Network Resource Clustering for IoT Computation Requests
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current IoT systems lack an efficient method for dynamically clustering computing resources across network nodes to handle computation requests effectively, especially considering energy and mobility configurations.
Innovation Solution
A method and system that periodically exchange resource usage messages between network nodes using a broker coordinator protocol to create and allocate Processor Unit (PU) clusters, taking into account computation requests, energy-configuration, mobility-configuration, and processing-configuration, through a multi-agent function for resource assignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If computing resources are distributed across multiple IoT devices, then system versatility and resource availability improve, but system complexity and coordination overhead increase
Solution Approach 1:
The system segments computing resources into discrete processor unit (PU) clusters that can be independently formed and managed. Each PU cluster represents a segmented unit of computation capability that can be allocated to different tasks, allowing the system to manage distributed resources in manageable chunks rather than as a monolithic complex system
Solution Approach 2:
The broker coordinator protocol acts as an intermediary mechanism between distributed IoT devices. It mediates resource requests and offers, coordinates PU cluster formation, and manages resource allocation without requiring direct complex interactions between all devices, thereby reducing coordination overhead while maintaining versatility
2Adaptability or versatility
If resources are dynamically allocated based on computation requests, then system adaptability improves, but resource allocation complexity and processing time increase
Solution Approach 1:
The system performs preliminary actions by pre-coordinating PU cluster formation based on resource offers from devices before actual computation requests arrive. The broker coordinator maintains an updated view of available resources and pre-established PU clusters, so when computation requests are received, allocation can occur rapidly without requiring time-consuming real-time coordination
Solution Approach 2:
The system implements dynamic resource allocation through the broker coordinator protocol that continuously receives resource offers and computation requests, dynamically forming and dissolving PU clusters based on current system state. This dynamic approach allows the system to adapt to changing conditions while maintaining efficient allocation through automated coordination rather than static pre-configuration
3Use of energy by moving object
If energy-configuration and mobility-configuration are optimized for computation requests, then energy efficiency improves, but system complexity and configuration computation overhead increase
Solution Approach 1:
The broker coordinator protocol serves multiple functions simultaneously: it coordinates resource allocation, optimizes energy configuration, manages mobility configuration, and forms PU clusters. This multi-functional approach consolidates what would otherwise be separate complex optimization systems into a single coordinated mechanism, reducing overall system complexity while achieving energy efficiency
Solution Approach 2:
The system optimizes energy and mobility configurations by dynamically adjusting parameters based on computation request characteristics and current resource states. The broker coordinator computes optimal configurations by changing parameters such as device selection, resource allocation ratios, and mobility settings, achieving energy efficiency through parameter optimization rather than structural complexity
Data Source
AI summary
A method and a network node for handling a computation request from a requesting party. Resources messages are periodically exchanged with neighboring network nodes indicating resources usage. A computation request is received from a requesting entity via a network interface; coordination takes place with the neighboring network nodes; one or more processor unit (PU) clusters are formed using resource usage data from the resource messages; and, taking into account the computation request; resources from the one or more PU clusters are allocated to the computation request before returning the result of the computation request to the requesting entity via the network interface.