Efficient data transfer in broadband networks is the anchor point of digital economy in modern era. One of the most challenging issues for providing different services in broadband is the bandwidth allocation. That is a realtime... more
Efficient data transfer in broadband networks is the anchor point of digital economy in modern era. One of the most challenging issues for providing different services in broadband is the bandwidth allocation. That is a realtime multi-dimensional problem solving requiring to satisfy QoS and SLA constraints at the same time. This problem is economically defined as a utility optimization issue aiming to maximize user profits. In this paper, we present an adaptive framework for the problem of optimal utility optimization of bandwidth allocation to broadband services. We used first an online optimization for the allocation based on user preferences and Network Utility Maximization. Our second solution is a particle swarm optimization method in order to consider both parameters at the same time to find an optimal allocation pattern. Simulation results showed satisfactory bandwidth allocation patterns in different scenarios according to the network utility and user preferences in SLA.
Efficient data transfer in broadband networks is the anchor point of digital economy in modern era. One of the most challenging issues for providing different services in broadband is the bandwidth allocation. That is a real-time... more
Efficient data transfer in broadband networks is the anchor point of digital economy in modern era. One of the most challenging issues for providing different services in broadband is the bandwidth allocation. That is a real-time multi-dimensional problem solving requiring to satisfy QoS and SLA constraints at the same time. This problem is economically defined as a utility optimization issue aiming to maximize user profits. In this paper, we present an adaptive framework for the problem of optimal utility optimization of bandwidth allocation to broadband services. We used first an online optimization for the allocation based on user preferences and Network Utility Maximization. Our second solution is a particle swarm optimization method in order to consider both parameters at the same time to find an optimal allocation pattern. Simulation results showed satisfactory bandwidth allocation patterns in different scenarios according to the network utility and user preferences in SLA.
Content delivery via High-Speed Broadband Fiber-to-the-Home Services in Malaysia has yet to improve the Quality of Experience of the average subscribers as static contents, program menus, and channel packages delivered cannot address... more
Content delivery via High-Speed Broadband Fiber-to-the-Home Services in Malaysia has yet to improve the Quality of Experience of the average subscribers as static contents, program menus, and channel packages delivered cannot address relevant and personalized contents to diversified subscribers in their needs and goals. Furthermore there is no common open service platform to integrate contents from licensed service providers and independent content providers alike. The objective of this research is to examine an open access network strategy that can improve the Quality of Service delivered and increase the level of Quality of Experience of the subscribers. The Open Access Network strategy will allow subscriber the freedom to select any service provider on the network. The deployment of an open-access based Active Optic Networks (AON) Fiber-To-The-Home model to individual homes enable subscribers to personalize and customize contents based on personal preference in real-time. Content...
Improvements in technology have led to generating and mining huge amounts of data. Sequence mining is a research area of data mining that aims to extract useful knowledge from raw databases. Although transactions with numerical... more
Improvements in technology have led to generating and mining huge amounts of data. Sequence mining is a research area of data mining that aims to extract useful knowledge from raw databases. Although transactions with numerical information are usually seen in real-world applications like bank records, customer baskets and network traffic records, and efforts for mining sequential patterns with quantitative values are reported in the technical literature, the issue of privacy of sensitive knowledge in the form of fuzzy sequential patterns has not received much attention. This paper addresses the problem of fuzzy sequential pattern hiding and proposes a multi-objective optimization procedure with few distortions which leads to the preserving of database fidelity. The proposed algorithm can also work with fuzzy databases and more details are handled by fuzzy sets. Distortions, fidelity and time-consumption of the proposed algorithm are three criteria used to compare the performance of it with the existing algorithms.