000			02790nam a22003615i 4500
001			108071
003			DE-He213
005			20230102113331.0
007			cr nn 008mamaa
008			180224s2018 gw | s |||| 0|eng d
020			_a9783319732145 _9
024	7		_a10.1007/978-3-319-73214-5 _2doi
040			_aES-MaUEC _bspa
050		4	_aQA76.585 2018 EB
100	1		_aTan, Rong Kun Jason _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aOptimized Cloud Based Scheduling _cby Rong Kun Jason Tan, John A. Leong, Amandeep S. Sidhu.
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2018.
300			_a1 recurso en línea (XIII, 99 páginas 33 ilustraciones)
347			_atext file _bPDF _2rda
490	0		_aData, Semantics and Cloud Computing, _x2524-6593 ; _v759
505	0		_aIntroduction -- Background -- Benchmarking -- Computation of Large Datasets -- Optimized Online Scheduling Algorithms.
520			_aThis book presents an improved design for service provisioning and allocation models that are validated through running genome sequence assembly tasks in a hybrid cloud environment. It proposes approaches for addressing scheduling and performance issues in big data analytics and showcases new algorithms for hybrid cloud scheduling. Scientific sectors such as bioinformatics, astronomy, high-energy physics, and Earth science are generating a tremendous flow of data, commonly known as big data. In the context of growing demand for big data analytics, cloud computing offers an ideal platform for processing big data tasks due to its flexible scalability and adaptability. However, there are numerous problems associated with the current service provisioning and allocation models, such as inefficient scheduling algorithms, overloaded memory overheads, excessive node delays and improper error handling of tasks, all of which need to be addressed to enhance the performance of big data analytics.
650		7	_aInformática en la nube _2embne _9666069
700	1		_aLeong, John A _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aSidhu, Amandeep S _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _1http://viaf.org/viaf/90888523
710	2		_aSpringerLink (Online service) _0http://id.loc.gov/authorities/names/no2005046756 _1http://viaf.org/viaf/148105729 _9106996
776	0	8	_iPrinted edition: _z9783319732121
776	0	8	_iPrinted edition: _z9783319732138
776	0	8	_iPrinted edition: _z9783030103330
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-73214-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
490	0		_aEngineering (Springer-11647)
998			_b03/2019 _dz _ep _feng _ggw _h0
999			_c108071 _d108071