Browsing by Author "Tan, Guan Z."

Now showing 1 - 7 of 7
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    Analysis of MS Power Saving Scheme to BS with Finite Buffer in IEEE 802.16e Network
    (IEEE, 2011) Mushi, Joseph C.; Tan, Guan Z.; Cheruiyot, Wilson; Musau, Felix
    This paper analyzes effects of power saving of mobile station (MS) to Base Station with finite buffer in IEEE802.16e class type I network. IEEE802.16e standard accept MS to switch to sleep-mode to minimize power when MS processing load is reduced. However, when packets destined to MS appear into BS buffer, they should be stored until end of MS sleep window. Although the sleep-mode designed in effort to conserve environment but it risks loss of packets once BS buffer overloaded with accumulated packets. This paper designs numerical analytic model to measure risk of packet drop. Through asymptotic analysis the effect of packets destined to sleeping MS into BS finite buffer is measured and analysed.
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    Enhanced Model for SaaS Delivery in Developing Economy
    (2011) Mushi, Joseph C.; Tan, Guan Z.; Cheruiyot, Wilson
    The emerging of cloud computing has brought about new hope for adoption and use of computer-based information system. Software as a Service (SaaS) allows online customers to use applications on the Internet on a pay-as-you-go basis without investing in new infrastructure or software license. However, the current SaaS pay-as-you-go phenomenon brings challenge to online customers in developing economy where financial services are poor to support online payments. This paper studies data and monetary service aspects of mobile network operator and use the concepts to propose a model which facilitate pay-as-you-go phenomenon through mobile monetary service (M-banking).
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    Genetic Algorithm-Enhanced Retrieval Process for Multimedia Data
    (2011) Cheruiyot, Wilson; Tan, Guan Z.; Mushi, Joseph C.; Musau, Felix
    The explosive growth of digital media content from various domains has given rise to the need for efficient techniques for retrieval of relevant information is getting more and more attention, especially in the large-scale Multimedia Digital Database (MDD) applications. It is for this reason that there has been an increased interest in the query reformulation for use in Multimedia Information Retrieval (MIR) using a combination of various techniques. In this paper, we propose a retrieval method that is formalized as an optimized similarity search process that combines Singular Value Decomposition (SVD), Query Quality Refinement (QQR) using Histogram Equalization and Genetic Algorithm (GA) enhancement. Experimental results show that the approach significantly narrows the search process by retrieving similar images satisfying the needs of the user.
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    Modeling M-SaaS delivery model for threshold-based credit recharging using M-banking
    (IEEE, 2011) Mushi, Joseph C.; Tan, Guan Z.; Musau, Felix; Cheruiyot, Wilson
    The emerging of cloud computing has brought about new hope for efficient adoption and use of computer- based information system. Software as a Service (SaaS) allows online customers to use applications on the Internet on a pay- as-you-go basis without investing in new infrastructure or software license. However, current SaaS delivery model bring challenge to online customers in community with poor financial services like online bank-transaction or credit cards. This study proposes Mobile-SaaS delivery model to facilitate online charging and credit-recharging mechanisms for SaaS application. The model use mobile-phone monetary services (M-banking) to support online charging, and adopts threshold-based credit recharge technique to support credit recharging. Keywords-software as a service (SaaS), mobile network, M- banking, online recharging.
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    Performance Analysis of Recharging Scheme of M-SaaS through M-banking
    (2011) Mushi, Joseph C.; Tan, Guan Z.; Musau, Felix; Wilson, Cheruiyot
    Mobile SaaS (M-SaaS) is SaaS delivery model designed to use mobile network infrastructure for reserving and recharging credits of SaaS usage in pay-as-you-go manner for areas with poor financial services. The model integrates M-banking monetary feature into delivery process of SaaS so that potential customers in areas with poor access to financial services, such as online banking and credit cards, participate in SaaS delivery in real-time payment manner. In this paper, we present numerical analysis of M-SaaS recharging process, which together with M-SaaS credit-reservation scheme make M-SaaS model. The analysis shows that utilization and throughput of components involved in the scheme are healthy to avoid interruption of their involvement in other mobile network activities. However, load distribution at equilibrium leads to great imbalance, which needs further study for usefulness of M-SaaS model to revel.
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    SO-Antnet for Improving Load Sharing in MANET
    (2009) Mushi, Joseph C.; Tan, Guan Z.
    SO-Antnet introduces new idea of load balancing over mobile ad-hoc networks based on intelligent agents inspired by organic metaphor of ants' food foraging behavior. With inspiration from Antnet approach, this study improves theoretical derivation of objective function by consider contribution of all four characteristics of ants' foraging behavior to achieve Self-Organization of a system. The study uses this objective function to optimize operation of intelligent agents, which collect information in mobile ad-hoc networks, to help the node to optimize route-cache contents and means of finding optimal path to particular destination. The study implements operational behavior of SO-Antnet by customizes DSR routing protocol modules in network simulator NS2. One major difference with other related work is that SO-Antnet simulation considers really cache implementation. Simulation results are compared with DSR performance, which show improvement in load balancing.
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    Using Genetic Algorithms to Optimize Web Caching in Multimedia-Integrated e-Learning Content
    (2011) Kipruto, Cheruiyot W.; Tan, Guan Z.; Musau, Felix; Mushi, Joseph C.
    The evolution of e-learning as a new information technology built around the use of internet has originated new possibilities to develop pedagogical methodologies that provide the necessary knowledge and skills in the higher education environment. This has in effect given rise to a large number of learners who desire to access the educational resources provided by the new technology. But for many institutions of higher learning, the users often experiences poor performance when they try to access contents or download e-learning files. The main reasons for such are often performance problems concerning network infrastructure and the fact that many people tend to access the same piece of information repetitively. This paper uses web caching scheme and genetic algorithm optimization to effectively lessen this service bottleneck, diminish the user access latency and reduce the network traffic.