Cache Invalidation and Replacement Strategies for Location-Dependent Data in Mobile Environments
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Transcript of Cache Invalidation and Replacement Strategies for Location-Dependent Data in Mobile Environments
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Cache Invalidation and Replacement Strategies for Location-Dependent Data in Mobile Environments
Speaker : Hsin-Chin Mao
Fu Jen Catholic UniversityComputer Science and Information Engineering Department
High Speed Networks Lab2003/10/28
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Outline
Introduction The System Model Location-Dependent Invalidation Strategies Location-Dependent Cache Replacement
Policies Simulation Model Performance Evaluation Conclusion References
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Introduction
two common issues in client cache management cache invalidation scheme cache replacement policy
location-dependent data location-dependent cache invalidation valid scopes
We first introduce two basic location-dependent invalidation schemes Polygonal Endpoints (PE) Approximate Circle (AC)
a generic method Cache-Efficiency Based scheme (CEB)
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The System Model
two distinct sets of entities mobile clients fixed hosts ( mobile support stations (MSSs))
data item value from data item Mobile clients can identify their locations usin
g systems such as the Global Positioning System (GPS)
cache data values on its local disk or in any storage system; fixed sizes and read-only
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Location-Dependent Invalidation Strategies The advantages of the idea that attach
complete/partial invalidation information two situations where validity checking is
necessary cache replacement policies
The Polygonal Endpoints (PE) Scheme a straightforward way
The Approximate Circle (AC) Scheme the overhead of this scheme can be minimized 56 bytes => 12 bytes
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Location-Dependent Invalidation Strategies The Caching-Efficiency-Based (CEB) Method
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Location-Dependent Cache Replacement Policies Data Distance
the distance between the current location of a mobile client and the valid scope of a data value
Valid Scope Area the geometric area of the valid scope of a data value propo
sed PA and PAID policies Probability Area (PA)
Probability Area Inverse Distance (PAID)
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Simulation Model
System Execution Model 110 points randomly distributed in a square Euclid
ean space the locations of 185 hospitals in the Southern Calif
ornia area Server Execution Model Client Execution Model
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Performance Evaluation
Evaluation of Location-Dependent Invalidation Schemes
Evaluation of Cache Replacement Policies uniform access (θ=0), skewed access(θ=0.5) Effect of Changing Query Interval Effect of Changing Moving Interval Effect of Cache Size
Effect of Combining Different Invalidation and Replacement Schemes
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Evaluation of Location-Dependent Invalidation Schemes
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Evaluation of Location-Dependent Invalidation Schemes
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Evaluation of Location-Dependent Invalidation Schemes
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Effect of Changing Query Interval
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Effect of Changing Query Interval
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Effect of Changing Moving Interval
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Effect of Changing Moving Interval
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Effect of Cache Size
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Effect of Combining Different Invalidation andReplacement Schemes
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Conclusions
explored cache invalidation and replacement issues for location-dependent data under a geometric location model PE, AC, CEB
proposed two cache replacement policies PA, PAID
future work location-dependent queries
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References
Baihua Zheng, Jianliang Xu, Dik Lun Lee: Cache Invalidation and Replacement Strategies for Location-Dependent Data in Mobile Environments. IEEE Transactions on Computers 51(10): 1141-1153 (2002)
Q. Ren and M.H. Dunham, “Using Semantic Caching to Manage Location Dependent Data in Mobile Computing,” Proc. Sixth Ann. ACM/IEEE Int’l Conf. Mobile Computing and Networking (MobiCom 2000), pp. 210-221, Aug. 2000.
G.K. Zipf, Human Behaviour and the Principle of Least Effort.Addison-Wesley, 1949.