Enhancement of Life Time of Sensor Nodes in Wireless Sensor Network

2021 ◽  
pp. 49-57
Author(s):  
Hemant Kumar Vijayvergia ◽  
Uma Shankar Modani
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor

scholarly journals An Evaluation of Various Clustering and Routing Protocols in Wireless Sensor Networks

2019 ◽  
Vol 9 (1) ◽  
pp. 3184-3187
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Routing Protocols ◽  
Routing Algorithm ◽  
Life Time ◽  
Research Field ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Growth ◽  
Wide Range

In the recent field of research the wireless sensor network plays an important role. Wireless sensor network is an important technology in this era. A Wireless Sensor Network (WSN) is a distributed network contains enormous sensor nodes with wide range of application. It transmits unlimited and enormous data like image, video, audio and data through end to end network. WSNs offer much solution to remote real time monitoring, recognition of physical occurrence and target tracking applications. This network growth is increasingly rapidly day by day and made the research field in difficult resurgence. The extended network lifetime, effective load balancing and scalability are essential for WSNs. The life time of the wireless network can be extended by the concept of clustering .Clustering is process of grouping the smaller localized networks in highly structured way. Diverse cluster technology available based on the network the clustering concept will be used. Efficient routing algorithm provide the way for efficient usage of bandwidth and reduce the delay in the network . This paper provides the survey of clustering and routing protocols to improve the efficiency in wireless technology in recent years

scholarly journals Energy Efficiency in Wireless Sensor Network using Randomized Switching for Maximizing Lifetime

2019 ◽  
Vol 8 (6) ◽  
pp. 1058-1061
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Threshold Energy ◽  
Life Time ◽  
Distributed Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Switching Algorithm

Wireless Sensor Network is distributed networks of sensors which have the ability to sense, process and communicate. Sensor nodes are also responsible for collection of data. Due to the limited battery power of sensor node energy consumption is an essential issue. To reduce the energy consumption balancing of node load is one of the major task. In this paper, we have used switching algorithm to switch the nodes to balance the node load which further increases the life time of each node by finding the shortest path to destination from the source node based on the threshold energy. Further we applied base localization algorithm to check the lifetime of each node.

WSN Management Self-Silence Design and Data Analysis for Neural Network Based Infrastructure

2020 ◽  
pp. 1440-1458
Author(s):  
Nilayam Kumar Kamila ◽  
Sunil Dhal
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Energy Conservation ◽  
Sensor Network ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Infrastructure ◽  
Network Life Time

In recent Wireless Sensor Network environment, battery energy conservation is one of the most important focus of research. The non-maintainable wireless sensor nodes need modern innovative ideas to save energy in order to extend the network life time. Different strategy in wireless sensor routing mechanism has been implemented to establish the energy conservation phenomenon. In earlier days, the nodes are dissipating maximum energy to communicate with each other(flooding) to establish the route to destination. In the next evolution of this research area, a clustering mechanism introduced which confirms the energy saving over the flooding mechanism. Neural Network is an advanced approach for self-clustering mechanism and when applied on wireless sensor network infrastructure, it reduces the energy consumption required for clustering. Neural network is a powerful concept with complex algorithms and capable to provide clustering solutions based on the wireless sensor network nodes properties. With the implementation of Neural Network on Wireless Sensor Network resolves the issues of high energy consumption required for network clustering. The authors propose a self-silence wireless sensor network model where sensor nodes change the sensing and transmitting mechanism by making self-silent in order to conserve the energy. This concept is simulated in neural network based wireless sensor network infrastructure of routing methodology and the authors observe that it extends the network life time. The mathematical analysis and simulation study shows the improved performance over the existing related neural network based wireless sensor routing protocols. Furthermore, the performance & related model parameters data set analysis provides the respective dependent relation information.

scholarly journals Enhancing the Performance of Wireless Sensor Networks thorugh Clustering and Joint Routing with Mobile Sink

2019 ◽  
Vol 8 (6) ◽  
pp. 323-327
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Networks ◽  
Sensor Network ◽  
Optimal Solution ◽  
Life Time ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Traffic Characteristics ◽  
Routing Methods

In wireless sensor network, randomly deployed nodes are formed as a clusters of varying size for each area depending upon the numbers of users. This paper deals with the cluster based joint routing with mobile sink and with static sink in cognitive based wireless sensor network. The Joint Routing (JR) is designed to overcome the problems, due to data gatherings of the sensor nodes for any application. Channel resources usually may vary among the different routing methods based on the traffic characteristics and application they require, which poses a great challenge to guarantee time delivery services. These problems poses a great challenge for cognitive radio based WSN. The resource allocation technique overcomes the problems like spatial priority, time delay, transmission delay and energy loss and here the channel resources are allocated with the help of TDMA technique. The static sink in networks consumes more energy which results the early die out of the nodes. Hence throughput of the networks declines which badly affect the network life time. To overcome these issues, static sink is replaced by mobile sink, which consumes less energy, before each transmission in a sensor networks. The networks with mobile sink provide us optimal solution and performance as well, while comparing with network with static sink. It is shown that the proposed system achieves 15% of improved throughput, 20% of less packet loss and 35% of less delay when compare with the system having centralized sink.

WSN Management Self-Silence Design and Data Analysis for Neural Network Based Infrastructure

2017 ◽  
Vol 4 (4) ◽  
pp. 82-100 ◽  
Author(s):  
Nilayam Kumar Kamila ◽  
Sunil Dhal
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Energy Conservation ◽  
Sensor Network ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Network Infrastructure ◽  
Network Life Time

In recent Wireless Sensor Network environment, battery energy conservation is one of the most important focus of research. The non-maintainable wireless sensor nodes need modern innovative ideas to save energy in order to extend the network life time. Different strategy in wireless sensor routing mechanism has been implemented to establish the energy conservation phenomenon. In earlier days, the nodes are dissipating maximum energy to communicate with each other(flooding) to establish the route to destination. In the next evolution of this research area, a clustering mechanism introduced which confirms the energy saving over the flooding mechanism. Neural Network is an advanced approach for self-clustering mechanism and when applied on wireless sensor network infrastructure, it reduces the energy consumption required for clustering. Neural network is a powerful concept with complex algorithms and capable to provide clustering solutions based on the wireless sensor network nodes properties. With the implementation of Neural Network on Wireless Sensor Network resolves the issues of high energy consumption required for network clustering. The authors propose a self-silence wireless sensor network model where sensor nodes change the sensing and transmitting mechanism by making self-silent in order to conserve the energy. This concept is simulated in neural network based wireless sensor network infrastructure of routing methodology and the authors observe that it extends the network life time. The mathematical analysis and simulation study shows the improved performance over the existing related neural network based wireless sensor routing protocols. Furthermore, the performance & related model parameters data set analysis provides the respective dependent relation information.

Cooja Based Approach for Estimation and Enhancement of Lifetime of 6LoWPAN Environment

2020 ◽  
Vol 10 (2) ◽  
pp. 207-216
Author(s):  
Ruchi Garg ◽  
Sanjay Sharma
Keyword(s):  
Wireless Sensor Network ◽  
Power Consumption ◽  
Sensor Network ◽  
Power Saving ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Packet Size ◽  
Suggested Approach ◽  
Header Compression

Background and Objective: The Scale with which Internet of Things (IoT) is penetrating our day to day life, time is not far away when it would be the Internet of Everything (IoE) that will require billions of devices to communicate with each other in the real world. To cater to the same, Wireless Sensor Network (WSN) is composed of 6LoWPAN sensor-nodes, which are mainly battery operated. One of the major issues, in such network, is nodes’ limited lifetime which is battery dependent. Methods: In this paper, we have suggested and implemented an approach for ‘Estimation and Enhancement of Lifetime of Wireless Sensor Network’ (E&EL-WSN). The aim of our study is to suggest an approach that helps in power saving of the batteries of sensor-nodes and will result in enhanced life-time of 6LoWPAN environment. Our suggested approach is based on the concept of reduced packet size resulting in saving of power consumption. Packet size is reduced by our Modified and Improved Header Compression (MIHC) method of IPv6 header compression. Results: The simulation, done in Cooja, shows, in our case, an improvement of approximately 19% saving of power consumption. This results in an enhancement of 70 days in the lifetime of the network, which is almost 23% better than the existing approach.

scholarly journals Reckoning Network Lifetime Ratio for Wireless Sensor Network

2019 ◽  
Vol 8 (11) ◽  
pp. 2238-2247
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Low Cost ◽  
Life Time ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Battery Life ◽  
Environment Change ◽  
Wireless Sensor Nodes

Advanced Technologies such as Internet of Things, Machine Networking give rise to the deployment of autonomous Wireless Sensor Nodes. They are used for various domains namely battlefield monitoring, enemy detection and monitoring the environment change. These Wireless Sensor Nodes have the properties of low cost and high battery life. NL (Network Lifetime) is an important phase of Wireless Sensor Network (WSNs), in which the nodes can maintain sensing for a more amount of time. NL can be improved by use of multiple techniques namely Opportunistic Transmission, Scheduling of Timed Data Packets, Clustering of Nodes, Energy Harvesting and Connectivity. This paper provides the energy consumption computation, life time ratio definition and the overview of NL improvement techniques. The paper also presents brief review of the Destination based and Source based routing algorithm

scholarly journals Routing Algorithm using Fuzzy Logic Based Clustering with Mobile Sink for Wireless Sensor Network

2019 ◽  
Vol 8 (4) ◽  
pp. 4000-4005
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Cluster Head ◽  
Life Time ◽  
Mobile Sink ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Node Degree

Minimization of the energy consumption in Wireless Sensor Network (WSN) is one of the most important area which has been explored by researchers through different methods. The use of non-stationary mobile sink has undoubtedly decreased the energy consumption within the sensor nodes and hence the life time of the system. Applying the Fuzzy Logic could effectively optimize the selection of Cluster Head. In this paper, Fuzzy Logic has been implemented for Cluster Head selection along with a mobile sink. The energy remaining in the sensor node, distance between the sink and the node, and the node degree are considered as the fuzzy inference variables. The life time of the node has been compared with the LEACH and Fuzzy logic based Clustering Combined with Mobile Sink (FCCMS) with mobile sink.

ROUTING PATH OPTIMIZAION TO MAXIMIZE THE LIFETIME OF WIRELESS SENSOR NETWORK

2009 ◽  
Vol 16 (06) ◽  
pp. 509-520
Author(s):  
P. MANJUNATHA ◽  
A. K. VERMA ◽  
A. SRIVIDYA
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Sensor Node ◽  
Minimum Energy ◽  
Life Time ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Routing

Wireless sensor network (WSN) consists of a large number of sensor nodes which are able to sense their environment and communicate with each other using wireless interface. However these sensor nodes are constrained in energy capacity. The lifetimes of sensor node and sensor network mainly depends upon these energy resources. To increase the life time of sensor network, many approaches have been proposed to optimize the energy usage. All these proposed protocols mainly use minimum hop or minimum energy path. Continuously using the shortest path will deplete energy of the nodes at a much faster rate and causes network partition. This paper proposes an energy efficient routing protocol to extend the network lifetime for delay constrained network. Each sensor node selects the optimized path for forwarding packets to the base station based on routing metrics. Proposed studies and simulation results shows that the protocol put forward in the paper can achieve higher network lifetime by striking a balance between the delay and power consumption in comparison to other routing protocols.

An Effective Congestion Control Algorithm based on Traffic Assignment and Reassignment in Wireless Sensor Network

2020 ◽  
Vol 13 (8) ◽  
pp. 1166-1174
Author(s):  
Chao Wang
Keyword(s):  
Wireless Sensor Network ◽  
Congestion Control ◽  
Sensor Network ◽  
Traffic Assignment ◽  
Transmission Rate ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Congestion Detection ◽  
Detection Technology ◽  
Average Transmission

Background: It is important to improve the quality of service by using congestion detection technology to find the potential congestion as early as possible in wireless sensor network. Methods: So an improved congestion control scheme based on traffic assignment and reassignment algorithm is proposed for congestion avoidance, detection and mitigation. The congestion area of the network is detected by predicting and setting threshold. When the congestion occurs, sensor nodes can be recovery quickly from congestion by adopting reasonable method of traffic reassignment. And the method can ensure the data in the congestion areas can be transferred to noncongestion areas as soon as possible. Results: The simulation results indicate that the proposed scheme can reduce the number of loss packets, improve the throughput, stabilize the average transmission rate of source node and reduce the end-to-end delay. Conclusion: : So the proposed scheme can enhance the overall performance of the network. Keywords: wireless sensor network; congestion control; congestion detection; congestion mitigation; traffic assignment; traffic reassignment.

Sign in / Sign up

Export Citation Format

Share Document