Distributed Data Center Mesh Network Latency Reduction
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Solution Overview
Problem
Centralized cloud-based systems experience latency and inefficiency due to the need for long-distance data transmission and processing, which can be exacerbated by the requirement for data to be sent to and from remote cloud storage for processing and consumption.
Innovation Solution
A distributed data center with a mesh network configuration that allows resources such as computing and storage to be located closer to the point of consumption, utilizing a dynamic software-defined mesh network to efficiently allocate and manage resources across the system, thereby reducing unnecessary data transmission and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If data is transmitted to centralized cloud storage for processing, then system resources can be accessed remotely, but latency increases due to long-distance transmission
Solution Approach 1:
The patent segments the centralized cloud system into distributed edge nodes deployed at multiple locations. Instead of a single centralized data center, the system creates a network of distributed nodes that can process data locally, thereby reducing transmission distance and latency while maintaining remote access capability through the mesh network architecture.
Solution Approach 2:
The patent implements local quality by placing computing and storage resources closer to where data is generated and consumed. Each edge node provides localized processing capabilities, allowing data to be processed at the point of need rather than requiring transmission to a distant centralized cloud, thus reducing latency while preserving accessibility.
2Adaptability or versatility
If centralized cloud-based systems are used, then system resources can be accessed from any location, but unnecessary long-range data transmission occurs
Solution Approach 1:
The system segments the centralized architecture into distributed edge nodes that handle data processing locally. This segmentation allows location-independent access through the mesh network while preventing unnecessary long-range transmissions by processing data at the nearest available node.
Solution Approach 2:
The patent introduces intermediate edge nodes that act as mediators between data sources and final consumers. These intermediaries process and route data through local networks before transmission, reducing the need for direct long-range transmissions to centralized clouds and thereby reducing energy consumption.
3Loss of time
If distributed resources are deployed at edge locations, then latency is reduced, but system complexity increases
Solution Approach 1:
The patent applies universality by designing edge nodes that can perform multiple functions including data storage, processing, routing, and mesh network management. This multi-functionality reduces the need for specialized dedicated components at each node, thereby managing complexity while enabling distributed low-latency processing.
Solution Approach 2:
The system implements feedback mechanisms where edge nodes continuously report their status, resource availability, and network conditions to the mesh network controller. This feedback enables automatic routing decisions and resource allocation, simplifying the management of distributed complexity through centralized coordination based on real-time information.
4Productivity
If mesh network configuration is used, then resource efficiency is improved, but network management complexity increases
Solution Approach 1:
The patent implements feedback mechanisms where edge nodes continuously report their status, resource availability, and network conditions to the mesh network controller. This feedback enables automatic routing decisions and resource allocation, simplifying the management of distributed complexity through centralized coordination based on real-time information.
Solution Approach 2:
The system applies dynamics by making the mesh network topology adaptable and reconfigurable based on real-time conditions. The network can dynamically adjust routes, allocate resources, and reconfigure connections in response to changing conditions, optimizing resource utilization while managing complexity through automated adaptation rather than static configuration.
Data Source
AI summary
Techniques are described for wireless communication. One method, for processing a request received via a first mesh network using resources of a second mesh network, includes receiving, at a first node, a request that was generated by a requesting node of the first mesh network. The method further includes determining at the first node, based on configuration information about the second mesh network that is different from the first mesh network, that a second node of the second mesh network has an available computing resources level to process data related to the request. In accordance with the determining, the method additionally includes instructing the second node of the second mesh network to process the data related to the request to create requested data. And the requested data is provided to the requesting node of the first mesh network.