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Mobile Computing and Databases (modified from ICDE98) Margaret H. Dunham Southern Methodist University Dept of Computer Science and Engineering Dallas, Texas 75275 [email protected] http://www.seas.smu.edu/~mhd Outline Introduction & Data Management Issues Query Processing Data Broadcasting Transaction Processing Projects & Products Conclusion 2/24/98 ICDE/SMU - Dunham 2 Mobile Computing Architecture 2/24/98 ICDE/SMU - Dunham 3 Terminology Fixed Network (FN) Base Station (BS) (Mobile Support Station (MSS)) Fixed Hosts (FH) Cell - Area covered by BS (1-2 miles) Handoff - Changing BS by intercell move Mobile Host (MH) (Mobile Unit (MU)) 2/24/98 ICDE/SMU - Dunham 4 Wireless Networks Cellular High Cost Scalability Issue Limited Bandwidth: 10 Kbps Wireless LAN Traditional LANs with wireless interface Low Cost Limited range: 10-100 meters Bandwidth: 10Mbps NCR Wavelan,ICDE/SMU Motorola ALTAIR 2/24/98 - Dunham 5 Wireless Networks (cont’d) Satellite Services Wide Coverage Very Expensive Low Bandwidth: 1-2Mbps Paging Networks Wide Coverage Sky Tel, Motorola Slow: (Ethernet: 10Mbps; FDDI or switched Ethernet: 100Mbps; ATM: 155Mbps) Ad Hoc Networks 2/24/98 ICDE/SMU - Dunham 6 Handoff Changing BS due to movement between cells State information transferred Current handoffs in cellular phones may take up to a few seconds with breaks in conversation of 100-300 ms. Soft - Temporarily connected to two BSs Hard - Only connected to one BS 2/24/98 ICDE/SMU - Dunham 7 Location Management Tracking mobile user User associated with home A location server (Home Agent) A May augment by searching in local S area first M May augment with user profiles Mobile IP [11,14] h f Triangle Routing Route Optimization Location Control (Routing Agent) 2/24/98 ICDE/SMU - Dunham S Ah Af M 8 Location Management (cont’d) Active Badge (Cambridge,[2]) Track employees and route telephone calls Unique code emitted every 15 seconds Sensors placed in offices and corridors Location Information Replications No HLR Hierarchy of Location Servers Each server maintains information about its subtree 2/24/98 ICDE/SMU - Dunham 9 Mobile Applications Information Services (Yellow Pages) Law Enforcement and Medical Emergencies Sales and Mobile Offices Weather, Traffic, Sports, Entertainment Trucking Cellular Subscribers in the United States: 90,000 in 1984;4.4 million in 1990; 13 million in 1994 Handheld computer market will grow to $1.77 billion by 2002 2/24/98 ICDE/SMU - Dunham 10 Technology Push Internet: ftp, telnet, email, http,html Advancing Wireless Communication Technologies Laptop, Notebook, and Palmtop Computers 2/24/98 ICDE/SMU - Dunham 11 Classification of Mobile Database Systems 2/24/98 ICDE/SMU - Dunham 12 Data Management Issues Speed of wireless link Scalability Mobility Location dependent data; Location specific queries Limited by battery power Disconnection (Voluntary, Involuntary) Replication/Caching Handoff 2/24/98 ICDE/SMU - Dunham 13 Insurance Example 2/24/98 ICDE/SMU - Dunham 14 Medical Example 911 Call Ambulance arrives/departs Closest hospital Access patient records Send vital signs Update patient records Page hospital personnel Order medical supplies 2/24/98 ICDE/SMU - Dunham 15 MC/DB Research Transaction Processing Caching - Replication Broadcast Disks Agents Mobility Location Dependent Data Recovery ACID (?) 2/24/98 ICDE/SMU - Dunham 16 Outline Introduction & Data Management Issues Query Processing Location Dependent Queries and Data New Query Types Query Optimization Data Broadcasting Transaction Processing Projects & Products Conclusion 2/24/98 ICDE/SMU - Dunham 17 Location Dependent Data Value of data depends on location Temporal Replication - One consistent value at one time Spatial Replication - Multiple different correct data values at one time Temporal Consistency - All data objects satisfy a given set of integrity constraints. Spatial Consistency - Consistency constraints satisfied within Data Region. SMU/University of Missouri at Kansas City, [17] 2/24/98 ICDE/SMU - Dunham 18 Location Dependent Queries Result depends on location Different from traditional distributed goal of location independence Ex: Yellow Pages, Directions, Map Predicates based on location: “Find the cheapest hotel in Dallas.” Location constraints: “Find the nearest hotel (to me).” 2/24/98 ICDE/SMU - Dunham 19 Similarity to Spatial Queries Spatial Data: Data associated with space occupied by object. Types of spatial queries: contains, contained in, intersects, neighboring, east of, etc. Spatial data structures Spatial operators Spatial selects and joins PSQL - extend SQL, [18,20] 2/24/98 ICDE/SMU - Dunham 20 Differences from Spatial Queries Client is actually moving Location of client may be Spatial data is dynamic part of the query itself May depend on direction of movement Data may not directly contain location information Includes temporal features as well 2/24/98 ICDE/SMU - Dunham 21 Querying Moving Objects Moving Objects Spatio-Temporal (MOST) data model Dynamic Attributes - Change over time Queries over temporal history: Instantaneous - Ex: “Find all restaurants I’ll reach in the next half hour. ” Continuous - Ex: “Find all restaurants within 5 miles.” The answer continuously changes as the MU moves. Persistent - Ex: “Find the cars that travel greater than 10 miles in the next half hour.” Future Temporal Logic (FTL) language University of Illinois, [20] 2/24/98 ICDE/SMU - Dunham 22 Query Optimization How best to satisfy the information request made by the client? Different Cost Factors: I/O, network Different Access Options: cache, FN, broadcast Dynamic and Adaptable - environment changes Alternative plans include deciding (based on state of MH and environment) whether to access in the cache at the MH, to request a mobile transaction, or to obtain from a broadcast disk. 2/24/98 ICDE/SMU - Dunham 23 Outline Introduction & Data Management Issues Query Processing Data Broadcasting Overview Indexing Research Transaction Processing Projects & Products Conclusion 2/24/98 ICDE/SMU - Dunham 24 Data Broadcasting Server continually broadcasts data to MUs. Scalability: Cost does not depend on number of users listening. Mobile Unit may/may not have cache. Facilitates data access during disconnected periods. Allows location dependent data access. No need to predict with 100% accuracy the future data needs. Broadcast based on probability of access. Periodic broadcasting of all data. 2/24/98 ICDE/SMU - Dunham 25 Data Broadcasting (cont’d) Classification: Coverage - Everything, Subset Content - Static, Dynamic Indices - Index, Self Descriptive Data Stream - Flat, Skewed, Multiple Disks Client - Passive, Active For uniform page access, flat disk has best expected performance. With skewed page access, nonflat disks are better. Push based. 2/24/98 ICDE/SMU - Dunham 26 Broadcast Disks Simulate multiple disks of varying sizes and speeds. Data of higher interest on smaller faster disks Figure 4.1 from [15] (broadcast more frequently). Each “disk” contains data with similar access behavior. Combination of caching and broadcast disks. 2/24/98 ICDE/SMU - Dunham 27 Broadcast Disks (cont’d) Don’t want to store hottest pages. They may be broadcast frequently. Store in cache if probability of access (P) is greater than the frequency of broadcast (X). Cost based page replacement. Replace cache page with smallest P/X - PIX. Too expensive to implement. LIX - PIX approximation. Works well particularly with noise. Brown, MITL, Maryland, [37,38,39] 2/24/98 ICDE/SMU - Dunham 28 Air-Cache Dynamic - Adapts to system workload. Define temperature of data: Vapor (Steamy) Hot - Accessed frequently and broadcast. Liquid Warm - Accessed often, not broadcast, but kept in server’s main memory. Frigid (Icy) Cold - Accessed infrequently and stored on secondary storage. 2/24/98 ICDE/SMU - Dunham 29 Air-Cache (cont’d) Three level memory hierarchy based on temperature. Sparks (access) to data can increase temperature. No sparks, results in a reduction of temperature. Simulation results predict very good performance. Maryland, [43] 2/24/98 ICDE/SMU - Dunham 30 Adaptive Protocols Dynamically modify broadcast contents. Constant Broadcast Size (CBS) Server Protocol: Limited size and periodic Priority Popularity Factor (PF) Ignore Factore (IF) Variable Broadcst Size (VBS) Server Protocol: Aperiodic All data above threshold PF included. Arizona and UMKC, [40] 2/24/98 ICDE/SMU - Dunham 31 Outline Introduction & Data Management Issues Query Processing Data Broadcasting Transaction Processing Overview Transaction Model Concurrency Recovery Research Projects & Products Conclusion 2/24/98 ICDE/SMU - Dunham 32 Mobile Transaction (MT) Database transaction requested from a MU. May execute in FN or MU Issues Disconnect/Handoff Mobility Location Dependent Data Error Prone MU Resources/ Power Recovery/Restart Management 2/24/98 ICDE/SMU - Dunham 33 MT Requirements Keep autonomy of local DBMS LLT Interactive Advanced transaction models Nested Multidatabase Request from MU Execute anywhere Capture movement ACID (?) 2/24/98 ICDE/SMU - Dunham 34 MT Approaches No consensus on accepted approach MU may not have primary copy of data [45]: Transaction Proxy: MU does no transaction processing Read Only Transaction: MU only reads data Weak Transaction: Read and update cached data; Must synchronize updates with primary copy on FN. MU may have primary copy of data MU may access data on other MUs First class and second class transactions 2/24/98 ICDE/SMU - Dunham 35 MT Recovery Transaction, site, media, network failure - More frequent than in wired network. Different types of failures (partial) Handoff Voluntary disconnection Battery problems Lose computer?? Checkpoint data at MU to BS Checkpoint at handoff Database log plus transaction log May need compensating transactions 2/24/98 ICDE/SMU - Dunham 36 Atomicity for MT Weaken or provide different types of atomicity May decompose transaction into subtransactions May require atomicity at lower than transaction level Atomic commitment difficult (expensive) Global commit/Local Commit 2/24/98 ICDE/SMU - Dunham 37 Consistency for MT Weakening isolation and atomicity may weaken this as well. May divide data into clusters with consistency within clusters. Reintegration of updates after reconnect may cause many conflicts. May use bounded inconsistency. Impacted by location dependent data 2/24/98 ICDE/SMU - Dunham 38 Isolation for MT May be too restrictive Can’t always do at MU (disconnection) Isolation at lower levels in transaction Commitment at different levels of transaction Cooperating transactions 2/24/98 ICDE/SMU - Dunham 39 Durability for MT Durability for partial results May want durability for parts of transactions. Due to conflicts at reconnect, even durability of subtransactions may not be guaranteed. Local commit vs.. Global commit 2/24/98 ICDE/SMU - Dunham 40 MT Concurrency Control Mobility of MUs may increase message traffic for lock management MU failure may leave some data locked /unlocked 2/24/98 1) T1: Lock(Xa); Read(Xa) 2) T1 moves to B Server A Cell A Server B Cell B Xb Yb Xa Ya 3) T1: Lock(Yb); Read(Yb) 6) T1: Unlock(Yb); Commit; 6) T1: Unlock(Xa); Commit; Fig 2 from [48] ICDE/SMU - Dunham Xc Yc Zc Server C Cell C 4) T1 moves to C 5) T1: Lock(Zc); Write(Zc); Unlock(Zc); Commit 41 Revised Optimistic Locking O2PL-MT Read locks may be executed at multiple servers. Read unlock can be executed at any site Benefit shown using analytic model Purdue, [48] 2/24/98 LOCK HELD W_INTEND R_LOCK W_LOCK LOCK REQUEST W_Intend No Yes No R_Lock No Yes No W_Lock No No No Figure 3 from [48] ICDE/SMU - Dunham 42 Kangaroo Transaction (KT) Built on top of global transactions Captures data and movement behavior DAA as BS - Maintains logging and transaction status Logging at BS Flexible atomicity Restart after disconnect Management moves 2/24/98 ICDE/SMU - Dunham 43 Kangaroo Transaction (cont’d) Local Transaction - Sequence of read and write operations ending in commit or abort Global Transaction - Sequence of global or local transactions Joey Transaction - Sequence of global and local transactions ending in commit, abort, or split Kangaroo Transaction - Sequence of one or more Joeys with last one ending in commit or abort. All earlier end in split SMU, [47] 2/24/98 ICDE/SMU - Dunham 44 KT and Movement 2/24/98 ICDE/SMU - Dunham 45 Reporting and Co-Transactions Mobile transaction is a special type of multidatabase transactions. GDMS exists at each base station. Subtransactions of the mobile transaction will commit or abort independently. Atomic and non-compensatable transactions. Reporting and co-transactions. Pittsburgh, [46] 2/24/98 ICDE/SMU - Dunham 46 Clustering Model Views mobile transaction as beginning on mobile and nonmobile hosts. Transaction migration Transaction model is designed to maintain consistency of the database. Database is divided into clusters. Data is divided into core and quasi copies. Mobile transactions and operations are decomposed into a set of weak and strict transactions. 2/24/98 ICDE/SMU - Dunham 47 Clustering Model (cont’d) Weak operations access only data in the same cluster. Strict operations allowed database wide access. Two copies of data can be maintained (strict and weak). Clusters defined based on location and user profile. Transaction Proxy: dual transaction of one executed at mobile host which includes only the updates. Purdue, [51,52] 2/24/98 ICDE/SMU - Dunham 48 Mobile Transactions and Ambulatory Care Medical Personal Digital Assistant (MPDA) Battlefield - Cache copy of soldiers’ medical records in MPDA Distributed Medical Database - EMT obtains patient’s medical record and updates. BSA (Base Station Agent) is responsible for logging and recovery. Recovery based on sagas with save-points. Mailboxes used to save information. Purdue, [49,50] 2/24/98 ICDE/SMU - Dunham 49 Semantics-Based Mobile Transaction Processing Views mobile transaction processing as a concurrency and cache coherency problem. A stationary database server dishes out the fragments of an object on a request from a Mobile Unit. On completion of the transaction, the Mobile Units return the fragments to the server. These fragments are put together again by the merge operation at the server. Pittsburgh, [54] 2/24/98 ICDE/SMU - Dunham 50 Multidatabase Transaction Processing Manager Mobile transactions built on top of multidatabase global transactions. Timestamps used to enforce ordering Allows voluntary disconnections. MU part of MDS Message Queuing Facility (MQF) MU sends request to designated coordinating node on FN. Monash, [56] 2/24/98 ICDE/SMU - Dunham 51 PRO-MOTION MC/Database Transaction Processing approach Multiple transaction types Controlled divergence ACID Update cache and later DB at FH Compact - Compact Agent at MU, Mobility Manager at BS, Compact Manager at Server Pittsburgh, [55] 2/24/98 ICDE/SMU - Dunham 52 MT Research Limitations Architectural Assumptions No support for location dependent data Few Implementations 2/24/98 ICDE/SMU - Dunham 53 MT Management Options MU BS Combination Fixed/Relocatable/Moving Agent 2/24/98 ICDE/SMU - Dunham 54 Outline Introduction & Data Management Issues Query Processing Data Broadcasting Transaction Processing Projects & Products Conclusion 2/24/98 ICDE/SMU - Dunham 55 Some DB/MC Projects URLs MobiDick - Monash Univ. (Australia); http://www.ct.monash.edu.au/~mobidick Mobisaic - Univ. of Washington; http://www.cs.washington.edu/homes/voelker/mobisaic Purdue; http://www.cs.purdue.edu/research/cse/mobile SMU; http://www.seas.smu.edu/~mhd/mobile.html MCC - Collaboration Managment Infrastructure; http://www.mcc.com/projects/transaction University of Ioanina; http://zeus.cs.uoi.gr/ Michigan - CITI; http://www.citi.umich.edu/projects/mobile.html UCLA - Ficus; http://ficus-www.cs.ucla.edu/ficus 2/24/98 ICDE/SMU - Dunham Columbia; http://www.mcl.cs.columbia.edu 56 Rover Figure 6.1 from [15] 2/24/98 ICDE/SMU - Dunham 57 Oracle Mobile Agent Commercial Product Application, Static, Multiple Message Manager - MU Message Gateway - BS Agent - FN (Server) [67,69] Message Manager Gateway Corporate Network Agent Database Server 2/24/98 ICDE/SMU - Dunham 58 Sybase - SQL Anywhere Designed for Windows, (95, 3.x, NT), OS/2, DOS Limited memory requirements Full TP capabilities Includes SQL Remote Compatible with Sybase SQL Server [68] 2/24/98 ICDE/SMU - Dunham Remote Database SQL Anywhere standalone engine Message agent Consolidated Database SQL Anywhere network server Message agent 59 Sybase (cont’d) - SQL Remote Two way replication based on Consolidat message passing. ed DB Remote database are synchronized with consolidated DB Message Agent required at DB server Replication of subscribed fragments Remote Databases Periodic changes sent from consolidated DB to remote DBs Updates from committed transactions at remote submitted to consolidated database. Conflicts: Consolidated is master; Triggers used. 60 2/24/98 ICDE/SMU - Dunham Informix I-Mobile 1.0 discontinued: No replication Three tier approach appropriate for long term, but in the short term users wanted to be able to use existing client-server applications (not rewrite). Small DBMS server to run on mobile client Only dial up needed for now Informix Dynamic Server/Personal Edition (IDS/PE) for Windows 95/NT. Mobiles and desktop clients [64,66] 2/24/98 ICDE/SMU - Dunham 61 Outline Introduction & Data Management Issues Query Processing Data Broadcasting Transaction Processing Products Conclusion 2/24/98 ICDE/SMU - Dunham 62 Future Combine different approaches Semantic caching Query Optimization Adaptive Data Broadcasting Performance Benchmarks Security Location Dependent Queries 2/24/98 ICDE/SMU - Dunham 63 Acknowledgements and URL Bibliographies Earlier version of this tutorial presented at the 1996 Brazilian Database Symposium. We particularly want to thank Evaggelia Pitoura for providing several tables and figures from her recent book [15]. Some slide information obtained from slides presented at a database class at the University of Massachusetts, http://www-ccs.cs.umass.edu/mobile. Online bibliographies http://www.seas.smu.edu/~mhd/mobile.html http://www.ct.monash.edu.au/~mobidick 2/24/98 ICDE/SMU - Dunham 64