Performance analysis of differentiated resource-sharing in a wireless ad-hoc network

In this paper we model and analyze a relay node in a wireless ad-hoc network; the capacity available at this node is used to both transmit traffic from the source nodes (towards the relay node), and to serve traffic at the relay node (so that it can be forwarded to successor nodes). Clearly, when a specific node is used more heavily than others, it is prone to becoming a performance bottleneck. In this paper we consider the situation that the relay node obtains a share of the capacity that is m times as large as the share that each source node receives. The main performance metrics considered are the workload at the relay node and the average overall flow transfer time, i.e., the average time required to transmit a flow from a source node via the relay node to the destination. Our aim is to find expressions for these performance metrics for a general resource-sharing ratio m, as well as a general flow-size distribution. The analysis consists of the following steps. First, for the special case of exponential flow sizes we analyze the source-node dynamics, as well as the workload at the relay node by a fluid-flow queueing model. Then we observe from extensive numerical experimentation over a broad set of parameter values that the distribution of the number of active source nodes is actually insensitive to the flow-size distribution. Using this remarkable (empirical) result as an approximation assumption, we obtain explicit expressions for both the mean workload at the relay node and the overall flow transfer time, both for general flow-size distributions

Setting the parameters right for two-hop IEEE 802.11e ad hoc networks

Two-hop ad-hoc networks, in which some nodes forward traffic for multiple sources, with which they also compete for channel access suffer from large queues building up in bottleneck nodes. This problem can often be alleviated by using IEEE 802.11e to give preferential treatment to bottleneck nodes. Previous results have shown that differentiation parameters can be used to allocate capacity in a more efficient way in the two-hop scenario. However, the overall throughput of the bottleneck may differ considerably, depending on the differentiation method used. By applying a very fast and accurate analysis method, based on steady-state analysis of an QBD-type infinite Markov chain, we find the maximum throughput that is possible per differentiation parameter. All possible parameter settings are explored with respect to the maximum throughput conditioned on a maximum buffer occupancy. This design space exploration cannot be done with network simulators like NS2 or Opnet, as each simulation run simply takes to long.\ud The results, which have been validated by detailed simulations, show that by differentiating TXOP it is possible to achieve a throughput that is about 50% larger than when differentiating AIFS and CW_min.\u

Improving the performance of QoS models in MANETs through interference monitoring and correction

Mobile Ad hoc Networks (MANETs) have been proposed for a wide variety of applications, some of which require the support of real time and multimedia services. To do so, the network should be able to offer quality of service (QoS) appropriate for the latency and throughput bounds to meet appropriate real time constraints imposed by multimedia data. Due to the limited resources such as bandwidth in a wireless medium, flows need to be prioritised in order to guarantee QoS to the flows that need it. In this research, we propose a scheme to provide QoS guarantee to high priority flows in the presence of other high as well as low priority flows so that both type of flows achieve best possible throughput and end-to-end delays. Nodes independently monitor the level of interference by checking the rates of the highest priority flows and signal corrective mechanisms when these rates fall outside of specified thresholds. This research investigates using simulations the effects of a number of important parameters in MANETs, including node speed, pause time, interference, and the dynamic monitoring and correction on system performance in static and mobile scenarios. In this report we show that the dynamic monitoring and correction provides improved QoS than fixed monitoring and correction to both high priority and low priority flows in MANETs

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