Georouting Edge Server Nodes for Latency Reduction
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Solution Overview
Problem
Centralized cloud systems face challenges in managing and processing data from edge devices due to increased latency and bandwidth limitations, as computations are routed away from users, leading to decreased performance and increased latency.
Innovation Solution
The system uses georouting to locate server nodes in close proximity to edge devices by converting geolocation data into geohash values, allowing HTTP requests to be forwarded to the nearest server node, thereby reducing latency and improving network throughput through a distributed edge computing platform that is API-compatible with cloud infrastructures like Google Cloud, AWS, and Microsoft Azure, and securely records each serverless request on a blockchain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If computations are routed to a centralized cloud cluster, then resource management is simplified, but latency increases and performance decreases for distant users
Solution Approach 1:
The patent segments the centralized cloud computing system into distributed edge computing nodes deployed geographically close to users. Each edge node handles local computations independently, dividing the monolithic centralized system into multiple smaller regional units that reduce communication latency while maintaining manageable resource allocation through localized decision-making
Solution Approach 2:
The patent introduces a spatial dimension to resource deployment by placing edge computing nodes in multiple geographic locations rather than concentrating all resources in a single data center. This dimensional expansion allows users to access nearby nodes, reducing latency without requiring complex centralized resource orchestration for every request
2Loss of time
If more server resources are deployed to reduce latency, then response time improves, but infrastructure cost and system complexity increase
Solution Approach 1:
The patent makes edge computing nodes universal by designing them to handle multiple types of workloads and services. Each node can serve different applications and user groups, reducing the need for specialized hardware deployments. The nodes use standardized interfaces and can dynamically allocate resources based on demand, improving response time without proportionally increasing infrastructure complexity
Solution Approach 2:
The patent implements self-service capabilities at edge nodes through automated resource provisioning and load balancing. Nodes can independently make decisions about resource allocation and can request additional resources from the cloud when needed, reducing the need for complex centralized management while maintaining improved response times through local autonomy
Data Source
AI summary
Systems and methods for locating server nodes in close proximity to edge devices using georouting. Microservers automatically form a global peer-to-peer network to serve edge functions and content to edge devices. Edge devices use HyperText Transfer Protocol (HTTP) to execute serverless functions or otherwise retrieve data from edge nodes located in close proximity to the HTTP client. Serverless functions are implemented in secure, isolated environment utilizing a blockchain.