Distributed Computer Dynamic Task Group Topology
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Solution Overview
Problem
Distributed computers face challenges in efficiently allocating tasks across multiple processors and maintaining robustness in the presence of node failures, with existing load balancing algorithms being inflexible and not well-suited for heterogeneous networks.
Innovation Solution
A method and apparatus for dynamically forming task groups within a distributed computer system by calculating a logical task group topology based on user-defined requirements and node capabilities, allowing for flexible resource utilization and heterogeneous network operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional load balancing algorithms are used to distribute tasks across processors, then task distribution is achieved, but the system lacks flexibility and cannot adapt well to heterogeneous networks
Solution Approach 1:
The patent implements dynamic task group topology calculation that adapts to changing network conditions and node capabilities. The system continuously evaluates node attributes and reconfigures task groups accordingly, allowing the distributed computer to adapt to heterogeneous networks and dynamic environments rather than using static allocation algorithms
Solution Approach 2:
The system changes parameters by considering multiple node attributes (processing power, memory, storage, network bandwidth) when forming task groups. By dynamically adjusting which nodes are grouped together based on their current state and capabilities, the system achieves adaptability to heterogeneous networks while managing complexity through parameter-based decision making
2Power
If purpose-built distributed computers with tens or hundreds of processors are used, then computing power is increased, but system cost and complexity increase significantly
Solution Approach 1:
The patent segments the distributed computer system into dynamic task groups rather than using a monolithic architecture with tens or hundreds of processors. By dividing the system into smaller, manageable task groups that can be independently configured and managed, the system achieves high computing power through coordinated collaboration of fewer nodes while reducing overall system complexity
Solution Approach 2:
The system enables ordinary desktop PCs to function as distributed computer nodes through the task group topology calculation method. By making standard hardware multi-functional (capable of participating in distributed computing tasks), the system achieves high computing power without requiring specialized purpose-built hardware, thereby reducing complexity and cost
3Reliability
If static task allocation methods are used, then implementation is simple, but the system cannot adapt to node failures or changing network conditions
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously monitors node status, capability changes, and network conditions. Based on this feedback, the task group topology is dynamically recalculated and reconfigured, enabling the system to adapt to node failures and changing conditions while maintaining reliability without requiring overly complex manual management
Data Source
AI summary
A distributed computing network is disclosed, the membership of which is determined in accordance with policy data stored at existing member nodes. A node wishing to join the distributed computing network sends profile data indicating the resources it has available for shared computation to a member node. The member node compares the resources with the requirement indicated in the priority data. If the comparison indicates that the applicant node should join, then data indicating the topology of the distributed computing network is updated at the member node and created at the applicant node. This allows for the creation of a distributed computing network whose topology is well-suited to a given task, provided the policy properly reflects the requirements of the task.