Distributed Video Management System Architecture for Bandwidth Efficiency
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Solution Overview
Problem
Current Digital Video Management (DVM) systems face limitations in scalability and bandwidth constraints when managing video data across geographically dispersed sites, requiring improved methods for efficient video data sharing and access between distributed systems.
Innovation Solution
A distributed DVM system architecture that allows for direct communication between clients and camera servers via TCP/IP connections, enabling seamless integration of remote camera servers with local systems, reducing latency and improving bandwidth efficiency by sharing resource-intensive video data directly between clients and camera servers, rather than relying on centralized database server communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If video data is shared through centralized database server communication, then system management is simplified, but bandwidth constraints and latency increase
Solution Approach 1:
The patent segments the centralized video data sharing architecture into distributed peer-to-peer connections. Each camera server is divided into independent units that can directly communicate with clients, eliminating the single point of congestion at the database server. This segmentation allows multiple parallel data streams to flow simultaneously, reducing latency while maintaining manageable system complexity through modular design.
Solution Approach 2:
The patent introduces a new communication dimension by enabling direct client-to-camera server connections alongside the existing database server pathway. This creates a multi-dimensional architecture where video data can flow through multiple paths: the traditional centralized route and new direct peer-to-peer routes. This dimensional expansion reduces latency by providing shorter, more direct data transmission paths.
2Quantity of substance
If more cameras are added to a single DVM system, then system functionality is enhanced, but scalability limitations are reached
Solution Approach 1:
The patent divides the monolithic DVM system into multiple independent DVM systems, each capable of managing a subset of cameras. This segmentation transforms the scalability problem by allowing horizontal expansion - new cameras can be added to existing systems or distributed to new systems without overwhelming a single centralized infrastructure. Each segmented system maintains full functionality, enabling flexible scaling to support large numbers of cameras across multiple distributed nodes.
Solution Approach 2:
The patent merges multiple independent DVM systems into a federated network where systems can share resources and data. This combining approach allows the overall system to support more cameras than any single system could handle alone, while maintaining the autonomy and manageability of individual systems. The merger creates enhanced scalability through coordinated operation of multiple systems working together.
3Reliability
If centralized database server manages all camera servers, then system coordination is improved, but bandwidth efficiency decreases
Solution Approach 1:
The patent introduces peer-to-peer communication as an intermediary pathway that bypasses the centralized database server for video data transmission. This intermediary direct connection allows camera servers to communicate efficiently with clients without routing all data through the database server, improving bandwidth efficiency. The database server retains its coordinating role for system management while video data flows through more efficient direct paths.
Solution Approach 2:
The patent extracts the video data transmission function from the centralized database server, separating it from the system coordination function. By taking out the data streaming role from the database server, the system eliminates unnecessary bandwidth consumption through the centralized node. Camera servers directly provide video data to clients, while the database server focuses on coordination tasks, optimizing both reliability and bandwidth efficiency.
Data Source
AI summary
Described herein are systems and methods for managing video data. In overview, various embodiments provide software, hardware and methodologies associated with the management of video data. In overview, a distributed DVM system includes a plurality of discrete DVM systems, which may be geographically or notionally distributed. Each discrete DVM system includes a respective central DVM database server thereby to provide autonomy to the discrete system. This server supports one or more camera servers, these camera servers in turn each being configured to make available live video data from one or more cameras. Each system additionally includes one or more clients, which provide a user interface for displaying video data (such as video data from one of the cameras). The discrete DVM systems are primarily linked by way of a centralized database server/database server communications interface. However, the clients are configured to connect directly to camera servers belonging to their local DVM system or a remote DVM system in the distributed architecture.