Optimal Configuration of Network Coding in Ad Hoc Networks
In this paper, we analyze the impact of network coding (NC) configuration on the performance of ad hoc networks with the consideration of two significant factors, namely, the throughput loss and the decoding loss, which are jointly treated as the overhead of NC. In particular, physical-layer NC and random linear NC are adopted in static and mobile ad hoc networks (MANETs), respectively. Furthermore, we characterize the goodput and delay/goodput tradeoff in static networks, which are also analyzed in MANETs for different mobility models (i.e., the random independent and identically distributed (i.i.d.) mobility model and the random walk model) and transmission schemes (i.e., the two-hop relay scheme and the flooding scheme). Moreover, the optimal configuration of NC, which consists of the data size, generation size, and NC Galois field, is derived to optimize the delay/ goodput tradeoff and goodput. The theoretical results demonstrate that NC does not bring about order gain on delay/goodput tradeoff for each network model and scheme, except for the flooding scheme in a random i.i.d. mobility model. However, the goodput improvement is exhibited for all the proposed schemes in mobile networks. To our best knowledge, this is the first work to investigate the scaling laws of NC performance and configuration with the consideration of coding overhead in ad hoc networks.
In the last few years, significant efforts have been devoted to designing schemes adopting NC, aiming at full utilization of network resources in applications such as wireless ad hoc networks, peer-to-peer networks, etc.
An important work by Liu et al. introduced the observation that only a constant factor of throughput improvement can be brought about to k-dimensional random static networks.
Further works by Zhang et al. analyzed the delay, throughput (including the overhead of NC), and their tradeoff in fast and slow mobility models for mobile ad hoc networks (MANETs) by employing random linear NC (RLNC). It was indicated in their results that order improvement of throughput scaling laws can be achieved by adopting RLNC in MANETs.
DISADVANTAGES OF EXISTING SYSTEM:
Do not carry any valuable data
However, a significant factor, e.g., throughput loss, was not taken into account in these works.
When considering the given two factors, the traditional definition of throughput in ad hoc networks is no longer appropriate since it does not consider the bits of NC coefficients and the linearly correlated packets that do not carry any valuable data. Instead, the goodput and the delay/goodput tradeoff are investigated in this paper, which only take into account the successfully decoded data.
Although there were some works focusing on throughput loss and decoding loss, in some other networks, their impact on scaling laws in ad hoc networks is still a challenging question. Moreover, if we treat the data size of each packet, the generation size (the number of packets that are combined by NC as a group), and the NC coefficient Galois field as the configuration of NC, it is necessary to find the scaling laws of the optimal configuration for a given network model and transmission scheme.
ADVANTAGES OF PROPOSED SYSTEM:
Consider the throughput loss and decoding loss
Improve the data efficiency
SYSTEM BLOCK DIAGRAM
Two significant factors
Good put and delay/good put tradeofff
Analyzed in MANETs
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Floppy Drive : 44 Mb.
Monitor : 15 VGA Colour.
Ram : 512 Mb.
Operating system : Windows XP/7/LINUX.
Implementation : NS2
NS2 Version : 2.28
Front End : OTCL (Object Oriented Tool Command Language)
Tool : Cygwin (To simulate in Windows OS)
Yi Qin, Feng Yang, Xiaohua Tian, Xinbing Wang, Member, IEEE, Hanwen Luo, Haiquan Wang, Member, IEEE, and Mohsen Guizani, Fellow, IEEE “Optimal Configuration of Network Coding in Ad Hoc Networks”, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 64, NO. 5, MAY 2015.