A testbed for MANETs: Implementation, experiences and learned lessons

In this paper, we present the implementation, experiences and lessons learned of our tesbed for Ad-hoc networks and Mobile Ad hoc Networks (MANETs). We used OLSR protocol for real experimental evaluation. We investigate the effect of mobility and topology changing in the throughput of a MANET. We study the impact of best-effort traffic for Mesh Topology and Linear Topology. In this work, we consider eight experimental models and we assess the performance of our testbed in terms of throughput, round trip time and packet loss. We found that some of the OLSR's problems can be solved, for instance the routing loop, but this protocol still has the self-interference problem. Also, there is an intricate interdependence between MAC layer and routing layer. We carried out the experiments considering stationary nodes of an Ad-hoc network and the node mobility of MANETs. We found that throughput of TCP was improved by reducing Link Quality Window Size (LQWS). For TCP data flow, we got better results when the LQWS value was 10. Moreover, we found that the node join and leave operations increase the packet loss. The OLSR protocol has a good performance when the source node is moving. However, the performance is not good when the relay nodes are moving.Peer ReviewedPostprint (published version

Adaptive Resource Control in 2-hop Ad-Hoc Networks

This paper presents a simple resource control\ud mechanism with traffic scheduling for 2-hop ad-hoc networks, in\ud which the Request-To-Send (RTS) packet is utilized to deliver\ud feedback information. With this feedback information, the\ud Transmission Opportunity (TXOP) limit of the sources can be\ud controlled to balance the traffic. Furthermore, a bottleneck\ud transmission scheduling scheme is introduced to provide fairness\ud between local and forwarding flows. The proposed mechanism is\ud modeled and evaluated using the well-known 20-sim dynamic\ud system simulator. Experimental results show that a fairer and\ud more efficient bandwidth utilization can be achieved than\ud without the feedback mechanism. The use of the structured and\ud formalized control-theoretical modeling framework has as\ud advantage that results can be obtained in a fast and efficient way

A survey of performance enhancement of transmission control protocol (TCP) in wireless ad hoc networks

This Article is provided by the Brunel Open Access Publishing Fund - Copyright @ 2011 Springer OpenTransmission control protocol (TCP), which provides reliable end-to-end data delivery, performs well in traditional wired network environments, while in wireless ad hoc networks, it does not perform well. Compared to wired networks, wireless ad hoc networks have some specific characteristics such as node mobility and a shared medium. Owing to these specific characteristics of wireless ad hoc networks, TCP faces particular problems with, for example, route failure, channel contention and high bit error rates. These factors are responsible for the performance degradation of TCP in wireless ad hoc networks. The research community has produced a wide range of proposals to improve the performance of TCP in wireless ad hoc networks. This article presents a survey of these proposals (approaches). A classification of TCP improvement proposals for wireless ad hoc networks is presented, which makes it easy to compare the proposals falling under the same category. Tables which summarize the approaches for quick overview are provided. Possible directions for further improvements in this area are suggested in the conclusions. The aim of the article is to enable the reader to quickly acquire an overview of the state of TCP in wireless ad hoc networks.This study is partly funded by Kohat University of Science & Technology (KUST), Pakistan, and the Higher Education Commission, Pakistan

TCP-Aware Backpressure Routing and Scheduling

In this work, we explore the performance of backpressure routing and scheduling for TCP flows over wireless networks. TCP and backpressure are not compatible due to a mismatch between the congestion control mechanism of TCP and the queue size based routing and scheduling of the backpressure framework. We propose a TCP-aware backpressure routing and scheduling that takes into account the behavior of TCP flows. TCP-aware backpressure (i) provides throughput optimality guarantees in the Lyapunov optimization framework, (ii) gracefully combines TCP and backpressure without making any changes to the TCP protocol, (iii) improves the throughput of TCP flows significantly, and (iv) provides fairness across competing TCP flows

CA-AQM: Channel-Aware Active Queue Management for Wireless Networks

In a wireless network, data transmission suffers from varied signal strengths and channel bit error rates. To ensure successful packet reception under different channel conditions, automatic bit rate control schemes are implemented to adjust the transmission bit rates based on the perceived channel conditions. This leads to a wireless network with diverse bit rates. On the other hand, TCP is unaware of such {\em rate diversity} when it performs flow rate control in wireless networks. Experiments show that the throughput of flows in a wireless network are driven by the one with the lowest bit rate, (i.e., the one with the worst channel condition). This does not only lead to low channel utilization, but also fluctuated performance for all flows independent of their individual channel conditions. To address this problem, we conduct an optimization-based analytical study of such behavior of TCP. Based on this optimization framework, we present a joint flow control and active queue management solution. The presented channel-aware active queue management (CA-AQM) provides congestion signals for flow control not only based on the queue length but also the channel condition and the transmission bit rate. Theoretical analysis shows that our solution isolates the performance of individual flows with diverse bit rates. Further, it stabilizes the queue lengths and provides a time-fair channel allocation. Test-bed experiments validate our theoretical claims over a multi-rate wireless network testbed