An adaptive fuzzy threshold-based approach for energy and performance efficient consolidation of virtual machines

Salimian, Leili; Safi-Esfahani, Faramarz; Nadimi-Shahraki, Mohammad H.

doi:10.1007/s00607-015-0474-5

Cited by 44 publications

(19 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…(4) Salimian et al [18] developed an algorithm based on adaptive fuzzy limits designed to detect overloaded and under-loaded hosts. Their objectives included reducing energy consumption, SLA violations, and the number of migrations.…”

Section: Related Workmentioning

confidence: 99%

Type-2 Fuzzy Logic Approach for Overloaded Hosts in Consolidation of Virtual Machines in Cloud Computing

Moura¹,

Schneider²,

Yamin³

et al. 2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

View full text Add to dashboard Cite

Dynamic consolidation of virtual machines (VMs) is an effective way to improve resource utilization and power efficiency in cloud computing. Determining when it is best to relocate VMs from an overloaded host is one aspect of dynamic VM consolidation that directly influences the resource utilization and Quality of Service (QoS) offered by the system. This paper presents a new proposal with a Type-2 Fuzzy Logic approach to address the uncertainties and inaccuracies in determining resource usage, aiming at energy savings with minimal performance degradation. Results in a simulated cloud computing environment show improvements in energy efficiency of 15.64% in the Median Absolute Deviation (MAD), 15.43% in the Inter Quartile Range (IQR), and 9.19% in the Local Regression (LR).The following research questions stand out: (i) do load balancers consider the uncertainties associated with factors such as CP, CC, and RAM? (ii) are the load balancers equipped with consistent techniques for the treatment of the uncertainties related to cloud computing environments? and (iii) do the users have the necessary knowledge about the computational and communication demands of their applications?This proposal extends the approaches in [16,15], modeling the uncertain variables generating CP, CC, and RAM in Load Balancing (LB) considering Type-2 Fuzzy Logic (T2FL) which can preserve the balance between energy efficiency and manage resources while ensuring QoS through SLAs for such cloud-based services.The paper is structured as follows. Related works are presented in section 2. Section 3 introduces basic concepts of Type-2 Fuzzy Logic. In section 4, details of the Int-FLBCC component and its conception are discussed, including database, fuzzification, rule base, inference, and defuzzification. Section 5 describes the experimental evaluation. Finally, section 6 presents conclusions and future work.

show abstract

Section: Related Workmentioning

confidence: 99%

Type-2 Fuzzy Logic Approach for Overloaded Hosts in Consolidation of Virtual Machines in Cloud Computing

Moura¹,

Schneider²,

Yamin³

et al. 2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

View full text Add to dashboard Cite

show abstract

“…There are many studies on the above three steps. In step (1), some adaptive threshold adjustment polices based on CPU historical utilisation have been proposed (Beloglazov and Buyya, 2010Salimian et al, 2016). In step (2), proposed four policies to select VMs: minimum migration time (MMT), minimisation of migrations (MM), highest potential growth and random choice (RC).…”

Section: Introductionmentioning

confidence: 99%

Energy-performance optimisation for the dynamic consolidation of virtual machines in cloud computing

Shuhua

2018

IJSOI

View full text Add to dashboard Cite

Dynamic consolidation of virtual machines (VMs) can reduce energy consumption by switching idle hosts to sleep mode. However, to meet the quality of service of customers, it is necessary to achieve the trade-off between energy and performance. This paper first puts forward a new dynamic threshold adjustment method using the variation coefficient of historical CPU utilisation, actual CPU utilisation and million instructions per second requests by VMs in migration list. Furthermore, it devises a novel VM allocation policy based on the grey correlation degree model, and formulates a conversion model of CPU utilisation for achieving better trade-off between energy consumption and performance. Finally, some experiments are carried out on the CloudSim and the PlanetLab workloads. The experimental results show that the methods proposed in this paper have obvious advantages on the trade-off between energy and performance during the VM consolidation.

show abstract

“…The Ref. [25] proposed an adaptive fuzzy threshold based manner to detect the over-loaded hosts and under-loaded hosts, which assisted to achieve energy and performance tradeoff.…”

Section: Related Workmentioning

confidence: 99%

“…Several works paid attention to the predictive frameworks, and variety of host overloading methods [20]- [22], [25] have been proposed. Z. Xiao et al [21] proposed the dynamic resources allocation using VMs in cloud data center.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Energy Efficient Resource Selection and Allocation Strategy for Virtual Machine Consolidation in Cloud Datacenters

Chang

Luo

et al. 2018

IEICE Trans. Inf. & Syst.

View full text Add to dashboard Cite

SUMMARYVirtual Machine Placement (VMP) plays an important role in ensuring efficient resource provisioning of physical machines (PMs) and energy efficiency in Infrastructure as a Service (IaaS) data centers. Efficient server consolidation assisted by virtual machine (VM) migration can promote the utilization level of the servers and switch the idle PMs to sleep mode to save energy. The trade-off between energy and performance is difficult, because consolidation may cause performance degradation, even service level agreement (SLA) violations. A novel residual available capacity (RAC) resource model is proposed to resolve the VM selection and allocation problem from the cloud service provider (CSP) perspective. Furthermore, a novel heuristic VM selection policy for server consolidation, named Minimized Square Root available Resource (MISR) is proposed. Meanwhile, an efficient VM allocation policy, named Balanced Selection (BS) based on RAC is proposed. The effectiveness validation of the BS-MISR combination is conducted on CloudSim with real workloads from the CoMon project. Evaluation results of experiments show that the proposed combination BS-MISR can significantly reduce the energy consumption, with an average of 36.35% compared to the Local Regression and Minimum Migration Time (LR-MMT) combination policy. Moreover, the BS-MISR ensures a reasonable level of SLAs compared to the benchmarks.

show abstract

An adaptive fuzzy threshold-based approach for energy and performance efficient consolidation of virtual machines

Cited by 44 publications

References 13 publications

Type-2 Fuzzy Logic Approach for Overloaded Hosts in Consolidation of Virtual Machines in Cloud Computing

Type-2 Fuzzy Logic Approach for Overloaded Hosts in Consolidation of Virtual Machines in Cloud Computing

Energy-performance optimisation for the dynamic consolidation of virtual machines in cloud computing

Energy Efficient Resource Selection and Allocation Strategy for Virtual Machine Consolidation in Cloud Datacenters

Contact Info

Product

Resources

About