Efficient Heuristic Based on Clustering Approach for OLSR

Choukri, Ali; Habbani, Ahmed; Koutbi, Mohamed El

doi:10.1155/2013/597461

Cited by 10 publications

(4 citation statements)

References 14 publications

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“…However, the evaluations did not consider the case where a mesh-like clustering scheme such as MPR would operate only using road traffic direction. In low-mobility MANETs (up to 10 m/s), the authors of [21] showed that an OLSRbased clustering approach, even with overlapping clusters, can help reduce end-to-end delay and routing traffic overhead. The authors did not conduct any comparison with a backbone-like clustering scheme.…”

Section: Related Workmentioning

confidence: 99%

A Comparison of Backbone and Mesh Clustering Strategies for Collaborative Management of 6G Vehicle-to-Vehicle Exchanges

Devred,

Wahl,

Sondi

2024

Electronics

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Sixth-generation (6G) announcements promise the best performance not only for latency but also for the number of connected objects. These characteristics particularly suit intelligent transport system (ITS) applications involving a large number of moving vehicles with stringent latency constraints. Moreover, in the 6G era, these applications will often operate while relying on direct cooperation and exchanges between vehicles, in addition to centralized services through a telecommunication infrastructure. Therefore, addressing collaborative intelligence for ad hoc routing protocols that ensure efficient management of multihop vehicle-to-vehicle communications is mandatory. Among the numerous organization models proposed in the literature, the chain–branch–leaf (CBL), a virtual backbone-like model, has demonstrated best performance regarding latency against the state-of-the-art approaches. However, its structure, which lacks redundancy, may lead to higher data loss in the case of the failure of one of the relaying branch nodes. This study investigated how the multipoint relay (MPR) technique—which is intrinsically redundant—used in the optimized link state routing (OLSR) protocol can be efficiently adapted to the road traffic context, especially by restricting MPR selection to a single traffic flow direction (TFD-OLSR). The simulation results confirmed that CBL-OLSR obtains the least end-to-end delay for various types of application traffic due to its efficient reduction in the number of relays and the amount of routing traffic. However, despite higher routing traffic, TFD-OLSR improves the delivery rate, especially for more than two-hop communications, thus demonstrating the benefits of its redundancy property.

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Section: Related Workmentioning

confidence: 99%

A Comparison of Backbone and Mesh Clustering Strategies for Collaborative Management of 6G Vehicle-to-Vehicle Exchanges

Devred,

Wahl,

Sondi

2024

Electronics

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“…This is shown in Figure 10 , which shows that the remaining liveliness in this situation is adequate until the death of the final node [ 37 ].…”

Section: Proposed Energy Protocol With Blockchainmentioning

confidence: 99%

Smart Healthcare System with Light-Weighted Blockchain System and Deep Learning Techniques

Singh

Mir

et al. 2022

Computational Intelligence and Neuroscience

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A radio communication sensor system is a collection of sensor modules that are connected to one another through wireless communication. It is common for them to be battery-powered and responsive to a nearby controller, referred to as the base station. They are capable of doing basic computations and transferring information to the base station in most scenarios. They are also in charge of transporting data from distant nodes, putting a burden on nodes with limited resources, and contributing to the quick depletion of energy in these nodes in the process. Nodes in close proximity to the base station are responsible for more than only detecting and sending data to the base station; they are also responsible for transmitting data from faraway nodes. To reward nodes that perform well, a protocol known as the Improved Fuzzy Inspired Energy Effective Protocol (IFIEEP) employs three separate sorts of nodes in order to provide more energy to those who do not. It takes into account the remaining node energy, the node's proximity to the base station, the node's neighbor concentration, and the node's centrality in a cluster when determining node viability. All of these assumptions are founded on a shaky understanding of the situation. Adaptive clustering must be applied to the most viable nodes in order to identify cluster leaders and transmit data to the base station, in addition to disseminating data across the rest of the network, in order to achieve success. In addition, the research provides proper heterogeneity parameters, which describe, among other things, the number of nodes as well as the starting energy of each node. The percentage gain in-network lifetime when compared to current approaches is minor for smaller numbers of supernodes; however, the percentage gain in the area covered 12.89 percent and 100% when more significant numbers of super nodes are used. These improvements in stability, residual energy, and throughput are accomplished by combining these improvements while also taking into consideration the previously neglected energy-intensive sensing energy aspect. The protocol that has been presented is meant to be used in conjunction with applications that make use of blockchain technology.

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“…This approach is proposed to reduce the storage and processing information within a cluster. In the literature we can have several clustering techniques; the K-means clustering technique is among the best methods known [11,12] used in MANETs. This one will allow clusters to be more stable and the center will be better chosen.…”

Section: Problem Formulationmentioning

confidence: 99%

Enhancenig OLSR routing protocol using K-means clustering in MANETs

Hamzaoui

Amnai

Choukri

et al. 2020

IJECE

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The design of robust routing protocol schemes for MANETs is quite complex, due to the characteristics and structural constraints of this network. A numerous variety of protocol schemes have been proposed in literature. Most of them are based on traditional method of routing, which doesn’t guarantee basic levels of Qos, when the network becomes larger, denser and dynamic. To solve this problem we use one of the most popular methods named clustering. In this work we try to improve the Qos in MANETs. We propose an algorithm of clustering based in the new mobility metric and K-Means method to distribute the nodes into several clusters; it is implemented to standard OLSR protocol giving birth a new protocol named OLSR Kmeans-SDE. The simulations showed that the results obtained by OLSR Kmeans-SDE exceed those obtained by standard OLSR Kmeans and OLSR Kmed+ in terms of, traffic Control, delay and packet delivery ratio.

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Efficient Heuristic Based on Clustering Approach for OLSR

Cited by 10 publications

References 14 publications

A Comparison of Backbone and Mesh Clustering Strategies for Collaborative Management of 6G Vehicle-to-Vehicle Exchanges

A Comparison of Backbone and Mesh Clustering Strategies for Collaborative Management of 6G Vehicle-to-Vehicle Exchanges

Smart Healthcare System with Light-Weighted Blockchain System and Deep Learning Techniques

Enhancenig OLSR routing protocol using K-means clustering in MANETs

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