Enterprise Network Content Distribution via Logical Grouping
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Solution Overview
Problem
Existing content distribution systems in enterprise networks face inefficiencies and high failure rates due to the lack of strategic planning in distributing large files, such as firmware updates, which leads to excessive network traffic and computational overhead, especially in large and topologically complex environments.
Innovation Solution
A content distribution system that groups devices logically based on exogenous information and selects group heads to measure network links efficiently, categorizing them into proximity categories for targeted measurements, using peer-to-peer protocols to optimize content distribution paths and reduce traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a device manager uses existing networking frameworks and protocols for large-scale file distribution, then the distribution can be performed across multiple subnets, but the network traffic and computational overhead become excessive
Solution Approach 1:
The patent segments the enterprise network into multiple subnets and introduces intermediate distribution points (edge devices) in each subnet. Instead of a single central device manager communicating with all devices, the system divides the distribution task across multiple segments, where each edge device handles local distribution within its subnet. This segmentation reduces the network traffic burden on any single link and improves overall distribution efficiency.
Solution Approach 2:
The patent introduces edge devices as intermediaries between the central device manager and managed devices. These edge devices receive content from the device manager and then distribute it locally within their respective subnets. This intermediary approach reduces direct communication overhead between the central manager and all devices, thereby reducing network traffic and computational load.
2Ease of operation
If a device manager resides within the same private IP sub-network to facilitate device access, then device management is simplified, but the device manager cannot efficiently distribute files across multiple subnets
Solution Approach 1:
The patent introduces edge devices as intermediaries that reside in each subnet. The central device manager communicates with these edge devices (which are in the same subnet, maintaining ease of operation), and the edge devices then handle distribution within their local subnets. This intermediary approach enables efficient cross-subnet distribution while preserving simple same-subnet access.
Solution Approach 2:
The patent segments the distribution architecture into a central management layer (device manager in one subnet) and multiple distribution layers (edge devices in different subnets). This segmentation allows the device manager to operate within its home subnet for simplified access while enabling cross-subnet distribution through the distributed edge devices.
3Adaptability or versatility
If topology-aware peer-to-peer content distribution solutions are used, then network conditions can be estimated to find suitable candidates, but the solutions do not plan the distribution and files are distributed based on demand rather than strategy
Solution Approach 1:
The patent performs preliminary actions by pre-planning the content distribution architecture before actual distribution occurs. The system pre-identifies edge devices in each subnet, pre-establishes distribution paths, and pre-configures the hierarchical structure. This preliminary planning enables efficient execution during actual distribution, avoiding the inefficiency of demand-based distribution without strategy.
Solution Approach 2:
The patent incorporates feedback mechanisms where the device manager receives information about network conditions, device availability, and distribution progress. This feedback allows the system to adapt the pre-planned distribution strategy in real-time, combining the benefits of topological awareness with strategic planning and demand responsiveness.
Data Source
AI summary
Embodiments described herein provide a system for facilitating dynamic content distribution in an enterprise environment. During operation, the system determines a set of logical groups based on a set of grouping criteria. A respective logical group can include one or more devices managed by a controller and a network that provides connections among the one or more devices. The system categorizes the set of logical groups based on exogenous information associated with a respective logical group and determines a corresponding condition of measurement for a respective category of links in the enterprise environment. The system then schedules a link for measurement based on the condition of measurement and the categorization of the set of logical groups.