A virtual machine re-packing approach to the horizontal vs. vertical elasticity trade-off for cloud autoscaling

Sedaghat, Mina; Hernández-Rodríguez, Francisco; Elmroth, Erik

doi:10.1145/2494621.2494628

Cited by 69 publications

(37 citation statements)

References 22 publications

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“…A capacity allocation problem in presented in [113] that exploits both horizontal and vertical elasticity. An integer linear problem is used to calculate an optimized new configuration able to deal with the current workload.…”

Section: Infrastructure-user Capacity Allocationmentioning

confidence: 99%

Quality-of-service in cloud computing: modeling techniques and their applications

Ardagna

Casale

Ciavotta

et al. 2014

J Internet Serv Appl

212

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Recent years have seen the massive migration of enterprise applications to the cloud. One of the challenges posed by cloud applications is Quality-of-Service (QoS) management, which is the problem of allocating resources to the application to guarantee a service level along dimensions such as performance, availability and reliability. This paper aims at supporting research in this area by providing a survey of the state of the art of QoS modeling approaches suitable for cloud systems. We also review and classify their early application to some decision-making problems arising in cloud QoS management.

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Section: Infrastructure-user Capacity Allocationmentioning

confidence: 99%

Quality-of-service in cloud computing: modeling techniques and their applications

Ardagna

Casale

Ciavotta

et al. 2014

J Internet Serv Appl

212

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“…• To react to a customer request [88] • To react to critical situations [41] and changes in system load [87] • In the course of a regular evaluation of the current placement, in order to improve overall optimization objectives (see Section 3.9)…”

Section: Actions Of the Cpmentioning

confidence: 99%

“…Beside the above reactive actions, a CP will also have to regularly review and potentially re-optimize the whole VM placement, in order to find a better fit to the changed demand of the existing VMs, modified eCP rental fees, modified electricity prices, or other changes that did not require immediate action but made the placement sub-optimal [87,93]. Such a review may be carried out at regular times (e.g., every 10 minutes), or it may be triggered by specific events.…”

Section: Actions Of the Cpmentioning

confidence: 99%

Allocation of Virtual Machines in Cloud Data Centers—A Survey of Problem Models and Optimization Algorithms

2015

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Data centers in public, private, and hybrid cloud settings make it possible to provision virtual machines (VMs) with unprecedented flexibility. However, purchasing, operating, and maintaining the underlying physical resources incurs significant monetary costs and also environmental impact. Therefore, cloud providers must optimize the usage of physical resources by a careful allocation of VMs to hosts, continuously balancing between the conflicting requirements on performance and operational costs. In recent years, several algorithms have been proposed for this important optimization problem. Unfortunately, the proposed approaches are hardly comparable because of subtle differences in the used problem models. This paper surveys the used problem formulations and optimization algorithms, highlighting their strengths and limitations, also pointing out the areas that need further research in the future.

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“…Vertical scaling mechanisms are limited to individual physical machines [239]. Furthermore, changing compute or memory resources on-the-fly is not supported in most cases.…”

Section: Elastic Cloud-based Idps Provisioningmentioning

confidence: 99%

Security configuration management in intrusion detection and prevention systems

Alsubhi

Alhazmi

Bouabdallah

et al. 2012

IJSN

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Intrusion Detection and/or Prevention Systems (IDPS) represent an important line of defense against a variety of attacks that can compromise the security and proper functioning of an enterprise information system. IDPSs can be network or host-based and can collaborate in order to provide better detection of malicious traffic. Although several IDPS systems have been proposed, their appropriate configuration and control for effective detection/prevention of attacks and efficient resource consumption is still far from trivial.Another concern is related to the slowing down of system performance when maximum security is applied, hence the need to trade off between security enforcement levels and the performance and usability of an enterprise information system.In this dissertation, we present a security management framework for the configuration and control of the security enforcement mechanisms of an enterprise information system. The approach leverages the dynamic adaptation of security measures based on the assessment of system vulnerability and threat prediction, and provides several levels of attack containment. Furthermore, we study the impact of security enforcement levels on the performance and usability of an enterprise information system. In particular, we analyze the impact of an IDPS configuration on the resulting security of the network, and on the network performance. We also analyze the performance of the IDPS for different configurations and under different traffic characteristics. The analysis can then be used to predict the impact of a given security configuration on the prediction of the impact on network performance.iii Acknowledgements All praise is due to Allah who guided me through out this research and beyond.My deepest gratitude is to my advisor, Prof. Raouf Boutaba, for his guidance, support, patience, and encouragement. I have been amazingly fortunate to have an advisor who gave me the freedom to explore on my own, and at the same time the guidance to recover when my steps faltered. He was always available, professional, and friendly. I have learned from him to think differently, be optimistic, and be self motivated. This work would have not been done without his advice and valuable comments.

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A virtual machine re-packing approach to the horizontal vs. vertical elasticity trade-off for cloud autoscaling

Cited by 69 publications

References 22 publications

Quality-of-service in cloud computing: modeling techniques and their applications

Quality-of-service in cloud computing: modeling techniques and their applications

Allocation of Virtual Machines in Cloud Data Centers—A Survey of Problem Models and Optimization Algorithms

Security configuration management in intrusion detection and prevention systems

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