Jeffrey A. Frey

Modeling and Managing State in Distributed Systems: The Role of OGSI and WSRF

We often encounter in distributed systems the need to model, access, and manage state. This state may be, for example, data in a purchase order, service level agreements representing resource availability, or the current load on a computer. We introduce two closely related approaches to modeling and manipulating state within a Web services (WS) framework: the Open Grid Services Infrastructure (OGSI) and WS-Resource Framework (WSRF). Both approaches define conventions on the use of the Web service definition language schema that enable the modeling and management of state. OGSI introduces the idea of a stateful Web service and defines approaches for creating, naming, and managing the lifetime of instances of services; for declaring and inspecting service state data; for asynchronous notification of service state change; for representing and managing collections of service instances; and for common handling of service invocation faults. WSRF refactors and evolves OGSI to exploit new Web services standards, specifically WS-addressing, and to respond to early implementation and application experiences. WSRF retains essentially all of the functional capabilities present in OGSI, while changing some syntax (e.g., to exploit WS-addressing) and also adopting a different terminology in its presentation. In addition, WSRF partitions OGSI functionality into five distinct composable specifications. We explain the relationship between OGSI and WSRF and the related WS-notification specifications, explain the common requirements that both address, and compare and contrast the approaches taken to the realization of those requirements.

Combining workstations and supercomputers to support grid applications: the parallel tomography experience

Computational grids are becoming an increasingly important and powerful platform for the execution of large-scale, resource-intensive applications. However, it remains a challenge for applications to tap into the potential of grid resources in order to achieve performance. In this paper, we illustrate how work queue applications can leverage grids to achieve performance through coallocation. We describe our experiences in developing a scheduling strategy for a production tomography application targeted at grids that contain both workstations and parallel supercomputers. Our strategy uses dynamic information exported by a supercomputers batch scheduler to simultaneously schedule tasks on workstations and immediately-available supercomputer nodes. This strategy is of great practical interest because it combines resources that are available in a typical research laboratory: time-shared workstations and CPU time in remote space-shared supercomputers. We show that this strategy improves the performance of the tomography application compared to traditional scheduling strategies, which target the application to either type of resource alone.

IBM unified resource manager introduction and overview

The IBM zEnterprise® 196 processor complex has been complemented with the zEnterprise System z® BladeCenter® Extension, a modular system structure that is capable of hosting native IBM POWER7® system and IBM System x® processing blades. The Unified Resource Manager has been introduced to provide integrated and advanced hardware and virtualization management capabilities. Together, these components work to form the basis of an integrated hybrid system architecture capable of hosting multitier heterogeneous business workloads, reducing operational complexity, and providing workload-aware optimization of the information technology infrastructure. This paper provides a descriptive overview of the major components of the IBM Unified Resource Manager.