Workload Modeling for Performance Evaluation
Performance Evaluation of Complex Systems: Techniques and Tools, Performance 2002, Tutorial Lectures
P2P '01 Proceedings of the First International Conference on Peer-to-Peer Computing
The Economic Rationale of Offering Media Files in Peer-to-Peer Networks
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 7 - Volume 7
An Empirical Analysis of Network Externalities in Peer-to-Peer Music-Sharing Networks
Information Systems Research
Analyzing Market-Based Resource Allocation Strategies for the Computational Grid
International Journal of High Performance Computing Applications
Scheduling for reduced CPU energy
OSDI '94 Proceedings of the 1st USENIX conference on Operating Systems Design and Implementation
Power-aware optimization of CPU and frequency allocation based on fairness of QoS
Systems and Computers in Japan
A Measurement-Based Method for Improving Data Center Energy Efficiency
SUTC '08 Proceedings of the 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008)
GECON'07 Proceedings of the 4th international conference on Grid economics and business models
MPaaS: Mobility prediction as a service in telecom cloud
Information Systems Frontiers
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The explosion of user generated data along with the evolution of web 2.0 applications (e.g. social networks, blogs, podcasts, etc.) has resulted in a tremendous demand for storage. With cloud computing posing as a possible all-in-one solution, "storage clouds" focus on providing distributed storage capability. We discuss the creation of a storage cloud using edge devices, based on Peer-to-Peer resource provisioning. In this approach, mobile phones, PCs/Media Centers, Set-top-boxes, modems and networked storage devices can all contribute as storage within these storage clouds. Combining all end-user edge devices may result in a scalable, very flexible storage capability that keeps the data comparatively close to the user, increasing availability, while reducing latency. This work addresses the issue of Quality of Service (QoS)-aware scheduling in a P2P storage cloud, built with edge devices by designing an optimization scheme that minimizes energy from a system perspective and simultaneously maximizing user satisfaction from the individual user perspective.