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.

Converting program code with access coordination for a shared memory

Abstract: A dynamic binary translator 19 converts a subject program 17 into target code 21 on a target processor 13 . For a multi-threaded subject environment, the translator 19 provides a global token 501 common to each thread 171, 172 , and one or more sets of local data 502 , which together are employed to coordinate access to a memory 18 as a shared resource. Adjusting the global token 501 allows the local datastructures 502 a,b in each thread to detect potential interference with the shared resource 18.

Self-organizing peer-to-peer social networks

Abstract: Peer-to-peer (P2P) systems provide a new solution to distributed information and resource sharing because of its outstanding properties in decentralization, dynamics, flexibility, autonomy, and cooperation, summarized as DDFAC in this paper. After a detailed analysis of the current P2P literature, this paper suggests to better exploit peer social relationships and peer autonomy to achieve efficient P2P structure design. Accordingly, this paper proposes Self-organizing peer-to-peer social networks (SoPPSoNs) to self-organize distributed peers in a decentralized way, in which neuron-like agents following extended Hebbian rules found in the brain activity represent peers to discover useful peer connections. The self-organized networks capture social associations of peers in resource sharing, and hence are called P2P social networks. SoPPSoNs have improved search speed and success rate as peer social networks are correctly formed. This has been verified through tests on real data collected from the Gnutella system. Analysis on the Gnutella data has verified that social associations of peers in reality are directed, asymmetric and weighted, validating the design of SoPPSoN. The tests presented in this paper have also evaluated the scalability of SoPPSoN, its performance under varied initial network connectivity and the effects of different learning rules.

A method to request resources in tv white spaces type environment

Abstract: Method, apparatus, and computer program product embodiments are disclosed for independent wireless resource sharing on a fair basis to enable selecting the most suitable coexistence between wireless networks. Example embodiments of the invention include a hierarchical resource request process that enables reallocation of radio resources in a coexistence band. When new resources are requested by a network, a search is made for free resources in the coexistence band. If this does not succeed, a check is made for any allocated but unused resources in the coexistence band that have been advertised by neighboring networks. If there are insufficient advertised resources, then the allocation of resources in neighboring networks is analyzed and compared with the requesting network's need for network resources. There are two graduated stages to the analysis. In an example light analysis stage, an analysis of the allocation of resources is limited to neighboring networks within the same network allocation group as the requesting network's. In a more extensive analysis stage, all of the neighboring networks are analyzed. In this manner, a more complete resource reallocation may be achieved.

Resource Sharing and Task Offloading in IoT Fog Computing: A Contract-Learning Approach

Abstract: With the rapid development of smart devices and compute-intensive applications, fog computing has emerged as a promising solution to accommodate the ever-increasing computational demands. Particularly, in the peak time, the computational tasks can be offloaded from the overloaded base stations to fog servers by leveraging the under-utilized computational resources at the demand side. However, there are two major obstacles hindering the wide deployment of fog computing in Internet of things, which are the lack of an effective incentive mechanism and a task offloading algorithm. In this paper, we develop a two-stage resource sharing and task offloading approach by integrating contract theory with computational intelligence. In the first stage, we propose an efficient incentive mechanism to encourage servers to share their residual computational resources by employing the contract theory. In the second stage, a distributed task offloading algorithm is proposed by leveraging the online learning capability of multi-armed bandit. Specifically, we propose a distance-aware, occurrence-aware, and task-property-aware volatile upper confidence bound algorithm to minimize the long-term delay of task offloading. Finally, extensive simulations are carried out to validate the performance of the proposed algorithm.

Method for effective utilizing of shared resources in computerized system

Abstract: A method for utilizing shared resources in a computerized system, where commands are processed by a processor and executed by one or more of the shared resources, the method comprises steps: a) deriving, from each of the commands, subcommands respectively related to the one or more shared resources, b) assigning priorities to the subcommands, c) forwarding the subcommands to one or more queues of the respective one or more shared resources, so that each of the queues comprises the subcommands related to a particular shared resource Each of the shared resources is thereby able to execute the subcommands from the queues in the asynchronous manner and according to their priorities