Research Of Mobile Query Strategy Based On Location-Dependent Data

Because of the user’s mobility, the location relevance of data, the disconnection of network and other factors, new challenge brought to query location-dependent data(LDD) in mobile computing environment. First, the changing location of user can bring complex problem: the results returned maybe invalid because the user’s location has been changed. Secondly, due to the location related attributes of data, the same queries received different results for the request location differently. Finally, the disconnection of network brought delay to data access and extended the query response time. If the results were failing, inaccurate or outdated, users may not accept or send request again. Therefore, we need to explore the query strategy to reflect the characteristics with location-attribute of LDD, use the rapid and effective approach to dealing with data access, and which is a challenging research topic.First, we studied data prefetching policy for location-dependent query (LDQ) under the weakly connected condition of network. Querying LDD in mobile environment,the result maybe outdated or disabled due to the weak links and low bandwidth of network, the mobility of users. While data prefetching technology can greatly improve the data access speed, shorten the response time of the query. The prefetching policy based on LDD considering the characteristics of data, but did not take the access probability and the use efficiency into account. In view of the above questions, proposes the cost-based data prefetch (CDP) strategy, CDP according to the value of the cost function select prefetching LDD. The experiments show that the CDP is more effective than other prefetching strategies to shorten the average response time and increase the cache hit rate.Secondly, because of the user’s mobility and the location dependency of data, new challenge has brought to cache replacement strategy for LDQ. Based on the detailed analyzing space location characteristics of LDD and several typical location dependent cache replacement strategies, the authors propose a prioritized approach cache replacement based on the lowest access cost(PLAC), the PLAC takes some important factors into account such things as access probabilities, update rates, data distance, valid scope, etc. To ensure the maximum utilization of limited cache, the PLAC cache replacement strategy according to the value of the lowest cost function to decide which data will be replaced. The contrast experiments show that the PLAC increase cache hit rate and shorten average response time of query more effectively than other location dependent cache replacement strategies.