A novel approach to improve network lifetime in WSN by energy efficient packet optimization

2016 ◽  
Author(s):  
Abhaykumar L. Gupta ◽  
Narendra Shekokar
Keyword(s):  
Network Lifetime ◽  
Energy Efficient ◽  
Novel Approach

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.

An Energy Efficient Estimation Algorithm for Wireless Sensor Network

2011 ◽  
Vol 216 ◽  
pp. 176-180
Author(s):  
Yong Ding ◽  
Yue Mei Su
Keyword(s):  
Energy Consumption ◽  
Wireless Sensor Network ◽  
Sensor Network ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Estimation Algorithm ◽  
Efficient Estimation ◽  
Wireless Sensor ◽  
Estimation Algorithms ◽  
Current Energy

Wireless Sensor Networks functionality is closely related to network lifetime which depends on the energy consumption, so require energy- efficient protocols to improve the network lifetime. According to the analysis and summary of the current energy efficient estimation algorithms in wireless sensor network An energy-efficient algorithm is proposed,. Then this optimization algorithm proposed in the paper is adopted to improve the traditional diffusion routing protocol. Simulation results show that this algorithm is to effectively balance the network energy consumption, improve the network life-cycle and ensure the communication quality.

scholarly journals Energy-Efficient Hybrid Routing Protocol for IoT Communication Systems in 5G and Beyond

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 537
Author(s):  
Mohammad Baniata ◽  
Haftu Tasew Reda ◽  
Naveen Chilamkurti ◽  
Alsharif Abuadbba
Keyword(s):  
Energy Efficiency ◽  
Network Lifetime ◽  
Energy Efficient ◽  
Communication Systems ◽  
Multiple Input Multiple Output ◽  
Sensor Nodes ◽  
Clustering Methods ◽  
Mimo Antenna ◽  
Improve Energy Efficiency ◽  
Art Research

One of the major concerns in wireless sensor networks (WSNs) is most of the sensor nodes are powered through limited lifetime of energy-constrained batteries, which majorly affects the performance, quality, and lifetime of the network. Therefore, diverse clustering methods are proposed to improve energy efficiency of the WSNs. In the meantime, fifth-generation (5G) communications require that several Internet of Things (IoT) applications need to adopt the use of multiple-input multiple-output (MIMO) antenna systems to provide an improved capacity over multi-path channel environment. In this paper, we study a clustering technique for MIMO-based IoT communication systems to achieve energy efficiency. In particular, a novel MIMO-based energy-efficient unequal hybrid clustering (MIMO-HC) protocol is proposed for applications on the IoT in the 5G environment and beyond. Experimental analysis is conducted to assess the effectiveness of the suggested MIMO-HC protocol and compared with existing state-of-the-art research. The proposed MIMO-HC scheme achieves less energy consumption and better network lifetime compared to existing techniques. Specifically, the proposed MIMO-HC improves the network lifetime by approximately 3× as long as the first node and the final node dies as compared with the existing protocol. Moreover, the energy that cluster heads consume on the proposed MIMO-HC is 40% less than that expended in the existing protocol.

scholarly journals Grid based Energy-Efficient Cross-Layer Optimization Model in WSN Using Dual Mobile Sinks

2021 ◽  
Author(s):  
Vimala D ◽  
Manikandan K
Keyword(s):  
Network Lifetime ◽  
Optimization Model ◽  
Energy Efficient ◽  
Simulation Analysis ◽  
Optimal Path ◽  
Maximum Energy ◽  
Base Station ◽  
Cross Layer ◽  
Cross Layer Optimization ◽  
Grid Based

Abstract In recent days, wireless sensor network (WSN) gained more attention among researchers as well as industries. It is composed with massive number of sensors which are independently organized cooperate with one another for collecting, processing and transmitting data to the base station (BS) or sink. Since sensors undergo random deployment in harsh environment, it is difficult or not even possible to replace the batteries. So, energy efficient clustering and routing techniques are preferable to reduce the dissipation of energy and improve the network lifetime. This paper introduces a new Grid based Energy-Efficient Cross-Layer Optimization Model in WSN Using Dual Mobile Sink (GEECLO). The proposed method involves three main processes namely grid partitioning, clustering and routing. Initially, the entire network is partitioned into different zones and then sub zones. Then, type II FL process gets executed to select the CHs and construct the clusters. Finally, dolphin swarm optimization algorithm (DSOA) based routing process takes place to select the optimal path for inter-cluster communication. A detailed simulation analysis takes place to ensure the betterment of the GEECLO algorithm. The obtained experimentation outcome depicted that the GEECLO model offers maximum energy efficiency and network lifetime.

scholarly journals Survey on Energy Efficient Cloud: A Novel Approach towards Green Computing

Helix ◽  
2018 ◽  
Vol 8 (5) ◽  
pp. 3976-3979 ◽  
Author(s):  
Anup Gade
Keyword(s):  
Energy Efficient ◽  
Green Computing ◽  
Novel Approach
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