Community-Based Mobile Search Cache for Latency Reduction
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Solution Overview
Problem
Mobile devices face challenges in providing quick and efficient search results due to the high latency and power consumption associated with using 3G or other wireless links for internet connectivity, which is exacerbated by limited resources and the need for frequent data transfers.
Innovation Solution
A Community-Based Mobile Search Cache that utilizes a local query cache populated by mining historical search data from a broader community of mobile devices, allowing for immediate retrieval of popular search results without the need for constant internet connection, with periodic updates and customization based on user behavior and location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mobile devices use 3G or wireless links for internet connectivity to access search results, then users can obtain search results from the cloud, but the latency and power consumption increase significantly
Solution Approach 1:
The system performs preliminary actions by constructing a local query cache on the mobile device that stores frequently accessed search results and query patterns. This cache is built in advance using historical search data from the same user and aggregated data from a broader community of users. When a search query is entered, the system first checks the local cache before connecting to the cloud, enabling immediate retrieval of cached results without waiting for cloud processing and wireless transmission, thus reducing search latency while maintaining result availability.
Solution Approach 2:
The local query cache acts as an intermediary layer between the mobile device and the cloud search services. Instead of directly querying the cloud for every search, the system uses the locally stored cache as a mediator to intercept and satisfy common search requests. This intermediary cache contains pre-fetched search results, query suggestions, and frequently accessed information, allowing the device to serve users locally for cached queries while still maintaining the ability to access the cloud when needed, thereby reducing overall latency and cloud dependency.
2Reliability
If mobile devices use 3G or wireless links for internet connectivity, then search results can be obtained from the cloud, but power consumption increases due to frequent radio link usage
Solution Approach 1:
The system performs preliminary actions by pre-populating a local query cache with search results, query patterns, and frequently accessed information before the user needs them. This cache is constructed using historical search data from the same user and aggregated community data, stored locally on the device. When searches are performed, the system checks the local cache first, serving results without activating the radio link for cloud communication. This preliminary caching significantly reduces the frequency of wireless connections, thereby lowering power consumption while maintaining search functionality.
Solution Approach 2:
The mobile device serves itself by maintaining a local query cache that enables autonomous handling of search queries without requiring continuous cloud connectivity. The cache stores locally relevant search results, query suggestions, and frequently accessed information that the device can retrieve independently. This self-service capability allows the device to satisfy user search needs using only local resources for cached queries, minimizing radio link usage and power consumption, while still providing comprehensive search functionality.
3Loss of time
If a local query cache is used to reduce latency and power consumption, then wireless link usage decreases, but the cache must be periodically updated to maintain data freshness
Solution Approach 1:
The system implements periodic action by updating the local query cache at scheduled intervals rather than continuously. The cache is refreshed periodically with new search results, updated query patterns, and fresh community data. Between updates, the cache serves search queries locally without requiring cloud connections. This periodic update approach maintains data freshness to an acceptable level while minimizing the frequency of wireless connections, thus balancing latency reduction with productive use of the device and network resources.
Solution Approach 2:
The system applies partial action by updating only the portions of the query cache that have expired or become stale, rather than performing a complete cache refresh. The cache maintenance mechanism identifies and updates only the necessary segments that require freshening, leaving the rest of the cache intact. This partial update approach maintains data freshness for critical information while reducing the overall update frequency and associated resource consumption, balancing cache productivity with the need to minimize wireless link usage.
Data Source
AI summary
A “Community-Based Mobile Search Cache” provides various techniques for maximizing the number of query results served from a local “query cache”, thereby significantly limiting the need to connect to the Internet or cloud using 3G or other wireless links to service search queries. The query cache is constructed remotely and downloaded to mobile devices. Contents of the query cache are determined by mining popular queries from mobile search logs, either globally or based on queries of one or more groups or subgroups of users. In various embodiments, searching and browsing behaviors of individual users are evaluated to customize the query cache for particular users or user groups. The content of web pages related to popular queries may also be included in the query cache. This allows cached web pages to be displayed without first displaying cached search results when a corresponding search result has a sufficiently high click-through probability.