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Answer: Breaking down large tasks into smaller subtasks for parallel execution
Task decomposition in a distributed computing system involves breaking down large tasks into smaller subtasks. This approach enables parallel execution across multiple nodes or processors, optimizing the use of distributed computing resources. By dividing the workload into manageable units that can be processed concurrently, task decomposition enhances parallelism, accelerates overall task completion, and improves system scalability and performance. It's a cornerstone concept in distributed computing, aimed at efficiently distributing computational loads across a cluster's nodes.
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What is the primary purpose of task decomposition in a distributed computing system?
A
Combining small tasks into larger tasks to reduce overhead
B
Synchronizing task execution across all nodes simultaneously
C
Breaking down large tasks into smaller subtasks for parallel execution
D
Distributing tasks across nodes without any specific strategy
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