A Novel Algorithm to Improve Network Lifetime of Wireless Sensor Networks

2013 ◽  
Vol 433-435 ◽  
pp. 599-602
Author(s):  
Rui Ma ◽  
Yan Cheng Liu ◽  
Chuan Wang
Keyword(s):  
Network Lifetime ◽  
Search Strategy ◽  
Hybrid Genetic Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Wireless Sensor Nodes ◽  
Sensor Cover ◽  
Simulation Results ◽  
Local Search Strategy ◽  
Novel Algorithm

One approach to extend the network lifetime is to divide the deployed sensors into disjoint subsets of sensors, or sensor covers, such that each sensor cover can cover all targets and work by turns. The more sensor covers can be found, the longer sensor network lifetime can be prolonged.This study propose a novel hybrid genetic algorithm (NHGA) comprising both basic generic operations with a fitness-improving local-search strategy to divide all wireless sensor nodes into a maximum number of disjoint set covers (DSCs). The simulation results show that NHGA outperforms the existing methods by generating more disjoint set covers and prolongs network lifetime.

Maximizing the Lifetime of Sliding Wireless Sensors in Barrier Coverage

2012 ◽  
Vol 157-158 ◽  
pp. 503-506 ◽  
Author(s):  
Tao Yang ◽  
Pan Guo Fan ◽  
De Jun Mu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Wireless Sensors ◽  
Specific Area ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Barrier Coverage ◽  
Coverage Ratio ◽  
Simulation Results

Wireless sensor network is always deployed in specific area for intrusion detection and environmental monitoring. The sensor nodes suffer mostly from their limited battery capacity.Maximizing the lifetime of the entire networks is mainly necessary considered in the design. Sliding the sensors in different barriers under the optimal barrier construction is a good solution for both maximizing network lifetime and providing predetermined coverage ratio. The simulation results demonstrate that the scheme can effectively reduce the energy consumption of the wireless sensor network and increase the network lifetime.

scholarly journals Evaluating the optimal sensor placement for smoke detection

2016 ◽  
Vol 26 (1) ◽  
pp. 33-50 ◽  
Author(s):  
Mirjana Maksimovic ◽  
Vladimir Milosevic
Keyword(s):  
Wireless Sensor Networks ◽  
Network Design ◽  
Network Lifetime ◽  
Fire Detection ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Smoke Detection ◽  
Wireless Sensor Nodes ◽  
Minimum Number ◽  
Fire Ignition

Wireless Sensor Networks (WSNs) consist of wireless sensor nodes, where the choice of their deployment scheme depends highly on the type of sensors, their application, and the environment they will operate in. The performance of WSNs can be affected if the network is deployed under different topologies. In this paper various strategies for positioning nodes in WSNs for fire detection (grid, triangular and strip) are discussed. We propose the proper placement of the smoke sensors to satisfy two important network design objectives: to maximize the network lifetime after fire ignition, and to achieve full coverage by using a minimum number of sensors (especially in a deterministic node deployment).

scholarly journals A Novel Algorithm for Barrier Coverage Based on Hybrid Wireless Sensor Nodes

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 118866-118875 ◽  
Author(s):  
Xuqi Wang ◽  
Zijian Tian ◽  
Wenqing Wang ◽  
Fangyuan He ◽  
Liyong Zhao ◽  
...  
Keyword(s):  
Sensor Nodes ◽  
Wireless Sensor ◽  
Barrier Coverage ◽  
Wireless Sensor Nodes ◽  
Novel Algorithm

The Estimation of Target Trajectory Based on Energy Attenuation of Wireless Sensor Nodes

2014 ◽  
Vol 687-691 ◽  
pp. 1827-1831
Author(s):  
Lin Feng ◽  
Xiao Min Ran ◽  
Guan Lin Mei
Keyword(s):  
Current Problem ◽  
Estimation Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Estimation Accuracy ◽  
Wireless Sensor Nodes ◽  
Trajectory Estimation ◽  
Target Trajectory ◽  
Simulation Results ◽  
High Degree

For current problem of the urgent needs for moving targets’ estimated trajectory and the large algorithm complexity for trajectory estimation algorithm, without affecting the accuracy requirements of the track, put forward an algorithm of target trajectory estimation based on energy attenuation of wireless sensor nodes (ETT-EA). The algorithm is a high degree of concern from the current direction of node energy attenuation, which roughly calculates the trajectory of invasion target. Simulation results show that the algorithm saves the complexity of the algorithm with satisfying certain trajectory estimation accuracy, which is simple and adapted to specific environments.

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

Enhanced Adaptive Distributed Energy-Efficient Clustering (EADEEC) for Wireless Sensor Networks

2020 ◽  
Vol 13 (2) ◽  
pp. 168-172
Author(s):  
Ravi Kumar Poluru ◽  
M. Praveen Kumar Reddy ◽  
Syed Muzamil Basha ◽  
Rizwan Patan ◽  
Suresh Kallam
Keyword(s):  
Network Lifetime ◽  
Routing Protocols ◽  
Energy Efficient ◽  
High Energy ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Distributed Energy ◽  
Stability Period ◽  
Energy Efficient Clustering

Background:Recently Wireless Sensor Network (WSN) is a composed of a full number of arbitrarily dispensed energy-constrained sensor nodes. The sensor nodes help in sensing the data and then it will transmit it to sink. The Base station will produce a significant amount of energy while accessing the sensing data and transmitting data. High energy is required to move towards base station when sensing and transmitting data. WSN possesses significant challenges like saving energy and extending network lifetime. In WSN the most research goals in routing protocols such as robustness, energy efficiency, high reliability, network lifetime, fault tolerance, deployment of nodes and latency. Most of the routing protocols are based upon clustering has been proposed using heterogeneity. For optimizing energy consumption in WSN, a vital technique referred to as clustering.Methods:To improve the lifetime of network and stability we have proposed an Enhanced Adaptive Distributed Energy-Efficient Clustering (EADEEC).Results:In simulation results describes the protocol performs better regarding network lifetime and packet delivery capacity compared to EEDEC and DEEC algorithm. Stability period and network lifetime are improved in EADEEC compare to DEEC and EDEEC.Conclusion:The EADEEC is overall Lifetime of a cluster is improved to perform the network operation: Data transfer, Node Lifetime and stability period of the cluster. EADEEC protocol evidently tells that it improved the throughput, extended the lifetime of network, longevity, and stability compared with DEEC and EDEEC.

Energy Efficient Clustering and Routing Algorithm for WSN

2019 ◽  
Vol 12 ◽  
Author(s):  
Mohit Kumar ◽  
Sonu Mittal ◽  
Md. Amir Khusru Akhtar
Keyword(s):  
Energy Consumption ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Hot Spot ◽  
Routing Algorithm ◽  
Relay Node ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Efficient Clustering ◽  
Hot Spot Problem

Background: This paper presents a novel Energy Efficient Clustering and Routing Algorithm (EECRA) for WSN. It is a clustering-based algorithm that minimizes energy dissipation in wireless sensor networks. The proposed algorithm takes into consideration energy conservation of the nodes through its inherent architecture and load balancing technique. In the proposed algorithm the role of inter-cluster transmission is not performed by gateways instead a chosen member node of respective cluster is responsible for data forwarding to another cluster or directly to the sink. Our algorithm eases out the load of the gateways by distributing the transmission load among chosen sensor node which acts as a relay node for inter-cluster communication for that round. Grievous simulations show that EECRA is better than PBCA and other algorithms in terms of energy consumption per round and network lifetime. Objective: The objective of this research lies in its inherent architecture and load balancing technique. The sole purpose of this clustering-based algorithm is that it minimizes energy dissipation in wireless sensor networks. Method: This algorithm is tested with 100 sensor nodes and 10 gateways deployed in the target area of 300m × 300m. The round assumed in this simulation is same as in LEACH. The performance metrics used for comparisons are (a) network lifetime of gateways and (b) energy consumption per round by gateways. Our algorithm gives superior result compared to LBC, EELBCA and PBCA. Fig 6 and Fig 7 shows the comparison between the algorithms. Results: The simulation was performed on MATLAB version R2012b. The performance of EECRA is compared with some existing algorithms like PBCA, EELBCA and LBCA. The comparative analysis shows that the proposed algorithm outperforms the other existing algorithms in terms of network lifetime and energy consumption. Conclusion: The novelty of this algorithm lies in the fact that the gateways are not responsible for inter-cluster forwarding, instead some sensor nodes are chosen in every cluster based on some cost function and they act as a relay node for data forwarding. Note the algorithm does not address the hot-spot problem. Our next endeavor will be to design an algorithm with consideration of hot-spot problem.

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