One of the major constraints of wireless sensor networks is limited energy available to sensor nodes because of the small size of the batteries they use as source of power. Clustering is one of the routing techniques ...
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One of the major constraints of wireless sensor networks is limited energy available to sensor nodes because of the small size of the batteries they use as source of power. Clustering is one of the routing techniques that have been using to minimize sensor nodes’ energy consumption during operation. In this paper, A Novel Clustering Algorithm for Energy Efficiency in Wireless Sensor Networks (ANCAEE) has been proposed. The algorithm achieves good performance in terms of minimizing energy consumption during data transmission and energy consumptions are distributed uniformly among all nodes. ANCAEE uses a new method of clusters formation and election of cluster heads. The algorithm ensures that a node transmits its data to the cluster head with a single hop transmission and cluster heads forward their data to the base station with multi-hop transmissions. Simulation results show that our approach consumes less energy and effectively extends network utilization.
Efficient scheduling is a key concern for the effectual execution of performance driven grid applications, such as workflows. Many list heuristics have been developed for scheduling workflows in centralized grid envir...
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In this paper, a reputation-based grid workflow scheduling algorithm is proposed to counter the effect of inherent unreliability and temporal characteristics of computing resources in large scale, decentralized grid o...
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Metaschedulers can distribute parts of a bag-of-tasks (BoT) application among various resource providers in order to speed up its execution. When providers cannot disclose private information such as their load and co...
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Metaschedulers can distribute parts of a bag-of-tasks (BoT) application among various resource providers in order to speed up its execution. When providers cannot disclose private information such as their load and computing power, which are usually heterogeneous, the metascheduler needs to make blind scheduling decisions. We propose three policies for composing resource offers to schedule deadline-constrained BoT applications. Offers act as a mechanism in which resource providers expose their interest in executing an entire BoT or only part of it without revealing their load and total computing power. We also evaluate the amount of information resource providers need to expose to the metascheduler and its impact on the scheduling. Our main findings are: (i) offer-based scheduling produces less delay for jobs that cannot meet deadlines in comparison to scheduling based on load availability (i.e. free time slots); thus it is possible to keep providers' load private when scheduling multi-site BoTs; and (ii) if providers publish their total computing power they can have more local jobs meeting deadlines.
Peering of Content Delivery Networks (CDNs) allow providers to rapidly scale-out to meet both flash crowds and anticipated increases in demand. Recent trends foster the need for a utility model for content delivery se...
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Peering of Content Delivery Networks (CDNs) allow providers to rapidly scale-out to meet both flash crowds and anticipated increases in demand. Recent trends foster the need for a utility model for content delivery services to provide transparency, high availability, reduced investment cost, and improved content delivery performance. Analysis of prior work reveals only a modest progress in evaluating the utility for peering CDNs. In this paper, we introduce a utility model and measure the content-serving ability of the peering CDNs system. Our model assists in providing a customer view of the system's health for different traffic types. Our model also captures the traffic activities in the system and helps to reveal the true propensities of participating CDNs to cooperate in peering. Through extensive simulations we unveil many interesting observations on how the utility of the peering CDNs system is varied for different system parameters and provide incentives for their exploitation in the system design.
Cloud resource providers in a market face dynamic and unpredictable consumer behavior. The way, how prices are set in a dynamic environment, can influence the demand behavior of price sensitive customers. A cloud reso...
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ISBN:
(纸本)9781424446469;9780769537559
Cloud resource providers in a market face dynamic and unpredictable consumer behavior. The way, how prices are set in a dynamic environment, can influence the demand behavior of price sensitive customers. A cloud resource provider has to decide on how to allocate his scarce resources in order to maximize his profit. The application of bid price control for evaluating incoming service requests is a common approach for capacity control in network revenue management. In this paper we introduce a customized version of the concept of self-adjusting bid prices and apply it to the area of cloud computing. Furthermore, we perform a simulation in order to test the efficiency of the proposed model.
With the growth of Utility grids and various grid market infrastructures, the need for efficient and cost effective scheduling algorithms is also increasing rapidly, particularly in the area of meta-scheduling. In the...
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distributedsystems emulators built with the aid of virtualization tools allow testing of systems in a testbed whose number of real elements are orders of magnitude smaller than the number of virtual elements being te...
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distributedsystems emulators built with the aid of virtualization tools allow testing of systems in a testbed whose number of real elements are orders of magnitude smaller than the number of virtual elements being tested. However, to allow testers to benefit from these systems, operation of the virtual environment should be hidden from them and performed automatically by the emulator. Moreover, testers may be unsure on the exact needs of their environment, and thus can request an environment that does not fit the experiment. In this paper we present our achievements in providing an emulation framework able to provide environment reconfiguration if the requested one does not comply with experiment's demands. Also, it supplies services such as execution log, environment monitoring, and automatic management of applications running in the virtual environment.
Scientific applications like neuroscience data analysis are usually compute and data-intensive. With the use of globally distributed resources and suitable middlewares, we can achieve much shorter execution time, dist...
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Scientific applications like neuroscience data analysis are usually compute and data-intensive. With the use of globally distributed resources and suitable middlewares, we can achieve much shorter execution time, distribute compute and storage load, and add greater flexibility to the execution of these scientific applications than we could ever achieve in a single compute *** this paper, we present the processing of image registration (IR) for functional magnetic resonance imaging(fMRI) studies on global grids. We characterize the application, list its requirements and transform it to a workflow. We then execute the application on gridpsila5000 platform and present extensive performance results. We show that the IR application can have 1) significantly improved makespan, 2) distribution of compute and storage load among resources used, and 3) flexibility when executing multiple times on global grids.
Efficient scheduling is a key concern for the effectual execution of performance driven grid applications, such as workflows. Many list heuristics have been developed for scheduling workflows in centralized grid envir...
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Efficient scheduling is a key concern for the effectual execution of performance driven grid applications, such as workflows. Many list heuristics have been developed for scheduling workflows in centralized grid environment. However, in this paper, we present a distributed list heuristic for decentralized scheduling of workflow applications in global grids. The simulation results show that the proposed scheduling approach is scalable with respect to increased workload on the system.
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