Energy Aware Hybrid Scheme of Client-Server and Mobile Agent Models for Data Aggregation in Wireless Sensor Networks

Fissaoui, Mohamed El; Beni‐Hssane, Abderrahim; Saadi, Mostafa

doi:10.1007/978-3-319-52941-7_23

Cited by 8 publications

(8 citation statements)

References 5 publications

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“…To reduce the energy consumption during the data forwarding of the sensor nodes, several studies propose the use a Mobile Data Collector. In [4], the MDC visits all sensor nodes deployed in the network, this conserves efficiently the energy of sensor nodes, however the long constructed path could not be supported by the MDC. A solution was proposed in previous works aiming to adopt multiple MDCs [12][13].…”

Section:   ( ) ( )mentioning

confidence: 99%

An Efficient Mobile Data Gathering Method with Tree Clustering Algorithm in Wireless Sensor Networks Balanced and Unbalanced Topologies

Meddah

Haddad

Ezzeddine

2021

Wireless Pers Commun

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Section:   ( ) ( )mentioning

confidence: 99%

An Efficient Mobile Data Gathering Method with Tree Clustering Algorithm in Wireless Sensor Networks Balanced and Unbalanced Topologies

Meddah

Haddad

Ezzeddine

2021

Wireless Pers Commun

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Section: Related Workmentioning

confidence: 99%

“…Previous researches propose to construct a static path for the MDC [4][8] [11], where the path is computed at the BS, the MDC travels among sensor nodes based on the pre-computed trajectory constructed by the BS. This technique is more suitable for monitoring applications in which data are gathered and communicated back to the sink.…”

Section: Related Workmentioning

confidence: 99%

“…This technique is more suitable for monitoring applications in which data are gathered and communicated back to the sink. In [4] a Hybrid Scheme of client/server and Mobile agent for data aggregation is proposed. Authors propose a weight based CH election scheme that selects the suitable sensor nodes as CHs.…”

Section: Related Workmentioning

confidence: 99%

“…Different approaches have been proposed to group sensor nodes into clusters. In [4] [6] and [7] authors chooses to create the clusters based on nodes density impact factor. Each sensor node will receives the impact factors from other sensor neighbors, then compares the accumulated impact factors and decides either to be elected or not as CH.…”

Section: Related Workmentioning

confidence: 99%

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An Efficient Mobile Data Gathering Method with Tree Clustering Algorithm in Wireless Sensor Networks Balanced and Unbalanced Topologies

Meddah

HADDAD²,

EZZEDDINE

2021

Preprint

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Mobile Data Collector device (MDC) is adopted to reduce the energy consumption in Wireless Sensor Networks. This device travels the network in order to gather the collected data from sensor nodes. This paper presents a new Tree Clustering algorithm with Mobile Data Collector in Wireless Sensor Networks, which establishes the shortest travelling path passing throw a subset of Cluster Heads (CH). To select CHs, we adopt a competitive scheme, and the best sensor nodes are elected according to the number of packets forwarded between sensor nodes, the number of hops to the tree’s root, the residual energy, and the distance between the node and the closest CH. In simulation results, we adopt the balanced and unbalanced topologies and prove the efficiently of our proposed algorithm considering the network lifetime, the fairness index and the energy consumption in comparison with the existing mobile data collection algorithms.

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An Efficient Intra‐Cluster Data Aggregation and finding the Best Sink location in WSN using EEC‐MA‐PSOGA approach

Sreedevi

Venkateswarlu

2022

Int J Communication

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Summary Wireless sensor networks (WSNs) consist of nodes. Issues involved with the use of a sensor network are energy‐saving and the effective use of energy. Clustering in WSNs is a proven technique for energy optimization. The relationship between sensor nodes and cluster heads (CHs) has only been considered prior to cluster‐based routing protocols. However, most clustering algorithms have failed to address the routing overhead and the energy consumption rate between CH nodes and SINK. In this paper, a new framework named as EEC‐MA‐PSOGA ‐ an energy‐efficient (EE) intra‐cluster mobile agent (INC‐MA)‐based particle swarm optimization–genetic algorithm (PSO‐GA), has been presented to initiate the distance communication and place the SINK optimally in WSNs. The cluster members send the collected data towards their respective CHs for aggregation. To find the sink's best position, the PSO‐GA‐based location estimation algorithm is initiated based on the network structure. The limited capability of WSNs makes them more vulnerable to attackers. The prevention mechanism must be less complex to ensure the fair operations in the network. Here, the attack detection ability of the proposed solution has been tested against clone attack. With varied communication range, simulation time, and sensor nodes, the tests are conducted extensively on various scenarios of WSNs. When compared with the prior mechanisms, the framework provides better results and better prevention with less overhead by analyzing the experimental results such as energy consumption, network lifetime, and throughput.

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Energy Aware Hybrid Scheme of Client-Server and Mobile Agent Models for Data Aggregation in Wireless Sensor Networks

Cited by 8 publications

References 5 publications

An Efficient Mobile Data Gathering Method with Tree Clustering Algorithm in Wireless Sensor Networks Balanced and Unbalanced Topologies

An Efficient Mobile Data Gathering Method with Tree Clustering Algorithm in Wireless Sensor Networks Balanced and Unbalanced Topologies

An Efficient Mobile Data Gathering Method with Tree Clustering Algorithm in Wireless Sensor Networks Balanced and Unbalanced Topologies

An Efficient Intra‐Cluster Data Aggregation and finding the Best Sink location in WSN using EEC‐MA‐PSOGA approach

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