Performance analysis of network coding‐based content distribution in vehicularad‐hocnetworks

Abstract

The authors investigate the content distribution among the vehicles of a cluster in a vehicular ad-hoc network, exploiting network coding. The vehicles collaborate to disseminate the coded data packets, received from a roadside infostation based on IEEE 802.11 medium access control (MAC) protocol. Two types of network coding are considered: random linear network coding (RLNC) over a large finite field and random XORed network coding (RXNC). An analytical model is proposed to address the effect of random access MAC as well as the correlation among received coded packets on the performance of content distribution. First, a p-persistent carrier sense multiple access approximation for IEEE 802.11 MAC is adopted, to derive the expected amount of time necessary to deliver the whole information (a data file) to the vehicles, that is, content distribution delay, based on RLNC. Second, the content distribution delay for RXNC is investigated. In this respect, the authors determine the probability of a newly received packet to be innovative for RXNC and characterise the probability that all nodes succeed to retrieve the data file, that is, content delivery ratio. Finally, the success of content distribution process for erasure channels is assessed.

Efficient Coding-Based Scheduling for Multi-Item Requests in Real-Time On-Demand Data Dissemination

“…In [40], Wang et al designed a joint rate selection and wireless network coding (RSNC) scheme with delay constraint so as to maximize the total benefit of the packets that are successfully received at the destinations without missing their deadlines. However, in At the beginning of each broadcast slot (1) for Each arrived multi-item request do (2) Insert into the requests' queue (3) end for (4) while The requests' queue is not empty do (5) for Each multi-item request do (6) C a l c u l a t e 's scheduling weight according to Definitions 1-10, insert into the service queue in descending order of scheduling weight PVC( ); (7) end for (8) Select the request with the most scheduling weight as the schedulable request * , further select the data item with the most absolute profit, ∈ * , as the seed for network coding. That is seed ← = arg max ∈ * profit( ) (9)…”

“…With the rapid development of communication technologies, modern mobile communication devices have obtained the capabilities of transmitting, storing, and processing information independently, enabling the rush of new applications with the purpose of safety, being economic, and infotainment [1][2][3][4]. Meanwhile, data acquisition becomes increasingly important for these emerging mobile applications [5][6][7][8].…”