Universal game-equilibrium semantic cache algorithm

Abstract

The invention provides an universal game-equilibrium semantic cache algorithm. Based on a Nash equilibrium mechanism, parameter expressions of three factors, namely semantics, time and location, are designed, analyzed and calculated, a game equilibrium point is found, a game-equilibrium equation is built, and the covariance coefficient of the relation role is calculated so as to obtain the universal game-equilibrium semantic cache algorithm; the semantic cache algorithm can be extended to the multifactor proportional change, also can be extended to any finite dimension, and can be widely applied to various mobile sensor database systems. How do limited mobile device resources deal with a large number of mobile user query services from a distributed database is an important issue. When a basic semantic cache technology is applied to query optimization of a sensor database, the existing method does not consider numerous reality multidimensional constraints, and therefore such the important issue is still a key and difficult issue in the semantic caching technology.

Description

technical field [0001] The invention relates to a semantic cache algorithm, in particular to a universal game-equilibrium semantic cache algorithm. Background technique [0002] Semantic caching is an important research content in O2O applications of various mobile sensor database systems. In recent years, under the background of the rapid development of big data and the Internet of Things, semantic caching technology has received extensive attention and attention. [0003] According to the research results at home and abroad, it is found that the traditional methods have limitations and cannot meet the needs of the current O2O mobile sensor database development. For example: [0004] In Document 1, although the cluster cache algorithm considers semantic and time factors, it only has qualitative analysis and no quantitative description (Q.Ren and M.H.Dunham, "Using clustering for effective management of asmantic cache in mobile computing," Mobile 99 Proceedings of the 1st ...

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Problems solved by technology

[0004] In Document 1, although the cluster cache algorithm considers semantic and time factors, it only has qualitative analysis and no quantitative description (Q.Ren and M.H.Dunham, "Using clustering for effective management of asmantic cache in mobile computing," Mobile 99 Proceedings of the 1st ACMinternational workshop on Data engineering for wireless and mobile access, 1999.); In Document 2, although branch bound and greedy dual-size frequency (BBGDSF) provides quantitative analysis considering semantic and time factors, it only considers the static location information model, Does not consider dynamic location factors (L.Savary, G.Gardarin, and K.Zeitouni, "Geocach a cache for gml geographic, data," International Journal of Data Warehousing & Mining, vol.3, pp.66–87, 2007.); In Document 3, although the cost model of collaborative spatial data sharing (CSDS) takes into account dynamic location factors, it does not consider semantic and time factors (Z. Huang, C.S. Jensen, and B. C. Ooi, "Collaborative spatial data sharing among mobile lightweight devices," SSTD'07 Proceeding for the 10th international conference on Advances in spatial and temporal databases, 2007.)

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