The resource management system is the central component of distributed network computing systems. There have been many projects focused on network computing that have designed and implemented resource management systems with a variety of architectures and services. In this paper, an abstract model and a comprehensive taxonomy for describing resource management architectures is developed. The taxonomy is used to identify approaches followed in the implementation of existing resource management systems for very large-scale network computing systems known as Grids. The taxonomy and the survey results are used to identify architectural approaches and issues that have not been fully explored in the research. Copyright © 2001 John Wiley & Sons, Ltd.

A taxonomy and survey of grid resource management systems for distributed computing

Computational Grids, emerging as an infrastructure for next generation computing, enable the sharing, selection, and aggregation of geographically distributed resources for solving large-scale problems in science, engineering, and commerce. As the resources in the Grid are heterogeneous and geographically distributed with varying availability and a variety of usage and cost policies for diverse users at different times and, priorities as well as goals that vary with time. The management of resources and application scheduling in such a large and distributed environment is a complex task. This thesis proposes a distributed computational economy as an effective metaphor for the management of resources and application scheduling. It proposes an architectural framework that supports resource trading and quality of services based scheduling. It enables the regulation of supply and demand for resources and provides an incentive for resource owners for participating in the Grid and motives the users to trade-off between the deadline, budget, and the required level of quality of service. The thesis demonstrates the capability of economic-based systems for peer-to-peer distributed computing by developing users' quality-of-service requirements driven scheduling strategies and algorithms. It demonstrates their effectiveness by performing scheduling experiments on the World-Wide Grid for solving parameter sweep applications.

Economic-based Distributed Resource Management and Scheduling for Grid Computing

Global computing achieves high throughput computing by harvesting a very large number of unused computing resources connected to the Internet. This parallel computing model targets a parallel architecture defined by a very high number of nodes, poor communication performance and continuously varying resources. The unprecedented scale of the global computing architecture paradigm requires us to revisit many basic issues related to parallel architecture programming models, performance models, and class of applications or algorithms suitable for this architecture. XtremWeb is an experimental global computing platform dedicated to provide a tool for such studies. The paper presents the design of XtremWeb. Two essential features of this design are multi-applications and high-performance. Accepting multiple applications allows institutions or enterprises to set up their own global computing applications or experiments. High-performance is ensured by scalability, fault tolerance, efficient scheduling and a large base of volunteer PCs. We also present an implementation of the first global application running on XtremWeb.

XtremWeb: a generic global computing system

In this introductory chapter, we lay the groundwork for the rest of the book by providing a more detailed picture of the expected purpose, shape, and architecture of future grid systems. We structure the chapter in terms of six questions that we believe are central to this discussion: Why do we need computational grids? What types of applications will grids be used for? Who will use grids? How will grids be used? What is involved in building a grid? And, what problems must be solved to make grids commonplace? We provide an overview of each of these issues here, referring to subsequent chapters for more detailed discussion.

Computational grids

This paper presents the gSOAP stub and skeleton compiler. The compiler provides a unique SOAP-to-C/C++ language binding for deploying C/C++ applications in SOAP Web Services, clients, and peer-to-peer computing networks. gSOAP enables the integratation of (legacy) C/C++/Fortran codes, embedded systems, and real-time software in Web Services, clients, and peers that share computational resources and information with other SOAP-enabled applications, possibly across different platforms, language environments, and disparate organizations located behind firewalls. Results on interoperability, legacy code integration, scalability, and performance are given.

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The gSOAP Toolkit for Web Services and Peer-to-Peer Computing Networks

The JAVM (Java Astra Virtual Machine) project is about harnessing the immense computational resource available in the Internet for parallel processing. In this paper, the suitability of Java for Internet-based parallel computing is explored. Next, existing implementations of systems that make use of Java for network parallel computing are presented and categorized. A critique of these implementations follows. Basing on the critique, the requirements and goals of an effective parallel computing system in the Internet environment are singled out. These serve as the blueprint for the development of the JAVM system. Its infrastructure and features, namely ease of use, heterogeneity, portability, security, fault tolerance, load balancing, scalability and accountability, are discussed. Lastly, experimental results based on the running of several parallel applications in the JAVM environment are presented. Basing on the results, the kind of parallel applications that would be well suited for running in JAVM are identified.

Javelin: Internet-based parallel computing using Java

Javelin is a Java-based infrastructure for global computing. This paper presents Javelin++, an extension of Javelin, intended to support a much larger set of computational hosts. Contributions to scalability and fault tolerance are presented. This is the focus of the paper. Two scheduling schemes are presented: probabilistic work stealing and deterministic work stealing. The distributed deterministic work stealing is integrated with a distributed deterministic eager scheduler, which is one of the paper's primary original contributions. An additional fault tolerance mechanism is implemented for replacing hosts that have failed or retreated. A Javelin++ API is sketched, then illustrated on a raytracing application. Performance results for the two schedulers are reported, indicating that Javelin++, with its broker network, scales better than the original Javelin. Copyright © 2000 John Wiley & Sons, Ltd.

Javelin++: scalability issues in global computing

This paper presents Javelin 2.0. It presents architectural enhancements that facilitate aggregating larger sets of host processors. It then presents: a branch-and-bound computational model, the supporting architecture, a scalable task scheduler using distributed work stealing, a distributed eager scheduler implementing fault tolerance, and the results of performance experiments. Javelin 2.0 frees application developers from concerns about complex interprocessor communication and fault tolerance among Internetworked hosts. When all or part of their application can be cast as a piecework or a branch-and-bound computation, Javelin 2.0 allows developers to focus on the underlying application.

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Javelin 2.0: Java-Based Parallel Computing on the Internet

Javelin: parallel computing on the internet

Recent advances in Internet connectivity and implementations of safer distributed computing through languages such as Java provide the foundation for transforming computing resources into tradable commodities. We have developed Javelin, a Java-based prototype of a globally distributed heterogeneous, high-performance computational infrastructure that conveniently enables rapid execution of massively parallel applications. Our infrastructure consists of three entities: Hosts, clients, and brokers. Our goal is to allow users to buy and sell computational power using supply and demand, and market mechanisms to marshal computational power far beyond what can be achieved via conventional techniques. Several research issues must be worked out to make this vision a reality: allocating resources between computational objects via market mechanisms; expressing and enforcing scheduling and quality of service constraints; modeling programming in a global computing ecosystem; supporting heterogeneous execution without sacrificing computational speed; ensuring host security; global naming and communication; and client privacy.

Michael O. Neary

Papers

Javelin: Internet-based parallel computing using Java

Javelin++: scalability issues in global computing

Javelin 2.0: Java-Based Parallel Computing on the Internet

Javelin: parallel computing on the internet

Market-based massively parallel Internet computing