Cloud-Edge Network Delay and Spectrum Optimization
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Solution Overview
Problem
Cloud-edge collaborative networks face high end-to-end delay and spectrum resource occupancy issues, which hinder efficient processing of user requests due to long transmission distances and insufficient computing resources at the edge.
Innovation Solution
A joint optimization method and system that initializes a cloud-edge collaborative network, establishes a target function for minimum average end-to-end delay and spectrum slot occupation, and enforces constraints for node and path selection, MEC server load, spectrum resource occupation, and continuity to optimize resource allocation and routing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If computing tasks are offloaded to cloud servers, then computing power is sufficient, but transmission distance is long causing high latency
Solution Approach 1:
The patent segments the centralized cloud computing system into a distributed cloud-edge collaborative architecture. Computing tasks are divided and processed at multiple levels: edge servers handle latency-sensitive tasks locally, while cloud servers handle computation-intensive tasks. This segmentation reduces transmission distance for time-critical operations while maintaining sufficient computing power through the hierarchical structure.
Solution Approach 2:
The patent introduces edge servers as intermediary nodes between terminal devices and cloud servers. These edge servers act as mediators that can process computing tasks locally, reducing the need for long-distance transmission to cloud servers. The edge servers bridge the gap between local processing capabilities and centralized cloud resources, optimizing both latency and computing power utilization.
2Loss of time
If computing tasks are processed locally at terminal devices, then transmission latency is low, but computing resources are insufficient
Solution Approach 1:
The patent merges local edge server resources with terminal device capabilities to form a collaborative computing system. The edge servers provide additional computing resources that supplement terminal device limitations, while maintaining low latency through local processing. This combination allows the system to achieve both sufficient computing power and low transmission latency simultaneously.
3Productivity
If more spectrum resources are allocated to handle increased network traffic, then network capacity increases, but spectrum resource occupancy increases
Solution Approach 1:
The patent employs spectrum flexibility technology that enables dynamic adjustment of spectrum parameters. The system can change spectrum allocation parameters in real-time based on traffic demands, allowing efficient utilization of existing spectrum resources. This parameter flexibility allows the network to handle increased traffic without proportionally increasing spectrum occupancy, as resources are dynamically optimized for current conditions.
Data Source
AI summary
The present invention provides a joint optimization method and system for delay and spectrum occupation in a cloud-edge collaborative network. The method includes: initializing a cloud-edge collaborative network, and generating a set of user requests; establishing a target function of minimum average end-to-end delay and minimum spectrum slot occupation of a user request; during processing of each user request based on the target function, sequentially determining whether a node and path selection uniqueness constraint, a mobile edge computing (MEC) server load constraint, a spectrum resource occupation and uniqueness constraint, a spectrum continuity constraint, and a spectrum consistency constraint are satisfied, where if all constraints are satisfied, the user request is successfully processed, and the process turns to step S4; or if any constraint is not satisfied, the user request fails to be processed; and calculating average end-to-end delay and spectrum resource occupancy of the user request.