@conference {12388,
	title = {CASPER: an integrated energy-driven approach for task graph scheduling on distributed embedded systems},
	booktitle = {Application-Specific Systems, Architecture Processors, 2005. ASAP 2005. 16th IEEE International Conference on},
	year = {2005},
	month = {2005/07//},
	pages = {191 - 197},
	abstract = {For multiprocessor embedded systems, the dynamic voltage scaling (DVS) technique can be applied to scheduled applications for energy reduction. DVS utilizes slack in the schedule to slow down processes and save energy. Therefore, it is generally believed that the maximal energy saving is achieved on a schedule with the minimum makespan (maximal slack). Most current approaches treat task assignment, scheduling, and DVS separately. In this paper, we present a framework called CASPER (combined assignment, scheduling, and power-management) that challenges this common belief by integrating task scheduling and DVS under a single iterative optimization loop via genetic algorithm. We have conducted extensive experiments to validate the energy efficiency of CASPER. For homogeneous multiprocessor systems (in which all processors are of the same type), we consider a recently proposed slack distribution algorithm (PDP-SPM) by S. Hua and G. Qu (2005): applying PDP-SPM on the schedule with the minimal makespan gives an average of 53.8\% energy saving; CASPER finds schedules with slightly larger makespan but a 57.3\% energy saving, a 7.8\% improvement. For heterogeneous systems, we consider the power variation DVS (PV-DVS) algorithm by Schmitz et al. (2004), CASPER improves its energy efficiency by 8.2\%. Finally, our results also show that the proposed single loop CASPER framework saves 23.3\% more energy over GMA+EE-GLSA by Schmitz et al. (2002), the only other known integrated approach with a nested loop that combines scheduling and power management in the inner loop but leaves assignment in the outer loop.},
	keywords = {CASPER, combined-assignment-scheduling-and-power-management, computational complexity, distributed system, dynamic voltage scaling, embedded systems, energy reduction, genetic algorithm, Genetic algorithms, graph theory, homogeneous multiprocessor system, maximal energy saving, Multiprocessing systems, multiprocessor embedded system, optimization loop, power management, power variation, Processor scheduling, slack distribution algorithm, task assignment, task graph scheduling},
	doi = {10.1109/ASAP.2005.23},
	author = {Kianzad,V. and Bhattacharyya, Shuvra S. and Gang Qu}
}
@conference {17892,
	title = {A high performance multi-perspective vision studio},
	booktitle = {Proceedings of the 17th annual international conference on Supercomputing},
	series = {ICS {\textquoteright}03},
	year = {2003},
	month = {2003///},
	pages = {348 - 357},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {We describe a multi-perspective vision studio as a flexible high performance framework for solving complex image processing and machine vision problems on multi-view image sequences. The studio abstracts multi-view image data from image sequence acquisition facilities, stores and catalogs sequences in a high performance distributed database, allows customization of back-end processing services, and can serve custom client applications, thus helping make multi-view video sequence processing efficient and generic. To illustrate our approach, we describe two multi-perspective studio applications, and discuss performance and scalability results.},
	keywords = {database, distributed system, high-performance, IMAGE PROCESSING, multi-perspective, VISION, volumetric reconstruction},
	isbn = {1-58113-733-8},
	doi = {10.1145/782814.782862},
	url = {http://doi.acm.org/10.1145/782814.782862},
	author = {Borovikov,Eugene and Sussman, Alan}
}
@conference {17575,
	title = {Clustering and server selection using passive monitoring},
	booktitle = {IEEE INFOCOM 2002. Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings},
	volume = {3},
	year = {2002},
	month = {2002///},
	pages = {1717- 1725 vol.3 - 1717- 1725 vol.3},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We consider the problem of client assignment in a distributed system of content servers. We present a system called Webmapper for clustering IP addresses and assigning each cluster to an optimal content server. The system is passive in that the only information it uses comes from monitoring the TCP connections between the clients and the servers. It is also flexible in that it makes no a priori assumptions about network topology and server placement and it can react quickly to changing network conditions. We present experimental results to evaluate the performance of Webmapper.},
	keywords = {client assignment, client-server systems, clustering, content servers, Delay, distributed system, Educational institutions, Internet, IP addresses, Monitoring, network conditions, Network servers, Network topology, optimal content server, passive monitoring, server selection, Space technology, TCPIP, Transport protocols, Web pages, Web server, Webmapper},
	isbn = {0-7803-7476-2},
	doi = {10.1109/INFCOM.2002.1019425},
	author = {Andrews,M. and Shepherd,B. and Srinivasan, Aravind and Winkler,P. and Zane,F.}
}
