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Writing parallel applications for computational grids is a challenging task. To achieve good performance, algorithms designed for local area networks must be adapted to the differences in link speeds. An important class of algorithms are collective operations, such as broadcast and reduce. We have developed MAGPIE, a library of collective communication operations optimized for wide area systems. MAGPIE's algorithms send the minimal amount of data over the slow wide area links, and only incur a single wide area latency. Using our system, existing MPI applications can be run unmodified on geographically distributed systems. On moderate cluster sizes, using a wide area latency of 10 milliseconds and a bandwidth of 1 MByte/s, MAGPIE executes operations up to 10 times faster than MPICH, a widely used MPI implementation; application kernels improve by up to a factor of 4. Due to the structure of our algorithms, MAGPIE's advantage increases for higher wide area latencies.

The Computational Grid provides a promising platform for the efficient execution of parameter sweep applications over very large parameter spaces. Scheduling such applications is challenging because target resources are heterogeneous, because their load and availability varies dynamically, and because independent tasks may share common data files. In this paper, we propose an adaptive scheduling algorithm for parameter sweep applications on the Grid. We modify standard heuristics for task/host assignment in perfectly predictable environments (Max-min, Min-min, Sufferage), and we propose an extension of Sufferage called XSufferage. Using simulation, we demonstrate that XSufferage can take advantage of file sharing to achieve better performance than the other heuristics. We also study the impact of inaccurate performance prediction on scheduling. Our study shows that: (i) different heuristics behave differently when predictions are inaccurate; (ii) increased adaptivity leads to better performance.

Advances in networking technologies will soon make it possible to use the global information infrastructure in a qualitatively different way—as a computational resource as well as an information resource. This idea for an integrated computation and information resource called the Computational Power Grid has been described by the recent book entitled The Grid: Blueprint for a New Computing Infrastructure [18]. The Grid will connect the nation’s computers, databases, instruments, and people in a seamless web, supporting emerging computation-rich application concepts such as remote computing, distributed supercomputing, tele-immersion, smart instruments, and data mining. To realize this vision, significant scientific and technical obstacles must be overcome. Principal among these is usability. Because the Grid will be inherently more complex than existing computer systems, programs that execute on the Grid will reflect some of this complexity. Hence, making Grid resources useful and accessible to scientists and engineers will require new software tools that embody major advances in both the theory and practice of building Grid applications. The goal of the Grid Application Development Software (GrADS) Project is to simplify distributed heterogeneous computing in the same way that the World Wide Web simplified information sharing

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The growing computational power requirements of grand challenge applications has promoted the need for linking highperformance computational resources distributed across multiple organisations. This is fueled by the availability of the Internet as a ubiquitous commodity communication media, low cost high-performance machines such as clusters across multiple organ isations, and the rise of scientific problems of multi-organisational interest. The availability of expensive, special class of scientific instruments or devices and data sources in few organisations has increased the interest in offering a remote access to these resources. The recent popularity of coupling (local and remote) computational resources, special class of scientific instruments, and data sources across the Internet for solving problems has led to the emergence of a new platform called "Computational Grid". This paper identifies the issues in resource management and scheduling driven by computational economy in the...

Advances in hardware and software technologies have made it possible to deploy parallel applications over increasingly large sets of distributed resources. Consequently, the study of scheduling algorithms for such applications has been an active area of research. Given the nature of most scheduling problems one must resort to simulation to effectively evaluate and compare their efficacy over a wide range of scenarios. It has thus become necessary to simulate those algorithms for increasingly complex distributed, dynamic, heterogeneous environments. In this paper we present Simgrid, a simulation toolkit for the study of scheduling algorithms for distributed application. This paper gives the main concepts and models behind Simgrid, describes its API and highlights current implementation issues. We also give some experimental results and describe work that builds on Simgrid's functionalities. 1.

Cloud computing systems fundamentally provide access to large pools of data and computational resources through a variety of interfaces similar in spirit to existing grid and HPC resource management and programming systems. These types of systems offer a new programming target for scalable application developers and have gained popularity over the past few years. However, most cloud computing systems in operation today are proprietary, rely upon infrastructure that is invisible to the research community, or are not explicitly designed to be instrumented and modified by systems researchers. In this work, we present EUCALYPTUS – an opensource software framework for cloud computing that implements what is commonly referred to as Infrastructure as a Service (IaaS); systems that give users the ability to run and control entire virtual machine instances deployed across a variety physical resources. We outline the basic principles of the EUCALYPTUS design, detail important operational aspects of the system, and discuss architectural trade-offs that we have made in order to allow Eucalyptus to be portable, modular and simple to use on infrastructure commonly found within academic settings. Finally, we provide evidence that EUCALYPTUS enables users familiar with existing Grid and HPC systems to explore new cloud computing functionality while maintaining access to existing, familiar application development software and Grid middle-ware. 1

Trust is a fundamental concern in large-scale open distributed systems. It lies at the core of all interactions between the entities that have to operate in such uncertain and constantly changing environments. Given this complexity, these components, and the ensuing system, are increasingly being conceptualised, designed, and built using agent-based techniques and, to this end, this paper examines the specific role of trust in multi-agent systems. In particular,

Abstract—This paper surveys and analyzes the state of the art of agent-mediated electronic commerce (e-commerce), concentrating particularly on the business-to-consumer (B2C) and business-to-business (B2B) aspects. From the consumer buying behavior perspective, agents are being used in the following activities: need identification, product brokering, buyer coalition formation, merchant brokering, and negotiation. The roles of agents in B2B e-commerce are discussed through the business-to-business transaction model that identifies agents as being employed in partnership formation, brokering, and negotiation. Having identified the roles for agents in B2C and B2B e-commerce, some of the key underpinning technologies of this vision are highlighted. Finally, we conclude by discussing the future directions and potential impediments to the wide-scale adoption of agent-mediated e-commerce. Index Terms—Agent-mediated electronic commerce, intelligent agents. 1