An Efficient Framework Model for Optimizing Routing Performance in VANETs

Abstract

Routing in Vehicular Ad hoc Networks (VANET) is a bit complicated because of the nature of the high dynamic mobility. The efficiency of routing protocol is influenced by a number of factors such as network density, bandwidth constraints, traffic load, and mobility patterns resulting in frequency changes in network topology. Therefore, Quality of Service (QoS) is strongly needed to enhance the capability of the routing protocol and improve the overall network performance. In this paper, we introduce a statistical framework model to address the problem of optimizing routing configuration parameters in Vehicle-to-Vehicle (V2V) communication. Our framework solution is based on the utilization of the network resources to further reflect the current state of the network and to balance the trade-off between frequent changes in network topology and the QoS requirements. It consists of three stages: simulation network stage used to execute different urban scenarios, the function stage used as a competitive approach to aggregate the weighted cost of the factors in a single value, and optimization stage used to evaluate the communication cost and to obtain the optimal configuration based on the competitive cost. The simulation results show significant performance improvement in terms of the Packet Delivery Ratio (PDR), Normalized Routing Load (NRL), Packet loss (PL), and End-to-End Delay (E2ED).

NCaAC: Network Coding-Aware Admission Control for Prioritized Data Dissemination in Vehicular Ad Hoc Networks

“…e original IDNCassisted algorithms without admission control are labeled as EDF, SIN, and PVDD, respectively. e algorithms with (1) If R i receives a newly arriving request r i then (2) Determine the priority of r i ; (3) if r i is high priority then (4) Admit r i and put r i into the high priority service queue; (5) else (6) Vectorize r i as rv ij , the mean vector of VE α as rv α , and the mean vector of VE β as rv β ; (7) Calculate rv α and rv β as described in Section 4.2.1; (8) Calculate the distance between rv ij and rv α , and the distance between rv ij and rv β , respectively; (9) Compare the distances (10) if dist(rv ij , rv α ) ≤ dist(rv ij , rv β ) then (11) Reject r i ; (12) Send a rejection message to the vehicle; (13) else (14) if dist(rv ij , rv α ) > dist(rv ij , rv β ) then (15) Admit r i and put r i into the low priority service queue; (16) end if (17) end if (18) end if (19) network coding-aware admission control are denoted as EDF_NCaAC, SIN_NCaAC, and PVDD_NCaAC. e results are obtained when the system is in a steady state and all data points are based on the average of over 5000 simulation runs.…”

“…cannot guarantee that all requests can be served in time and network congestion will occur and make a great negative impact on the received QoS [3]. To provide user-satisfying QoS for wireless applications in VANETs, it is vital to avoid network congestion and prevent system overload through rational utilization of network resources.…”

An Optimal Network Selection and Efficient Two Level Cluster-Based Routing Mechanisms for Seamless Vertical Handover in Vehicular Networks

“…This communication is termed as Vehicle to Infrastructure (V2I) communication. Service providers giving out the obtaining work and updated information by the vehicles is granted by V2I [2] Yang et al [12] proposed a residual route function time to compute the overlapping time between the vehicles quantitatively with information route by means of novel cluster head metric selection is offered. Mechanism of future-cluster head is devised in addition, though which the message exchanges at intersections could be prevented and the overhead of cluster maintenance could be reduced.…”

Enhanced Vehicular AD HOC Network Protocol to Improve Quality of Service in Vehicle to Vehicle Communication

“…The previous solutions were based on the single layers of a particular stack. Therefore, in this research a cross layered decision based routing was assisted which selected the best path for the delivery of the packets to meet the needs of QoS [8] [9]. The present protocol gathered the information about the channel rate specifically in the decision making procedure.…”