Remote Server Scheduling for DVR Conflict Resolution
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Solution Overview
Problem
Modern digital video recorders (DVRs) face computational burdens when scheduling future recordings, which can lead to increased costs and reduced attractiveness due to the need for significant processing resources, especially when resolving conflicts between overlapping program broadcasts.
Innovation Solution
A method where a remotely located server schedules upcoming program recordings on behalf of the DVR, determining conflict-free broadcast times and sending a 'to do' list to the DVR, thereby reducing the computational load on the DVR and allowing for cheaper construction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the DVR performs scheduling computations locally, then recording scheduling can be done autonomously, but the processing resources and costs increase significantly
Solution Approach 1:
The scheduling computation function is extracted from the DVR and relocated to a remote server. The DVR sends recording requests to the server, which performs the conflict detection and resolution computations, then returns the scheduled recording times to the DVR. This extraction eliminates the need for complex local processing resources while maintaining autonomous scheduling capability.
Solution Approach 2:
A remote server acts as an intermediary between multiple DVRs and the recording scheduling system. The server receives scheduling requests from DVRs, performs conflict detection and resolution, and manages the scheduling database. This intermediary approach allows centralized computation that benefits all connected DVRs without requiring each DVR to have high processing capabilities.
2Reliability
If the DVR resolves program conflicts locally, then recording conflicts can be managed in real-time, but the computational burden increases
Solution Approach 1:
The conflict resolution computation is extracted from the DVR and performed remotely on the server. The DVR sends program recording requests to the server, which detects conflicts between requested programs and existing schedules, then resolves them by selecting alternative broadcast times or notifying the user. This extraction maintains reliable conflict resolution while dramatically reducing the computational load on the DVR.
Solution Approach 2:
The server performs conflict detection and resolution in advance before the actual recording execution. By pre-calculating conflict-free scheduling options and preparing alternative recording times, the system ensures reliable conflict management without requiring intensive real-time computation at the DVR during recording operations.
3Productivity
If the DVR maintains a comprehensive to-do list locally, then all scheduled recordings can be managed autonomously, but the storage and processing requirements increase
Solution Approach 1:
The scheduling database and to-do list management are extracted from the DVR and relocated to the remote server. The server maintains the comprehensive recording schedule database, while the DVR receives only the specific recording instructions it needs to execute. This extraction maintains efficient recording management while reducing storage requirements at the DVR.
Solution Approach 2:
The scheduling data is moved from local DVR storage to remote server storage, transitioning the data management dimension from local to cloud-based. This allows the DVR to access comprehensive scheduling information without maintaining large local storage resources, as the data resides in another dimension (remote server storage) that can be accessed on demand.
Data Source
AI summary
A DVR sends, over the Internet, to a server, information that indicates a set of programs. The information also may indicate a ranking of the programs in the set relative to each other. In response to receiving the information from the DVR, the server determines a “to do” list of programs that the DVR should record as those programs are broadcasted in the future. The “to do” list indicates recording times and channels for each program. The server sends the “to do” list back to the DVR over the Internet. The DVR receives the “to do” list over the Internet and stores the “to do” list. As the programs on the “to do” list are broadcasted, the DVR automatically records those programs at the list-specified times and on the list-specified channels. The DVR stores those programs on the DVR's hard disk drive for later viewing by the DVR user.