Distributed Node Intra-Group Task Scheduling for Load Balancing
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Solution Overview
Problem
Existing task scheduling methods in distributed computing environments, such as cloud and grid computing, face challenges in load balancing and resource allocation, particularly in large-scale networks where centralized computing is inefficient and may lead to unbalanced resource utilization.
Innovation Solution
A distributed node intra-group task scheduling method that collects resource state and history service information from each node, calculates resource utilization rates, and selects execution nodes to minimize resource utilization increments and balance resource occupation, ensuring efficient task allocation across multiple service nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If centralized computing is used for task scheduling in large-scale distributed networks, then task allocation can be coordinated, but computing efficiency decreases and computing overhead increases
Solution Approach 1:
The patent divides the centralized scheduling system into multiple distributed node groups, where each group independently performs scheduling tasks. This segmentation eliminates the single-point bottleneck of centralized computing while maintaining coordinated task allocation across the network.
Solution Approach 2:
The patent introduces group leaders as intermediary nodes that coordinate between individual nodes within a group and other groups. This intermediary layer reduces direct communication overhead while maintaining system-wide coordination efficiency.
2Loss of time
If Min-Min algorithm is used for task scheduling, then task completion time is minimized, but load balancing deteriorates
Solution Approach 1:
The patent modifies the scheduling algorithm by incorporating multiple parameters including resource utilization rates, node load factors, and task priorities. This multi-parameter approach allows the system to balance task completion time with load distribution across nodes.
Solution Approach 2:
The patent implements dynamic scheduling where node groups and their leaders are formed or dissolved based on real-time system state. This dynamic reorganization allows the system to adapt to changing load conditions and maintain both efficiency and balance.
3Productivity
If Max-Min algorithm is used for task scheduling, then load balancing is improved, but task completion time increases
Solution Approach 1:
By dividing the system into multiple node groups with independent scheduling capabilities, the patent allows parallel task processing across groups. This segmentation enables the system to achieve load balancing within groups while maintaining overall fast completion through concurrent execution.
4Adaptability or versatility
If distributed scheduling is implemented across multiple node groups, then system scalability is improved, but inter-group coordination complexity increases
Solution Approach 1:
The patent introduces group leaders as intermediary nodes that handle inter-group coordination. This intermediary layer abstracts the complexity of distributed coordination, allowing individual groups to operate independently while maintaining system-wide consistency through the leader mediation layer.
Data Source
AI summary
A distributed node intra-group task scheduling method includes: step 101) collecting resource state information and history service information about each node in a group; step 102) receiving a service request command and parsing the request command to obtain a request task; step 103) according to the resource state information and history service information about each node, calculating the resource utilization rate increment after each node in the group loads a task and the occupation condition of each kind of resource in the group; and according to a principle of making the resource utilization rate increment of each node in the group as low as possible and the occupation of each kind of resource in the group as balanced as possible, selecting service execution nodes in the group, and providing the request task by the selected service execution nodes.