Distributed Computing and Storage with Adaptive Task Allocation
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Solution Overview
Problem
Existing distributed computing systems face challenges in efficiently utilizing diverse end-user devices with varying capabilities and connectivity for parallel processing and storage tasks due to differences in processor speeds, memory capacities, and network stability, leading to inefficiencies and potential unavailability of resources.
Innovation Solution
A distributed computing and storage system that employs a distribution management module to coordinate and manage tasks across multiple user node devices, utilizing asynchronous multithreading, redundancy, and machine learning to optimize task distribution and ensure efficient processing and storage, even in the absence of full control over user devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed computing systems utilize diverse end-user devices with varying capabilities, then resource utilization and processing power are improved, but system reliability and task completion consistency deteriorate due to differences in processor speeds, memory capacities, and network stability
Solution Approach 1:
The system dynamically adapts task distribution based on real-time device capabilities and performance metrics. The distribution management module continuously monitors processor speeds, memory capacities, and network stability of user devices, adjusting task allocation to optimize resource utilization while maintaining reliable task completion through adaptive scheduling and load balancing
Solution Approach 2:
The system changes operational parameters such as task size, complexity, and distribution strategy based on device characteristics. By modifying task parameters to match device capabilities and using machine learning to predict performance outcomes, the system achieves high resource utilization while ensuring consistent task completion across heterogeneous devices
2Productivity
If the system transmits storage tasks to multiple user node devices for parallel processing, then processing speed and throughput are improved, but system complexity and coordination overhead increase
Solution Approach 1:
The system segments storage tasks into smaller sub-tasks that can be independently executed by multiple user node devices. The distribution management module divides large data processing operations into manageable chunks, assigning them to different devices based on availability and capability, thereby increasing processing speed while reducing the coordination complexity of any single task
Solution Approach 2:
The distribution management module acts as an intermediary that simplifies coordination between the central system and multiple user node devices. It handles task distribution, result aggregation, and error management, shielding individual devices from complex coordination requirements while enabling parallel processing across the distributed network
3Reliability
If the system maintains redundancy across multiple user node devices, then system reliability and fault tolerance are improved, but resource consumption and storage overhead increase
Solution Approach 1:
The system implements local quality by distributing different types of data replicas to different user node devices based on their specific capabilities and reliability metrics. Rather than uniform redundancy, the system places critical data replicas on devices with higher reliability while using devices with lower reliability for less critical replicas, thereby achieving fault tolerance with optimized storage overhead
Data Source
AI summary
Apparatuses, systems, methods, and program products are disclosed for techniques for distributed computing and storage. An apparatus includes a processor and a memory that includes code that is executable to receive a request to perform a storage task, transmit at least a portion of the storage task to a plurality of user node devices, receive results of the at least a portion of the storage task from at least one of the plurality of user node devices, and transmit the received results.