Multimedia Edge Cloud Load Balancing for Mobile QoS
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Solution Overview
Problem
Multimedia services over wireless networks to mobile devices face significant quality of service issues due to limitations in cloud processing power and mobile device capabilities, leading to delays and quality degradation.
Innovation Solution
A multimedia aware cloud is configured as multiple edge clouds geographically close to mobile devices, with load balancing servers that identify multimedia types, determine desired quality of service levels, evaluate device and network capabilities, and adapt multimedia data for optimal delivery, utilizing clusters of servers for general computing, graphic computing, and data storage, and employing parallel and serial processing techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cloud processing power is increased to improve multimedia service quality, then quality of service improves, but system complexity and cost increase
Solution Approach 1:
The cloud infrastructure is segmented into multiple edge clouds distributed geographically closer to mobile devices. Each edge cloud handles specific multimedia processing tasks locally, reducing the need for centralized processing power while maintaining service quality. This segmentation distributes system complexity across multiple simpler nodes rather than requiring one complex centralized system.
Solution Approach 2:
The patent introduces a spatial dimension to cloud computing by deploying edge clouds at multiple geographic locations closer to end users. This transforms the traditional single-point cloud architecture into a distributed multi-dimensional network, improving quality of service through reduced latency without proportionally increasing overall system complexity.
2Reliability
If mobile device processing power is increased to handle multimedia tasks, then quality of service improves, but battery consumption increases
Solution Approach 1:
Edge clouds act as intermediaries between mobile devices and the central cloud infrastructure. These intermediaries perform computationally intensive multimedia processing tasks locally, allowing mobile devices to offload processing work while maintaining high quality of service. This eliminates the need for mobile devices to have high processing power while preserving battery life.
3Reliability
If network bandwidth is increased to deliver high-quality multimedia, then quality of service improves, but network cost and infrastructure complexity increase
Solution Approach 1:
Multimedia content is pre-processed, pre-rendered, and pre-formatted at edge clouds before being delivered to mobile devices. This preliminary action at the edge reduces the amount of data that needs to be transmitted over the network, allowing high-quality service delivery without requiring proportionally high network bandwidth or complex network infrastructure.
Data Source
AI summary
Techniques for configuring and operating a multimedia aware cloud, particularly configured for mobile device computing, are described herein. In some instances, clusters of servers are organized for general computing, graphic computing and data storage. A load balancing server may be configured to: identify multimedia types currently being processed within the multimedia edge cloud; determine desired quality of service levels for each identified multimedia type; evaluate individual abilities of devices communicating with the multimedia edge cloud; and assess bandwidth of each network over which the multimedia edge cloud communicates with a mobile device. With that information, multimedia data may be adapted accordingly, to result in an acceptable quality of service level when delivered to a specific mobile device. In one example of the techniques, graphic computing server clusters may be configured to process workload using a configuration that includes elements of both parallel and serial computing.