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001-es BibID:	BIBFORM086227
Első szerző:	Moghadasi, Mohammad (informatikus)
Cím:	Cloud Computing Auditing : roadmap and process / Mohammad Moghadasi, Seyed Majid Mousavi, Gábor Fazekas
Dátum:	2018
ISSN:	2158-107X 2156-5570
Megjegyzések:	Cloud Computing is a new form of IT system and infrastructure outsourcing as an alternative to traditional IT Outsourcing (ITO). Hence, migration to cloud computing is rapidly growing among organizations. Adopting this technology brings numerous positive aspects, although imposing different risks and concerns to organization. An organization which officially deputes its cloud computing services to outside (offshore or inshore) providers and implies that it outsources its functions and process of its IT to external BPO services providers. Therefore, customers of cloud must evaluate and manage the IT infrastructure construction and the organization's IT control environment of BPO vendors [25]. Since cloud is an internet-based technology, cloud auditing would be very critical and challengeable in such an environment. This paper focuses on practices related to auditing processes, methods, techniques, standards and frameworks in cloud computing environments.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk
Megjelenés:	International Journal of Advanced Computer Science and Applications. - 9 : 12 (2018), p. 467-472. -
További szerzők:	Mousavi, Seyedmajid (1982-) (informatika) Fazekas Gábor (1952-) (informatikus, matematikus)
Internet cím:	Szerző által megadott URL DOI Intézményi repozitóriumban (DEA) tárolt változat
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001-es BibID:	BIBFORM070550
035-os BibID:	(WoS)000428151900012 (Scopus)85047228414
Első szerző:	Mousavi, Seyedmajid (informatika)
Cím:	Dynamic resource allocation using combinatorial methods in Cloud : A case study / Seyed Majid Mousavi, Mohammad Moghadasi, Gabor Fazekas
Dátum:	2017
Megjegyzések:	Utilizing dynamic resource allocation for loadbalancing is considered as an important optimization process oftask scheduling in cloud computing. A poor scheduling policymay overload certain virtual machines while remaining virtualmachines are idle. Accordingly, this paper proposes a hybrid loadbalancing algorithm with combination of Teaching-Learning-Based Optimization (TLBO) and Grey Wolves Optimizationalgorithms, which can well contribute in maximizing thethroughput using well balanced load across virtual machines andovercome the problem of trap into local optimum. The hybridalgorithm is benchmarked on eleven test functions and acomparative study is conducted to verify the results with particleswarm optimization (PSO), Biogeography-based optimization(BBO), and GWO. To evaluate the performance of the proposedalgorithm for load balancing, the hybrid algorithm is simulatedand the experimental results are presented.
ISBN:	978-1-5386-1264-4
Tárgyszavak:	Műszaki tudományok Informatikai tudományok előadáskivonat könyvrészlet cloud computing resource allocation optimization
Megjelenés:	8th IEEE International Conference on Cognitive Infocommunications: CogInfoCom 2017 : Proceedings : September 11-14, 2017 Debrecen, Hungary. - p. 73-78. -
További szerzők:	Moghadasi, Mohammad (1985-) (informatikus) Fazekas Gábor (1952-) (informatikus, matematikus)
Internet cím:	Intézményi repozitóriumban (DEA) tárolt változat DOI
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