Resource management for Infrastructure as a Service (IaaS) in cloud computing: A survey

Manvi, Sunilkumar S.; Shyam, Gopal K.

doi:10.1016/j.jnca.2013.10.004

Cited by 502 publications

(213 citation statements)

References 48 publications

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“…For example, Singh and Chana [11] focused on autonomic computing with a particular emphasis on QoS-aware management of resources; Jennings and Stadler [12] used resource management functions as a classification method; Mustafa et al [13] reviewed the literature based on the metrics used and discussed the underlying research problems. Manvi and Shyam [14] classified the literature into problem specific categories such as resource provisioning and allocation; whereas Singh and Chana [15] targeted resource provisioning in general, wherein elasticity is considered as a trait of resource provisioning mechanism.…”

Section: Cloud Resource Managementmentioning

confidence: 99%

A control theoretical view of cloud elasticity: taxonomy, survey and challenges

Ullah

Shen

et al. 2018

Cluster Comput

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The lucrative features of cloud computing such as pay-as-you-go pricing model and dynamic resource provisioning (elasticity) attract clients to host their applications over the cloud to save up-front capital expenditure and to reduce the operational cost of the system. However, the efficient management of hired computational resources is a challenging task. Over the last decade, researchers and practitioners made use of various techniques to propose new methods to address cloud elasticity. Amongst many such techniques, control theory emerges as one of the popular methods to implement elasticity. A plethora of research has been undertaken on cloud elasticity including several review papers that summarise various aspects of elasticity. However, the scope of the existing review articles is broad and focused mostly on the highlevel view of the overall research works rather than on the specific details of a particular implementation technique. While considering the importance, suitability and abundance of control theoretical approaches, this paper is a step forward towards a stand-alone review of control theoretic aspects of cloud elasticity. This paper provides a detailed taxonomy comprising of relevant attributes defining the following two perspectives, i.e., control-theory as an implementation technique as well as cloud elasticity as a target application domain. We carry out an exhaustive review of the literature by classifying the existing elasticity solutions using the attributes of control theoretic perspective. The summarized results are further presented by clustering them with respect to the type of control solutions, thus helping in comparison of the related control solutions. In last, a discussion summarizing the pros and cons of each type of control solutions are presented. This discussion is followed by the detail description of various open research challenges in the field.

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Section: Cloud Resource Managementmentioning

confidence: 99%

A control theoretical view of cloud elasticity: taxonomy, survey and challenges

Ullah

Shen

et al. 2018

Cluster Comput

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“…The management of MCC resources is also a great challenge owing to the number of objectives that need to be met while considering the relative size (large) of the infrastructures [17] [20]. Few studies have previously addressed these issues [18] [19] [20] [26], and as a consequence, it is a salient issue for service providers to design powerful resource management schemes that will satisfy the requirements of the MCC applications in real time [21]. This paper is outlined as follows: Section 2 reviewed the related works regarding the recommended method, while Sections 3 provided a brief discussion of the suggested methodology.…”

Section: Introductionmentioning

confidence: 99%

A Novel Approach of Reducing Energy Consumption by Utilizing Enthalpy in Mobile Cloud Computing

Mohammed¹,

Țăpuș²

2017

STUD INFORM CONTROL

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Abstract:The Mobile Cloud Computing (MCC) technology is a growing technology that aids in improving the quality of mobile services. The resources in MCC are dynamically allocated to the users based on their needs. The users pay for the resources consumed by their programs, but the drawbacks of process failures and knapsack problems of resource allocation still exist in MCC. Furthermore, the scheduling of energy consumption and computational cost is very high. To solve these issues, an optimized energy efficiency resource management technique is set forth in this study. The recommended method holds two stages: a) the initial stage, when the task loss, transmission probability, delay, utilization and reputation for every single task is individually measured and the enthalpy was calculated, and b) the second stage, when the enthalpy-related Cuckoo Search Optimization (CSO) algorithm was used to optimize and prioritize the resources to the powerful resource management. The execution of the recommended method automatically reduced the knapsack issue, energy and cost. A formal analysis of the resource management framework has ensured that the provider executes resources based on the power consumption. The performance of the suggested algorithm was benchmarked against the performance of other conventional algorithms.

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“…It is a network based environment that allows sharing of computation as well as resources. Customers whether belongs to small or large organization are drawn toward cloud's promise of nimbleness reduced cost and enhanced IT resources [1]. IT companies are transforming their services from providing their own IT infrastructure to utilize computation services provided by cloud to their IT need [1].…”

Section: Introductionmentioning

confidence: 99%

“…Customers whether belongs to small or large organization are drawn toward cloud's promise of nimbleness reduced cost and enhanced IT resources [1]. IT companies are transforming their services from providing their own IT infrastructure to utilize computation services provided by cloud to their IT need [1]. Even cloud computing provides abundant opportunities to its customer but still it has lot of issues to be resolved.…”

Section: Introductionmentioning

confidence: 99%

Data Security Enhancement in Cloud Computing using Proxy Blind Signature

Mohanty¹,

Hota²,

Pattanayak³

2017

IJCA

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Cloud computing is a rapidly growing internet based computing that endeavors to be dynamic, reliable and available with guaranteed quality of service. This has become a sophisticated computing platform or technology for customers as well as organizations for its availability of resources such as software, storage and network with minimum cost. Using the business model like Software as a Service (SaaS), Platform as a Service (PaaS) and Infrastructure as a service (IaaS) this environment have increased distribute computing capacity. Preserving confidentiality, integrity and availability are the vexing issues in cloud computing environment. This paper highlights cloud computing threats and proposes a distributed and efficient encryption algorithm to enhance the data security in cloud.

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Resource management for Infrastructure as a Service (IaaS) in cloud computing: A survey

Cited by 502 publications

References 48 publications

A control theoretical view of cloud elasticity: taxonomy, survey and challenges

A control theoretical view of cloud elasticity: taxonomy, survey and challenges

A Novel Approach of Reducing Energy Consumption by Utilizing Enthalpy in Mobile Cloud Computing

Data Security Enhancement in Cloud Computing using Proxy Blind Signature

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