@conference {17843,
	title = {Decentralized dynamic scheduling across heterogeneous multi-core desktop grids},
	booktitle = {2010 IEEE International Symposium on Parallel \& Distributed Processing, Workshops and Phd Forum (IPDPSW)},
	year = {2010},
	month = {2010/04/19/23},
	pages = {1 - 9},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The recent advent of multi-core computing environments increases both the heterogeneity and complexity of managing desktop grid resources, making efficient load balancing challenging even for a centralized manager. Even with good initial job assignments, dynamic scheduling is still needed to adapt to dynamic environments, as well as for applications whose running times are not known a priori. In this paper, we propose new decentralized scheduling schemes that backfill jobs locally and dynamically migrate waiting jobs across nodes to leverage residual resources, while guaranteeing bounded waiting times for all jobs. The methods attempt to maximize total throughput while balancing load across available grid resources. Experimental results via simulation show that our scheduling scheme has performance competitive with an online centralized scheduler.},
	keywords = {backfill jobs, bounded waiting time, Computer science, decentralized dynamic scheduling, desktop grid resource management, Dynamic scheduling, Educational institutions, Environmental management, grid computing, heterogeneous multicore desktop grid, job assignment, job migration, load balancing, Load management, multicore computing environment, Peer to peer computing, Processor scheduling, residual resources, resource allocation, Resource management, scheduling, Scheduling algorithm, Throughput},
	isbn = {978-1-4244-6533-0},
	doi = {10.1109/IPDPSW.2010.5470877},
	author = {Jaehwan Lee and Keleher,P. and Sussman, Alan}
}
@conference {15684,
	title = {Dynamic load balancing across mirrored multimedia servers},
	booktitle = {2003 International Conference on Multimedia and Expo, 2003. ICME {\textquoteright}03. Proceedings},
	volume = {2},
	year = {2003},
	month = {2003/07/06/9},
	pages = {II- 53-6 vol.2 - II- 53-6 vol.2},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The purpose of this paper is to present protocols for efficient load balancing across replicated multimedia servers in a metropolitan area network. Current multimedia infrastructures, even when they use mirrored servers, do not have standardized load balancing schemes. Existing schemes frequently require participation from the clients in balancing the load across the servers efficiently. We propose two protocols in this paper for fair load balancing without any client-side processing being required. Neither protocol requires any change to the network-level infrastructure. Using network packet loss and packet transmission delay as the chief metrics, we show the effectiveness of the protocols through extensive simulations.},
	keywords = {client-server systems, Delay, Internet, load balancing protocols, Load management, media streaming, metropolitan area network, metropolitan area networks, mirrored multimedia servers, Multimedia communication, multimedia servers, network packet loss, Network servers, packet transmission delay, Propagation losses, Protocols, Streaming media, Topology, Traffic control, Web server},
	isbn = {0-7803-7965-9},
	doi = {10.1109/ICME.2003.1221551},
	author = {Matthur,A. and Mundur, Padma}
}
@article {14805,
	title = {A tool to help tune where computation is performed},
	journal = {IEEE Transactions on Software Engineering},
	volume = {27},
	year = {2001},
	month = {2001/07//},
	pages = {618 - 629},
	abstract = {We introduce a new performance metric, called load balancing factor (LBF), to assist programmers when evaluating different tuning alternatives. The LBF metric differs from traditional performance metrics since it is intended to measure the performance implications of a specific tuning alternative rather than quantifying where time is spent in the current version of the program. A second unique aspect of the metric is that it provides guidance about moving work within a distributed or parallel program rather than reducing it. A variation of the LBF metric can also be used to predict the performance impact of changing the underlying network. The LBF metric is computed incrementally and online during the execution of the program to be tuned. We also present a case study that shows that our metric can accurately predict the actual performance gains for a test suite of six programs},
	keywords = {Computational modeling, Current measurement, Distributed computing, distributed program, distributed programming, load balancing factor, Load management, parallel program, parallel programming, Performance analysis, performance evaluation, Performance gain, performance metric, Programming profession, software metrics, software performance evaluation, Testing, Time measurement, tuning},
	isbn = {0098-5589},
	doi = {10.1109/32.935854},
	author = {Eom, Hyeonsang and Hollingsworth, Jeffrey K}
}
@conference {17640,
	title = {Optimal design of signaling networks for Internet telephony},
	booktitle = {IEEE INFOCOM 2000. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings},
	volume = {2},
	year = {2000},
	month = {2000///},
	pages = {707-716 vol.2 - 707-716 vol.2},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We present an approach for efficient design of a signaling network for a network of software switches supporting Internet telephony. While one may take an integer programming approach to solve this problem, it quickly becomes intractable even for modest-sized networks. Instead, our topology design uses random graphs that we show to be nearly optimal in cost, highly connected, and computationally efficient even for large networks. We then formulate a quadratic assignment problem (QAP) to map the abstract topology into the physical network to achieve optimal load balancing for given demand forecasts, which we solve using randomized heuristics. Numerical results on several example networks illustrate the performance and computational efficiency of our method. A graphical design tool has been developed based on our algorithms},
	keywords = {bandwidth allocation, Computational efficiency, Computer networks, Cost function, Demand forecasting, demand forecasts, graph theory, graphical design tool, Internet telephony, Linear programming, Load forecasting, Load management, Network topology, optimal design, optimal load balancing, optimisation, performance, quadratic assignment problem, random graphs, randomised algorithms, randomized heuristics, Signal design, signaling networks, Switches, telecommunication signalling, topology design},
	isbn = {0-7803-5880-5},
	doi = {10.1109/INFCOM.2000.832245},
	author = {Srinivasan, Aravind and Ramakrishnan,K. G and Kumaran,K. and Aravamudan,M. and Naqvi,S.}
}
@conference {15691,
	title = {Integrated admission control in hierarchical video-on-demand systems},
	booktitle = {IEEE International Conference on Multimedia Computing and Systems, 1999},
	volume = {1},
	year = {1999},
	month = {1999/07//},
	pages = {220-225 vol.1 - 220-225 vol.1},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We develop a unified model of a hierarchical video-on-demand (VoD) system by integrating the storage and the network subsystems. Rather than restricting the analysis to an isolated subsystem the performance of the VoD system is analyzed as an end-to-end system. On a system-wide basis, request handling and admission control policies are designed to minimize global performance metrics. Through our simulation, we compare different request handling policies and show that a hierarchical VoD architecture with request handling that allows retrials at more than one resource will minimize overall blocking},
	keywords = {Admission control, Bandwidth, blocking, Computer science, Design methodology, end-to-end system, hierarchical video-on-demand systems, integrated admission control, Intelligent networks, Load management, Motion pictures, Network servers, network subsystem, performance, Performance analysis, performance evaluation, quality of service, request handling, resource allocation, Resource management, simulation, storage subsystem, video on demand, video servers},
	isbn = {0-7695-0253-9},
	doi = {10.1109/MMCS.1999.779196},
	author = {Mundur, Padma and Simon,R. and Sood,A.}
}
@conference {14784,
	title = {LBF: a performance metric for program reorganization},
	booktitle = {18th International Conference on Distributed Computing Systems, 1998. Proceedings},
	year = {1998},
	month = {1998/05/26/29},
	pages = {222 - 229},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We introduce a new performance metric, called Load Balancing Factor (LBF), to assist programmers with evaluating different tuning alternatives. The LBF metric differs from traditional performance metrics since it is intended to measure the performance implications of a specific tuning alternative rather than quantifying where time is spent in the current version of the program. A second unique aspect of the metric is that it provides guidance about moving work within a distributed or parallel program rather than reducing it. A variation of the LBF metric can also be used to predict the performance impact of changing the underlying network. The LBF metric can be computed incrementally and online during the execution of the program to be tuned. We also present a case study that shows that our metric can predict the actual performance gains accurately for a test suite of six programs},
	keywords = {case study, Computational modeling, computer network, Computer science, Debugging, distributed processing, distributed program, Educational institutions, Integrated circuit testing, LBF metric, load balancing factor, Load management, measurement, NIST, parallel program, parallel programming, performance metric, program reorganization, program tuning, Programming profession, resource allocation, software metrics, software performance evaluation, US Department of Energy},
	isbn = {0-8186-8292-2},
	doi = {10.1109/ICDCS.1998.679505},
	author = {Eom, H. and Hollingsworth, Jeffrey K}
}
