Cloud Resource Selection via Wireless Device Mobility Patterns
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Solution Overview
Problem
Current distributed cloud computing architectures do not efficiently distribute data and applications for wireless communication devices among computing resources, leading to real-time limitations due to physical distances and network congestion.
Innovation Solution
The method involves obtaining mobility information for wireless communication devices over a time period to determine their access patterns, and then selecting the appropriate cloud computing resource based on this information to optimize data handling and reduce latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If data is distributed over geographically dispersed data centres, then round trip time and packet loss are reduced, but device complexity and routing management become more complex
Solution Approach 1:
The system performs preliminary actions by obtaining mobility information for wireless communication devices over a time period before making cloud computing resource selection. This advance preparation allows the network to predict device locations and pre-establish optimal routing paths, reducing round trip time while managing routing complexity through proactive rather than reactive decisions
Solution Approach 2:
The system dynamically selects cloud computing resources based on obtained mobility information. The routing configuration changes adaptively as devices move between geographic areas and access subnetworks, allowing the system to optimize round trip time dynamically while the network manager handles the complexity of these dynamic routing changes centrally
2Productivity
If cloud computing resources are distributed geographically closer to access subnetworks, then network performance improves, but deployment cost increases
Solution Approach 1:
The system implements local quality by distributing cloud computing resources to specific geographic areas based on device mobility patterns. Instead of uniform distribution, cloud resources are placed locally in areas where devices frequently access the network, improving network performance for those regions while avoiding unnecessary deployment costs in areas with low device density or high mobility
3Adaptability or versatility
If mobility information is collected and analyzed, then cloud computing resource selection is optimized, but information processing requirements increase
Solution Approach 1:
The system introduces a network manager as an intermediary that handles the information processing load. The network manager obtains mobility information, analyzes device access patterns, and makes cloud computing resource selections centrally. This mediator approach optimizes resource selection adaptability while concentrating the information processing requirements in a dedicated management entity rather than distributing the load across the entire system
Data Source
AI summary
A method is disclosed for handling cloud computing resources in a wireless communication network comprising a first and a second access subnetwork providing wireless access to wireless communication devices residing in a first and a second geographic area, respectively, and a first and a second cloud computing resource connected to the first and the second access subnetwork, respectively. The method comprises obtaining mobility information over a time period for the wireless communication devices of when, during the time period, each of the devices has wireless access to the communication network via the first access subnetwork and when they have wireless access to the communication network via the second access subnetwork. The method also comprises selecting which of the first or second cloud computing resource that is to serve each of the devices based on the obtained mobility information, and sending an instruction to each of the devices to connect to a server that is connected to the selected cloud computing resource for that wireless communication device.