Kuokkwee Wee

Discretionary bandwidth granting scheme for homogenous real-time applications

IEEE 802.16e is an advanced wireless access technology that provides high-speed data transmission in long distance and offers quality of service (QoS) to subscribers. The provisioning of QoS is one of the great features by IEEE 802.16 to support both real-time and non-real-time applications. In IEEE 802.16, the common part sublayer in the MAC layer is responsible for maintaining the QoS services. There are many functions in the common part sublayer; the most popular topics discussed by researchers are the uplink and downlink scheduling algorithms. Many discussions had been made and focused on these two classes of schedulers. Another equally important component but overlooked so far is the bandwidth request and grant module. Bandwidth request and grant module arbitrates the amount of bandwidth to be granted, besides handling the bandwidth requests. This bandwidth request and grant process has always been developed in a conventional way, and its importance has been underestimated. In addition, the bandwidth distribution within a same service class or category also attracted little attention thus far. Many algorithms for interclass scheduling have been studied and proposed but not as much for intraclass scheduling. However, in bandwidth request and grant process, constraints on the required knowledge by the schedulers limit the intraclass scheduling algorithms to be applied onto them. We view the bandwidth request and grant process as an important part of the QoS architecture. In this paper, we proposed a new bandwidth granting scheme for the bandwidth request and granting process, which enables bandwidth to be fairly granted based on the necessity to all the requests from the same service class or category. By applying our scheme, significant improvements have been observed and recorded. Experiment results have proven and confirmed the effectiveness of our proposed scheme as compared to the conventional scheme.

Video and voice transmission over LTE networks

Video and voice transmission over wireless broadband has become popular and attracted more attention ever since. More and more hand phone owners use their phones to play video and voice over the Internet. Transmitting video and voice in a good quality over the wireless networks is a challenge to service providers. LTE, also known as one of the beyond 3G wireless network technology is designed to have a greater delivery service for multimedia, voice and video applications to end users. However, the QoS provisioning of the voice/video/multimedia in the intricacy wireless network is highly depended on the QoS framework of a network. The QoS framework for LTE network is studied and comparisons among the scheduling algorithms are made in this study. Extensive simulation results showed that the performance of the scheduling algorithms could enhance the video and voice delivery quality.

Causal Discovery and Reasoning for Intrusion Detectionusing Bayesian Network

technology world today; confidentiality, availability and integrity of data are the aspects concerned. Firewall has been widely deployed as a protection but it is no longer adequate to against the intelligent intrusions and attacks which keep changing and transforming. A network intrusion detection and analysis system has been introduced in this paper to resolve the problems of data confidentiality, availability and integrity. The challenge of the study is; first, to model the network intrusion detection domain and second, to perform causal reasoning for intrusion detection and analysis based on the domain model constructed earlier. In this paper, a methodology has been proposed to resolve the two problems mentioned above. Both problems will be addressed under causal knowledge driven approach where intrusion detection is viewed as fault diagnosis and prognosis processes. We have proposed Bayesian network for the modeling of network intrusion domain. Also, powerful reasoning capabilities of Bayesian network have been applied to discover intrusion attacks. Since the capabilities of causal reasoning using Bayesian network have not been fully discovered in the domain of intrusion detection by most of the researchers before, this research work is to bridge the gap. From the results of the experiment, we have concluded that the capability of Bayesian learning is reasonably accurate and efficient.

A Performance Study of Downlink Scheduling Algorithms in Wireless Broadband Networks

IEEE 802.16 is also known as WiMAX was developed to produce high performance in Broadband Wireless Access (BWA) systems with a lower deployment cost than wired broadband services. Like other broadband services, IEEE 802.16 is designed to support applications such as Voice over IP (VoIP), video streaming, video conferencing and online gaming. In IEEE 802.16 standard, five types of service classes have been formed to cater the Quality of Service (QoS) needs for different applications. However, the standard does not state any specific scheduling algorithms for either uplink or downlink transmission. Therefore, scheduling algorithm implementations are depending on the vendors, service providers and researchers. In our presented work, an analysis of various available scheduling algorithms in wireless environment has been carried out. Upon the literature study and analysis, Round Robin (RR), Strict Priority (SP), Self-Clock Fair (SC) and Weighted Fair Queuing (WFQ) were tested in downlink scheduling. For each scheduling algorithm, two scenarios were created, 1) 64QAM and 2) the combination of 16QAM & 64QAM. Simulation results indicate that all the schedulers were struggling to perform as the number of Subscriber Station (SS) increases. Furthermore, the impact on having bad quality channel, which is 16QAM, is also one of the reasons that produces poor performance among all the schedulers. Hence, the traditional schedulers are not suitable for the uncertainty condition in wireless environment because they do not satisfy the QoS demand in WiMAX. 

A True Bayesian Estimate concept in LTE downlink scheduling algorithm

Demands for multimedia application have been raised in the current technology era. Multiple simultaneous users may be streaming video or using VoIP call. Thus a better solution to ensure the QoS satisfaction for LTE downlink needs to be designed. Existing algorithm such as Modified Largest Weighted Delay First (MLWDF) have been widely used to cope with the situation arise. Still the need to inquire a more focused multimedia scheduler is there. Incorporating one of the Bayesian elements, True Bayesian Estimate (TBE) is used for the key design of a new downlink scheduler. The simulation results shown that TBE have a more focused scheduling which resulted better throughput, lesser delay and lesser packet loss, for both video and VoIP compared to well-known MLWDF.

Low Complexity in Exaggerated Earliest Deadline First Approach for Channel and QoS-aware Scheduler

Long Term Evolution (LTE) is a Quality of Service (QoS) provisioning wireless network for today’s technology and as well as for future demands. There is a high demand for better network performance over LTE network, either for real-time or non-real-time traffic. Specifically, the existing scheduling algorithms for real-time application, Exponential/Proportional Fair (EXP/PF), Proportional Fair (PF), and Modified-Largest Weighted Delay First (M-LWDF) have not fully optimized in LTE network. Hence, this paper aims to deliver new scheduling algorithm in the LTE network which overcomes several QoS and channel concerns. Several algorithms were studied, tested and compared which includes EXP/PF, PF, and M-LWDF, which are the popular scheduling algorithms for real-time application in today’s deployment. A typical LTE network is simulated and several experiments were conducted. Extensive simulation results showed that our proposed scheduling algorithm, Exaggerated Earliest Deadline First (E2DF), has outperformed the three existing scheduling algorithms. The proposed algorithm is a LTE compliance module and it able to provide great performance improvement as compared to the other algorithms for real-time application. 

Reasoning with Cause and Effect in Intrusion Detection

detection is an essential tool to protect hacking and unauthorized access in computer networks nowadays. Mechanisms used to attack keep evolving as the internet technology is improving. Hence, the task of differentiating authorized and unauthorized access has become more and more challenging. The modeling of network intrusion domain and causal reasoning for the intrusion detection has been proposed in this paper to address the security issues of a network. Bayesian network modeling with causal knowledge-driven approach has been selected for a network intrusion domain. Reasoning capabilities of Bayesian network have been adapted to perform detection and analysis in the domain.There are two main problems to be addressed in this paper: the first problem is to model the network intrusion domain and the second problem is to perform causal reasoning for intrusion detection and analysis. A methodology has been proposed to solve the two problems mentioned above. Intrusion detection is viewed as fault diagnosis in causal reasoning, and the analysis of the effect is viewed as fault prognosis. To address the first problem under causal knowledge-driven approach, we propose Bayesian network for the modeling of network intrusion domain. The second problem is addressed by applying the powerful reasoning capabilities of Bayesian network. The capabilities of causal reasoning using Bayesian network have not been fully discovered in the domain of intrusion detection. This research work is to bridge the gap.