A Scalable QoS-Aware Service Aggregation Model for Peer-to-Peer Computing Grids
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
Adaptive Offloading Inference for Delivering Applications in Pervasive Computing Environments
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
QoS-Assured Service Composition in Managed Service Overlay Networks
ICDCS '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Grid resource management
Adaptive Offloading for Pervasive Computing
IEEE Pervasive Computing
The Journal of Supercomputing
Disruption-aware service composition and recovery in dynamic networking environments
Proceedings of the 2007 workshop on Automating service quality: Held at the International Conference on Automated Software Engineering (ASE)
Minimum disruption service composition and recovery in mobile ad hoc networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
A tentative model for virtualized resource-aware dynamic media-oriented service composition
CFI '09 Proceedings of the 4th International Conference on Future Internet Technologies
A semantic approach for building pervasive spaces
Proceedings of the 6th Middleware Doctoral Symposium
ZebraX: a model for service composition with multiple QoS constraints
GPC'07 Proceedings of the 2nd international conference on Advances in grid and pervasive computing
Low-complexity unequal packet loss protection for real-time video over ubiquitous networks
ICCSA'07 Proceedings of the 2007 international conference on Computational science and its applications - Volume Part I
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Ubiquitous computing promotes the proliferation of various stationary, embedded and mobile devices interconnected by heterogeneous networks. It leads to a highly dynamic distributed system with many devices and services coming and going frequently. Many emerging distributed multimedia applications are being deployed in such a computing environment. In order to make the experience for a user truly seamless and to provide soft performanceguarantees, we must meet the following challenges: (1) users should be able to perform tasks continuously, despite changes of resources, devices and locations; (2) users should be able to efficiently utilize all accessible resources within runtime environments to receive the best possible Quality-of-Service (QoS). In this paper, we propose an integrated QoS-aware service configuration model to address the above problems. The configuration model includes twotiers: (1) service composition tier, which is responsible for choosing and composing current available service components appropriately and coordinating arbitrary interactions between them to achieve the user's objectives; and (2) service distribution tier, which is responsible for dividing an application into several partitions and distributing them to different available devices appropriately. Our initial ex-perimental results based on both prototype and simulationsshow the soundness of our model and algorithms.