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008			220601s2008 sz | s |||| 0|eng d
020			_a9783031024771
024	7		_a10.1007/978-3-031-02477-1 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA76.59 _b2008 EB
100	1		_aTerry, Douglas A. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9665572
245	1	0	_aReplicated Data Management for Mobile Computing _cby Terry Douglas
250			_a1st edition 2008
264		1	_aCham _bSpringer International Publishing _c2008
300			_a1 recurso en línea (XII, 93 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_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.
988			_aSynthesis Collection of Technology_2008
650		7	_2embne _9476230 _aInformática móvil
650		7	_2embne _9666053 _aComputación ubicua
650		7	_2embne _9673059 _aGestión de memoria
776	0	8	_iPrinted edition: _z9783031013492
776	0	8	_iPrinted edition: _z9783031036057
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02477-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _esc _zSI