TDRRTech, Drugs and Rock & Roll (Boston University)
TDRRThroughput Deficit Round Robin
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The final probability of TDRR prediction is derived based on equations (9) and (10).
However, in VANET, accidents are prone when vehicles are in close distance, hence TDRR is used in MarPVS as one of the criteria to determine priority levels.
When TDRR between vehicles is near, in Table 3, we observed that the default IEEE802.11p traffics' priorities are upgraded by one level in MarPVS priority scheme.
In MarPV S, an enhanced priority scheme based on TDRR and data type is proposed to ensure safety messages in near TDRR has higher reliability in reaching its destination node in time.
In algorithm 2, if the predicted TDRR between communicating vehicles is near and type of data transmitted is of high priority, the packet is categorized as priority level 5.
Proposed MarPVS Pseudo code Input: Transmitted and Received Power Output: TDRR. Priority While ("messages are received") do Algorithm 1: TDRR Prediction foreach Time do Calculate TDRR based equation (2).
Nodes' transmission priority is defined by TDRR and data type in MarPV S.
where L = average packet length, C = link transmission capacity, d = TDRR, v = propagation speed, [lambda] = arrival rate, [??] = [lambda]/[mu], [mu] = C/L and [gamma] = priority queuing delay.
The accuracy of the proposed TDRR prediction with Markov model is shown in Fig.
With the proposed MarPVS, vehicles within close TDRR are permitted to transmit with higher priority which results in overall shorter queuing delay.
Results show that in VANET high nodes density and mobility networks, distribution of packets prioritized according to TDRR and data type achieve better optimization and adaptation of contention window and improve transmission latency.
This is because higher priority is given to packet transmission between close TDRR vehicles which is usually less affected by interference and noise as compared to packet transmission between far TDRR vehicles.