Incorporating diversity in cloud-computing: a novel paradigm and architecture for enhancing the performance of future cloud radio access networks

Periola, A. A.

doi:10.1007/s11276-018-01915-2

Cited by 19 publications

(9 citation statements)

References 26 publications

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“…The locations in (9) correspond to pre-defined stratosphere coordinates. Each HAP-DC has a location database entity (LDE) that stores information on locations in (9). The location information aboard each HAP-DC is different.…”

Section: Hap-data Centers (Hap-dcs) With Dynamic Locationmentioning

confidence: 99%

“…The siting of data centers in Scandinavia and other North American cold locations increases the latency associated with content access from distant Sub-Saharan African countries. The latency can be reduced by siting data centers in other locations such as the ocean [9] and the stratosphere [10]. Siting data centers in these locations enhances energy efficiency due to the availability of free cooling.…”

Section: Introductionmentioning

confidence: 99%

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Aerial computing—security from missile threats and enhancing PUE

Periola

2020

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Data centers have operational challenges due to high cooling costs and the necessity of ensuring physical security to keep data safe. The activities of malicious organizations in countries without sophisticated missile defence systems also necessitate enhancing data center security. The expending of significant power for cooling degrades data center power usage effectiveness (PUE). The use of high altitude platform data centers (HAP-DCs) is proposed to address these challenges. The HAP-DC incorporates a location mechanism which ensures that HAP-DCs have a dynamic location making them difficult targets for aerial missiles. The paper also proposes a stratospheric scheduling mechanism to enhance the HAP-DC's PUE. The scheduling mechanism ensures that HAP-DCs sited where the stratosphere has best cooling ability are used for workload execution. Analysis shows that the location mechanism enhances safety against missile threats by at least 6.7% and up to 35.4% on average. The scheduling mechanism enhances the PUE by at least 43.8% and up to 81.1% on average.

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Section: Hap-data Centers (Hap-dcs) With Dynamic Locationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Aerial computing—security from missile threats and enhancing PUE

Periola

2020

Self Cite

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“…This has led to the use of renewable energy in data centres [5][6]. The cooling costs can be reduced by changing data centre location to alternative locations such as the ocean [7][8][9]. The use of underwater data centres is unsuitable for geographical locations with insufficient maritime resources.…”

Section: Introductionmentioning

confidence: 99%

Sustainable cloud computing for cognitive intent based networks

Periola¹,

Obayiuwana²

2021

Nig. J. Tech.

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Intent based networks enable auto-configuration and require low latency access to cloud platforms. The use of cloud platforms incurs high operational costs. Low latency access can be realized by siting data centres close to subscribers. This paper proposes aquaria data centers with low operating costs and latency. In LTE, cloud platforms are normally accessed via the packet network gateway reachable via the serving gateway and mobility management entity. Aquaria data centers are sited close to LTE subscribers and accessed via the mobility management entity. This reduces the size of control packets in the LTE network. Simulations show that the proposed architecture reduces the size of control packets by up to 49.7% and 99.3% when header packets are uncompressed and compressed respectively. The delay associated with receiving configuration information is reduced by 50% on average. The channelcapacity is enhanced by up to 22.8% on average. Keywords: Data centers, LTE-Advanced, Peak Age of Information, Channel Capacity, Header (Control) Packet

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“…It is a model of computing that allows the flexible 12 use of virtual servers, massive scalability, and management services for the delivery of 13 information services [2]. With the low-cost pay-per-use model of on-demand computing 14 [3], the cloud has grown massively over the years, both in terms of size and complexity. 15 Today, almost everyone is connected to the cloud in one way or the other because 16 of cost-effectiveness with pay-as-you-go or subscription-based service model for on-17 demand access to IT resources [1], [3].…”

Section: Introduction 10mentioning

confidence: 99%

A Combined Metrics Approach to Cloud Service Reliability using Artificial Intelligence

Chhetri¹,

Dehury²,

Lind³

et al. 2021

Preprint

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Identifying and anticipating potential failures in the cloud is an effective method for increasing cloud reliability and proactive failure management. Many studies have been conducted to predict potential failure, but none have combined SMART (Self-Monitoring, Analysis, and Reporting Technology) hard drive metrics with other system metrics such as CPU utilisation. Therefore, we propose a combined metrics approach for failure prediction based on Artificial Intelligence to improve reliability. We tested over 100 cloud servers’ data and four AI algorithms: Random Forest, Gradient Boosting, Long-Short-Term Memory, and Gated Recurrent Unit. Our experimental result shows the benefits of combining metrics, outperforming state-of-the-art.

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Incorporating diversity in cloud-computing: a novel paradigm and architecture for enhancing the performance of future cloud radio access networks

Cited by 19 publications

References 26 publications

Aerial computing—security from missile threats and enhancing PUE

Aerial computing—security from missile threats and enhancing PUE

Sustainable cloud computing for cognitive intent based networks

A Combined Metrics Approach to Cloud Service Reliability using Artificial Intelligence

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