region and delivers it to the base station (BS) for further decision. The hotspot problem occurs when cluster head (CH) nearer to BS may die prematurely due to uneven energy depletion resulting in partitioning the network. To overcome the issue of hotspot or energy hole, unequal clustering is used where variable size clusters are formed. Motivated from the aforesaid discussion, we propose an enhanced fuzzy unequal clustering and routing protocol (E-FUCA) where vital parameters are considered during CH candidate selection, and intelligent decision using fuzzy logic (FL) is taken by non-CH nodes during the selection of their CH for the formation of clusters. To further extend the lifetime, we have used FL for the next-hop choice for efficient routing. We have conducted the simulation experiments for four scenarios and compared the propound protocol’s performance with recent similar protocols. The experimental results validate the improved performance of E-FUCA with its comparative in respect of better lifetime, protracted stability period, and enhanced average energy.

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 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 An Implementation of Grouping Nodes in Wireless Sensor Network Based on Distance by Using k-Means Clustering

2018 ◽  
Vol 12 (2) ◽  
pp. 97
Author(s):  
Rizqi Fauzil Azhar ◽  
Ahmad Zainudin ◽  
Prima Kristalina ◽  
Bagas Mardiasyah Prakoso ◽  
Niam Tamami
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Power Efficiency ◽  
Clustering Algorithm ◽  
Nearest Neighbor ◽  
Cluster Head ◽  
Channel Modeling ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Observation Area

Wireless Sensor Network (WSN) is a network consisting of several sensor nodes that communicate with each other and work together to collect data from the surrounding environment. One of the WSN problems is the limited available power. Therefore, nodes on WSN need to communicate by using a cluster-based routing protocol. To solve this, the researchers propose a node grouping based on distance by using k-means clustering with a hardware implementation. Cluster formation and member node selection are performed based on the nearest device of the sensor node to the cluster head. The k-means algorithm utilizes Euclidean distance as the main grouping nodes parameter obtained from the conversion of the Received Signal Strength Indication (RSSI) into the distance estimation between nodes. RSSI as the parameter of nearest neighbor nodes uses lognormal shadowing channel modeling method that can be used to get the path loss exponent in an observation area. The estimated distance in the observation area has 27.9% error. The average time required for grouping is 58.54 s. Meanwhile, the average time used to retrieve coordinate data on each cluster to the database is 45.54 s. In the system, the most time-consuming process is the PAN ID change process with an average time of 14.20 s for each change of PAN ID. The grouping nodes in WSN using k-means clustering algorithm can improve the power efficiency by 6.5%.

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 Unequal Clustering Multipath Routing Algorithm for Wireless Sensor Network based on Clustering and Ant Colony

2021 ◽  
Vol 3 (3) ◽  
pp. 156-160
Author(s):  
Jin Yong-xian
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Algorithm ◽  
Multipath Routing ◽  
Cluster Head ◽  
Optimal Number ◽  
Wireless Sensor ◽  
Unequal Clustering ◽  
Selection Probability ◽  
Factor Node

To improve the energy efficiency of the wireless sensor network (WSN), and extend the network life. This paper proposes an improved unequal clustering multipath routing algorithm (UCMRA). The algorithm improves the formula of cluster head selection probability and competition radius, and considers the energy factor, node density, optimal number of cluster heads, etc. Experimental results show that, compared with the traditional algorithm, UCMRA has more stable cluster head distribution, less energy consumption and longer network lifetime.

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