Enhanced PEGASIS using ant colony optimization for data gathering in WSN

Ghosh, Swaroop; Mondal, Sanjoy; Biswas, Utpal

doi:10.1109/icices.2016.7518930

Cited by 17 publications

(10 citation statements)

References 6 publications

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“…In order to increase NL the zone based and tree-based method provides a decrease in EC. The energy efficiency and NL improvement are done using E-PEGASIS [48] which is built on top of the PEGASIS protocol and the monitoring can be done in a proactive manner on hierarchical data routing protocols in order to improve energy levels and NL improvement.…”

Section: Coverage and Connectivity Constraintmentioning

confidence: 99%

Reckoning Network Lifetime Ratio for Wireless Sensor Network

Saqhib¹,

S²

2019

IJITEE

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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

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Section: Coverage and Connectivity Constraintmentioning

confidence: 99%

Reckoning Network Lifetime Ratio for Wireless Sensor Network

Saqhib¹,

S²

2019

IJITEE

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“…The goal of their work was to save the sensor nodes energy consumption regardless of the other consequences on the network performance. However, many research have been done to improve the chain-based routing and overcome the deficiencies in PEGASIS protocol such as in [6][7][8][9][10][11]. One of these improvements was by IEEPB protocol.…”

Section: Pegasis Protocolmentioning

confidence: 99%

Comparison by simulation of PEGASIS and IEEPB routing protocols

Alnajdi

Bajaber

2019

IJEECS

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<span>As the applications of wireless sensor networks (WSNs) became widely used throughout the years the importance of advanced sensor networks techniques increased as well. One of the main techniques used in WSNs is hierarchical routing which mainly aims to reduce the consumption of sensor nodes energy by assigning different roles to the sensor nodes to create multi-layer scheme for data transmission. This paper embraces a simulation for two known hierarchical routing protocols: Power-Efficient Gathering in Sensor Information Systems (PEGASIS) protocol and an Improved Energy-Efficient PEGASIS-Based (IEEPB) protocol. Both protocols aim to reduce the transmission distance in order to save the nodes energy by performing chain-based clustering. For evaluation, we measured the residual energy and control overhead throughout the network operation time and the results showed major flaws in both protocols such as long link problem and poor leader selection method in PEGASIS. Moreover, high nodes density problem in IEEPB.</span>

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“…Ghosh et al [13] presented an enhanced version of PEGASIS (E-PEGASIS) which can overcome the shortcomings of PEGASIS and energy efficiency. The simulation results using Matlab 12 show that E-PEGASIS extended the life span of WSN compared to PEGASIS, PEGASIS Binary and LBEERA.…”

Section: Related Workmentioning

confidence: 99%

Enhanced PEGASIS using Dynamic Programming for Data Gathering in Wireless Sensor Network

Mufid

Rasyid

Syarif

2019

emitter

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A number of routing protocol algorithms such as Low-Energy Adaptive Clustering Hierarchy (LEACH) and Power-Efficient Gathering in Sensor Information Systems (PEGASIS) have been proposed to overcome the problem of energy consumption in Wireless Sensor Network (WSN) technology. PEGASIS is a development of the LEACH protocol, where within PEGASIS all nodes are active during data transfer rounds thus limiting the lifetime of the WSN. This study aims to propose improvements from the previous PEGASIS version by giving the name Enhanced PEGASIS using Dynamic Programming (EPDP). EPDP uses the Dominating Set (DS) concept in selecting a subset of nodes to be activated and using dynamic programming based optimization in forming chains from each node. There are 2 topology nodes that we use, namely random and static. Then for the Base Station (BS), it will also be divided into several scenarios, namely the BS is placed outside the network, in the corner of the network, and in the middle of the network. Whereas to determine the performance between EPDP, PEGASIS and LEACH, an analysis of the number of die nodes, number of alive nodes, and remaining of energy were analyzed. From the experiment result, it was found that the EPDP protocol had better performance compared to the LEACH and PEGASIS protocols in terms of number of die nodes, number of alive nodes, and remaining of energy. Whereas the best BS placement is in the middle of the network and uses static node distribution topologies to save more energy.

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Enhanced PEGASIS using ant colony optimization for data gathering in WSN

Cited by 17 publications

References 6 publications

Reckoning Network Lifetime Ratio for Wireless Sensor Network

Reckoning Network Lifetime Ratio for Wireless Sensor Network

Comparison by simulation of PEGASIS and IEEPB routing protocols

Enhanced PEGASIS using Dynamic Programming for Data Gathering in Wireless Sensor Network

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