David Abramson

Nimrod/G: an architecture for a resource management and scheduling system in a global computational grid

The availability of powerful microprocessors and high-speed networks as commodity components has enabled high-performance computing on distributed systems (wide-area cluster computing). In this environment, as the resources are usually distributed geographically at various levels (department, enterprise or worldwide), there is a great challenge in integrating, coordinating and presenting them as a single resource to the user, thus forming a computational grid. Another challenge comes from the distributed ownership of resources, with each resource having its own access policy, cost and mechanism. The proposed Nimrod/G grid-enabled resource management and scheduling system builds on our earlier work on Nimrod (D. Abramson et al., 1994, 1995, 1997, 2000) and follows a modular and component-based architecture enabling extensibility, portability, ease of development, and interoperability of independently developed components. It uses the GUSTO (GlobUS TOolkit) services and can be easily extended to operate with any other emerging grid middleware services. It focuses on the management and scheduling of computations over dynamic resources scattered geographically across the Internet at department, enterprise or global levels, with particular emphasis on developing scheduling schemes based on the concept of computational economy for a real testbed, namely the Globus testbed (GUSTO).

Economic models for resource management and scheduling in Grid computing

The accelerated development in peer‐to‐peer and Grid computing has positioned them as promising next‐generation computing platforms. They enable the creation of virtual enterprises for sharing resources distributed across the world. However, resource management, application development and usage models in these environments is a complex undertaking. This is due to the geographic distribution of resources that are owned by different organizations or peers. The resource owners of each of these resources have different usage or access policies and cost models, and varying loads and availability. In order to address complex resource management issues, we have proposed a computational economy framework for resource allocation and for regulating supply and demand in Grid computing environments. This framework provides mechanisms for optimizing resource provider and consumer objective functions through trading and brokering services. In a real world market, there exist various economic models for setting the price of services based on supply‐and‐demand and their value to the user. They include commodity market, posted price, tender and auction models. In this paper, we discuss the use of these models for interaction between Grid components to decide resource service value, and the necessary infrastructure to realize each model. In addition to usual services offered by Grid computing systems, we need an infrastructure to support interaction protocols, allocation mechanisms, currency, secure banking and enforcement services. We briefly discuss existing technologies that provide some of these services and show their usage in developing the Nimrod‐G grid resource broker. Furthermore, we demonstrate the effectiveness of some of the economic models in resource trading and scheduling using the Nimrod/G resource broker, with deadline and cost constrained scheduling for two different optimization strategies, on the World‐Wide Grid testbed that has resources distributed across five continents. Copyright

High performance parametric modeling with Nimrod/G: killer application for the global grid?

This paper examines the role of parametric modeling as an application for the global computing grid, and explores some heuristics which make it possible to specific soft real time deadlines for larger computational experiments. We demonstrate the scheme with a case study utilizing the Globus toolkit running on the GUSTO testbed.

The Grid Economy

This work identifies challenges in managing resources in a Grid computing environment and proposes computational economy as a metaphor for effective management of resources and application scheduling. It identifies distributed resource management challenges and requirements of economy-based Grid systems, and discusses various representative economy-based systems, both historical and emerging, for cooperative and competitive trading of resources such as CPU cycles, storage, and network bandwidth. It presents an extensive, service-oriented Grid architecture driven by Grid economy and an approach for its realization by leveraging various existing Grid technologies. It also presents commodity and auction models for resource allocation. The use of commodity economy model for resource management and application scheduling in both computational and data grids is also presented.

Scheduling Aircraft Landings--The Static Case

In this paper, we consider the problem of scheduling aircraft (plane) landings at an airport. This problem is one of deciding a landing time for each plane such that each plane lands within a predetermined time window and that separation criteria between the landing of a plane and the landing of all successive planes are respected. We present a mixed-integer zero--one formulation of the problem for the single runway case and extend it to the multiple runway case. We strengthen the linear programming relaxations of these formulations by introducing additional constraints. Throughout, we discuss how our formulations can be used to model a number of issues (choice of objective function, precedence restrictions, restricting the number of landings in a given time period, runway workload balancing) commonly encountered in practice. The problem is solved optimally using linear programming-based tree search. We also present an effective heuristic algorithm for the problem. Computational results for both the heuristic and the optimal algorithm are presented for a number of test problems involving up to 50 planes and four runways.

Nimrod: a tool for performing parametrised simulations using distributed workstations

This paper discusses Nimrod, a tool for performing parametrised simulations over networks of loosely coupled workstations. Using Nimrod the user interactively generates a parametrised experiment. Nimrod then controls the distribution of jobs to machines and the collection of results. A simple graphical user interface which is built for each application allows the user to view the simulation in terms of their problem domain. The current version of Nimrod is implemented above OSF DCE and runs on DEC Alpha and IBM RS6000 workstations (including a 22 node SP2). Two different case studies are discussed as an illustration of the utility of the system.

Computational Science — ICCS 2003

Numerical simulation of industrial crystal growth is difficult due to its multidisciplinary nature and complex geometry of real-life growth equipment. An attempt is made to itemize physical phenomena dominant in different methods for growth of bulk crystals from melt and from vapour phase and to review corresponding numerical approaches. Academic research and industrial applications are compared. Development of computational engine and graphic user interface of industryoriented codes is discussesd. In conclusion, a simulator for the entire growth process of bulk crystals by sublimation method is described.

An Evaluation of Economy-based Resource Trading and Scheduling on Computational Power Grids for Parameter Sweep Applications

Computational Grids are becoming attractive and promising platforms for solving large-scale (problem solving) applications of multi-institutional interest. However, the management of resources and scheduling computations in the Grid environment is a complex undertaking as they are (geographically) distributed, heterogeneous in nature, owned by different individuals or organisations with their own policies, different access and cost models, and have dynamically varying loads and availability. This introduces a number of challenging issues such as site autonomy, heterogeneous substrate, policy extensibility, resource allocation or co-allocation, online control, scalability, transparency, and “economy of computations”. Some of these issues are being addressed by system-level Grid middleware toolkits such as Globus.

Economic models for management of resources in peer-to-peer and grid computing

The accelerated development in Peer-to-Peer (P2P) and Grid computing has positioned them as promising next generation computing platforms. They enable the creation of Virtual Enterprises (VE) for sharing resources distributed across the world. However, resource management, application development and usage models in these environments is a complex undertaking. This is due to the geographic distribution of resources that are owned by different organizations or peers. The resource owners of each of these resources have different usage or access policies and cost models, and varying loads and availability. In order to address complex resource management issues, we have proposed a computational economy framework for resource allocation and for regulating supply and demand in Grid computing environments. The framework provides mechanisms for optimizing resource provider and consumer objective functions through trading and brokering services. In a real world market, there exist various economic models for setting the price for goods based on supply-and-demand and their value to the user. They include commodity market, posted price, tenders and auctions. In this paper, we discuss the use of these models for interaction between Grid components in deciding resource value and the necessary infrastructure to realize them. In addition to normal services offered by Grid computing systems, we need an infrastructure to support interaction protocols, allocation mechanisms, currency, secure banking, and enforcement services. Furthermore, we demonstrate the usage of some of these economic models in resource brokering through Nimrod/G deadline and cost-based scheduling for two different optimization strategies on the World Wide Grid (WWG) testbed that contains peer-to-peer resources located on five continents: Asia, Australia, Europe, North America, and South America.

Displacement problem and dynamically scheduling aircraft landings

In this paper we define a generic decision problem — the displacement problem. The displacement problem arises when we have to make a sequence of decisions and each new decision that must be made has an explicit link back to the previous decision that was made. This link is quantified by means of the displacement function. One situation where the displacement problem arises is that of dynamically scheduling aircraft landings at an airport. Here decisions about the landing times for aircraft (and the runways they land on) must be taken in a dynamic fashion as time passes and the operational environment changes. We illustrate the application of the displacement problem to the dynamic aircraft landing problem. Computational results are presented for a number of publicly available test problems involving up to 500 aircraft and five runways.