Broker System for Distributed Task Allocation
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Solution Overview
Problem
Existing distributed computing infrastructures face limitations in scalability, performance, and flexibility due to the need for dedicated software installations on participating devices, which restricts their ability to meet the demands of diverse computing jobs and incur significant costs.
Innovation Solution
A system comprising worker clients and a broker system that dynamically allocates computing tasks without requiring pre-installed client software on devices, using a runtime environment obtained from a broker system, allowing arbitrary computing devices to process tasks and scale computing capacity based on demand.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dedicated client software is installed on participating devices to form a distributed computing infrastructure, then task coordination and processing reliability are improved, but device complexity and ease of operation deteriorate due to installation and maintenance requirements
Solution Approach 1:
The patent introduces a broker system as an intermediary component that mediates between task requesters and worker devices. The broker system receives task requests, discovers available worker devices through advertisements, allocates tasks, and coordinates communication. This intermediary approach maintains reliable task coordination without requiring dedicated client software on worker devices, as the broker handles all coordination logic centrally while workers only need to listen for and execute assigned tasks.
2Stability of the object's composition
If dedicated client software is installed and maintained on participating devices, then computing infrastructure stability is improved, but ease of operation and scalability worsen due to update requirements and manual participation
Solution Approach 1:
The patent implements a self-service mechanism where worker devices automatically advertise their availability and capabilities to the broker system without requiring manual configuration or software updates. The broker system automatically discovers these advertisements, evaluates worker suitability, and assigns tasks. This eliminates the need for manual software maintenance and updates on worker devices, allowing the infrastructure to scale dynamically as devices join and leave the network organically.
3Power
If centralized hardware infrastructure with data centers is used, then computing power and reliability are improved, but loss of substance increases due to capital investment and running costs
Solution Approach 1:
The patent creates a universal distributed computing platform that can utilize any device with processing capabilities (smartphones, tablets, laptops, servers) as worker nodes. The broker system provides a unified interface for task submission and worker discovery, allowing diverse hardware resources to be pooled together. This multi-functional approach replaces the need for dedicated centralized data centers with existing ubiquitous devices, eliminating capital investment in specialized infrastructure while providing comparable computing power through aggregated consumer and enterprise devices.
4Ease of operation
If non-centralized hardware infrastructures without pre-installed software are used, then ease of operation and scalability are improved, but device complexity increases due to runtime environment requirements
Solution Approach 1:
The patent extracts the runtime environment and task execution logic from the worker devices and relocates it to the broker system. Worker devices only need to advertise their availability and receive task assignments via advertisements; all task processing, environment setup, and execution occur on the broker system or in cloud-based virtual machines. This extraction eliminates runtime environment complexity from worker devices while maintaining ease of operation, as devices simply participate by listening for and executing assigned tasks without any software installation or configuration.
Data Source
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AI summary
A worker client (101, 102) has a runtime environment (120) obtained previously from a broker system (201) having a broker reference (422). It further has an interface component (111) communicating with the broker system (201) using the broker reference (422) previously obtained from a further computing device. The interface component (111) is adapted to receive at least one computing task specification. The runtime environment (120) is configured to process task input data according to the at least one computing task specification with a task program (122) resulting in task output data. The interface component (111) is further adapted to send the task output data to a previously determined recipient device.