Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Adaptive wireless thin-client model for mobile computing
AU - Al-Turkistany, M.
AU - Helal, Sumi
AU - Schmalz, M.
PY - 2009/1
Y1 - 2009/1
N2 - The thin-client computing model has the potential to significantly increase the performance of mobile computing environments. By delivering any application through a single, small-footprint client (called a thin client) implemented on a mobile device, it is possible to optimize application performance without the need for building wireless application gateways. We thus present two significant contributions in the area of wireless thin-client computing. Firstly, a mathematical performance model is derived for wireless thin-client system. This model identifies factors that affect the performance of the system and supports derivation and analysis of adaptation strategies to maintain a user-specified quality of service (QoS). Secondly, a proxy-based adaptation framework is developed for wireless thin-client systems, which dynamically optimizes performance of a wireless thin client via dynamically discovered context. This is implemented with rule-based fuzzy logic that responds to variations in wireless link bandwidth and client processing power. Our fuzzy inference engine uses contextual data to dynamically optimize tradeoffs among different quality of service parameters offered to the end users. Additionally, our adaptation framework uses highly scalable wavelet-based image coding to provide scalable QoS that can degrade gracefully. Our thin-client adaptation framework shields the user from ill effects of highly variable wireless network quality and mobile device resources. This improves performance of active applications, in which the display changes frequently. Further, active application behaviour may produce high transmission latency for screen updates, which can adversely affect user perception of QoS, resulting in poor interactivity. We report measured adaptive performance under realistic mobile device and network conditions for several different clients and servers. Copyright © 2008 John Wiley & Sons, Ltd.
AB - The thin-client computing model has the potential to significantly increase the performance of mobile computing environments. By delivering any application through a single, small-footprint client (called a thin client) implemented on a mobile device, it is possible to optimize application performance without the need for building wireless application gateways. We thus present two significant contributions in the area of wireless thin-client computing. Firstly, a mathematical performance model is derived for wireless thin-client system. This model identifies factors that affect the performance of the system and supports derivation and analysis of adaptation strategies to maintain a user-specified quality of service (QoS). Secondly, a proxy-based adaptation framework is developed for wireless thin-client systems, which dynamically optimizes performance of a wireless thin client via dynamically discovered context. This is implemented with rule-based fuzzy logic that responds to variations in wireless link bandwidth and client processing power. Our fuzzy inference engine uses contextual data to dynamically optimize tradeoffs among different quality of service parameters offered to the end users. Additionally, our adaptation framework uses highly scalable wavelet-based image coding to provide scalable QoS that can degrade gracefully. Our thin-client adaptation framework shields the user from ill effects of highly variable wireless network quality and mobile device resources. This improves performance of active applications, in which the display changes frequently. Further, active application behaviour may produce high transmission latency for screen updates, which can adversely affect user perception of QoS, resulting in poor interactivity. We report measured adaptive performance under realistic mobile device and network conditions for several different clients and servers. Copyright © 2008 John Wiley & Sons, Ltd.
KW - Mobile computing models
KW - Mobility adaptations
KW - Thin-client model
KW - Applications
KW - Fuzzy inference
KW - Fuzzy logic
KW - Image coding
KW - Mobile devices
KW - Network performance
KW - Object recognition
KW - Portable equipment
KW - Quality control
KW - Quality of service
KW - Telecommunication equipment
KW - Telecommunication systems
KW - Visual communication
KW - Wireless networks
KW - Active applications
KW - Adaptation frameworks
KW - Adaptation strategies
KW - Application performance
KW - Device resources
KW - End users
KW - Fuzzy inference engines
KW - High transmissions
KW - Interactivity
KW - Mathematical performance
KW - Mobile computing environments
KW - Network conditions
KW - Processing power
KW - Quality of Service parameters
KW - Rule-based
KW - Thin-client computing
KW - Thin-client systems
KW - User perceptions
KW - Wavelet-based image coding
KW - Wireless applications
KW - Wireless links
KW - Mobile computing
U2 - 10.1002/wcm.603
DO - 10.1002/wcm.603
M3 - Journal article
VL - 9
SP - 47
EP - 59
JO - Wireless Communications and Mobile Computing
JF - Wireless Communications and Mobile Computing
SN - 1530-8669
IS - 1
ER -