Cluster Connectivity Assurance Metrics in Vehicular ad hoc Networks

Aissa, Mohamed; Belghith, Abdelfettah; Bouhdid, Badia

doi:10.1016/j.procs.2015.05.088

Cited by 17 publications

(7 citation statements)

References 11 publications

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“…Realizing the promising future of smart vehicles, various vehicle clustering algorithms have been proposed to harness its potential in the areas of vehicular routing or vehicle resources. Nonetheless, the existing research efforts focus on creating stable clusters of mobile vehicles [7], [34]- [38]. The authors in [27] propose the idea of ParkCast that leverages roadside parking to distribute contents in urban Vehicular Ad-hoc Networks (VANETs).…”

Section: Background Studymentioning

confidence: 99%

Off-Street Vehicular Fog for Catering Applications in 5G/B5G: A Trust-Based Task Mapping Solution and Open Research Issues

Rahman

Newaz

et al. 2020

IEEE Access

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One of the key enablers in serving the applications requiring stringent latency in 5G networks is fog computing as it is situated closer to the end users. With the technological advancement of vehicles' on-board units, their computing capabilities are becoming robust, and considering the underutilization of the off-street vehicles, we envision that the off-street vehicles can be an enormously useful computational source for the fog computing. Additionally, clustering the vehicles would be advantageous in order to improve the service availability. As the vehicles become highly connected, trust is needed especially in distributed environments. However, vehicles are made from different manufacturers, and have different platforms, security mechanisms, and varying parking duration. These lead to the unpredictable behavior of the vehicles where quantifying trust value of vehicles would be difficult. A trust-based solution is necessary for task mapping as a task has a set of properties including expected time to complete, and trust requirements that need to be met. However, the existing metrics used for trust evaluation in the vehicular fog computing such as velocity and direction are not applicable in the off-street vehicle fog environments. In this paper, we propose a framework for quantifying the trust value of off-street vehicle fog computing facilities in 5G networks and forming logical clusters of vehicles based on the trust values. This allows tasks to be shared with multiple vehicles in the same cluster that meets the tasks' trust requirements. Further, we propose a novel task mapping algorithm to increase the vehicle resource utilization and meet the desired trust requirements while maintaining imposed latency requirements of 5G applications. Results obtained using iFogSim simulator demonstrate that the proposed solution increases vehicle resource utilization and reduces task drop noticeably. This paper presents open research issues pertaining to the study to lead the way for future research directions.

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Section: Background Studymentioning

confidence: 99%

Off-Street Vehicular Fog for Catering Applications in 5G/B5G: A Trust-Based Task Mapping Solution and Open Research Issues

Rahman

Newaz

et al. 2020

IEEE Access

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“…However, if the number of nodes was less than the specific threshold, it must reformat the cluster and this made the cluster unstable. In [5] the author proposed that vehicles with low average velocity, same direction and low distance to their neighbours were elected as CH . In previous work [6] the author proposed dividing the area into static cluster and CH.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Load Balance Algorithm for Vehicular Ad-Hoc Network

Abbas

Audah

Alduais

2018

2018 Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS)

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clustering technique divided vehicles into groups; the admin of the group was called the cluster-head (CH) and other vehicles in same transmission range was known as the cluster-member (CM). The admin was responsible for the inter and intra cluster communications. Inter-cluster refers to the communication between CM and another CM in the same cluster. While intra-cluster refers to the communication between CM with another CM in a different cluster. The clustering techniques was chosen in order to solve the issues mentioned above. However, high vehicles mobility causes high network topology change of (VANETs). This problem made the cluster unstable and this caused network load, interconnect, overhead, collision, packet loss, packet drop and handoff. To solve these problems, the authors used a different method to elect CH based on different parameters. Because when CH still long time of period, the stability of network would increase and the above problems would reduce. This paper presents a novel method of intelligent cluster head election (ICHE) to form a cluster with more stability and reduce the number of uplink connection by reducing the number of CH in the networks. The reduced number of CH resulted the reduce of load at the base station (BS).

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“…These MAC-based approaches use IEEE 802.11 MAC protocol [24] for the formulation of clusters [21]. A traditional clustering algorithm is sub-divided into active-based [25] and passive-based clustering [26], [27]. In active-based, a clustering mechanism continuously updates the routing record of a cluster.…”

Section: Introductionmentioning

confidence: 99%

StabTrust—A Stable and Centralized Trust-Based Clustering Mechanism for IoT Enabled Vehicular Ad-Hoc Networks

et al. 2020

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Vehicular Ad-hoc Network (VANET) is a modern era of dynamic information distribution among societies. VANET provides an extensive diversity of applications in various domains, such as Intelligent Transport System (ITS) and other road safety applications. VANET supports direct communications between vehicles and infrastructure. These direct communications cause bandwidth problems, high power consumption, and other similar issues. To overcome these challenges, clustering methods have been proposed to limit the communication of vehicles with the infrastructure. In clustering, vehicles are grouped together to formulate a cluster based on certain rules. Every cluster consists of a limited number of vehicles/nodes and a cluster head (CH). However, the significant challenge for clustering is to preserve the stability of clusters. Furthermore, a secure mechanism is required to recognize malicious and compromised nodes to overcome the risk of invalid information sharing. In the proposed approach, we address these challenges using components of trust. A trust-based clustering mechanism allows clusters to determine a trustworthy CH. The novel features incorporated in the proposed algorithm includes trust-based CH selection that comprises of knowledge, reputation, and experience of a node. Also, a backup head is determined by analyzing the trust of every node in a cluster. The major significance of using trust in clustering is the identification of malicious and compromised nodes. The recognition of these nodes helps to eliminate the risk of invalid information. We have also evaluated the proposed mechanism with the existing approaches and the results illustrate that the mechanism is able to provide security and improve the stability by increasing the lifetime of CHs and by decreasing the computation overhead of the CH re-selection. The StabTrust also successfully identifies malicious and compromised vehicles and provides robust security against several potential attacks. INDEX TERMS Intelligent transport system, security, vehicular ad-hoc networks, trust-based clustering, VANET attacks.

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Cluster Connectivity Assurance Metrics in Vehicular ad hoc Networks

Cited by 17 publications

References 11 publications

Off-Street Vehicular Fog for Catering Applications in 5G/B5G: A Trust-Based Task Mapping Solution and Open Research Issues

Off-Street Vehicular Fog for Catering Applications in 5G/B5G: A Trust-Based Task Mapping Solution and Open Research Issues

An Efficient Load Balance Algorithm for Vehicular Ad-Hoc Network

StabTrust—A Stable and Centralized Trust-Based Clustering Mechanism for IoT Enabled Vehicular Ad-Hoc Networks

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