Control-based load-balancing techniques: Analysis and performance evaluation via a randomized optimization approach

Papadopoulos, Alessandro Vittorio; Klein, Cristian; Maggio, Martina; Dürango, Jonas; Dellkrantz, Manfred; Hernández-Rodríguez, Francisco; Elmroth, Erik; Årzén, Karl-Erik

doi:10.1016/j.conengprac.2016.03.020

Cited by 19 publications

(8 citation statements)

References 63 publications

(79 reference statements)

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“…Various algorithms and controllers have been employed to extend the brownout-concept as originally envisioned, including how it can be used to optimize both service delivery [9], [10], [11], [12], [13] and cloud infrastructure power consumption [14], [15], [16]. These results validate the claim that great utility and efficiency increases can be made using a qualityreduction approach.…”

Section: Related Workmentioning

confidence: 72%

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Quality-Elasticity: Improved Resource Utilization, Throughput, and Response Times Via Adjusting Output Quality to Current Operating Conditions

Larsson

Tärneberg

Klein

et al. 2019

2019 IEEE International Conference on Autonomic Computing (ICAC)

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This work addresses two related problems for online services, namely poor resource utilization during regular operating conditions, and low throughput, long response times, or poor performance under periods of high system load. To address these problems, we introduce our notion of qualityelasticity as a manner of dynamically adapting response qualities from software services along a fine-grained spectrum. When resources are abundant, response quality can be increased, and when resources are scarce, responses are delivered at a lower quality to prioritize throughput and response times. We present an example of how a complex online shopping site can be made quality-elastic. Experiments show that, compared to state of the art, improvements in throughput (57% more served queries), lowered response times (8 time reduction for 95 th percentile responses), and an estimated 40% profitability increase can be made using our quality-elastic approach. When resources are abundant, our approach may achieve upwards of twice as high resource utilization as prior work in this field.

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Section: Related Workmentioning

confidence: 72%

“…We would also then like to implement and compare with more recent work on Brownout, e.g. [9], [10], [11], [12], [13]. • Study the relationship between utilization and utility, as a measure of how useful customers find a service.…”

Section: Future Workmentioning

confidence: 99%

Quality-Elasticity: Improved Resource Utilization, Throughput, and Response Times Via Adjusting Output Quality to Current Operating Conditions

Larsson

Tärneberg

Klein

et al. 2019

2019 IEEE International Conference on Autonomic Computing (ICAC)

Self Cite

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“…Also, the formulation can use the maximization of the minimum confidence level (18) use the minimization of the maximum risk (19).…”

Section: Confidence Level Optimization Of Decentralized Control Parammentioning

confidence: 99%

“…Vector of production reactive powers ( [18,19] which bear a high computational burden. However, in general, chance constrained or max-p problems are not convex [20].…”

Section: Introductionmentioning

confidence: 99%

Convex formulation of confidence level optimization of DG affine reactive power controllers in distribution grids

Buire

Dieulot

Colas

et al. 2020

Electric Power Systems Research

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is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. This is an author-deposited version published in: https://sam.ensam.eu Handle ID AbstractVolatile productions and consumptions generate a stochastic behavior of distribution grids and make its supervision difficult to achieve. Usually, the Distributed Generators reactive powers are adjusted to perform decentralized voltage control. Industrial controllers are generally equipped with a local affine feedback law, which settings are tuned at early stage using local data. A centralized and more efficient tuning method should aim to maximize the probability that all the node voltages of distribution grids remain within prescribed bounds. When the characteristics of the stochastic power forecasts are known, the centralized algorithm allows to update the settings on a regular time basis. However, the method requires to solve stochastic optimization problem. Assuming that stochastic variables have Gaussian distributions, a procedure is given which guarantees the convergence of the stochastic optimization. Convex problems drastically reduce the difficulty and the computational time required to reach the global minimum, compared to nonconvex optimal power flow problems. The linear controllers with optimized parameters are compared to traditional control laws using simulations of a real distribution grid model. The results show that the algorithm is reliable and moreover fast enough. Hence, the proposed method can be used to update periodically the control parameters.

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“…On other side, Papadopoulos has proposed a resource management technique for balancing workload of cloud servers. The technique works on control-based self-adaptive randomized optimization [11]. Vasudevan et al have suggested a honey bee theory based technique that assigns available resources to cloud network.…”

Section: Releated Workmentioning

confidence: 99%

Dynamic Load Balancing in Cloud Computing Platform

Joshi¹

2019

IJCET

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The cloud computing platform has played significant role behind the exponential growth of modern IT industry. More and more organizations & individuals from various sectors of society are directory or indirectly consuming cloud computing platform. Such rising demand for cloud based computing resources has generated requirement of optimized resource management and load balancing. Extensive research work is taking place for efficient resource management and load balancing. A dynamic approach for virtual machine load balancing is presented here. The load balancing mechanism presented here offers better efficiency due to its multi-threaded approach.

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Control-based load-balancing techniques: Analysis and performance evaluation via a randomized optimization approach

Abstract: Control-based load-balancing techniques: Analysis and performance evaluation via a randomized optimization approach.

Cited by 19 publications

References 63 publications

Quality-Elasticity: Improved Resource Utilization, Throughput, and Response Times Via Adjusting Output Quality to Current Operating Conditions

Quality-Elasticity: Improved Resource Utilization, Throughput, and Response Times Via Adjusting Output Quality to Current Operating Conditions

Convex formulation of confidence level optimization of DG affine reactive power controllers in distribution grids

Dynamic Load Balancing in Cloud Computing Platform

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