Grid computing is a distributed system in which many interconnected machines (nodes) share diverse resources such as processing power, storage, communication bandwidth and specialized software to function as one environment. These resources are accessible by users with different levels of access and restrictions. Processing power is the most commonly used resource for performing tasks on remote machines, executing parallel across multiple processors or replication across nodes for large-scale processing. Grid storage unifies distrubted memory and disk systems into data grids, enhancing capacity, accessibility and reliability through network file systems. Grid communication enables data transfer within and outside the grid where bandwidth and network toplogy directly impact performance. Additionally, constraints in software licenses, hardware architectures and policies will also affect how jobs will be assigned and executed on the grid.
Job management mechanisms such as scheduling, reservation and scavenging are used to efficiently allocate resources between grid components. Scheduling automatically allocates jobs to suitable machine based on availability and requirements while reservation allows resources to be preallocated to guarantee performance and deadlines. Scravenging optimizes resource utilization by using idle machines without disrupting their primary users, though it introduces unpredictability in execution time. Applications in a grid usually consist of smaller jobs or subjobs that can run in parallel and thereby enhance scalability however, practical limits may be encountered due to interdependencies or resources contention. Grid architectures range from simple homogenous clusters in a single department to complex heterogenous systems spanning several organizations (intragrid). Where policies, security, prioritization etc. Have to be established and enforced. Overall grid computing represensts a powerful but very complex approach for the efficient use of distributed resources for the solution of large scale problems.