Aruna Jayasuriya

Modelling service time distribution in cellular networks using phase-type service distributions

Third generation mobile communication networks are designed to provide a variety of high data rate services with higher quality of service (QoS) than second-generation systems. Handover becomes one of the major problems in such a mobile environment as it is of utmost importance to provide a higher guarantee that the users are able to continue their service during the entire length of the transmission, without it being blocked during the handover or loss of quality or data. Careful dimensioning of the network and the underlying teletraffic analysis plays a major role in determining the various grade of service (GoS) parameters that service providers can provide at various network loads. The channel holding time of a cell is one of the major parameters that needs to be accurately modelled in the teletraffic analysis. This paper focuses on using phase-type distributions of generalised Erlang form to model channel holding time in a mobile environment. We also present the quasi-birth-death process, which characterises the queuing models with generalized Erlang service and exponential inter-arrival distributions. Further we investigate the use of channels exclusively reserved for handover users to improve the handover performance.

Throughput performance of multiple independent paths in wireless multihop network

We investigate the improvement in throughput performance achievable by multiple independent paths in a single-channel wireless multi-hop network. We show that a major limiting factor in multiple path routing is the degree of spatial reuse that can be achieved at the source node; that is, the maximum achievable throughput improvement of multiple paths is determined by the achievable degree of spatial reuse rather than the number of paths used. Hence having more than 2 paths does not significantly improve the performance. We also show that the average throughput improvement resulting from 2 independent paths depends on the probability of finding such independent paths in the network; this probability, although increasing with node density, is not always large enough to guarantee significant improvement in throughput.

Sensor Networks Protocol Design Using Random Markov Field Theory

In this paper, we present a new general framework allowing sensor networks design using Random Markov Fields (MRF) theory. We explain how the principles underlying MRF theory naturally fit design requirements in sensor networks in particular the need to rely on decentralised and distributed methods to solve global optimisation problems. We illustrate the potential of this new general concept with the practical problems of power control and resource allocation. In addition, we present a new method to improve the convergence rate of the simulated annealing when the sensor network design problem is a constrained optimisation problem.

A New Contour Detection Approach in Mammogram Using Rational Wavelet Filtering and MRF Smoothing

This paper presents a new approach to detect breast contour in mammogram. Formed from a class of rational orthogonal wavelets (ROWs), a 2-D image filter is constructed for prefiltering of the mammogram. The filtered image facilitates a simple binarisation of the mammogram. An initial breast contour is then extracted from the binarised image with a simple boundary scan technique. Based on Markov Random Field (MRF) modelling and iterated conditional modes (ICM) relaxation, a smoothing algorithm is developed to further smooth the initial contour. The proposed smoothing algorithm has a unique advantage of smoothing the breast contour while the nipple is preserved with high fidelity. In comparison with contour detection techniques relying on the calculation of varying thresholds based on histgram analysis, a single fixed ROW image filter is sufficient for all mammograms being analysed. The ROW filter is adaptive to varying statistics of mammograms regarding the pixel intensity. Results prove the robustness of the proposed detection algorithm for 82 mammograms from the Mini-MIAS database.

Efficient Admission Control based on Predicted Traffic Characteristics

As the use of bandwidth hungry applications such as video conferencing increases, ensuring quality of service (QoS) becomes increasingly important. In wireless access networks such as WiFi and WiMax, admission control is necessary to control QoS. Many admission control methods use the mean bitrate of a flow to determine if it can be allowed, however there is a lack of methods that accurately assess variable bit rate flows. We propose a simple alternative method that uses the bitrate statistics of each flow to approximate the probability of exceeding the medium bandwidth. A new flow is permitted only if the probability of exceeding the channel bandwidth is sufficiently low.

Aggregation of Wi-Fi Links: When Does it Work?

We conducted a systematic experimental and simulation study on the behaviour of aggregated Wi-Fi links for WLAN access. The Wi-Fi links were aggregated by bonding multiple Wi-Fi interfaces. We demonstrated a close to linear improvement in maximum throughput with the number of aggregated links. We analyse unstable behaviour which appears in both UDP and TCP based applications when flows are split over multiple Wi-Fi links, even when the links are statistically symmetric. We show that this unstable behaviour is due to the short term variations in packet latencies, and occurs in distinct regimes, starting before the saturation of throughput. Our analysis suggests that since the origin of the instability is local, it could be suppressed by intelligent control applied locally at the wireless interfaces.

Performance Analysis of the IEEE 802.11 DCF

Wireless local area networks (WLANs) have been attracted significant research interest during the last few years. The IEEE 802.11 standard is the most mature and widely adopted standard in current wireless networks. This paper proposes a new model to analyze channel throughput, packet processing rate, packet loss probability and average packet delay in IEEE 802.11 wireless local area networks. Theoretical results are derived and subsequently compared with simulation results using ns2. The close agreement between the theoretical and simulation results under number of conditions reaffirms the accuracy of the derived analytical model

Improved Opportunistic Auto Rate protocols for wireless networks

Currently a number of 802.11 based standards support multiple rates at physical layer and recently 802.11 MAC protocols have been modified to make use of these multiple rates. Two such mechanisms, opportunistic auto rate (OAR) and receiver based auto rate (RBAR) have shown to improve throughput performance of wireless LANs as well as infrastructure-less wireless networks. However these protocols are unable to adapt to short-term changes in channel conditions during transmission as well as unable to use optimum power and throughput during packet transmissions. In this paper, an improved opportunistic auto rate protocol (IOAR) has been proposed as an efficient rate adaptive MAC. Two subtypes of IOAR based on power control requirement have been proposed. Using an event based simulation we show that the proposed schemes outperform the existing rate adaptive MAC protocols such as RBAR and OAR, in terms of throughput by upto about 24%.

Estimating throughput available to a node in wireless ad-hoc network

We propose a new technique to estimate the throughput available to a wireless node in a multi-hop network. Our technique exploits the nearly linear relationship between throughput at a node and the channel occupancy contributed by that node. It provides estimates of available throughput on the basis of local measurements and neighbourhood information available locally at a node. This technique allows timely and non-intrusive estimation without active probing. It is shown by simulations that this new technique provides robust estimates of the throughput available to a node in an ad hoc network environment characterised by numerous active neighbours and dependencies between the levels of node activity along a multi-hop path.

Handover Channel Allocation Based on Mobility Predictions

Future cellular communication networks must use superior handover processing techniques to guarantee that continuity of connections during handover. Although previous studies have shown that the blocking handover probabilities can be reduced by exclusively reserving resources for handover users, this mechanism only results in marginal increase in overall system performance. This is due to the increased blocking probabilities suffered by new users as a result of channel being permanently allocated for handover users, even when no handover user requires them. In this paper we propose a method to dynamically allocate the handover channel after estimating the number of handover channels required by impending handover users at any given time. We use a mobility model to predict the user’s handover probabilities and a dynamic resource allocation algorithm to estimate the number of channels required to support the predicted handover traffic. Results of the study show that the proposed solution increases the system utilisation up to 5%.