A Study on Strategic Provisioning of Cloud Computing Services

Table 1

Requirements of cloud service provisioning requirements.

Requirements	Features	Solving approaches	Attributes	References
Agility and availability	Virtualised optical network (VON)	Appropriate optical bandwidth at the appropriate time	Any-to-any connectivity	Jinno and Tsukishima [36]
	Combining SOA and cloud computing.	An interactive session that offers insights from previous field engagements	Realizing business requirements	Hirzalla [37]
	A framework for resource provisioning	Through network virtualisation	Optimised resources, on-demand scalability	Peng et al. [39]
Pricing	Multidimensional procurement auction for composite services	Based on a graph structure	The auction mechanism	Weinhardt et al. [41]
	Single pricing strategies for customer satisfaction	Multinomial logit (MNL) framework is used	Pricing policies called time-of-use (ToU)	Saure et al. [42]
	Resource pricing and allocation policy	Future resource price prediction	Game theory and implemented in CloudSim simulation	Teng and Magoulès [43]
	Using tariffs and charging	Regulations, tax laws, and SLA	Pricing models	Samimi and Patel [45]
	Joint optimisation of scheduling and pricing decisions	Dynamic scheduling and pricing (Dyn-SP) algorithms	Higher revenue with the same queuing delay	Ren and van der Schaar [50]
Security and trust	Secured cloud service selection	Secured service framework	Software engineering	Mouratidis et al. [52]
	Insurance models for cloud security	Cloud security insurance framework	MEGHAND	Dasgupta and Rahman [53]
	Federated identity management	Hierarchical cloud based risk aggregation system based service provisioning	Risk metrics	Arias-Cabarcos et al. [54]
	Ranking based fault tolerant framework	FT cloud model	Ranking with optimal fault tolerance	Zheng et al. [55]
	Quantitative risk and impact management	QURIC framework	Wideband Delphi method	Saripalli and Walters [57]
QoS	QoS-based utility optimum service selection	Optimization with minimum requirements	Response time, availability, and throughput	Salama et al. [59]
	Service selection carried out by CWS tree constriction	FSM, SAW, tree pruning algorithm	Possible execution path	[60]
	System model of personalized user support to optimize QoS support.	Algorithm	Trust, response time, price, and platform	Zhao et al. [61]
	QoS prediction system (CloudRank) considering past user experience	KRCC and ranking prediction algorithm	Preference of services	Zheng et al. [62]