A survey on optimal utilization of preemptible VM instances in cloud computing

Mishra, Ashish Kumar; Umrao, Brajesh Kumar; Yadav, Dharmendra Kumar

doi:10.1007/s11227-018-2509-0

Cited by 12 publications

(2 citation statements)

References 59 publications

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“…Several other techniques encompassing task migration [25,26], duplication [26], and checkpointing [25,27,28] have been proposed. Mishra et al [29] have published an article extensively surveying on improving the fault tolerance level of spot instances in Amazon EC2. Much of the research was devoted to tolerating the out-of-bid events, neglecting the problems of delay and failure in acquiring spot instances.…”

Section: Related Workmentioning

confidence: 99%

Constructing Reliable Computing Environments on Top of Amazon EC2 Spot Instances

Sampaio

Barbosa

2020

Algorithms

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Cloud provider Amazon Elastic Compute Cloud (EC2) gives access to resources in the form of virtual servers, also known as instances. EC2 spot instances (SIs) offer spare computational capacity at steep discounts compared to reliable and fixed price on-demand instances. The drawback, however, is that the delay in acquiring spots can be incredible high. Moreover, SIs may not always be available as they can be reclaimed by EC2 at any given time, with a two-minute interruption notice. In this paper, we propose a multi-workflow scheduling algorithm, allied with a container migration-based mechanism, to dynamically construct and readjust virtual clusters on top of non-reserved EC2 pricing model instances. Our solution leverages recent findings on performance and behavior characteristics of EC2 spots. We conducted simulations by submitting real-life workflow applications, constrained by user-defined deadline and budget quality of service (QoS) parameters. The results indicate that our solution improves the rate of completed tasks by almost 20%, and the rate of completed workflows by at least 30%, compared with other state-of-the-art algorithms, for a worse-case scenario.

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Section: Related Workmentioning

confidence: 99%

Constructing Reliable Computing Environments on Top of Amazon EC2 Spot Instances

Sampaio

Barbosa

2020

Algorithms

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“…In this study, we selected the Bollinger Bands trading strategy over others since Bollinger Bands provides a unique advantage by dynamically adapting to market volatility, offering a robust framework for identifying potential price reversals [29,30]. Their flexibility and proven effectiveness make them a superior choice compared to static trading rules, enhancing adaptability to evolving market conditions and even optimizing trading opportunities [31,32]. However, exploration of the Bollinger Bands trading strategy (BBTS) remains limited.…”

Section: Introductionmentioning

confidence: 99%

Using Big Data Analytics and Heatmap Matrix Visualization to Enhance Cryptocurrency Trading Decisions

Ni,

Chiang,

Day

et al. 2023

Applied Sciences

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Using the Bollinger Bands trading strategy (BBTS), investors are advised to buy (and then sell) Bitcoin and Ethereum spot prices in response to BBTS’s oversold (overbought) signals. As a result of analyzing whether investors would profit from round-turn trading of these two spot prices, this study may reveal the following remarkable outcomes and investment strategies. This study first demonstrated that using our novel design with a heatmap matrix would result in multiple higher returns, all of which were greater than the highest return using the conventional design. We contend that such an impressive finding could be the result of big data analytics and the adaptability of BBTS in our new design. Second, because cryptocurrency spot prices are relatively volatile, such indices may experience a significant rebound from oversold to overbought BBTS signals, resulting in the potential for much higher returns. Third, if history repeats itself, our findings might enhance the profitability of trading these two spots. As such, this study extracts the diverse trading performance of multiple BB trading rules, uses big data analytics to observe and evaluate many outcomes via heatmap visualization, and applies such knowledge to investment practice, which may contribute to the literature. Consequently, this study may cast light on the significance of decision-making through the utilization of big data analytics and heatmap visualization.

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Efficient Resource Allocation in Virtualized Cloud Platforms Using Encapsulated Virtualization Based Ant Colony Optimization (EVACO)

Mukhopadhyay,

Tewari,

Choubey

et al. 2023

6G Enabled Fog Computing in IoT

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A survey on optimal utilization of preemptible VM instances in cloud computing

Cited by 12 publications

References 59 publications

Constructing Reliable Computing Environments on Top of Amazon EC2 Spot Instances

Constructing Reliable Computing Environments on Top of Amazon EC2 Spot Instances

Using Big Data Analytics and Heatmap Matrix Visualization to Enhance Cryptocurrency Trading Decisions

Efficient Resource Allocation in Virtualized Cloud Platforms Using Encapsulated Virtualization Based Ant Colony Optimization (EVACO)

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