International Journal of Computer Networks & Communications (IJCNC)

AIRCC PUBLISHING CORPORATION

ijcnc

CROSS LAYER BASED CONGESTION FREE ROUTESELECTION IN VEHICULAR AD HOC NETWORKS

Rashmi Patil1 and  Dr. Rekha Patil2

Assistant Professor, Department of Information Science and Engineering,
Faculty of Engineering and Technology (Exclusively for women),
Sharnbasva University, Kalaburagi, Karnataka, India
2Professor, Department of CSE, PDA college of Engineering,
Kalaburagi, Karnataka, India

 

ABSTRACT

For creating a mobile network, the moving cars consider as nodes in the Vehicular Ad-Hoc Networks(VANETs). Each participating car is turned into a wireless router in the VANETs that allows theconnecting and creating a network. To improve the comfort and safety of driving of automotive users, the vehicular environment system develops in the vehicular environment systems using the wireless access. The channel congestion causes the degradation of quality of service in such cases with higher vehicle density. The real-time and reliable communication is required for various safety applications of VANETs. The dense traffic network has included one of the major challenges as avoiding the communication channels egradation. To provide the network with efficient operation, most of the studies are recommended to use the appropriate congestion control methods. It’s important to note that many congestion control mechanisms are not implemented for event-driven real-time safety messages. Based on the congestion probability approach estimation, CFRS-CP-Congestion free route selection is introduced for minimizing the total number of data flow packets that passing through the congested nodes. At each node, the congestion probability is estimated using the proposed technique of CFRS-CP based on link quality, MAC overhead, neighbour density & vehicle velocity. Then, the estimated congestion probability is used for route assessment. The estimated probability value is appended to the control packets for comparison. All the available routes are assessed based on the estimated congestion probability which results in congestion free routing path for every round of data communication. The simulation results prove that the proposed method decreases end to end delay by 32% and improves PDR up to 30% and throughput up to 45% compared to the existing protocols.

KEYWORDS

Congestion, Link quality, MAC, Neighbor density, VANET, Vehicle velocity.

1. INTRODUCTION

The communication of vehicles on roads is allowed using the emerging technology of the vehicular ad-hoc network (VANET) to enhance the comfort and driving safety for automotive users [1]. In VANETs, the communication can be established among vehicles and vehicular infrastructures, like vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I)communications. With one OBU, each vehicle is equipped in the V2V communications among On-Board Units (OBUs), and the communications of V2I is occurred between OBUs and RoadSide Units (RSUs)[2]. VANETs can be implemented in different non-safety and safetyapplications, such as infotainment, optimization of traffic, toll payment, and parking management.The characterization of VANETs has been performed based on the changes of high topology rate, high variability, and high mobility in node density. Some challenges like data dissemination,routing scalability, security, and total performance degradation are resulted due to these characteristics in VANETs [3]. For enhancing the VANET’s performance, the policies of Qualities of Service (QoS) have been utilized. The congestion control is one of the major operations of a network to improve the parameters of QoS, including delay and reliability. For ensuring the reliable and safe communication without any delay, the congestion control is exploited. By using the self-organized and decentralized techniques, the congestion should be controlled owing to the frequently route break and dynamic changing topology. In VANETs, some of the existing strategies for congestion control are controlled the network congestion efficiently in VANETs, but in most cases they increase number of computations needed and time complexity for controlling congestion which results in high overhead in the network [4]. Figure 1 shows the architecture view of VANET


Figure 1. A VANET architecture


Figure 1. A VANET architecture

Where, 𝑅𝑇𝑆𝑡𝑖𝑚𝑒 and 𝐶𝑇𝑆𝑡𝑖𝑚𝑒 represent the consumed time on Request To Send and Clear To Send, respectively while SIFStime refers to the Short Inter Frame Space period. The equation (2) isused to determine the MAC overhead:

Where, 𝑇𝑎𝑐𝑐 refers to the time taken because of the access contention.

 

Where, 𝑇𝑎𝑐𝑐 refers to the time taken because of the access contention.

3.2. Link Quality:

From the physical layer, the received signal strength can be utilized for predicting the quality of a link and abandon the links, which have lower signal strength by using a route selection. The transmission power 𝑃𝑡𝑟𝑎𝑛𝑠 is contained in the broadcasted RTS packets if broadcasting the RTS packets from the sender nodes. The below-mentioned relationship uses for free-space propagation model by the received signal strength that measures using the intended node upon receiving the RTS packet. The equation (3) is used to estimate the link quality from the above observations:

Where, 𝐶𝑃𝑎_𝑎𝑣𝑟 refers to the node a’s average CP values and 𝐶𝑃𝑏 indicates the node b’s CP at
time t.
The equation (8) is used to define the set of relative neighbours for node a:

Where, 𝐶𝑃𝑎_𝑎𝑣𝑟 refers to the node a’s average CP values and 𝐶𝑃𝑏 indicates the node b’s CP at
time t.
The equation (8) is used to define the set of relative neighbours for node a:


Figure 2. updated control packet structure

Table 1. Simulation table



Figure 3. End to End Delay

Table 2. End to End Delay proposed technique compared to the other existing methods



Figure 4. Routing overhead

Table 3. Routing overhead proposed technique compared to the other existing methods



Figure 5. Packet delivery ratio


Table 4. Table 4


Figure 6. Throughput

p style=”text-align:center;”>Table 5. Throughput proposed technique compared to the other existing methods<


Figure 7. Performance comparison of obtained End to End Delay (ms) using existing and proposed congestion routing protocol



Figure 8. Performance comparison of obtained Routing overhead (%) using existing and proposed congestion routing protocol




Figure 9. Performance comparison of obtained Packet delivery ratio (%) using existing and proposed congestion routing protocol


Author Name: Rashmi Patil
PhD studying college: PoojyaDoddappaAppa college of Engineering, Kalaburagi.
UG& PG degree with college: Poojya Doddappa Appa college of Engineering, Kalaburagi & Appa Institute of Engineering & Technology, Kalaburagi.
Working details: Assistant Professor, Department of Information Science and Engineering, Faculty of Engineering and Technology (Exclusively for Women), Sharnbasva University, Kalaburagi.
Area of interests: Networking

Co Author
Co-author name: Dr. Rekha Patil
Working details: Professor, Department of Computer Science and Engineering, Poojya Doddappa Appa college of Engineering, Kalaburagi

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This entry was posted on August 9, 2022 by .
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