Jawaharlal Nehru Technological University Hyderabad MCA 2022 CLOUD APPLICATIONS Previous Question Paper (September/October - 2022 - R20)

Parallel computing and distributed computing differ primarily in their architecture, resource sharing, and coupling level. In parallel computing, multiple processors or cores work simultaneously on a single task by breaking it into smaller sub-tasks, typically sharing a common memory space and clock signal. It is tightly coupled, designed for high-speed execution within a single system or cluster.

In contrast, distributed computing involves multiple autonomous computers connected via a network that communicate and coordinate their actions by passing messages. Each computer has its own local memory and processor, making it loosely coupled. While parallel computing focuses on maximizing throughput and reducing execution time for a single complex problem, distributed computing focuses on resource sharing, scalability, and fault tolerance across geographically dispersed systems.

Major computing paradigms represent different models for organizing computational resources to solve problems:

• Centralized Computing: All computing power is concentrated in a single, powerful mainframe or server. Users access resources via terminals, making management simple but creating a single point of failure.
• Parallel Computing: Employs multiple processors to execute instructions simultaneously. It is categorized by architectures like SIMD (Single Instruction, Multiple Data) or MIMD (Multiple Instruction, Multiple Data) to solve computationally intensive tasks.
• Distributed Computing: A system where components located on networked computers communicate and coordinate actions. It allows for horizontal scaling and high availability by distributing workloads across multiple nodes.
• Cloud Computing: An on-demand delivery model that provides shared computing resources, software, and data as a service over the internet. It abstracts the underlying infrastructure, offering elasticity and pay-as-you-go pricing.
• Grid Computing: A form of distributed computing where a 'super virtual computer' is composed of many networked, loosely coupled computers acting in concert to perform large-scale tasks, often used in scientific research.
• Ubiquitous/Edge Computing: Focuses on processing data near the source of generation (at the edge of the network) rather than in a centralized data center, reducing latency for real-time applications.