A framework for the evaluation of routing protocols in opportunistic networks

Akestoridis, Dimitrios-Georgios; Papapetrou, Evangelos

doi:10.1016/j.comcom.2019.06.003

Cited by 11 publications

(2 citation statements)

References 45 publications

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“…Based on the historical interaction information between nodes and the recommendation information of trusted neighbour nodes, a trust evaluation model is established to analyze and judge the trusted status of nodes timely and accurately [15], [16]. Selfish nodes can be refused to participate in the process of message forwarding, and cooperative relations with low-trust nodes in the network are avoided to ensure safe and reliable communication between nodes.…”

Section: ) Trust Model and Security Measurementmentioning

confidence: 99%

A Wireless Mesh Opportunistic Network Routing Algorithm Based on Trust Relationships

Zhao

Srivastava

2022

IEEE Access

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To solve the problem of low message delivery rate and high network resource consumption when forwarding messages in opportunistic networks, an opportunistic routing algorithm based on trust relationships for wireless mesh networks is proposed. Firstly, the wireless mesh network is analyzed and the opportunistic routing model is constructed; By analyzing the security mechanism and security threat of communication entities, then measuring the trust degree of links and nodes, establishing the trust relationship between nodes, and defining and quantifying a new security measurement method based on the trust model; Finally, according to the security measurement method defined by the model, select the node with high trust value to participate in the message forwarding process. At the same time, give priority to the node with greater trust with the destination node as the relay node, and allocate the message copy according to the trust degree to make the message pass along the direction of increasing trust, to complete the design of opportunistic routing algorithm in wireless mesh networks. Experimental results show that the routing algorithm can effectively improve the message delivery rate, up to about 95%, and reduce the consumption of network resources.

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Section: ) Trust Model and Security Measurementmentioning

confidence: 99%

A Wireless Mesh Opportunistic Network Routing Algorithm Based on Trust Relationships

Zhao

Srivastava

2022

IEEE Access

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“…Although with the notice of such impacts, researchers mainly focus on designing mechanisms to deal with weak links [8][9][10][11] and propose evaluation model for wireless multi-hop network. 12 The power control method, 13 artificial intelligence (AI)-based link quality prediction, 14,15 softwaredefined networking (SDN) 16 architecture, and multichannel mechanism 17 are applied to deal with the weak link problems and good results have been achieved. However, the innate characters and how the weak links affect the topology discovery are seldom researched.…”

Section: Topology Updatementioning

confidence: 99%

The impacts of weak links on topology discovery process in large-scale wireless multi-hop networks

Wenxing

Shi

Chen

2020

International Journal of Distributed Sensor Networks

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In wireless multi-hop networks, especially large-scale wireless multi-hop networks, obtaining the network topology is of vital significance. In fact, in both proactive and reactive routing protocols, before establishing an appropriate end-to-end route, the source node needs to obtain the global or local topology. Our previous research has studied the impacts of weak links on reactive routing protocols, which can also be considered as local topology discovery process. In this article, in order to get insight of the impacts of weak links on topology discovery process, especially the global topology discovery on which the proactive routing protocols rely, we apply a Markov chain to model the most common used topology discovery process in large-scale wireless multi-hop networks. Considering the fading characteristics of wireless channel, we analyze the impacts of weak links on topology discovery algorithms. Simulation and theoretical results show that, with the increase in the network scale, the weak links have great impacts on the stability and even on the feasibility of wireless multi-hop networks.

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A Probabilistic Routing Algorithm Based on CNN and Q‐Learning for Vehicular Edge Network

Ma,

You,

et al. 2024

Trans Emerging Tel Tech

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Vehicular edge networks represent a novel architecture that utilizes vehicles as mobile edge nodes, characterized by high‐speed dynamic changes. To effectively transmit data in vehicular edge networks, opportunistic routing methods can be employed, selecting suitable relay nodes based on encounter opportunities between nodes. Although existing opportunistic routing algorithms primarily select the optimal transmission path based on the encounter characteristics between nodes, the dynamism of network topology, the uncertainty of node mobility, and the heterogeneity between nodes still pose significant challenges to the implementation of opportunistic routing. In response to this, we propose a probabilistic routing algorithm based on Convolutional Neural Networks (CNN) and Q‐learning, named PRCQ. This algorithm predicts node state transition probabilities using decomposed latent node features and dynamically adjusts optimal routing strategies using Q‐learning. Extensive simulations were conducted on the NS‐2.35 simulator based on two different city scenarios to evaluate the performance of the PRCQ algorithm compared to other existing algorithms. The results indicate that, compared with other existing opportunistic routing algorithms, PRCQ exhibits superior performance in terms of average transmission delay and packet delivery ratio.

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A framework for the evaluation of routing protocols in opportunistic networks

Cited by 11 publications

References 45 publications

A Wireless Mesh Opportunistic Network Routing Algorithm Based on Trust Relationships

A Wireless Mesh Opportunistic Network Routing Algorithm Based on Trust Relationships

The impacts of weak links on topology discovery process in large-scale wireless multi-hop networks

A Probabilistic Routing Algorithm Based on CNN and Q‐Learning for Vehicular Edge Network

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