Mohd Hasbullah Omar

Feasibility Study of Using IEEE 802.22 Wireless Regional Area Network (WRAN) in Malaysia

This paper introduces the implementation of IEEE 802.22 Wireless Regional Area Network (WRAN) for broadband internet access in rural areas. It highlights the advantage of implementing such technology and feasibility to co-exist with Digital Video Broadcasting – Terrestrial (DVB-T) in Malaysia. It adopts a model to determine the maximum number of WRAN base stations (BSs) by analyzing its co-channel interference between the BSs. The analysis shown that maximum WRAN BSs that could co-exist is 8 to 19 BSs outside the protection contour of the DVB-T BS. Coverage areas of 30 – 100 km will also feasible to co-exist. By implementing the IEEE 802.22 WRAN, the digital divide can be narrowed and broadband penetration would be increased.

Enhancing DCCP congestion control mechanism for long delay link

Most of the multimedia applications use the User Datagram Protocol (UDP) as a transport layer protocol because it is suitable for the delivery of multimedia data over the Internet. However, the use of UDP could endanger the stability of the network because there is no congestion control applied. To a certain extent, the network can collapse if too many applications deliberately use this protocol. Subsequently, instead of using the UDP, the applications have choices to use the Datagram Congestion Control Protocol (DCCP), which has a built-in congestion control that can provide a better network. Nevertheless, the congestion control mechanism in the Congestion Control Identifier (CCID)-2 TCP-like can cause problems when delivering multimedia data over a long delay link. To alleviate the problems, such as longer time taken for achieving maximum throughput, and throughput fluctuation during a congestion avoidance phase, two approaches have been used, i.e. setting of an appropriate slow-start threshold value and adjusting congestion window during a congestion avoidance phase. “TCP-like Threshold Window (TCP-like TW)” has been developed and modeled in the Network Simulator 2 (ns-2). For a long delay link, the TCP-like TW congestion control mechanism is able to minimize the time taken to achieve the maximum throughput. It also can smooth the fluctuation of throughput after achieving the maximum throughput.

Short Term Traffic Forecasting Based on Hybrid of Firefly Algorithm and Least Squares Support Vector Machine

The goal of an active traffic management is to manage congestion based on current and predicted traffic conditions. This can be achieved by utilizing traffic historical data to forecast the traffic flow which later supports travellers for a better journey planning. In this study, a new method that integrates Firefly algorithm (FA) with Least Squares Support Vector Machine (LSSVM) is proposed for short term traffic speed forecasting, which is later termed as FA-LSSVM. In particular, the Firefly algorithm which has the advantage in global search is used to optimize the hyper-parameters of LSSVM for efficient data training. Experimental result indicates that the proposed FA-LSSVM generates lower error rate and a higher accuracy compared to a non-optimized LSSVM. Such a scenario indicates that FA-LSSVM would be a competitor method in the area of time series forecasting.

Performance Enhancement of DCCP TCP-like over Long Delay Link Networks

The performance of DCCP TCP-like degrades significantly over long delay link networks. Despite the TCP-like congestion control mechanism follows the TCP SACK, the performance is really affected by the congestion window growth algorithms as employed by Jacobson based TCP variants. In this paper, all the experiments are done using Network Simulator ns-2, and we manipulated the congestion window size drop during congestion avoidance phase to enhance the performance of DCCP TCP-like over long delay link networks. Instead of halving the current congestion window when congestion events are detected, the reduction of current congestion window drop has been shown to improve the DCCP TCP-like throughput with minimal drop packet percentage.

SVD-Based Signal Detector for Cognitive Radio Networks

This paper examines the implementation of the Singular Value Decomposition (SVD) method to detect the presence of wireless signal. The method is used to find the maximum and minimum eigenvalues. We simulated the algorithm using common digital signal in wireless communication namely rectangular pulse shape, raised cosine and root-raised cosine to test the performance of the signal detector. The SVD-based signal detector was found to be more efficient in sensing signal without knowing the properties of the transmitted signal. The execution time is acceptable compared to the favorable energy detection. The computational complexity of SVD-based detector is medium compared to the energy detector. The algorithm is suitable for blind spectrum sensing where the properties of the signal to be detected are unknown. This is also the advantage of the algorithm since any signal would interfere and subsequently affect the quality of service (QoS) of the IEEE 802.22 connection. Furthermore, the algorithm performed better in the low signal-to-noise ratio (SNR) environment.

Survey and Comparison of Operating Concept for Routing Protocols in DTN

Delay Tolerant Network (DTN) are promising techniques to enable data transmission in challenging scenarios where sophisticated infrastructure is not available and the end-to-end path does not exist at the moment of data transmission. These networks are characterized by a long delay, intermittent connectivity and high error rates. Furthermore, the dynamic topology of the network may change randomly. Therefore, routing is one of the most crucial issues that affect the performance of DTN in terms of data delivery, latency and using resources if node mobility is considered. The routing design in DTN raises many challenges to the networks. Therefore, the problem of how to route a packet from one node to another in DTN is of the essence. This paper puts forward a rigorous survey of various routing protocols as well as performs a comparison of diverse routing strategies regarding significant issues in DTN.

ANALYSIS OF INTERNET TRAFFIC IN EDUCATIONAL NETWORK BASED ON USERS' PREFERENCES

The demand for Internet services and network resour ces in Educational networks are increasing rapidly. Specifically, the revolution of web 2.0 “also refer red to as the Read-Write Web” has changed the way of information exchange and distribution. Although web 2.0 has gained attraction in all sectors of the education industry, but it results in high-traffic loads on networks which often leads to the Internet users’ dissatisfaction. Therefore, analyzing Internet traf fic becomes an urgent need to provide high-quality service, monitoring bandwidth usage. In this study, we focus on analyzing the Internet traffic in Universiti Ut ara Malaysia (UUM) main campus. We performed measurement analysis form the application level characteristics based on users’ preferences. A tota l of three methodological steps are carried out to meet the objective of this study namely data collection, dat a analysis and data presentation. The finding shows that social networks are the most web applications visit ed in UUM. These findings lead to facilitate the enhancement of Educational network performance and Internet bandwidth strategies.

Performance Evaluation of Wi-Fi and White-Fi: Simulation Approach

Wi-Fi is widely used to connect electronic devices wirelessly using ISM radio bands. Previous studies have reported traffic congestion in Wi-Fi due to several reasons. As an alternative, unused spectrum in TV band known as TV white space (TVWS) can be utilized for the same purpose. The use of Wi-Fi technology in TV band is also known as White-Fi. TVWS ranges in VHF and UHF that is not utilized by licensed user in a particular time and location. This paper presents a network performance comparison between Wi-Fi and White-Fi by evaluating the average throughput, end-to-end delay and packet delivery ratio (PDR). The simulation result shows White-Fi (IEEE 802.11af) has a significant percentage of average throughput and PDR with 25.94% and 24.06% compared to Wi-Fi (IEEE 802.11g) respectively. In addition, the percentage of average end-to-end delay in White-Fi is 60.79% lower than Wi-Fi.

Node Placement Strategy in Wireless Sensor Network

The performance and quality of services in wireless sensor networks WSNs depend on coverage and connectivity. Node placement is a fundamental issue closely related to the coverage and connectivity in sensor networks. Node placement influences the target position, coverage area, and connectivity in sensor networks. In random deployment, sensor nodes are deployed randomly in a non-invasive way. The deployment process may cause issues like coverage holes, overlapping, and connectivity failure. Enhancing coverage and connectivity are important for sensor networks to provide a reliable communication within sensing. Placing many sensor nodes in a WSN application region area is not the best solution due to cost and it results in multiple sensors used. Mobile sensor node is used as an alternative to overcome the random deployment problem. The virtual force based self node deployment is used in the mobility sensor to improve the coverage and connectivity area. Virtual Force Algorithm VFA approach using virtual repulsive and attractive forces is used to find the optimal node placement to minimize the problems. Simulation results proofed that a uniform deployment achieved using VFA approach with an optimal sensing range to cover the region of interest.

Eigenvalue-based signal detectors performance comparison

The purpose of this paper is to compare the performance of eigenvalue-based signal detectors designed for IEEE 802.22Wireless Regional Area Network (WRAN). Two eigenvalue techniques were studied, which are the eigenvalue decomposition (EVD) and singular value decomposition (SVD). Both techniques were implemented on Matlab as detection algorithms. Using Monte Carlo simulations, we tested the algorithms to compare their performance. We also adopted the maximum-minimum eigenvalue threshold method as the decision statistic for detecting signals. The tests were done for their ability to detect signal, receiver operating characteristics, expected performance, robustness and computational complexity. Empirically, the performance of SVD technique found to be better compared to the EVD technique.