Filter Data Structure for Device Update Campaign Membership
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Solution Overview
Problem
Conventional systems face significant challenges in efficiently processing device update requests for large campaigns, such as those involving V2X vehicles, due to high resource requirements and substantial latency caused by linear or binary searches.
Innovation Solution
The implementation of a server-based system that utilizes a filter data structure, such as a cuckoo filter or Xor filter, to quickly determine whether a computerized device belongs to an update campaign, thereby reducing hardware resources and processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If linear or binary search methods are used to determine campaign membership, then the system can process device update requests, but the processing time and resource consumption increase significantly
Solution Approach 1:
The patent creates a simplified copy of the campaign membership data structure - specifically a filter structure (Bloom filter, Cuckoo filter, or Xor filter) that contains only the essential membership information. This filter is a compact representation that can be queried rapidly without accessing the full campaign database, thereby reducing query time while maintaining membership determination accuracy.
Solution Approach 2:
The filter structure is pre-computed and stored before any device update requests are processed. By preparing the membership determination mechanism in advance (creating the filter from campaign data beforehand), the system eliminates the need for time-consuming searches during actual request processing, thus reducing latency.
2Ease of operation
If conventional search methods are used to process device update requests, then all requests can be handled, but hardware resource requirements become excessive
Solution Approach 1:
Instead of using the full campaign database for every membership check, the system uses a compact filter structure that is a simplified copy containing only the necessary membership bits. This filter structure requires significantly less memory and computational resources to query, reducing hardware resource consumption while maintaining the ability to process device update requests.
Solution Approach 2:
The patent extracts only the essential membership determination information from the complete campaign data and stores it in the filter structure. By taking out only the necessary elements (membership bits) and discarding redundant data, the system reduces memory usage and processing overhead while preserving the core functionality of determining campaign membership.
Data Source
AI summary
Systems, methods, and computer-readable media that quickly and efficiently identify the computerized devices that are part of an update campaign. The operations of the systems, methods, and computer-readable media may include: obtaining a filter data structure comprising a plurality of hash values, each hash value corresponding to a computerized device of a plurality of computerized devices in an update campaign; determining whether a requesting computerized device is in the update campaign using a hash function of the filter data structure and identifying information that identifies the requesting computerized device; in response to determining that the computerized device is in the update campaign, providing a device update to the computerized device; and in response to determining that the computerized device does not belong to the update campaign, providing, to the computerized device, an indication that there is no device update for the computerized device.