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Mobile Computing and Databases (modified from ICDE98)

Mobile Computing and Databases (modified from ICDE98). Margaret H. Dunham Southern Methodist University Dept of Computer Science and Engineering Dallas, Texas 75275 mhd@seas.smu.edu http://www.seas.smu.edu/~mhd. Outline. Introduction & Data Management Issues Query Processing

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Mobile Computing and Databases (modified from ICDE98)

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  1. Mobile Computing and Databases (modified from ICDE98) Margaret H. Dunham Southern Methodist University Dept of Computer Science and Engineering Dallas, Texas 75275 mhd@seas.smu.edu http://www.seas.smu.edu/~mhd

  2. Outline • Introduction & Data Management Issues • Query Processing • Data Broadcasting • Transaction Processing • Projects & Products • Conclusion ICDE/SMU - Dunham

  3. Mobile Computing Architecture ICDE/SMU - Dunham

  4. 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)) ICDE/SMU - Dunham

  5. 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, Motorola ALTAIR ICDE/SMU - Dunham

  6. 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 ICDE/SMU - Dunham

  7. 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 ICDE/SMU - Dunham

  8. Location Management • Tracking mobile user • User associated with home location server (Home Agent) • May augment by searching in local area first • May augment with user profiles • Mobile IP [11,14] • Triangle Routing • Route Optimization • Location Control (Routing Agent) S Ah Af M ICDE/SMU - Dunham

  9. 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 ICDE/SMU - Dunham

  10. 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 ICDE/SMU - Dunham

  11. Technology Push • Internet: ftp, telnet, email, http,html • Advancing Wireless Communication Technologies • Laptop, Notebook, and Palmtop Computers ICDE/SMU - Dunham

  12. Classification of Mobile Database Systems ICDE/SMU - Dunham

  13. 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 ICDE/SMU - Dunham

  14. Insurance Example ICDE/SMU - Dunham

  15. Medical Example • 911 Call • Ambulance arrives/departs • Closest hospital • Access patient records • Send vital signs • Update patient records • Page hospital personnel • Order medical supplies ICDE/SMU - Dunham

  16. MC/DB Research • Transaction Processing • Caching - Replication • Broadcast Disks • Agents • Mobility • Location Dependent Data • Recovery • ACID (?) ICDE/SMU - Dunham

  17. Outline • Introduction & Data Management Issues • Query ProcessingLocation Dependent Queries and DataNew Query TypesQuery Optimization • Data Broadcasting • Transaction Processing • Projects & Products • Conclusion ICDE/SMU - Dunham

  18. 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] ICDE/SMU - Dunham

  19. 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).” ICDE/SMU - Dunham

  20. 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] ICDE/SMU - Dunham

  21. Differences from Spatial Queries • Client is actually moving • Location of client may be part of the query itself • May depend on direction of movement • Data may not directly contain location information • Includes temporal features as well Spatial data is dynamic ICDE/SMU - Dunham

  22. 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] ICDE/SMU - Dunham

  23. 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. ICDE/SMU - Dunham

  24. Outline • Introduction & Data Management Issues • Query Processing • Data BroadcastingOverviewIndexingResearch • Transaction Processing • Projects & Products • Conclusion ICDE/SMU - Dunham

  25. 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. ICDE/SMU - Dunham

  26. 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. ICDE/SMU - Dunham

  27. Broadcast Disks • Simulate multiple disks of varying sizes and speeds. Data of higher interest on smaller faster disks (broadcast more frequently). • Each “disk” contains data with similar access behavior. • Combination of caching and broadcast disks. Figure 4.1 from [15] ICDE/SMU - Dunham

  28. 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] ICDE/SMU - Dunham

  29. 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. ICDE/SMU - Dunham

  30. 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] ICDE/SMU - Dunham

  31. 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] ICDE/SMU - Dunham

  32. Outline • Introduction & Data Management Issues • Query Processing • Data Broadcasting • Transaction ProcessingOverviewTransaction ModelConcurrencyRecoveryResearch • Projects & Products • Conclusion ICDE/SMU - Dunham

  33. 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 ICDE/SMU - Dunham

  34. MT Requirements • Keep autonomy of local DBMS • LLT • Interactive • Advanced transaction models • Nested • Multidatabase • Request from MU • Execute anywhere • Capture movement • ACID (?) ICDE/SMU - Dunham

  35. 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 ICDE/SMU - Dunham

  36. 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 ICDE/SMU - Dunham

  37. 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 ICDE/SMU - Dunham

  38. 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 ICDE/SMU - Dunham

  39. 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 ICDE/SMU - Dunham

  40. 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 ICDE/SMU - Dunham

  41. MT Concurrency Control 1) T1: Lock(Xa); Read(Xa) 2) T1 moves to B Server A Cell A Xa Ya 3) T1: Lock(Yb); Read(Yb) Server B Cell B 6) T1: Unlock(Yb); Commit; Xb Yb 4) T1 moves to C Xc Yc Zc 5) T1: Lock(Zc); Write(Zc); Unlock(Zc); Commit Server C Cell C • Mobility of MUs may increase message traffic for lock management • MU failure may leave some data locked /unlocked 6) T1: Unlock(Xa); Commit; Fig 2 from [48] ICDE/SMU - Dunham

  42. 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] Figure 3 from [48] ICDE/SMU - Dunham

  43. 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 ICDE/SMU - Dunham

  44. 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] ICDE/SMU - Dunham

  45. KT and Movement ICDE/SMU - Dunham

  46. 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] ICDE/SMU - Dunham

  47. 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. ICDE/SMU - Dunham

  48. 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] ICDE/SMU - Dunham

  49. 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] ICDE/SMU - Dunham

  50. 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] ICDE/SMU - Dunham

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