Cloud DVR Storage Region Selection Based on Consumption Metrics
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Solution Overview
Problem
Cloud digital video recorder (CDVR) deployments face high costs and resource inefficiencies due to legal and contractual constraints that prevent mirroring, caching, and sharing of content, leading to increased space and network requirements for broadcast providers, as they must maintain multiple copies of recorded content across geographically dispersed users.
Innovation Solution
A system that computes and compares values associated with storing broadcast video recordings in different cloud storage regions based on user consumption patterns and resource usage to determine the most cost-effective storage location, optimizing the selection of data centers for recording and playback, using metrics such as BGP Hops, recording cost factors, and available capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple copies of recorded content are maintained for each user in cloud storage, then legal and contractual requirements are satisfied, but storage space requirements and network costs increase significantly
Solution Approach 1:
The patent applies local quality by making storage capacity dynamic and location-specific. Each user's storage allocation is adjusted based on their specific consumption patterns, geographic location, and access frequency. This allows the system to maintain required content copies locally for compliance while optimizing overall storage distribution, rather than uniformly duplicating content across all users.
Solution Approach 2:
The system implements dynamics by continuously adapting storage allocations based on changing user behavior patterns. Storage capacity and content distribution are not static but dynamically adjusted according to real-time consumption data, user location, and access frequency, allowing the system to maintain compliance while minimizing redundant storage.
2Speed
If content is distributed to multiple geographically dispersed data centers, then user access speed is improved, but network resource consumption and distribution costs increase
Solution Approach 1:
The patent applies preliminary action by pre-positioning content in data centers based on predicted user consumption patterns and geographic location data. Before users actually access content, the system analyzes historical data and user profiles to determine which content will be needed in which regions, and proactively distributes content to appropriate data centers. This reduces actual access latency while minimizing unnecessary network transfers.
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor user access patterns, consumption behavior, and data center performance. This feedback loop allows the system to optimize content distribution decisions, adjusting which content is replicated to which data centers based on actual usage data, thereby reducing network resource consumption while maintaining fast access speeds.
3Adaptability or versatility
If cloud storage infrastructure is expanded to serve more users, then service coverage is improved, but total cost of ownership and operational expenses increase
Solution Approach 1:
The patent applies universality by designing a multi-functional cloud storage system that simultaneously serves multiple purposes: content delivery, user profile management, consumption pattern analysis, and dynamic resource allocation. This integrated approach allows the same infrastructure to support expanding service coverage while reducing per-user operational costs through shared resources and centralized intelligence.
Solution Approach 2:
The system implements parameter changes by dynamically adjusting storage capacity, content replication factors, and data center selection based on varying user demands and consumption patterns. Rather than provisioning fixed resources for potential maximum usage, the system adapts resource parameters in real-time to actual usage, enabling expanded service coverage without proportionally increasing operational expenses.
Data Source
AI summary
In one embodiment, a first value is computed on a networked computing device, the first value being associated with storing a recording of a broadcast video at a first cloud storage device situated in a first one of a plurality of regions, for playback on a remote client device situated in the first one of the plurality of regions, the first value being a measure of user consumption patterns and use of computing and network resources. A second value is computed on the networked computing device, the second value being associated with storing the recording of the broadcast video at a second cloud storage device situated in a second one of the plurality of regions, for playback on a remote client device situated in the second one of the plurality of regions, the second value being a measure of user consumption patterns and use of computing and network resources. The first and second values are compared on the networked computing device in order to determine a preferred storage region, the recording of the broadcast video is stored on the one of the first cloud storage device and the second cloud storage device in the preferred storage region, and the one of the first cloud storage device and the second cloud storage device in the preferred storage region is instructed to store the recording of the broadcast video. Related hardware, systems, and methods are also described.