Cache Invalidation and Replacement Strategies for Location-Dependent Data in Mobile Environments Speaker : Hsin-Chin Mao Fu Jen Catholic University Computer Science and Information Engineering Department High Speed Networks Lab 2003/10/28

Outline Introduction The System Model Location-Dependent Invalidation Strategies Location-Dependent Cache Replacement Policies Simulation Model Performance Evaluation Conclusion References

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)

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 using 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

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

Location-Dependent Invalidation Strategies The Caching-Efficiency-Based (CEB) Method

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 proposed PA and PAID policies Probability Area (PA) Probability Area Inverse Distance (PAID)

Simulation Model System Execution Model 110 points randomly distributed in a square Euclidean space the locations of 185 hospitals in the Southern California area Server Execution Model Client Execution Model

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

Evaluation of Location-Dependent Invalidation Schemes

Effect of Changing Query Interval

Effect of Changing Moving Interval

Effect of Cache Size

Effect of Combining Different Invalidation and Replacement Schemes

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

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): (2002) Baihua ZhengDik Lun Lee IEEE Transactions on Computers 51 Q. Ren and M.H. Dunham, Using Semantic Caching to Manage Location Dependent Data in Mobile Computing, Proc. Sixth Ann. ACM/IEEE Intl Conf. Mobile Computing and Networking (MobiCom 2000), pp , Aug G.K. Zipf, Human Behaviour and the Principle of Least Effort.Addison-Wesley, 1949.