Cheikh Sarr

Improving Accuracy in Available Bandwidth Estimation for IEEE 802.11-based Ad Hoc Networks

In this article, we propose a method to enhance accuracy of the available bandwidth estimation in IEEE 802.11-based ad hoc networks. This method combines medium state monitoring, probability of collision estimation and backoff time evaluation, improving the method described in C. Sarr et al., (2005). We evaluate our solution by simulation on different scenarios and compare it with different QoS routing protocols based on different available bandwidth estimation techniques

Retransmission-based available bandwidth estimation in IEEE 802.11-based multihop wireless networks

Estimating the available bandwidth in IEEE 802.11-based multihop wireless networks is a very difficult task due to the medium sharing among contending nodes and collisions between hidden stations. Several methods have been proposed so far for these networks to compute the available bandwidth on wireless links. If some recent solutions such as ABE and IAB now take into account collisions and their impact on the mean backoff, none considers the packet retransmissions due to collisions although these retransmissions have an impact on the available bandwidth. In this article, we propose a new available bandwidth estimation for multihop wireless networks called RABE (Retransmission-based Available Bandwidth). This method integrates the average number of retransmission attempts in the available bandwidth estimation. RABE is evaluated by simulation and the obtained results show that RABE can achieve a mean error ratio of 17% in comparison with the real measurement. Furthermore, RABE is at least two times more accurate than ABE and ten times more accurate than IAB.

Average end-to-end delay computation in IEEE 802.11 ad hoc networks

In this study, we present a new analytic model for evaluating average end-to-end delay in IEEE 802.11 multihop wireless networks. Our model gives closed expressions for the end-to-end delay in function of arrivals and service time patterns. Each node is modelled as a G/G/1/K queue from which we can derive expressions for service time via queueing theory. By combining this delay evaluation with different admission controls, we design a protocol called DEAN (Delay Estimation in Ad hoc Networks). DEAN is able to provide delay guarantees for quality of service applications in function of the application level requirements. Through extensive simulations, we compare the performance evaluation of DEAN with other approaches.