000 04205nam a22005655i 4500
001 978-3-031-02477-1
003 DE-He213
005 20240730163938.0
007 cr nn 008mamaa
008 220601s2008 sz | s |||| 0|eng d
020 _a9783031024771
_9978-3-031-02477-1
024 7 _a10.1007/978-3-031-02477-1
_2doi
050 4 _aQA1-939
072 7 _aPB
_2bicssc
072 7 _aMAT000000
_2bisacsh
072 7 _aPB
_2thema
082 0 4 _a510
_223
100 1 _aDouglas, Terry.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_981304
245 1 0 _aReplicated Data Management for Mobile Computing
_h[electronic resource] /
_cby Terry Douglas.
250 _a1st ed. 2008.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2008.
300 _aXII, 93 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Mobile & Pervasive Computing,
_x1933-902X
505 0 _aIntroduction -- System Models -- Data Consistency -- Replicated Data Protocols -- Partial Replication -- Conflict Management -- Case Studies -- Conclusions -- Bibliography.
520 _aManaging data in a mobile computing environment invariably involves caching or replication. In many cases, a mobile device has access only to data that is stored locally, and much of that data arrives via replication from other devices, PCs, and services. Given portable devices with limited resources, weak or intermittent connectivity, and security vulnerabilities, data replication serves to increase availability, reduce communication costs, foster sharing, and enhance survivability of critical information. Mobile systems have employed a variety of distributed architectures from client-server caching to peer-to-peer replication. Such systems generally provide weak consistency models in which read and update operations can be performed at any replica without coordination with other devices. The design of a replication protocol then centers on issues of how to record, propagate, order, and filter updates. Some protocols utilize operation logs, whereas others replicate state. Systems might provide best-effort delivery, using gossip protocols or multicast, or guarantee eventual consistency for arbitrary communication patterns, using recently developed pairwise, knowledge-driven protocols. Additionally, systems must detect and resolve the conflicts that arise from concurrent updates using techniques ranging from version vectors to read-write dependency checks. This lecture explores the choices faced in designing a replication protocol, with particular emphasis on meeting the needs of mobile applications. It presents the inherent trade-offs and implicit assumptions in alternative designs. The discussion is grounded by including case studies of research and commercial systems including Coda, Ficus, Bayou, Sybase's iAnywhere, and Microsoft's Sync Framework. Table of Contents: Introduction / System Models / Data Consistency / Replicated Data Protocols / Partial Replication / Conflict Management / Case Studies / Conclusions / Bibliography.
650 0 _aMathematics.
_911584
650 0 _aEngineering.
_99405
650 0 _aMobile computing.
_93438
650 0 _aCooperating objects (Computer systems).
_96195
650 0 _aUser interfaces (Computer systems).
_911681
650 0 _aHuman-computer interaction.
_96196
650 1 4 _aMathematics.
_911584
650 2 4 _aTechnology and Engineering.
_981305
650 2 4 _aMobile Computing.
_93438
650 2 4 _aCyber-Physical Systems.
_932475
650 2 4 _aUser Interfaces and Human Computer Interaction.
_931632
710 2 _aSpringerLink (Online service)
_981306
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031013492
776 0 8 _iPrinted edition:
_z9783031036057
830 0 _aSynthesis Lectures on Mobile & Pervasive Computing,
_x1933-902X
_981307
856 4 0 _uhttps://doi.org/10.1007/978-3-031-02477-1
912 _aZDB-2-SXSC
942 _cEBK
999 _c85151
_d85151