Parameter-sweep has been widely adopted in large numbers of scientific applications. Parameter-sweep features need to be incorporated into grid workflows so as to increase the scale and scope of such applications. New...
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Parameter-sweep has been widely adopted in large numbers of scientific applications. Parameter-sweep features need to be incorporated into grid workflows so as to increase the scale and scope of such applications. New scheduling mechanisms and algorithms are required to provide optimized policy for resource allocation and task arrangement in such a case. This paper addresses scheduling sequential parameter-sweep tasks in a fine-grained manner. The optimization is produced by pipelining the subtasks and dispatching each of them onto well-selected resources. Two types of scheduling algorithms are discussed and customized to adapt the characteristics of parameter-sweep, as well as their effectiveness has been compared under multifarious scenarios.
Over the last few years, grid technologies have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on utility computing models. Users consume these services based on th...
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Over the last few years, grid technologies have progressed towards a service-oriented paradigm that enables a new way of service provisioning based on utility computing models. Users consume these services based on their QoS (quality of service) requirements. In such "pay-per-use" grids, workflow execution cost must be considered during scheduling based on users' QoS constraints. In this paper, we propose a cost-based workflow scheduling algorithm that minimizes execution cost while meeting the deadline for delivering results. It can also adapt to the delays of service executions by rescheduling unexecuted tasks. We also attempt to optimally solve the task scheduling problem in branches with several sequential tasks by modeling the branch as a Markov decision process and using the value iteration method
Mobile medical applications have the capacity to provide services for patients and healthcare professionals regardless of time or place. The aim of this paper is to explore the current status of mobile, wireless and w...
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Mobile medical applications have the capacity to provide services for patients and healthcare professionals regardless of time or place. The aim of this paper is to explore the current status of mobile, wireless and wearable technological applications within the medical environment. After conducting a literature review on the availability of mobile, wireless and wearable computing applications within medicine, a summary of their purpose, features and functions was conceptually mapped to the Gibson and Nolan (1974) Stages of Growth Framework. Findings from the literature, the mapping process and limitations for growth are discussed within each of the technology categories. Limitations and challenges of development are highlighted and suggestions are made for future research.
computersystems hosting critical e-commerce applications must typically satisfy stringent quality-of-service (QoS) requirements under dynamic operating conditions and workloads. Also, as such systems increase in size...
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Feedback control real-time scheduling (FCS) aims at satisfying performance specifications of real-time systems based on adaptive resource management. Existing FCS algorithms often rely on the existence of continuous c...
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Feedback control real-time scheduling (FCS) aims at satisfying performance specifications of real-time systems based on adaptive resource management. Existing FCS algorithms often rely on the existence of continuous control variables in real-time systems. A number of real-time systems, however, support only a finite set of discrete configurations that limit the adaptation mechanisms. This paper presents hybrid supervisory utilization control (HySUCON) for scheduling such real-time systems. HySUCON enforces processor utilization bounds by managing the switchings between the discrete configurations. Our approach is based on a best-first-search algorithm that is invoked only if reconfiguration is necessary. Theoretical analysis and simulations demonstrate that the approach leads to robust utilization bounds for varying execution times. Experimental results demonstrate the algorithm performance for a representative application scenario.
Grid and peer-to-peer (P2P) network technologies enable aggregation of distributed resources for solving large-scale and computationally-intensive applications. These technologies are well-suited for bag-of-tasks (BoT...
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Grid and peer-to-peer (P2P) network technologies enable aggregation of distributed resources for solving large-scale and computationally-intensive applications. These technologies are well-suited for bag-of-tasks (BoT) applications, because each application consists of many parallel and independent tasks. With multiple users competing for the same resources, the key challenge is to finish a user application within a specified deadline. In this paper, we propose a time optimization algorithm that schedules a user application on auction-based resource allocation systems. These allocation systems, which are based on proportional share, allow users to bid higher in order to gain more resource shares. Therefore, this algorithm adjusts a user bid periodically on these systems in order to finish the application on time.
Autonomic computersystems react to changes in the system, including failures, load changes, and changed user behaviour. Autonomic control may be based on a performance model of the system and the software, which impl...
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Autonomic computersystems react to changes in the system, including failures, load changes, and changed user behaviour. Autonomic control may be based on a performance model of the system and the software, which implies that the model should track changes in the system. A substantial theory of optimal tracking filters has a successful history of application to track parameters while integrating data from a variety of sources, an issue which is also relevant in performance modeling. This work applies extended Kalman filtering to track the parameters of a simple queueing network model, in response to a step change in the parameters. The response of the filter is affected by the way performance measurements are taken, and by the observability of the parameters.
Data mining has proven a successful gateway for discovering useful knowledge and for enhancing business intelligence in a range of application fields. Incorporating this knowledge into already deployed applications, t...
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Data mining has proven a successful gateway for discovering useful knowledge and for enhancing business intelligence in a range of application fields. Incorporating this knowledge into already deployed applications, though, is highly impractical, since it requires reconfigurable software architectures, as well as human expert consulting. In an attempt to overcome this deficiency, we have developed agent academy, an integrated development framework that supports both design and control of multiagent systems (MAS), as well as agent training. We define agent training as the automated incorporation of logic structures generated through data mining into the agents of the system. The increased flexibility and cooperation primitives of MAS, augmented with the training and retraining capabilities of agent academy, provide a powerful means for the dynamic exploitation of data mining extracted knowledge. In this paper, we present the methodology and tools for agent retraining. Through experimental results with the agent academy platform, we demonstrate how the extracted knowledge can be formulated and how retraining can lead to the improvement - in the long run - of agent intelligence.
This article addresses the generation of traces to monitor the execution of distributed Java systems, and investigates the use of aspect-oriented programming (AOP) as the instrumentation strategy to get the necessary ...
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This article addresses the generation of traces to monitor the execution of distributed Java systems, and investigates the use of aspect-oriented programming (AOP) as the instrumentation strategy to get the necessary information at runtime. The overall objective is to gather enough information to help people understand program executions by abstracting out design details related to thread and distributed communications, for instance under the form of UML sequence diagrams. We show how AspectJ, the main Java implementation of AOP, can be used to solve such issues, assuming RMI is the distribution middleware and thread communications employ specific data structures. The most important aspects are discussed and experiments on a case study are reported.
Security critical systems must perform at the required security level, make effective use of available resources, and meet end-users expectations. Balancing these needs, and at the same time fulfilling budget and time...
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