Harsha R. Sirisena

Handover in Mobile WiMAX Networks: The State of Art and Research Issues

The next-generation Wireless Metropolitan Area Networks, using the Worldwide Interoperability for Microwave Access (WiMAX) as the core technology based on the IEEE 802.16 family of standards, is evolving as a Fourth-Generation (4G) technology. With the recent introduction of mobility management frameworks in the IEEE 802.16e standard, WiMAX is now in competition with the existing and forthcoming generations of wireless technologies for providing ubiquitous computing solutions. However, the success of a good mobility framework largely depends on the capability of performing fast and seamless handovers irrespective of the deployed architectural scenario. Now that the IEEE has defined the Mobile WiMAX (IEEE 802.16e) MAC-layer handover management framework, the Network Working Group (NWG) of the WiMAX Forum is working on the development of the upper layers. However, the path to commercialization of a full-fledged WiMAX mobility framework is full of research challenges. This article focuses on potential handover-related research issues in the existing and future WiMAX mobility framework. A survey of these issues in the MAC, Network and Cross-Layer scenarios is presented along with discussion of the different solutions to those challenges. A comparative study of the proposed solutions, coupled with some insights to the relevant issues, is also included.

Hybrid error control mechanism for video transmission in the wireless IP networks

Considering the limited bandwidth of the wireless link, it is important that the error control mechanism in wireless networks be spectrally efficient. Towards this end, we develop a hybrid error control architecture which takes into account the use of hierarchical video coding. Additionally, the architecture also includes a module which estimates the packet error rate and round trip time observed by the receiver and adjusts the level of redundancy used based on the estimate. By choosing different options in the architecture, we get different error control schemes. In this paper, we investigate the performance of five different error control schemes, namely ARQ, pure FEC, hybrid FEC/ARQ, hybrid FEC/ARQ with priority-dependent redundancy, and adaptive hybrid FEC/ARQ with priority-dependent redundancy. We evaluate the performance of these schemes using MPEG-2 video traces. The results show that pure FEC offers the worst overall performance. The ARQ scheme offers the best performance under low bit error rate and short round trip time, while the priority-aware hybrid FEC/ARQ with or without FEC adaptation offers the best performance under other conditions.

Quantifying agitation in sedated ICU patients using digital imaging

Agitation is a significant problem in the Intensive Care Unit (ICU), affecting 71% of sedated adult patients during 58% of ICU patient-days. Subjective scale based assessment-methods focused primarily on assessing excessive patient motion are currently used to assess the level of patient agitation, but are limited in their accuracy and resolution. This research quantifies this approach by developing an objective agitation measurement from patient motion that is sensed using digital video image processing. A fuzzy inference system (FIS) is developed to classify levels of motion that correlate with observed patient agitation, while accounting for motion due to medical staff working on the patient. Clinical tests for five ICU patients have been performed to verify the validity of this approach in comparison to agitation graded by nursing staff using the Riker Sedation-Agitation Scale (SAS). All trials were performed in the Christchurch Hospital Department of Intensive Care, with ethics approval from the Canterbury Ethics Committee. Results show good correlation with medical staff assessment with no false positive results during calm periods. Clinically, this initial agitation measurement method promises the ability to consistently and objectively quantify patient agitation to enable better management of sedation and agitation through optimised drug delivery leading to reduced length of stay and improved outcome.

The influence of long-range dependence on traffic prediction

Predicting traffic requirements is a fundamental objective of network management algorithms, whether explicitly stated or not. Considering the abundant evidence that traffic is long-range dependent (LRD) and the fact that the history of long-range dependent processes has significant impact on the present value of the process, it is natural to assume that predicting LRD traffic would be rather rewarding. Although there is indeed significant performance gain in using the correlation structure as the Hurst parameter increases, we show in this paper that this is primarily due to the utilization of the specific short-term correlations that occur within the structure of the traffic, rather than storing a long history of the traffic and utilizing the long-term correlations that exist between the future traffic level and this stored history. This conclusion is demonstrated using two specific management functions: rate control for elastic connections, and queue management using probabilistic packet discarding.

A mobility management protocol for IP-based cellular networks

Mobile IP is an IETF RFC that supports transparent host migration on the Internet. In the transition to IP-based cellular networks, it is widely agreed that Mobile IP provides an elegant solution for inter-domain, or macro- mobility management, but lacks critical aspects of mobility management needed within cellular networks. The shortcomings have led to the recent emergence of micro- mobility management protocols. This paper presents an IP- based mobility management protocol, µ-Mobile IP, based on two enhancements, proactive handoff and paging support, to an Internet Draft proposal Regional Registrations. A signaling cost analysis is used to justify the need for such enhancements. We show through simulations the protocols suitability for supporting real-time communications.

Performance improvement of backpropagation algorithm by automatic activation function gain tuning using fuzzy logic

Abstract We propose a method for improving the performance of the backpropagation algorithm using a fuzzy logic system for automatically tuning the activation function gain. Instead of a fixed activation function gain, the fuzzy logic system is used to dynamically adjust the gain, based upon a set of problem domain heuristics derived from a preliminary simulation study. The efficacy of the proposed method is verified by means of simulations on a parity problem, a function approximation problem, and a pattern recognition problem. The results show that the proposed method improves considerably on the performance of the general backpropagation algorithm, including when using momentum.

Utility of algebraic connectivity metric in topology design of survivable networks

In studies of survivable networks, it is important to be able to differentiate network topologies by means of a robust numerical measure that indicates the levels of immunity of these topologies to failures of their nodes and links. Ideally, such a measure should be sensitive to the existence of nodes or links which are more important than others, for example, if their failures cause the networks disintegration. In this paper, we suggest using an algebraic connectivity metric, adopted from spectral graph theory, namely the 2nd smallest eigenvalue of the Laplacian matrix of the network topology, instead of the average nodal degree that is usually used to characterize network connectivity in studies of the spare capacity allocation problem. Extensive simulation studies confirm that this metric is a more informative and more accurate parameter than the average nodal degree for characterizing network topologies in survivability studies.

Trust-Based Fast Authentication for Multiowner Wireless Networks

In multiowner wireless networks, access points (APs) are owned and operated by different administrations, leading to significant authentication delays during handoff between APs. We propose to exploit the trust between the owners of neighboring APs for reducing the authentication delay. In the proposed authentication scheme, neighboring APs that trust each other share the security key for the visiting node to avoid lengthy authentication routines each time the visiting node switches APs. The performance of the proposed trust-based authentication scheme is evaluated using a Markov model. Using numerical experiments, we first study a basic scenario where mobile nodes are not aware of the trust networks that exist in a given neighborhood. Subsequently, we consider an advanced scenario where a mobile node functionality is augmented to discover the trust network so as to minimize roaming beyond the trusted APs. We find that, even with the basic implementation, the average number of full authentications needed for a roaming mobile reduces linearly as the likelihood of two neighboring APs trusting each other increases. With the advanced implementation, our experiments show that quadratic reduction is achieved. The Markov model is validated using discrete event simulation.

Detection of adaptive inverse models in the human motor system

Abstract This study aimed to find evidence for the formation of an internal inverse model of a novel visuomotor relationship for feedforward control in the brain. An experiment was carried out involving 20 normal adult subjects who performed a pursuit random tracking task with a steering wheel for input. During learning the response cursor was periodically blanked, removing all feedback about the external system (i.e., about the relationship between hand motion and response cursor motion). Results showed a transfer of learning from the unblanked runs to the blanked runs for a static nonlinear system (linear trend RMS error F (1,19)=5.05, p =0.037) thereby demonstrating adaptive feedforward control in the nervous system. No such transfer was observed for a dynamic linear system, indicating a dominant adaptive feedback control component. Results are consistent with inverse modeling and suggest a combination of feedforward and feedback adaptive control in the brain.

Coup de fouet based VRLA battery capacity estimation

The most important battery state of health (SOH) parameter is capacity. Capacity, the energy storage capability of a battery, is difficult to measure for the valve regulated lead acid (VRLA) battery. One of the most reliable approaches involves fully discharging the battery. However, this leaves the telecommunication system vulnerable to mains failure, is expensive and time consuming. Recently the authors have discovered a correlation between battery capacity, and parameters found within the voltage profile during the initial stages of discharge. This region is known as the coup de fouet. This paper presents the issues relating to the construction of a model for extracting battery capacity, knowledge from the coup de fouet. Results obtained so far indicate that this approach will form the basis of an intelligent battery management system.