TCP Performance in Wireless multi-hop Networks

Introduction

Early research showed TCP suffers poor Performance in wireless networks because of packet losses and corruption caused by wireless inducted errors Further studies searched for mechanism to improve TCP performance in cellular wireless systems Other researches investigated other network problems that negativly affect TCP performance, such as bandwidth asymmetry and large round trip times, which are prevalent in satelite networks During the presentaition we adress another network charackteristic that impacts TCP performance, which is common in mobile ad hoc networks: link failures due to mobility First present performance analysis of standart TCP over mobile ad hoc networks Then present analysis of the use of explicit notification techniques to counter the affects of link failures

Simulation Environment and Methodology

For simulations the ns network simulator from Lawrence Berkles National Laboratory was used, with extensions from the MONARCH project at Carnegie Mellon Extensions include a set of mobile ad hoc network routing protocols, an implementation of BSDs ARP protocol, an 802.11 MAC Layer, a radio propagation model and mechanisms to model node mobility using pre-computed mobility patterns that are fed to the simulation at run time No modifications were made to the simulator (accept minor bug fixes that were necessary) All results based on a network configuration consisting of TCP-Reno over IP on an 802.11 wireless network, with routing provided by the Dynamic Source Routing (DSR) protocol and BSDs ARP protocol (used to resolve IP adresses to MAC adresses) Objective was to observe TCPs performance in the presence of mobility inducted failures in a plausible network environment, for which any of the proposed mobile wireless ad hoc routing protocols would have sufficed Network model consists of 30 nodes in 1500x300 meter flat, rectangular area Nodes move according to random waypoint mobility model In random waypoint model each node x picks a random destination and speed in the area and travels to destination in straight line Once x arrives, it pauses, picks another destination and goes on No pause, so every node is always in moving All nodes communicate with identical half duplex wireless radios, which are modeld after 802.11 based Wave Lan wireless radios, with a bandwith of 2Mbps and nominal transmission radius of 250m TCP packet size was 1460bytes, maximum window was eight packets All simulation results based on average throughput of 50 scenarios or patterns Each pattern, generated randomly, designates the initial placement and heading of each of the nodes over simulated time Used same pattern for different mean speeds For a given pattern at different speeds, same sequence of movements (and link failures) occur Speed of each node is uniformly distributed in an interval of 0,9v - 1,1v for some mean speed v

Performance Metric

Throughput as performance metric used TCP throughput ussually less than optimal due to TCP senders inability to accurate determine the cause of a packet loss TCP sender assumes that all packets losses are caused by congestion When link on TCP route breaks, TCP sender reacts as if congestion was the cause, reducing its congestion window and, in instance of a timeout, backing-off its retransmission timeout (RTO) Therefore, route changes due to host mobility can detrimental impact on TCP performance To gauge impact of route changes on TCP perfomance, we derived an upper bound on TCP throughput, the expected throughput TCP throughput measure obtained by simulation is then compared with expected throughput Expected throughput was obtained as the following: - First simulated a static (fixed) network of n nodes that formed a linear chain containing n-1 wireless hops - Nodes used 802.11 protocol for medium access - Then a one-way TCP data transfer was performed between the two nodes at the ends of the linear chain, and the TCP throughput was measured between these nodes

Hops	Throughput (Kbps)	Table 1 shows measured TCP throughput as a function of number of hops, averaged over ten runs Throughput decreases rapidly when number of hops is increased from 1, then stabilizes once the number of hops becomes large
1	1463.0
2	729.0
3	484.4
4	339.9
5	246.4
6	205.2
7	198.1
8	191.8
9	185.3
10	182.4

Our objective here is to use these measurements to determine expected troughput Expected throughput is a function of mobility pattern For instance, if two nodes are always adjacent and move together, the expected thoughput for the TCP connection between them would be identical to that for one hop in Table 1

expected throughput = ${\frac {\sum _{i=1}^{\infty }T_{i}*t_{i}}{\sum _{i=1}^{\infty }t_{i}}}$