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Large scale Grid computing systems are often organized as an inter-Grid architecture, where multiple Grid domains are interconnected through their local broker. In this context, the main challenge is to devise appropriate job scheduling policies that can satisfy goals such as global load balancing together with maintaining the local policies of the different Grids. This paper presents SLICK, a scalable...
Federated Grid resources typically span multiple administrative domains and utilize heterogeneous schedulers. This complexity complicates not only provisioning of quality of service but also management and enforcement of end-user resource utilization allocations. to overcome these problems, we propose to combine high-level meta-scheduling techniques with lower-level fairs hare prioritization mechanisms...
Design of scheduling algorithms for a heterogeneous computing system interconnected with an arbitrary communication network is one of the actual concerns in distributed systems research, due to the heterogeneous nature of resource, computing capacity, memory, devices, internet and institutional policies. Multi-agent systems have been a nice option of solution because of its distributed nature, autonomy,...
The new Italian GPS receiver for Radio Occultation has been launched from Satish Dhawan Space Center (Sriharikota, India) on board of the Indian Remote Sensing OCEANSAT-2 satellite. The Italian Space Agency has established a set of Italian universities and research centers to develop an infrastructure based on hybrid architecture, that is implemented for the overall processing Radio Occultation chain...
The rapidly spreading cloud computing paradigm delegates to the network the provision of most resources, even those strictly linked to hardware as storage and CPU time. This approach enables the development of applications which may exploit a variable amount of resources in a flexible way, so as to satisfy the actual load of requests coming from the users. A side effect of such flexibility is that...
This paper introduces the existing connectivity and interoperability issues of Clouds, Grids and Clusters, and provides solutions to overcome these issues. The paper proposes several possible solution variants how to pool Cloud resources for executing bag of tasks type jobs. It presents two implementations based on BOINC and Condor. It details performance measurement results obtained by executing...
Cloud computing has been build upon the development of distributed computing, grid computing and virtualization. Since cost of each task in cloud resources is different with one another, scheduling of user tasks in cloud is not the same as in traditional scheduling methods. The objective of this paper is to schedule task groups in cloud computing platform, where resources have different resource costs...
The huge data requirements of large nowadays applications in science and engineering make optimised and scalable data placement mechanisms an essential need. For this purpose, we propose a scheduling scheme based on an efficient data locality management for data-intensive workflows. Transfer and placement decisions are made based on constructions in the workflow, representing inter-relationships between...
Grid computing aims at offering standardized access to heterogeneous and distributed resources for scientific communities. However, in order to support emerging next generation Grid applications with specific Quality of Service requirements, the interconnecting networks have also been considered as first-class allocable Grid resources and have been also taken into account for the co-scheduling process...
The execution of workflow oriented applications for eScience should be based on efficient solutions for available resource monitoring and scheduling by revising the allocation solution at the task level based on requirements of subsequent tasks. The PEGAF project aims at providing a platform for workflow oriented applications development and execution, implementing adaptive scheduling strategies....
This paper presents a new approach of the Semantically Enhanced Resource Allocation (SERA) distributed as a multi-agent system. It presents a distributed resource allocation process which combines the benefits of semantic web for making easier the integration between multiple resource providers in the Cloud and agent technologies for coordinating and adapting the execution accross the different providers...
The emerging computational grid infrastructure consists of widely distributed heterogeneous resources, which makes mapping of increasingly complex applications a very challenging task. Utility Management Systems (UMS) manage large number of workflows with high resource requirements and thereby optimization of resource utilization has to be adapted. In this work we propose the architecture that implements...
The SORMSYS project's main goal is to optimize resource management in large scale distributed systems with the capability of self-organization. This paper will present the design of management architecture based on existing middleware solutions through the design of algorithms and methods inspired by natural models. The architecture is full decentralized and it will aim to optimize resource management...
This paper focuses on grid performance optimization in large scale workflow applications with an intelligent workflow scheduling mechanism. Utility Management Systems (UMS) are managing very large numbers of workflows with very high resource requirements. This paper proposes a UMS scheduling architecture which dynamically executes a scheduling algorithm using near real-time feedback about the current...
Meta-scheduling is proven to be an essential tool for resource management in cross-domain environments like Grids. This paper takes one step further in combining meta-scheduling with application management tool to present a novel multi-domain cloud environment for biological research. With the scalable architecture and stable performance, Community Scheduler Framework (CSF) is a mature meta-scheduler...
Data Grid integrates graphically distributed resources for solving data sensitive scientific applications. The main issues in data grid are task scheduling and data management. As data grid spans multiple organization areas, it makes centralized resource management difficult. Therefore, it is necessary to study decentralized resource management. In this paper, a decentralized architecture of integration...
Grid Computing is a widespread distributed computing environment that consists of heterogeneous resources and it provides huge computational power for the large scale distributed application. In this job scheduling is an essential objective to prioritize the jobs based on the job characteristics. It is a big challenge to design and implement an efficient Job Scheduling algorithm and the Job Scheduling...
This paper designs the ScGridBroker as an scheduler of ScGrid that uses grid technology for managing large-scale distributed resources based on Economic Scheduling Algorithms. It discusses a layered and component-oriented modular architecture for the broker design and development. The architecture is generic enough to leverage services provided by various Grid middleware systems such as Globus, Legion,...
Grid computing deals with computationally intensive distributed resources on heterogeneous environment, so grid scheduling is a fundamental challenge and is critical to performance and cost. Traditional grid scheduling algorithms most use deterministic models. But grid environments in the real world are subject to many sources of uncertainty or randomness, such as network status, job execution costs,...
The mobility issue in grid environments has established new challenges to the research communities particularly in the areas of scheduling, adaptation, security and mobility. Especially, the resource allocation becomes more challenging when mobility is considered in grid environment. Hence it is necessary to consider the mobility of users along with the resource availability while scheduling the resources...
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