Related Research Articles
The Association for Computing Machinery (ACM) is a US-based international learned society for computing. It was founded in 1947 and is the world's largest scientific and educational computing society. The ACM is a non-profit professional membership group, reporting nearly 110,000 student and professional members as of 2022. Its headquarters are in New York City.
The client–server model is a distributed application structure that partitions tasks or workloads between the providers of a resource or service, called servers, and service requesters, called clients. Often clients and servers communicate over a computer network on separate hardware, but both client and server may reside in the same system. A server host runs one or more server programs, which share their resources with clients. A client usually does not share any of its resources, but it requests content or service from a server. Clients, therefore, initiate communication sessions with servers, which await incoming requests. Examples of computer applications that use the client–server model are email, network printing, and the World Wide Web.
In telecommunication, provisioning involves the process of preparing and equipping a network to allow it to provide new services to its users. In National Security/Emergency Preparedness telecommunications services, "provisioning" equates to "initiation" and includes altering the state of an existing priority service or capability.
Grid computing is the use of widely distributed computer resources to reach a common goal. A computing grid can be thought of as a distributed system with non-interactive workloads that involve many files. Grid computing is distinguished from conventional high-performance computing systems such as cluster computing in that grid computers have each node set to perform a different task/application. Grid computers also tend to be more heterogeneous and geographically dispersed than cluster computers. Although a single grid can be dedicated to a particular application, commonly a grid is used for a variety of purposes. Grids are often constructed with general-purpose grid middleware software libraries. Grid sizes can be quite large.
Checkpointing is a technique that provides fault tolerance for computing systems. It basically consists of saving a snapshot of the application's state, so that applications can restart from that point in case of failure. This is particularly important for long running applications that are executed in failure-prone computing systems.
In computer science, concurrency is the ability of different parts or units of a program, algorithm, or problem to be executed out-of-order or in partial order, without affecting the outcome. This allows for parallel execution of the concurrent units, which can significantly improve overall speed of the execution in multi-processor and multi-core systems. In more technical terms, concurrency refers to the decomposability of a program, algorithm, or problem into order-independent or partially-ordered components or units of computation.
HTCondor is an open-source high-throughput computing software framework for coarse-grained distributed parallelization of computationally intensive tasks. It can be used to manage workload on a dedicated cluster of computers, or to farm out work to idle desktop computers – so-called cycle scavenging. HTCondor runs on Linux, Unix, Mac OS X, FreeBSD, and Microsoft Windows operating systems. HTCondor can integrate both dedicated resources and non-dedicated desktop machines into one computing environment.
TeraGrid was an e-Science grid computing infrastructure combining resources at eleven partner sites. The project started in 2001 and operated from 2004 through 2011.
Concurrent computing is a form of computing in which several computations are executed concurrently—during overlapping time periods—instead of sequentially—with one completing before the next starts.
Edge computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data. This is expected to improve response times and save bandwidth. Edge computing is an architecture rather than a specific technology, and a topology- and location-sensitive form of distributed computing.
In computer science, high-throughput computing (HTC) is the use of many computing resources over long periods of time to accomplish a computational task.
A sensor grid integrates wireless sensor networks with grid computing concepts to enable real-time data collection and the sharing of computational and storage resources for sensor data processing and management. It is an enabling technology for building large-scale infrastructures, integrating heterogeneous sensor, data and computational resources deployed over a wide area, to undertake complicated surveillance tasks such as environmental monitoring.
A computer cluster is a set of computers that work together so that they can be viewed as a single system. Unlike grid computers, computer clusters have each node set to perform the same task, controlled and scheduled by software. The newest manifestation of cluster computing is cloud computing.
Cloud computing is the on-demand availability of computer system resources, especially data storage and computing power, without direct active management by the user. Large clouds often have functions distributed over multiple locations, each of which is a data center. Cloud computing relies on sharing of resources to achieve coherence and typically uses a pay-as-you-go model, which can help in reducing capital expenses but may also lead to unexpected operating expenses for users.
Data-intensive computing is a class of parallel computing applications which use a data parallel approach to process large volumes of data typically terabytes or petabytes in size and typically referred to as big data. Computing applications that devote most of their execution time to computational requirements are deemed compute-intensive, whereas applications are deemed data-intensive require large volumes of data and devote most of their processing time to I/O and manipulation of data.
Computation offloading is the transfer of resource intensive computational tasks to a separate processor, such as a hardware accelerator, or an external platform, such as a cluster, grid, or a cloud. Offloading to a coprocessor can be used to accelerate applications including: image rendering and mathematical calculations. Offloading computing to an external platform over a network can provide computing power and overcome hardware limitations of a device, such as limited computational power, storage, and energy.
Fog computing or fog networking, also known as fogging, is an architecture that uses edge devices to carry out a substantial amount of computation, storage, and communication locally and routed over the Internet backbone.
Multi-access edge computing (MEC), formerly mobile edge computing, is an ETSI-defined network architecture concept that enables cloud computing capabilities and an IT service environment at the edge of the cellular network and, more in general at the edge of any network. The basic idea behind MEC is that by running applications and performing related processing tasks closer to the cellular customer, network congestion is reduced and applications perform better. MEC technology is designed to be implemented at the cellular base stations or other edge nodes, and enables flexible and rapid deployment of new applications and services for customers. Combining elements of information technology and telecommunications networking, MEC also allows cellular operators to open their radio access network (RAN) to authorized third parties, such as application developers and content providers.
Social cloud computing, also peer-to-peer social cloud computing, is an area of computer science that generalizes cloud computing to include the sharing, bartering and renting of computing resources across peers whose owners and operators are verified through a social network or reputation system. It expands cloud computing past the confines of formal commercial data centers operated by cloud providers to include anyone interested in participating within the cloud services sharing economy. This in turn leads to more options, greater economies of scale, while bearing additional advantages for hosting data and computing services closer to the edge where they may be needed most.
Soft computing is an umbrella term used to describe types of algorithms that produce approximate solutions to unsolvable high-level problems in computer science. Typically, traditional hard-computing algorithms heavily rely on concrete data and mathematical models to produce solutions to problems. Soft computing was coined in the late 20th century. During this period, revolutionary research in three fields greatly impacted soft computing. Fuzzy logic is a computational paradigm that entertains the uncertainties in data by using levels of truth rather than rigid 0s and 1s in binary. Next, neural networks which are computational models influenced by human brain functions. Finally, evolutionary computation is a term to describe groups of algorithm that mimic natural processes such as evolution and natural selection.
References
- ↑ Spruce; Special Priority and Urgent Computing Environment [ unreliable source? ] spruce.teragrid.org
- ↑ Beckman, Pete (March 2008). "Urgent Computing: Exploring Supercomputing's New Role". CTWatch Quarterly. 4 (1).
- ↑ Cope, Jason M (2009). Data management for urgent computing environments (Thesis). OCLC 650213207. ProQuest 304873520.[ page needed ]
- ↑ "Preemptive Parallel Job Scheduling for Heterogeneous Systems Supporting Urgent Computing | IEEE Journals & Magazine | IEEE Xplore". ieeexplore.ieee.org. doi:10.1109/access.2021.3053162 . Retrieved 2023-12-18.