Edge Distributed Unit for Low-Latency Mobile Code Execution
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Solution Overview
Problem
Mobile computing devices face limitations in executing code due to limited local resources and high latency when accessing remote computing resources, preventing them from running applications that require significant processing power or real-time interactions.
Innovation Solution
Implementing a distributed unit within the radio access network that executes code on behalf of mobile devices, leveraging its abundant computing resources and proximity to reduce latency and improve performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If mobile computing devices execute code locally, then processing speed is limited by device resources, but accessing remote computing resources introduces high latency
Solution Approach 1:
The patent introduces a new spatial dimension for code execution by deploying distributed units at edge locations within the radio access network, physically closer to mobile devices than centralized cloud data centers. This dimensional shift from centralized remote execution to distributed edge execution reduces transmission distance and latency while providing access to powerful computing resources that would be unavailable on mobile devices themselves.
Solution Approach 2:
The distributed unit acts as an intermediary between mobile computing devices and the core network/cloud infrastructure. It receives code execution requests from mobile devices, executes the code locally at the edge, and returns results, thereby mediating the trade-off between local resource constraints and remote processing capabilities while minimizing latency.
2Power
If mobile devices access remote computing resources, then processing power increases, but latency increases due to distance
Solution Approach 1:
The patent segments the centralized cloud computing infrastructure into distributed edge computing units deployed throughout the radio access network. Each distributed unit provides localized computing power for mobile devices in its vicinity, reducing the distance data must travel while maintaining access to substantial processing capabilities through virtualized environments and containerized applications.
Solution Approach 2:
The solution adds a spatial dimension to computing resource distribution by placing distributed units at multiple edge locations within the network, creating a multi-dimensional architecture that balances computing power availability with proximity to end devices, thereby reducing latency while maintaining processing capability.
3Adaptability or versatility
If code is executed on mobile devices, then resource constraints limit application capabilities, but executing on remote servers increases latency
Solution Approach 1:
The patent implements dynamic code execution environments on distributed units, where virtualized operating systems and containerized applications can be instantiated, configured, and executed on-demand. This dynamic approach allows the system to adapt to diverse application requirements while providing real-time execution capabilities that minimize latency compared to static remote server architectures.
Solution Approach 2:
The distributed units provide universal computing capabilities through virtualized environments that can execute various types of code and support multiple applications simultaneously. This multi-functional approach enables a single distributed unit to serve diverse application needs while maintaining low latency for all users in its coverage area.
Data Source
AI summary
Systems and methods are described for implementing a distributed unit in a radio access network that executes code on behalf of mobile devices. A distributed unit may be implemented on an edge server that is in close physical proximity to a radio unit, with few or no intervening devices. The edge server may thus provide services to mobile devices, such as executing code on behalf of a mobile device in an execution environment on the edge server, at significantly lower latency than more distant cloud-based servers. The edge server may preload computing environments with code for which a mobile device is likely to request execution (e.g., because a particular application is executing on the mobile device), and may determine whether to execute code on the edge server or on a cloud provider network.