overview of mobile database caching
DESCRIPTION
Overview of Mobile Database Caching. Presented By: Rooma Rathore Rohini Prinja. Overview. Motivation Problem definition Caching Overview Caching Granularity Cache Coherence Cache Replacement Summary Future Work. Motivation. Popularity of mobile database applications is increasing - PowerPoint PPT PresentationTRANSCRIPT
Overview of Mobile Database Caching
Presented By:Rooma Rathore
Rohini Prinja
Overview
Motivation Problem definition Caching Overview Caching Granularity Cache Coherence Cache Replacement Summary Future Work
Motivation
Popularity of mobile database applications is increasing
Caching can improve performance Caching in mobile DB is different Many papers have addressed
different issues in mobile caching There are not many survey papers
Problem Definition
Given Applications running on mobile databases
Find Efficient caching mechanisms to improve the
response time Objectives
Cache is consistent at all the times Cache-hit ratio is high
Constraints Low bandwidth Frequent Disconnections Limited battery power
Basic Setup of Mobile Environment
MSS MSS MSS MSS
LAN, WAN etc
Database Servers
Cells
MH1 MH2 MH3 MH4 MH5 MH6
How mobile caching is different?
Wireless transmission is much slower Very important to minimize transmission
Frequent disconnections by client Server might not be able to reach all clients for
updates Clients have limited battery power
Energy efficiency is important Uplink speed is much slower
Important to reduce uplink queries from clients
Caching Overview
Caching mechanism characterized by Caching Granularity
What to cache? Cache Coherence
How to maintain consistency? Cache Replacement
Which items to discard when new ones need to be inserted ?
Caching Granularity
Page based caching mechanisms not suitable in mobile environment
Object Caching Server sends all attributes of object, which are
cache by client Attribute Caching
Only attributes requested in query are sent and cached
Hybrid Caching Cache the attributes likely to be used in future
Semantic Caching
Caching Granularity - Comparison
Object Attribute Hybrid Semantic Requires more cache space But good if all attributes are used
Saves cache space Not very good if some attributes used in one query and other in second.
Best of object and attributeHard to identify, which attributes will be used
Semantic information is to be saved New queries with partial cached data can be answered while disconnectedVery good in continuous queries, where just the remaining part can be sent to server.
Cache Coherence 1/3
Broadly classified into 3 categories Stateful Server
Server knows status and contents of all clients
Client Verification Client verifies before use of cache
Stateless Server Server doesn’t know about client’s
status or its cache contents Mostly used in mobile environment
Cache Coherence 2/3
Different kinds of schemes Timestamp based
Broadcasting Timestamps Amnesic Terminals Signature
Adaptive Vary transmission speed Adaptive Invalidation with Fixed Window Adaptive Invalidation with Adjusting Window
Cache Coherence 3/3
Asynchronous Stateful A Stateful scheme Based on HLC at MSS
Validity Scoped Suitable for Location dependent data Bit Vector with Compression (BVC) Grouped Bit Vector (GBVC) Implicit Scope Information (ISI)
Cache Coherence- Comparison
Timestamp Adaptive Asynchronous
Validity - based
o Periodic broadcasto IR can become too longo Long query delayo Simple
o Adapt to load and other parameterso Complexo Difficult to identify threshold
o A stateful schemeo Additional overhead of HLC on MSSo Invalidation messages sent to individual clients so bandwidth utilization is low.
o Only suitable in location dependent data environmento Doesn’t deal with data updates on servero No periodic broadcast needed
Cache Replacement
Tradition Schemes like LRU, LRU-K, MRU are not very suitable
Access Frequency based Mean – mean inter operation duration Window – highest mean in window EWMA – recent use has higher weight
Gain based SAIU – Stretch Access rate Inverse Update
Frequency MinSAUD – Minimum Stretch integrated with
Access rates Update frequency and cache validation Delay
Target Driven
Cache Replacement - Comparison
Access Freq. based
Gain Based Target driven
Uses past access frequency to predict futureoNot very good if access behavior suddenly changes
Tries to minimize stretch. Computation is complex and consumes battery power Assumes , access rate and update frequency of item is known or can be predicted correctly
Provides generalized cost function Optimal results Function can be modified to optimize different parameters Doesn’t address what to do when more than one parameter needs to be optimized. Computation is complex
Summary
Why mobile caching is important? How mobile caching is different? Discussed papers in these areas
Caching granularity Cache coherence Cache replacement
Future Work
More research is needed in area of cache replacement
Study can be done to find which combination of techniques is suitable for what applications
Study to determine which algorithms are currently being used in commercial applications.
References 1/3
[1] Kahol, S. Khurana, S.K.S. Gupta and P.K. Srimani, “A strategy to managecache consistency in a distributed mobile wireless environment”, IEEE Trans.on Parallel and Distributed System, 12(7), pp 686700, 2001
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[3] Alok Madhukar, Reda Alhajj “An Adaptive Energy Efficient Cache InvalidationScheme for Mobile Databases” April 2006, Proceedings of the 2006 ACMsymposium on Applied computing SAC '06
[4] Ken. C.K. Lee, H.V. Leong, Antonio Si “Semantic Query Caching in MobileEnvironments”, June 2005, Proceedings of the 4th ACM international workshopon Data engineering for wireless and mobile access
[5] Chi-Yin Chow, Hong Va Leong, Alvin T. S. Chan “Distributed Group-basedCooperative Caching in a Mobile Broadcast Environment” May 2005,Proceedings of the 6th international conference on Mobile data managementMDM '05
[6] Boris Y. L. Chan, Antonio Si, Hong Va Leong . “Cache Management for MobileDatabases: Design and Evaluation.” 1998, Proceedings of the FourteenthInternational Conference on Data Engineering
[7] Jianliang Xu; Qinglong Hu; Wang-Chien Lee; Dik Lun Lee; “Performanceevaluation of an optimal cache replacement policy for wireless datadissemination” 2004, IEEE Transactions on Knowledge and Data Engineering
[8] Quen Ren, Margret Dunham, “Semantic Caching in Mobile computing” (2001)
References 2/3[9] Baihua Zheng, Dik Lun Lee, “Semantic Caching in Location-Dependent Query
Processing”, Lecture Notes in Computer Science (2001)[10] D. Barbara, “Mobile Computing and Databases—A Survey”, IEEE Trans.
Knowledge and Data Eng., vol. 11, no. 1, Jan./Feb. 1999.[11] Kristian Kvilekval, Ambuj Singh, “SPREE: Object Prefetching for Mobile
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Maintenance Scheme for Mobile Environment” ,(2000) InternationalConference on Distributed Computing Systems
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Cache Invalidation Schemes for Mobile Environments”, 2002.[18] H. Song; G. Cao, “Cache-miss-initiated prefetch in mobile environments”, IEEE
International Conference on Mobile Data Management, 2004 Page(s):370 – 381[19] K.-L. Wu, P. S. Yu, and M.-S. Chen. “Energy-efficient caching for wireless
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[20] Xu, Q.L. Hu, and D.L. Lee, W.-C. Lee, “SAIU: An Efficient Cache ReplacementPolicy for Wireless On-Demand Broadcasts”, Proc. Ninth ACM Int'l Conf.Information and Knowledge Management, pp. 46-53, Nov. 2000
[21] Chun-Hung Yuen, J.; Chan, E.; Lam, K.-Y.; Leung, H.W. “Database andExpert Systems Applications”, 2000. Proceedings. 11th International Workshopon 4-8 Sept. 2000 Page(s):155 - 159
[22] J. Jing, A. K. Elmargarmid, S. Helal, and R. Alonso. “Bit-Sequences: AnAdaptive Cache Invalidation Method in Mobile Client/Server Environments”.ACM/Baltzer Mobile Networks and Applications, 2(2), 1997
[23] Q.L. Hu and D. L. Lee. “Adaptive cache invalidation methods in mobileenvironments”. In Proceedings of the 6th IEEE International Symposium onHigh Performance Distributed Computing, August 1997.
[24] L. Yin, G. Cao, and Y. Cai. “Target-Driven Cache Replacement for MobileEnvironments”, Journal of Parallel and Distributed Computing, Vol. 65, pp.583-594, 2005
Questions
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