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Computing and Information Systems - Research Publications
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ItemAdaptive threshold-based approach for energy-efficient consolidation of virtual machines in cloud data centersBeloglazov, A ; Buyya, R (ACM, 2010-11-29)
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ItemA Taxonomy of CDNsPathan, M ; Buyya, R ; Buyya, R ; Pathan, M ; Vakali, A (SPRINGER, 2008)
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ItemSensor web: Integration of sensor networks with web and cyber infrastructureKobialka, T ; Buyya, R ; Deng, P ; Kulik, L ; Palaniswami, M (IGI Global, 2010-12-01)As sensor network deployments grow and mature there emerge a common set of operations and transformations. These can be grouped into a conceptual framework called Sensor Web. Sensor Web combines cyber infrastructure with a Service Oriented Architecture (SOA) and sensor networks to provide access to heterogeneous sensor resources in a deployment independent manner. In this chapter we present the Open Sensor Web Architecture (OSWA), a platform independent middleware for developing sensor applications. OSWA is built upon a uniform set of operations and standard data representations as defined in the Sensor Web Enablement Method (SWE) by the Open Geospatial Consortium (OGC). OSWA uses open source and grid technologies to meet the challenging needs of collecting and analyzing observational data and making it accessible for aggregation, archiving and decision making.
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ItemDecentralized overlay for federation of enterprise cloudsRanjan, R ; Buyya, R (IGI Global, 2009-12-01)This chapter describes Aneka-Federation, a decentralized and distributed system that combines enterprise Clouds, overlay networking, and structured peer-to-peer techniques to create scalable wide-area networking of compute nodes for high-throughput computing. The Aneka-Federation integrates numerous small scale Aneka Enterprise Cloud services and nodes that are distributed over multiple control and enterprise domains as parts of a single coordinated resource leasing abstraction. The system is designed with the aim of making distributed enterprise Cloud resource integration and application programming flexible, efficient, and scalable. The system is engineered such that it: enables seamless integration of existing Aneka Enterprise Clouds as part of single wide-area resource leasing federation; self-organizes the system components based on a structured peer-to-peer routing methodology; and presents end-users with a distributed application composition environment that can support variety of programming and execution models. This chapter describes the design and implementation of a novel, extensible and decentralized peer-to-peer technique that helps to discover, connect and provision the services of Aneka Enterprise Clouds among the users who can use different programming models to compose their applications. Evaluations of the system with applications that are programmed using the Task and Thread execution models on top of an overlay of Aneka Enterprise Clouds have been described here.
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ItemScheduling parallel applications on Utility Grids: Time and cost trade-off managementGarg, SK ; Buyya, R ; Siegel, HJ (Australian Computer Society, 2009-12-01)
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ItemEnergy-efficient management of data center resources for cloud computing: A vision, architectural elements, and open channelsBuyya, RB ; BELOGLAZOV, A ; Abawajy, J (World Academy of Science, Engineering and Technology, 2010)Cloud computing is offering utility-oriented IT services to users worldwide. Based on a pay-as-you-go model, it enables hosting of pervasive applications from consumer, scientific, and business domains. However, data centers hosting Cloud applications consume huge amounts of energy, contributing to high operational costs and carbon footprints to the environment. Therefore, we need Green Cloud computing solutions that can not only save energy for the environment but also reduce operational costs. This paper presents vision, challenges, and architectural elements for energy-efficient management of Cloud computing environments. We focus on the development of dynamic resource provisioning and allocation algorithms that consider the synergy between various data center infrastructures (i.e., the hardware, power units, cooling and software), and holistically work to boost data center energy efficiency and performance. In particular, this paper proposes (a) architectural principles for energy-efficient management of Clouds; (b) energy-efficient resource allocation policies and scheduling algorithms considering quality-of-service expectations, and devices power usage characteristics; and (c) a novel software technology for energy-efficient management of Clouds. We have validated our approach by conducting a set of rigorous performance evaluation study using the CloudSim toolkit. The results demonstrate that Cloud computing model has immense potential as it offers significant performance gains as regards to response time and cost saving under dynamic workload scenarios.
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ItemA Particle Swarm Optimization-based Heuristic for Scheduling Workflow Applications in Cloud Computing EnvironmentsPandey, S ; Wu, L ; Guru, SM ; Buyya, R (IEEE COMPUTER SOC, 2010)
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ItemWorkflow Scheduling Algorithms for Grid ComputingYu, J ; Buyya, R ; Ramamohanarao, K ; Xhafa, F ; Abraham, A (SPRINGER-VERLAG BERLIN, 2008)
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ItemScheduling parameter sweep applications on global Grids: A deadline and budget constrained cost-time optimization algorithmBuyya, R ; Murshed, M ; Abramson, D ; Venugopal, S (Wiley, 2005)Computational Grids and peer-to-peer (P2P) networks enable the sharing, selection, and aggregation of geographically distributed resources for solving large-scale problems in science, engineering, and commerce. The management and composition of resources and services for scheduling applications, however, becomes a complex undertaking. We have proposed a computational economy framework for regulating the supply of and demand for resources and allocating them for applications based on the users' quality-of-service requirements. The framework requires economy-driven deadline- and budget-constrained (DBC) scheduling algorithms for allocating resources to application jobs in such a way that the users' requirements are met. In this paper, we propose a new scheduling algorithm, called the DBC cost-time optimization scheduling algorithm, that aims not only to optimize cost, but also time when possible. The performance of the cost-time optimization scheduling algorithm has been evaluated through extensive simulation and empirical studies for deploying parameter sweep applications on global Grids.
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ItemAn SCP-based heuristic approach for scheduling distributed data-intensive applications on global gridsVenugopal, S ; Buyya, R (ACADEMIC PRESS INC ELSEVIER SCIENCE, 2008-04)
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