Efficient and Reliable Cluster-Based Data Transmission for Vehicular Ad Hoc Networks
TL;DR: A link reliability-based clustering algorithm (LRCA) to provide efficient and reliable data transmission in VANETs and a routing protocol of LRCA to serve the infotainment applications in VIANET is proposed.
Abstract: Vehicular ad hoc network (VANET) is an emerging technology for the future intelligent transportation systems (ITSs). The current researches are intensely focusing on the problems of routing protocol reliability and scalability across the urban VANETs. Vehicle clustering is testified to be a promising approach to improve routing reliability and scalability by grouping vehicles together to serve as the foundation for ITS applications. However, some prominent characteristics, like high mobility and uneven spatial distribution of vehicles, may affect the clustering performance. Therefore, how to establish and maintain stable clusters has become a challenging problem in VANETs. This paper proposes a link reliability-based clustering algorithm (LRCA) to provide efficient and reliable data transmission in VANETs. Before clustering, a novel link lifetime-based (LLT-based) neighbor sampling strategy is put forward to filter out the redundant unstable neighbors. The proposed clustering scheme mainly composes of three parts: cluster head selection, cluster formation, and cluster maintenance. Furthermore, we propose a routing protocol of LRCA to serve the infotainment applications in VANET. To make routing decisions appropriate, we nominate special nodes at intersections to evaluate the network condition by assigning weights to the road segments. Routes with the lowest weights are then selected as the optimal data forwarding paths. We evaluate clustering stability and routing performance of the proposed approach by comparing with some existing schemes. The extensive simulation results show that our approach outperforms in both cluster stability and data transmission.
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TL;DR: A fuzzy cluster head selection scheme in Cognitive Radio (CR) VANET, which uses the CR technology for the spectrum sensing algorithm, provides stability and reliability to the cluster compared to the state of art techniques.
Abstract: The Vehicular Ad Hoc Network (VANET) plays a vital role in the development of smart cities, especially in ensuring vehicles' safety on roads. However, VANET wireless-based networks face some challenges such as security, stability, communication, and reliability. To resolve these issues, we propose a fuzzy cluster head selection scheme in Cognitive Radio (CR) VANET, which uses the CR technology for the spectrum sensing algorithm. In this technology, the free spectrums of the primary user are utilized by secondary users without any correlation. Moreover, we have considered some input parameters such as vehicles' average velocity, distance, network connectivity level, lane weight and trustworthiness for the fuzzy system based CR VANET in this research. The selected cluster head provides stability and reliability to the cluster compared to the state of art techniques. Extensive experiments were conducted in order to evaluate the effectiveness of the proposed approach. However, simulation results authenticate more stable and secure cluster formation using the proposed fuzzy logic based CR VANET.
27 citations
Additional excerpts
...The LRCA process contains cluster head selection, cluster formation, and cluster maintenance [9]....
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TL;DR: An optimization algorithm named Vehicular Genetic Bee Clustering (VGBC) based on honey bee algorithm and properties of genetic algorithm solves the CP in VANETs is suggested and it outperform existing schemes in terms of cluster count, cluster duration, re-affiliation rate, computational overhead, load balancing, VANet lifetime and clustering overhead.
Abstract: In vehicular ad hoc network (VANET), the size of routing table can be reduced with the help of clustering architecture. The frequent changes in topology are the noteworthy characteristics of a VANET as its nature is dynamic. To manage the topology dynamics in VANET with less overhead, the concept of clustering can be used. Henceforth, an effective procedure that adjusts quickly to the topology changes should be designed. Firstly, the clustering problem (CP) in VANET is formulated into a dynamic optimization problem in this paper. Secondly, an optimization algorithm named Vehicular Genetic Bee Clustering (VGBC) based on honey bee algorithm and properties of genetic algorithm solves the CP in VANETs is suggested. In VGBC, individuals (bees) represent a realistic clustering structure and its fitness is measured on the basis of load balancing and stability. A technique that merges the properties of genetic algorithm and honey bee algorithm is proposed. It helps the population to handle the topology changes and harvest high quality solutions. The simulation results piloted for justification demonstrate that the VGBC form steady and balanced clusters. The simulation results are matched with state of the art clustering schemes in VANET. The VGBC outperform existing schemes in terms of cluster count, cluster duration, re-affiliation rate, computational overhead, load balancing, VANET lifetime and clustering overhead.
21 citations
TL;DR: An ad hoc TROPHY (TAD-HOC) routing protocol for the VANET network for increasing efficiency and effective resource utilization of the network and comparative analysis of the proposed approach shows that the proposed TAD- HOC exhibited effective performance.
Abstract: Intelligent Transportation System (ITS) is a critical factor for Vehicular Ad hoc Networks (VANET). Even though VANET belongs to the class of Mobile Ad hoc Network (MANET), none of the MANET routing protocol applies to VANET. VANET network is dynamic, due to increased vehicle speed and mobility. Vehicle mobility of VANET affects conventional routing algorithm performance, which deals with the dynamicity of the network node. The evaluation of the existing research stated that Ad hoc On-Demand Distance Vector (AODV) is an effective MANET protocol to adopt network changes for significant resource utilization and also provides effective adaptation in the network change. Due to the effective performance of the AODV protocol, it is considered as an effective routing protocol for VANET. This paper proposed an ad hoc TROPHY (TAD-HOC) routing protocol for the VANET network for increasing efficiency and effective resource utilization of the network. To improve the overall performance, ad hoc network is combined with Trustworthy VANET ROuting with grouP autHentication keYs (TROPHY) protocol. The proposed TAD-HOC protocol transmits data based on time demand in the VANET network with the desired authentication. Results of the proposed approach show the increased performance of the VANET network with packet delay, transmission range, and end-to-end delay. The comparative analysis of the proposed approach with I-AODV, AODV-R, and AODV-L shows that the proposed TAD-HOC exhibited effective performance.
20 citations
Cites background from "Efficient and Reliable Cluster-Base..."
...For effective performance, message authentication is speeding up through high priority emergency messages or small area communication [21, 22]....
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...Refreshment update r(t) along with auxiliary information processes asymmetric cryptography in the network [21]....
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TL;DR: The proposed scheme is tested on the real map of Chengdu, southwestern China’s Sichuan province, with different vehicular mobilities and shows significant improvement in the cluster head stability during high vehicular density.
Abstract: VANET is the spontaneous evolving creation of a wireless network, and clustering in these networks is a challenging task due to rapidly changing topology and frequent disconnection in networks. The cluster head (CH) stability plays a prominent role in robustness and scalability in the network. The stable CH ensures minimum intra- and intercluster communication, thereby reducing the overhead. These challenges lead the authors to search for a CH selection method based on a weighted amalgamation of four metrics: befit factor, community neighborhood, eccentricity, and trust. The stability of CH depends on the vehicle’s speed, distance, velocity, and change in acceleration. These all are included in the befit factor. Also, the accurate location of the vehicle in changing the model is very vital. Thus, the predicted location with the Kalman filter’s help is used to evaluate CH stability. The results have shown better performance than the existing state of the art for the befit factor. The change in dynamics and frequent disconnection in communication links due to the vehicle’s high speed are inevitable. To comprehend this problem, a graphing approach is used to evaluate the eccentricity and the community neighborhood. The link reliability is calculated using the eigengap heuristic. The last metric is trust; this is one of the concepts that has not been included in the weighted approach to date as per the literature. An adaptive spectrum sensing is designed for evaluating the trust values specifically for the primary users. A deep recurrent learning network, commonly known as long short-term memory (LSTM), is trained for the probability of detection with various signals and noise conditions. The false rate has drastically reduced with the usage of LSTM. The proposed scheme is tested on the real map of Chengdu, southwestern China’s Sichuan province, with different vehicular mobilities. The comparative study with the individual and weighted metric has shown significant improvement in the cluster head stability during high vehicular density. Also, there is a considerable increase in network performance in energy, packet delay, packet delay ratio, and throughput.
18 citations
TL;DR: The experimental results demonstrate that both the variants of EES-WCA are useful and classify seven different kinds of patterns, and the performance of network quality of services such as packet delivery rate, throughput, end to end delay, and energy consumption confirm the superiority of the EES -WCA algorithm.
Abstract: The Wireless Sensor Network (WSN) is an application-centric network, where the data is collected using sensor nodes and communicated to the server or base station to process raw data and to obtain the decisions. For this, it is essential to maintain efficiency and security to serve critical applications. To deal with this requirement, most of the existing techniques modify the routing techniques to secure the network from one or two attacks, but there are significantly fewer solutions that can face multiple kinds of attacks. Therefore, this paper proposed a data-driven and machine learning-based Energy Efficient and Secure Weighted Clustering Algorithm (EES-WCA). The EES-WCA is a combination of EE-WCA and machine learning-based centralized Intrusion detection system (IDS). This technique first creates network clusters, then, without disturbing the WSN routine activity, collect traffic samples on the base station. The base station consists of two machine learning models: Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) to classify the traffic data and identify the malicious nodes in the network. This technique is validated through the generated traffic from the NS2.35 simulator and is also examined in real-time scenarios. The experimental results demonstrate that both the variants of EES-WCA are useful and classify seven different kinds of patterns. According to the simulation results on validation test data, we found up to 90% detection accuracy. Additionally, in real-time scenarios, it replicates the performance by approximately 75%. The performance of EES-WCA in terms of network quality of services such as packet delivery rate, throughput, end to end delay, and energy consumption confirm the superiority of the EES-WCA algorithm.
17 citations
References
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TL;DR: This paper describes a self-organizing, multihop, mobile radio network which relies on a code-division access scheme for multimedia support that provides an efficient, stable infrastructure for the integration of different types of traffic in a dynamic radio network.
Abstract: This paper describes a self-organizing, multihop, mobile radio network which relies on a code-division access scheme for multimedia support. In the proposed network architecture, nodes are organized into nonoverlapping clusters. The clusters are independently controlled, and are dynamically reconfigured as the nodes move. This network architecture has three main advantages. First, it provides spatial reuse of the bandwidth due to node clustering. Second, bandwidth can be shared or reserved in a controlled fashion in each cluster. Finally, the cluster algorithm is robust in the face of topological changes caused by node motion, node failure, and node insertion/removal. Simulation shows that this architecture provides an efficient, stable infrastructure for the integration of different types of traffic in a dynamic radio network.
1,695 citations
16 Apr 2001
TL;DR: A distributed clustering algorithm, MOBIC, is proposed based on the use of this mobility metric for selection of clusterheads, and it is demonstrated that it leads to more stable cluster formation than the "least clusterhead change" version of the well known Lowest-ID clustering algorithms.
Abstract: We present a novel relative mobility metric for mobile ad hoc networks (MANETs). It is based on the ratio of power levels due to successive receptions at each node from its neighbors. We propose a distributed clustering algorithm, MOBIC, based on the use of this mobility metric for selection of clusterheads, and demonstrate that it leads to more stable cluster formation than the "least clusterhead change" version of the well known Lowest-ID clustering algorithm (Chiang et al., 1997). We show reduction of as much as 33% in the rate of clusterhead changes owing to the use of the proposed technique. In a MANET that uses scalable cluster-based services, network performance metrics such as throughput and delay are tightly coupled with the frequency of cluster reorganization. Therefore, we believe that using MOBIC can result in a more stable configuration, and thus yield better performance.
680 citations
"Efficient and Reliable Cluster-Base..." refers methods in this paper
...*e originally notable clustering algorithms were designed for mobile ad hoc networks (MANETs) [4], such as the popular lowest identifier (LID) [5] and Mobility Clustering (MOBIC) [6]....
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Book•
01 Oct 1991
TL;DR: This book systematically introduces important special functions and explores their salient properties and is suitable as a classroom textbook in courses dealing with higher mathematical functions or as a reference text for practicing engineers and scientists.
Abstract: This book systematically introduces important special functions and explores their salient properties. Suitable as a classroom textbook in courses dealing with higher mathematical functions or as a reference text for practicing engineers and scientists.
597 citations
"Efficient and Reliable Cluster-Base..." refers methods in this paper
...⎧⎪ ⎨ ⎪ ⎩ (5) By using the Gauss error function Erf [38], the integral in (5) can be obtained as follows: rt lij �Erf ((2R)/t)−μΔvij σΔvij � 2 √⎛⎝ ⎞⎠ −Erf ((2R)/(t + LLT))−μΔvij σΔvij � 2 √⎛⎝ ⎞⎠, when LLT>0....
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...(6) *e Erf function is calculated as follows: Erf(x) � 2 � π √ x 0 e −η2 dη, −∞ x +∞....
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...By using the Gauss error function Erf [38], the integral in (5) can be obtained as follows:...
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TL;DR: This paper proposes a hybrid architecture, namely, VMaSC-LTE, combining IEEE 802.11p-based multihop clustering and the fourth-generation (4G) cellular system, i.e., Long-Term Evolution (LTE), with the goal of achieving a high data packet delivery ratio (DPDR) and low delay while keeping the usage of the cellular architecture at a minimum level.
Abstract: Several vehicular ad hoc network (VANET) studies have focused on communication methods based on IEEE 802.11p, which forms the standard for wireless access for vehicular environments. In networks employing IEEE 802.11p only, the broadcast storm and disconnected network problems at high and low vehicle densities, respectively, degrade the delay and delivery ratio of safety message dissemination. Recently, as an alternative to the IEEE 802.11p-based VANET, the usage of cellular technologies has been investigated due to their low latency and wide-range communication. However, a pure cellular-based VANET communication is not feasible due to the high cost of communication between the vehicles and the base stations and the high number of handoff occurrences at the base station, considering the high mobility of the vehicles. This paper proposes a hybrid architecture, namely, VMaSC–LTE, combining IEEE 802.11p-based multihop clustering and the fourth-generation (4G) cellular system, i.e., Long-Term Evolution (LTE), with the goal of achieving a high data packet delivery ratio (DPDR) and low delay while keeping the usage of the cellular architecture at a minimum level. In VMaSC–LTE, vehicles are clustered based on a novel approach named Vehicular Multihop algorithm for Stable Clustering (VMaSC). The features of VMaSC are cluster head (CH) selection using the relative mobility metric calculated as the average relative speed with respect to the neighboring vehicles, cluster connection with minimum overhead by introducing a direct connection to the neighbor that is already a head or a member of a cluster instead of connecting to the CH in multiple hops, disseminating cluster member information within periodic hello packets, reactive clustering to maintain the cluster structure without excessive consumption of network resources, and efficient size- and hop-limited cluster merging mechanism based on the exchange of cluster information among CHs. These features decrease the number of CHs while increasing their stability, therefore minimizing the usage of the cellular architecture. From the clustered topology, elected CHs operate as dual-interface nodes with the functionality of the IEEE 802.11p and LTE interface to link the VANET to the LTE network. Using various key metrics of interest, including DPDR, delay, control overhead, and clustering stability, we demonstrate the superior performance of the proposed architecture compared with both previously proposed hybrid architectures and alternative routing mechanisms, including flooding and cluster-based routing via extensive simulations in ns-3 with the vehicle mobility input from the Simulation of Urban Mobility. The proposed architecture also allows achieving higher required reliability of the application quantified by the DPDR at the cost of higher LTE usage measured by the number of CHs in the network.
401 citations
TL;DR: This paper explores the design choices made in the development of clustering algorithms targeted at VANETs and presents a taxonomy of the techniques applied to solve the problems of cluster head election, cluster affiliation, and cluster management, and identifies new directions and recent trends in the design of these algorithms.
Abstract: A vehicular ad hoc network (VANET) is a mobile ad hoc network in which network nodes are vehicles—most commonly road vehicles. VANETs present a unique range of challenges and opportunities for routing protocols due to the semi-organized nature of vehicular movements subject to the constraints of road geometry and rules, and the obstacles which limit physical connectivity in urban environments. In particular, the problems of routing protocol reliability and scalability across large urban VANETs are currently the subject of intense research. Clustering can be used to improve routing scalability and reliability in VANETs, as it results in the distributed formation of hierarchical network structures by grouping vehicles together based on correlated spatial distribution and relative velocity. In addition to the benefits to routing, these groups can serve as the foundation for accident or congestion detection, information dissemination and entertainment applications. This paper explores the design choices made in the development of clustering algorithms targeted at VANETs. It presents a taxonomy of the techniques applied to solve the problems of cluster head election, cluster affiliation, and cluster management, and identifies new directions and recent trends in the design of these algorithms. Additionally, methodologies for validating clustering performance are reviewed, and a key shortcoming—the lack of realistic vehicular channel modeling—is identified. The importance of a rigorous and standardized performance evaluation regime utilizing realistic vehicular channel models is demonstrated.
379 citations