Cross-Layer Greedy position-based routing for multihop wireless sensor networks in a real environment

Benzerbadj, Ali; Kechar, Bouabdellah; Bounceur, Ahcène; Pottier, Bernard

doi:10.1016/j.adhoc.2018.01.003

Cited by 18 publications

(17 citation statements)

References 17 publications

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“…Choosing large cluster size for the communication increases the work load of the cluster head, and the small cluster size results in many clusters, which in turn downgrades the performance. 54 • Some technique try to reduce the transmit power of the node as a part of energy saving strategy, but it results in increased packet loss rate, and increased retransmission. In the worst case, it can result in increased energy usage.…”

Section: Challengesmentioning

confidence: 99%

“…While implemented in the large network, maintaining number of alive nodes was difficult. Ali Benzerbadj et al 54 proposed the Cross‐Layer Greedy Routing algorithm (CL‐GR), and it selected the routing path for the WSN in a greedy way. The path establishment was carried on by ensuring high Packet Delivery Ratio (PDR) and low energy consumption.…”

Section: Literature Surveymentioning

confidence: 99%

“…Some of the challenges listed in the existing works for developing the multipath routing algorithm for WSN are given below: In the cluster based techniques, choosing the cluster size is an important factor and the average size of the cluster determines the performance. Choosing large cluster size for the communication increases the work load of the cluster head, and the small cluster size results in many clusters, which in turn downgrades the performance 54 Some technique try to reduce the transmit power of the node as a part of energy saving strategy, but it results in increased packet loss rate, and increased retransmission.…”

Section: Literature Surveymentioning

confidence: 99%

See 2 more Smart Citations

A modified rider optimization algorithm for multihop routing in WSN

Augustine¹,

Ananth²

2020

Int J Numerical Modelling

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Wireless Sensor Networks (WSNs) have an important role in establishing the communication between the Internet of things (IoT) devices. Routing is an important research field in the WSN as it helps in finding the suitable paths for the communication. This paper proposes a multipath routing algorithm based on the optimization approach. The proposed routing algorithm has two important phases, namely, Cluster head selection and multipath routing. Initially, the cluster head selection is carried out by the kernel based Fuzzy C Means (kernel FCM) algorithm. Then, the multipath routing is established by the newly developed Rider Salp Swarm Optimization algorithm (RSSA), which is the integration of the Rider Optimization Algorithm (ROA) and Salp Swarm Algorithm (SSA). The fitness function of the proposed RSSA is designed by considering the several factors, such as energy, QoS and trust. The simulation of the proposed work is carried out using different WSN setups, and the results are compared with several comparative techniques. From the results, it can be summarized that the proposed RSSA based multipath routing has better performance with values of 0.2526, 0.0764, 0.5, and 26 for delay, energy, throughput and number of alive nodes, respectively.

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Section: Challengesmentioning

confidence: 99%

Section: Literature Surveymentioning

confidence: 99%

Section: Literature Surveymentioning

confidence: 99%

See 1 more Smart Citation

A modified rider optimization algorithm for multihop routing in WSN

Augustine¹,

Ananth²

2020

Int J Numerical Modelling

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“…Thus energy efficient routing protocol is considered as a major goal for most researches to attain reduced power consumption in networks. Conventional techniques can be classified into two types: direct transmission [1][2][3] and multi hop transmission [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18]. In direct transmission, the data is sent directly from nodes to base station.…”

Section: Introductionmentioning

confidence: 99%

Improved Energy Efficient Wireless Sensor Networks Using Balanced Multi-Hop Routing Protocol

Sivakumar¹,

Parthiban²

2018

IJET

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In this paper, consumption of energy by the sensor nodes in Wireless Sensor Nodes (WSNs) is been handled effectively using a combined technique. The objective of the paper is to increase the network lifetime with dynamic routing protocol. Here, the proposed routing algorithm, named Balanced Multi-Hop (BMH) protocol combines the multi-hop and direct transmission communication. This method further uses Dijkstra algorithm to route the packets between the sensor nodes and base station in mobile network. This method avoids the use of central router to control the other nodes. The results of the proposed method is tested against various result metrics. The evaluation over other existing methods prove that the BMH method achieves higher lifetime and high network throughput.

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“…Furthermore, the node position obtained is not precise enough, leading to a routing failure. Consequently, in existing geographic rutting protocols the high overhead problem and problem of location is also present various methods on GRP [5] - [11] is adopted, however, for the main part of geographical routing (greedy forwarding mode and transmission mode [3]), the void routing problem and network planarization problem [4] [17] [18] occur, resulting in a long path with a higher overhead.…”

Section: Introductionmentioning

confidence: 99%

Optimized Geographic Routing in Mobile Ad Hoc Network Using Gray Wolf Optimization

Vimalnath¹,

Ravi²

2018

EAI Endorsed Transactions on Energy Web

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The geographic routing protocol (GRP) in general seeks the location of sensor nodes to decide the routing path in mobile ad hoc network. This increases the routing overhead while finding the location of nodes. On other hand, the GRP undergoes location inaccuracy and routing void problem. In order to resolve this, in this paper, Gray Wolf Optimization (GWO) is used. This GWO is responsible for proper selection of nodes selected by GRP based on the parameters and selection criteria in order to forward the packets to the next forwarding nodes to reach its destination. The simulation is carried out effectively between the GWO-GRP and existing ACO and fuzzy based GRP with varying network densities. The simulation results show that the GWO-GRP method achieves reduced average delay, increased network lifetime and reduced energy consumption than other methods. Further, it avoids the problems associated with GRP i.e. the location inaccuracy and routing void problem.

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Cross-Layer Greedy position-based routing for multihop wireless sensor networks in a real environment

Cited by 18 publications

References 17 publications

A modified rider optimization algorithm for multihop routing in WSN

A modified rider optimization algorithm for multihop routing in WSN

Improved Energy Efficient Wireless Sensor Networks Using Balanced Multi-Hop Routing Protocol

Optimized Geographic Routing in Mobile Ad Hoc Network Using Gray Wolf Optimization

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