scholarly journals Social-aware routing for cognitive radio–based vehicular ad hoc networks

2019 ◽  
Vol 15 (7) ◽  
pp. 155014771986638 ◽  
Author(s):  
Jing Wang ◽  
Huyin Zhang ◽  
Xing Tang ◽  
Sheng Hao
Keyword(s):  
Cognitive Radio ◽  
Ad Hoc Networks ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Communication Process ◽  
Delivery Ratio ◽  
Packet Delivery ◽  
Routing Schemes ◽  
Hoc Networks ◽  
Overhead Ratio

Cognitive radio–based vehicular ad hoc networks can solve the problem of limited spectrum resource and growing vehicular communication service demands in intelligent transportation systems, and thus, it receives much concern recently. In cognitive radio–based vehicular ad hoc networks, the high mobility of vehicles and the dynamic spectrum activity of cognitive radio make routing in such networks a great challenge. Some routing researches have been proposed in cognitive radio–based vehicular ad hoc networks with single-objective optimization and neglecting the nodes’ social behaviors which can improve the network performance. From this perspective, we propose a social-aware routing scheme for cognitive radio–based vehicular ad hoc networks, with the purpose of increasing the packet delivery ratio and decreasing the overhead ratio. First, we analyze the social centrality of primary users to offer an accuracy spectrum hole measurement. Moreover, we develop a social community partition algorithm to divide secondary users into intra-community and inter-community groups. Furthermore, considering the tradeoff between the packet delivery ratio and the overhead ratio, we adopt different replication policies and forwarding ranks in different community communication processes. In the intra-community communication process, we employ the single-copy policy and the contact duration rank. In the inter-community communication process, we utilize the optimized-binary-tree replication policy and the bridge coefficient rank. Simulation results show that our social-aware routing scheme achieves the higher package delivery ratio and the lower overhead ratio when compared with the existing cognitive radio–based vehicular ad hoc networks routing schemes and other standard routing schemes.

scholarly journals 802.11p Profile Adaptive MAC Protocol for Non-Safety Messages on Vehicular Ad Hoc Networks

2018 ◽  
Vol 12 (1) ◽  
pp. 208
Author(s):  
Shamsul J Elias ◽  
M. Elshaikh ◽  
M. Yusof Darus ◽  
Jamaluddin Jasmis ◽  
Angela Amphawan
Keyword(s):  
Ad Hoc Networks ◽  
Congestion Control ◽  
Data Transmission ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Mac Protocol ◽  
Packet Delivery Ratio ◽  
Delivery Ratio ◽  
Packet Delivery ◽  
Hoc Networks

<p>Vehicular Ad hoc Networks (VANET) play a vital Vehicle to Infrastructure (V2I) correspondence frameworks where vehicle are convey by communicating and conveying data transmitted among each other. Because of both high versatility and high unique network topology, congestion control should be executed distributedly. Optimizing the congestion control in term of delay rate, packet delivery ratio (PDR) and throughput could limit the activity of data packet transmissions. These have not been examined altogether so far – but rather this characteristic will be fundamental for VANET system execution and network system performance. This paper exhibits a novel strategy for congestion control and data transmission through Service Control Channel (SCH) in VANET. The Taguchi strategy has been connected in getting the optimize value of parameter for congstion control in highway environment. This idea lessens the pointless activity of data transmission and decreases the likelihood of congested in traffic in view of execution for measuring the delay rate, packet delivery ratio (PDR) and throughput. The proposed execution performance is estimated with the typical VANET environment in V2I topology in highway driving conditions and the simulation results demonstrate and enhance network execution performance with effective data transmission capacity.</p>

Research of Improvement of GPSR Protocol in Vehicular Ad Hoc Networks

2015 ◽  
Vol 738-739 ◽  
pp. 1115-1118
Author(s):  
Li Cui Zhang ◽  
Xiao Nan Zhu ◽  
Zhi Gang Wang ◽  
Guang Hui Han
Keyword(s):  
Ad Hoc Networks ◽  
Routing Protocol ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Packet Delivery Ratio ◽  
Data Packet ◽  
Delivery Ratio ◽  
Packet Delivery ◽  
End To End Delay ◽  
Hoc Networks

Considering the shortcoming of the traditional Greedy Perimeter Stateless Routing Protocol in the Vehicular Ad hoc Networks ,this paper focuses on an improved GPSR protocol based on the density of vehicle flow .This new scheme includes macro-directing algorithm , micro-forwarding strategy and the maintenance of the neighbor list.The simulation result shows that compared with the traditional GPSR protocol, the new GPSR protocol improves data packet delivery ratio, but its average end-to-end delay is slightly larger than before.

Middle-Order Vehicle-Based Clustering Model for Reducing Packet Loss in Vehicular Ad-hoc Networks

2020 ◽  
Vol 29 (11) ◽  
pp. 2050180
Author(s):  
S. David ◽  
P. T. Vanathi
Keyword(s):  
Ad Hoc Networks ◽  
Packet Loss ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Packet Delivery Ratio ◽  
Frequency Variation ◽  
Delivery Ratio ◽  
Packet Delivery ◽  
Clustering Model ◽  
Hoc Networks

Vehicular Ad-hoc NETworks (VANETs) are typically termed as a wireless ad-hoc network that contains extreme node mobility and also the network carries a great significance in various traffic-oriented commercial applications and safety services. Due to its high mobility, routing in VANET has been a challenging work and also proving a higher rate of packet delivery ratio with reduced packet loss has been more important to be considered in route formations. With that note, this paper contributes to developing a clustering model called Middle-Order Vehicle-based Clustering (MOVC) model for managing the frequent topological change and high vehicle mobility, and efficiently handling the typical road traffic scenario. Moreover, the algorithm is intended to maintain the cluster to be constant for managing the vehicles in effective ways and also to provide uninterrupted communication between the vehicles. An algorithm for Effective Cluster Head Election (ECHE) is also derived in this paper for proficiently handling the frequency variation on the highways. Further, the model is simulated and evaluated on the basis of various metrics of VANET routing, specifically packet loss, packet delivery ratio, network lifetime and throughput. The results show that the proposed mechanism outperforms the results of existing models.

scholarly journals A Bipolar Traffic Density Awareness Routing Protocol for Vehicular Ad Hoc Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
David Chunhu Li ◽  
Li-Der Chou ◽  
Li-Ming Tseng ◽  
Yi-Ming Chen ◽  
Kai-Wei Kuo
Keyword(s):  
Ad Hoc Networks ◽  
Routing Protocol ◽  
Routing Protocols ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Path Selection ◽  
Traffic Density ◽  
Delivery Ratio ◽  
Packet Delivery ◽  
Hoc Networks

To support an increasing amount of various new applications in vehicular ad hoc networks (VANETs), routing protocol design has become an important research challenge. In this paper, we propose a Bipolar Traffic Density Awareness Routing (BTDAR) protocol for vehicular ad hoc networks. The BTDAR aims at providing reliable and efficient packets delivery for dense and sparse vehicle traffic network environments. Two distinct routing protocols are designed to find an optimal packet delivery path in varied vehicular networks. In dense networks, a link-stability based routing protocol is designed to take vehicles connectivity into consideration in its path selection policy and maximize the stability of intervehicle communications. In sparse networks, a min-delay based routing protocol is proposed to select an optimal route by analyzing intermittent vehicle connectivity and minimize packets delivery latency. Intervehicles connectivity model is analyzed. The performance of BTDAR is examined by comparisons with three distinct VANET routing protocols. Simulation results show that the BTDAR outperforms compared counterpart routing protocols in terms of packet delivery delay and packet delivery ratio.

scholarly journals NDN-CRAHNs: Named Data Networking for Cognitive Radio Ad Hoc Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Rana Asif Rehman ◽  
Jong Kim ◽  
Byung-Seo Kim
Keyword(s):  
Cognitive Radio ◽  
Ad Hoc Networks ◽  
Ad Hoc ◽  
Future Internet ◽  
Delivery Ratio ◽  
Named Data Networking ◽  
Packet Delivery ◽  
End To End ◽  
Hoc Networks ◽  
Data Networking

Named data networking (NDN) is a newly proposed paradigm for future Internet, in which communication among nodes is based on data names, decoupling from their locations. In dynamic and self-organized cognitive radio ad hoc networks (CRAHNs), it is difficult to maintain end-to-end connectivity between ad hoc nodes especially in the presence of licensed users and intermittent wireless channels. Moreover, IP-based CRAHNs have several issues like scalability, inefficient-mapping, poor resource utilization, and location dependence. By leveraging the advantages of NDN, in this paper, we propose a new cross layer fine-grained architecture called named data networking for cognitive radio ad hoc networks (NDN-CRAHNs). The proposed architecture provides distinct features such as in-networking caching, security, scalability, and multipath routing. The performances of the proposed scheme are evaluated comparing to IP-based scheme in terms of average end-to-end delay and packet delivery ratio. Simulation results show that the proposed scheme is effective in terms of average contents download time and packet delivery ratios comparing to conventional cognitive radio ad hoc networks.

Performance Analysis of TCP Variants using AODV and DSDV Routing Protocols in MANETs

2019 ◽  
Vol 13 ◽  
Author(s):  
Rajnesh Singh ◽  
Neeta Singh ◽  
Aarti Gautam Dinker
Keyword(s):  
Ad Hoc Networks ◽  
Routing Protocols ◽  
Ad Hoc ◽  
Packet Delivery Ratio ◽  
Transport Layer ◽  
Destination Node ◽  
Delivery Ratio ◽  
Packet Delivery ◽  
Two Measures ◽  
Hoc Networks

TCP is the most reliable transport layer protocol that provides reliable data delivery from source to destination node. TCP works well in wired networks but it is assumed that TCP is less preferred for ad-hoc networks. However, for application in ad-hoc networks, TCP can be modified to improve its performance. Various researchers have proposed improvised variants of TCP by only one or two measures. These one or two measures do not seem to be sufficient for proper analysis of improvised version of TCP. So, in this paper, the performance of different TCP versions is investigated with DSDV and AODV routing Protocols. We analyzed various performance measures such as throughput, delay, packet drop, packet delivery ratio and number of acknowledgements. The simulation results are carried out by varying number of nodes in network simulator tool NS2. It is observed that TCP Newreno achieved higher throughput and packet delivery ratio with both AODV and DSDV routing protocols.Whereas TCP Vegas achieved minimum delay and packet loss with both DSDV and AODV protocol. However TCP sack achieved minimum acknowledgment with both AODV and DSDV routing protocols. In this paper the comparison of all these TCP variants shows that TCP Newreno provides better performance with both AODV and DSDV protocols.

Artificial Intelligence Based Intrusion Detection System to Detect Flooding Attack in VANETs

2018 ◽  
pp. 87-100 ◽  
Author(s):  
Mannat Jot Singh Aneja ◽  
Tarunpreet Bhatia ◽  
Gaurav Sharma ◽  
Gulshan Shrivastava
Keyword(s):  
Intrusion Detection ◽  
Ad Hoc Networks ◽  
Intrusion Detection System ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Performance Metrics ◽  
Detection System ◽  
Delivery Ratio ◽  
Flooding Attack ◽  
Hoc Networks

This chapter describes how Vehicular Ad hoc Networks (VANETs) are classes of ad hoc networks that provides communication among various vehicles and roadside units. VANETs being decentralized are susceptible to many security attacks. A flooding attack is one of the major security threats to the VANET environment. This chapter proposes a hybrid Intrusion Detection System which improves accuracy and other performance metrics using Artificial Neural Networks as a classification engine and a genetic algorithm as an optimization engine for feature subset selection. These performance metrics have been calculated in two scenarios, namely misuse and anomaly. Various performance metrics are calculated and compared with other researchers' work. The results obtained indicate a high accuracy and precision and negligible false alarm rate. These performance metrics are used to evaluate the intrusion system and compare with other existing algorithms. The classifier works well for multiple malicious nodes. Apart from machine learning techniques, the effect of the network parameters like throughput and packet delivery ratio is observed.

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