Selective Edge Offload for Visual Frame Processing Latency
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Solution Overview
Problem
Conventional systems fail to provide low latency for real-time display of offloaded visual frames and lack dynamic functionality to perform data services on-device while offloading others, lacking a coordinated set of edge devices configured to manage data services across a geographic location.
Innovation Solution
The implementation selectively offloads visual frames from client devices to edge systems for processing, using an edge manager to discover and preload edge devices with workload resources, and dynamically map processing locations based on client device capabilities and latency criteria, ensuring real-time communication and efficient data service delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If visual frames are offloaded to remote cloud systems for processing, then computing power is improved, but latency increases and real-time display cannot be achieved
Solution Approach 1:
The patent transitions from a single centralized cloud processing model to a multi-dimensional distributed edge computing architecture. By deploying edge servers at multiple geographic locations closer to client devices, the system creates multiple processing dimensions, reducing network latency while maintaining high computing power through distributed parallel processing capabilities.
Solution Approach 2:
The patent introduces edge servers as intermediary components between client devices and remote cloud systems. These edge servers act as local processing intermediaries that can handle compute-intensive workloads nearby, reducing the need for data to travel to distant cloud data centers and back, thereby minimizing latency while still leveraging centralized cloud resources when needed.
2Adaptability or versatility
If all data services are offloaded to edge systems, then client device capabilities are overcome, but network bandwidth is consumed and efficiency decreases
Solution Approach 1:
The patent implements local quality by enabling client devices to perform data services locally when capable, while offloading only specific compute-intensive services to edge systems. The system dynamically determines which services to handle locally versus remotely based on device capabilities, service requirements, and current conditions, optimizing network bandwidth usage by avoiding unnecessary remote processing for simple tasks.
Solution Approach 2:
The patent applies partial action by selectively offloading only the necessary portion of data services to edge systems rather than all services. The system assesses each service's computational requirements and offloads only those that exceed client device capabilities or benefit from remote processing, leaving simpler services to be handled locally, thus reducing overall network bandwidth consumption.
3Device complexity
If a static processing location is used, then system complexity is reduced, but adaptability to different client device capabilities is lost
Solution Approach 1:
The patent implements dynamics by transitioning from static processing location assignments to dynamic, adaptive service location mapping. The system continuously monitors client device capabilities, edge server availability, and service requirements to dynamically determine the optimal processing location for each data service. This dynamic approach allows the system to adapt to changing conditions while maintaining manageable complexity through automated decision-making algorithms.
Solution Approach 2:
The patent applies universality by creating a multi-functional service location mapping system that can handle multiple scenarios: local device processing, edge server processing, and cloud processing. The same mapping infrastructure supports different client device types, varying service requirements, and multiple processing locations, providing a universal solution that adapts to diverse capabilities without requiring separate systems for each scenario.
4Reliability
If edge servers are deployed across a geographic region, then service availability is improved, but system complexity and coordination requirements increase
Solution Approach 1:
The patent implements self-service by enabling edge servers to autonomously discover available services and capabilities of nearby client devices without requiring complex centralized coordination for each interaction. Edge servers can independently register their capabilities, receive service requests, and process data services locally, reducing the coordination overhead while maintaining high service availability across the distributed network.
Data Source
AI summary
Implementations selectively offload visual frames from a client device to an edge system for processing. The client device can receive streaming visual frames and a request to process the visual frames using a data service. The client device can offload visual frames to an edge system preloaded with a workload resource that corresponds to the requested data service. After the edge system processes the offloaded visual frames using the workload resource, the edge system can return the processed visual frame to the client device. In some implementations, the edge system and client device are situated in a network such that a latency for the offload communications support real-time video display. A cloud system can maintain a registry of edge systems and provide client devices with information about nearby edge systems. The cloud system can also preload the edge systems with workload resources that correspond to data services.