Optimizing virtual machine placement for energy and SLA in clouds using utility functions

Mosa, Abdelkhalik; Paton, Norman W.

doi:10.1186/s13677-016-0067-7

Cited by 71 publications

(58 citation statements)

References 31 publications

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“…For this work, simulation were carried out using Cloudsim [21] and a data centre similar to that used in [12,16,18,20] was used and consisted of a number of heterogeneous PMs. These PMs were of two categories with specifications and power consumption models based on benchmarked data from real servers [36] and given as follows: category one had 2 CPU cores clocked at 1,860MHz and 4GB of memory, while the second category also had 2 CPU cores each clocked at 2,600MHz and with 4GB of memory.…”

Section: Resultsmentioning

confidence: 99%

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Fourth Industrial Revolution for Development: The Relevance of Cloud Federation in Healthcare Support

Ajayi

Bagula

2019

IEEE Access

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Inefficient healthcare is a major concern among many African nations and can be mitigated by building world-class infrastructure connecting different medical facilities for collaboration and resource sharing. Such infrastructure should support the collection and exchange of medical data among healthcare practitioners for the purpose of accessing expertise not available locally. It should be equipped with the most recent technologies of the fourth Industrial Revolution (4IR), providing decision support to doctors thereby enabling African nations leapfrog from poorly equipped to medically prepared countries. Sadly, world-class healthcare infrastructure are a missing piece in the African public health ecosystem. Medical facilities are either non-existent or prohibitively expensive when they exist. Federated cloud computing can provide a solution to this challenge. Being a model that allows collaboration between multiple Cloud Service Providers (CSPs) by pooling computing resources together with the aim of meeting specific business or technological need; it allows for the execution of tasks on computing resources in a flexible and cost efficient manner. This paper aims to connect unconnected medical facilities in Africa by proposing a cloud federation for healthcare using co-operative and competitive collaboration models. Simulations were carried out to test the efficacy of these models using five different workload allocation schemes: First-Fit-Descending (FFD), Best-Fit-Descending (BFD) and Binary-Search-Best-Fit (BSBF); Genetic Algorithm meta-heuristic and the Stable Roommate Allocation (SRA) economic model for both light and heavy workloads. Results of simulations revealed that the co-operative cloud federation model resulted in lower allocation delays but higher resource utilisation; while the competitive model provided faster service delivery and better Quality of service (QoS) adherence. It also showed that BSBF and BFD gave the best resources utilisation and energy conservation, while FFD was the fastest overall. Finally, deployment considerations and potential business models for the federated cloud for healthcare in Africa were presented.

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Section: Resultsmentioning

confidence: 99%

“…Genetic Algorithm-based VM Allocation (GAVA): There have been a number of works that have applied GA to Cloud resource allocation; of particular 8/25 [14,20]. Like in those works, we also followed the classical GA steps described in [19], however our implementation was a bit different.…”

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confidence: 99%

Fourth Industrial Revolution for Development: The Relevance of Cloud Federation in Healthcare Support

Ajayi

Bagula

2019

IEEE Access

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“…And it also can be used to dynamically track cloud workloads and relocate VMs to keep resource utilization higher even under dynamically changing workload conditions. There are a number of different algorithms that manage dynamic workloads within cloud environments using overcommitment and live-migration technologies [3][4][5]. In the next section we describe a simple heuristic algorithm which we implemented based on the JINR cloud workloads profile.…”

Section: Dynamic Relocation Of Resources 21 Overcommitment and Live-mentioning

confidence: 99%

Advanced Scheduling in IaaS Clouds

et al. 2019

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The complexity of modern software libraries and applications makes it hard to predict possible workloads generated by the software that may lead to significant underutilization of hardware in Infrastructure-as-a-Service (IaaS) clouds. In this paper, we give a review of an approach aimed to deal with resource underutilization in cloud environments, including description of a developed software framework and an example algorithm. IaaS clouds following this universal approach can help increase overall cloud resource utilization independently of the variety of cloud applications. * Corresponding author: balashov@jinr.ru

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“…A comparison of different power aware placement solutions with respect to the proposed one has been depicted in × Our approach I. Power-aware VM placement has been widely studied in the cloud computing environment [9]- [12]. Surveys on VM placement techniques can be found in [13], [14].…”

Section: Related Workmentioning

confidence: 99%

Power-Aware Virtual Network Function Placement and Routing Using an Abstraction Technique

Varasteh

Andrade

Machuca

et al. 2018

2018 IEEE Global Communications Conference (GLOBECOM)

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The Network Function Virtualization (NFV) is very promising for efficient provisioning of network services and is attracting a lot of attention. NFV can be implemented in commercial off-the-shelf servers or Physical Machines (PMs), and many network services can be offered as a sequence of Virtual Network Functions (VNFs), known as VNF chains. Furthermore, many existing network devices (e.g., switches) and collocated PMs are underutilized or over-provisioned, resulting in low powerefficiency. In order to achieve more energy efficient systems, this work aims at designing the placement of VNFs such that the total power consumption in network nodes and PMs is minimized, while meeting the delay and capacity requirements of the foreseen demands. Based on existing switch and PM power models, we propose a Integer Linear Programming (ILP) formulation to find the optimal solution. We also propose a heuristic based on the concept of Blocking Islands (BI), and a baseline heuristic based on the Betweenness Centrality (BC) property of the graph. Both heuristics and the ILP solutions have been compared in terms of total power consumption, delay, demands acceptance rate, and computation time. Our simulation results suggest that BIbased heuristic is superior compared with the BC-based heuristic, and very close to the optimal solution obtained from the ILP in terms of total power consumption and demands acceptance rate. Compared to the ILP, the proposed BI-based heuristic is significantly faster and results in 22% lower end-to-end delay, with a penalty of consuming 6% more power in average.

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Optimizing virtual machine placement for energy and SLA in clouds using utility functions

Cited by 71 publications

References 31 publications

Fourth Industrial Revolution for Development: The Relevance of Cloud Federation in Healthcare Support

Fourth Industrial Revolution for Development: The Relevance of Cloud Federation in Healthcare Support

Advanced Scheduling in IaaS Clouds

Power-Aware Virtual Network Function Placement and Routing Using an Abstraction Technique

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