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.

Method and apparatus to automatically deinstall an application module when not functioning

Abstract: A method and apparatus for automatically installing a target application module and de-installing the target application module if it fails to execute or function properly is described. In one embodiment, the method includes determining whether a shared resource exists on a target media, and, if the shared resource exists, determining whether the application module functioned properly on the target media, and automatically de-installing the application module if the application module failed to function properly.

Enabling Edge Cooperation in Tactile Internet via 3C Resource Sharing

Abstract: Tactile Internet often requires: 1) the ultra-reliable and ultra-responsive network connection and 2) the proactive and intelligent actuation at edge devices. A promising approach to address these requirements is to enable mobile edge devices to share their communication, computation, and caching (3C) resources via device-to-device connections. In this paper, we propose a general 3C resource sharing framework, which includes many existing 1C/2C sharing models in the literature as special cases. Comparing with the 1C/2C models, the proposed 3C framework can further improve the resource utilization efficiency by offering more flexibilities in terms of the device cooperation and resource scheduling. As a typical example, we focus on the energy utilization under the proposed 3C framework. Specifically, we formulate an energy consumption minimization problem, which is an integer non-convex optimization problem. To solve the problem, we first transform it into an equivalent integer linear programming problem that is much easier to solve. Then, we propose a heuristic algorithm based on linear programming, which can further reduce the computation time and produce an empirically close-to-optimal solution. Moreover, we evaluate the energy reduction due to the 3C sharing both analytically and numerically. Numerical results show that, comparing with the existing 1C/2C approaches, the proposed 3C sharing framework can reduce the total energy consumption by 83.8% when the D2D energy is negligible. The energy reduction is still 27.5% when the D2D transmission energy per unit time is twice as large as the cellular transmission energy per unit time.

Method, system, and program for managing locks enabling access to a shared resource

Abstract: Provided are a method, system, and program for managing locks enabling access to a shared resource. A first server receives a lock request from a client for the shared resource. A determination is made as to whether a second server owns the client locks. The first server issues a request to the second server to transfer ownership of the client locks to the first server, wherein the client lock requests are handled by the server owning the client locks.

Generalized resource sharing

Abstract: Resource sharing is one of the main tasks in high-level synthesis, and although many algorithms have addressed the problem there are still several limitations which restrict the generality and applicability of current algorithms. Most clique-partitioning-based algorithms use local and inaccurate cost-functions which result in inefficient results. This paper presents algorithms for the resource sharing problem on registers and functional units, and shows how they overcome the limitations of existing algorithms. The main characteristics of this work are: interleaved register and functional unit merging in a global clique partitioning based framework, accurate merging cost estimation, accurate interconnect cost estimation, relative control cost taken into account and efficient false loop elimination. The results obtained show significant improvements in the delay of designs, while also minimizing area, specially for large designs with many sharing possibilities.

Shared Resource Monitoring and Throughput Optimization in Cloud-Computing Datacenters

Abstract: Many data centers employ server consolidation to maximize the efficiency of platform resource usage. As a result, multiple virtual machines (VMs) simultaneously run on each data center platform. Contention for shared resources between these virtual machines has an undesirable and non-deterministic impact on their performance behavior in such platforms. This paper proposes the use of shared resource monitoring to (a) understand the resource usage of each virtual machine on each platform, (b) collect resource usage and performance across different platforms to correlate implications of usage to performance, and (c) migrate VMs that are resource-constrained to improve overall data center throughput and improve Quality of Service (QoS). We focus our efforts on monitoring and addressing shared cache contention and propose a new optimization metric that captures the priority of the VM and the overall weighted throughput of the data center. We conduct detailed experiments emulating data center scenarios including on-line transaction processing workloads (based on TPC-C) middle-tier workloads (based on SPECjbb and SPECjAppServer) and financial workloads (based on PARSEC). We show that monitoring shared resource contention (such as shared cache) is highly beneficial to better manage throughput and QoS in a cloud-computing data center environment.