Shared resource

About: Shared resource is a research topic. Over the lifetime, 7536 publications have been published within this topic receiving 123491 citations. The topic is also known as: network share.

Pure exchange markets for resource sharing in federated clouds

Abstract: Cloud Computing is the latest paradigm proposed toward fulfilling the vision of computing being delivered as an utility such as phone, electricity, gas and water services. It enables users to have access to computing infrastructure, platform and software as services over the Internet. The services can be accessed on demand and from anywhere in the world in a quick and flexible manner, and charged for based on their usage, making the rapid and often unpredictable expansion demanded by nowadays' business environment affordable also for small spin-off and start-up companies. In order to be competitive, however, Cloud providers need to be able to adapt to the dynamic loads from users, not only optimizing the local usage and costs but also engaging into agreements with other Clouds so as to complement local capacity. The infrastructure in which competing Clouds are able to cooperate to maximize their benefits is called a Federated Cloud. Just as Clouds enable users to cope with unexpected demand loads, a Federated Cloud will enable individual Clouds to cope with unforeseen variations of demand. The definition of the mechanism to ensure mutual benefits for the individual Clouds composing the federation, however, is one of its main challenges. This paper proposes and investigates the application of market-oriented mechanisms based on the General Equilibrium Theory of Microeconomics to coordinate the sharing of resources between the Clouds in the Federated Cloud. Copyright © 2010 John Wiley & Sons, Ltd.

Efficient spare-resource allocation for fast restoration of real-time channels from network component failures

Abstract: Since real-time applications usually require not only timeliness but also fault-tolerance, it is essential to incorporate fault-tolerance into real-time communication services that are indispensable to distributed real-time applications. The techniques for failure recovery in datagram communication are not adequate for real-time communication, because they cannot provide recovery-delay guarantees. To ensure fast recovery of a real-time channel from network component failures, we need to reserve network resources (spare resources) along a backup route before failures actually occur. The focus of this paper is on minimizing the amount of spare resources while meeting the fault-tolerance requirement. Specifically, we present resource sharing mechanisms and backup-route selection algorithms, and evaluate their efficiency with extensive simulations.

Method and apparatus for controlling exclusive access to a shared resource in a data storage system

Abstract: A method for controlling exclusive access to a resource shared by multiple processors in a data storage system includes providing a system lock procedure to permit a processor to obtain a lock on the shared resource preventing other processors from accessing the shared resource and providing a faked lock procedure to indicate to the system lock procedure that a processor has a lock on the shared resource where such a lock does not exist, and wherein the faked lock procedure prevents another processor from obtaining the lock on the shared resource, but does not prevent other processors from accessing the shared resource. A data storage system according to the invention includes a shared resource, a plurality of processors coupled to the shared resource through a communication channel, and a lock services procedure providing the system lock procedure and the faked lock procedure. In one embodiment, the shared resource is a cache and the system lock procedure permits a processor to lock the entire cache whereas the faked lock procedure is implemented by a processor seeking exclusive access of a cache slot.

Real-time performance analysis of multiprocessor systems with shared memory

Abstract: Predicting timing behavior is key to reliable real-time system design and verification, but becomes increasingly difficult for current multiprocessor systems on chip. The integration of formerly separate functionality into a single multicore system introduces new intercore timing dependencies resulting from the common use of the now shared resources. This feedback of system timing on local timing makes traditional performance analysis approaches inappropriate.This article presents a general methodology to model the shared resource traffic and consider its effect on the local task execution. The aggregate busy time captures the timing of multiple accesses to a shared memory far better than the traditional models that focus on the timing of individual events. An iterative approach is proposed to tackle the analysis dependencies that exist in systems with event-driven task activation and dynamic resource arbitration.