Energy and Network Aware Workload Management for Geographically Distributed Data Centers

Hogade, Ninad; Pasricha, Sudeep; Siegel, Howard Jay

doi:10.1109/tsusc.2021.3086087

Cited by 26 publications

(10 citation statements)

References 31 publications

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“…[130][131][132][133] These efforts often pursue the concept of "follow-the-sun" (for solar-powered facilities) or "follow-the-renewables" (for wind and/or solar) computation, wherein computing workloads migrate dynamically towards sites that have larger availability of renewable energy. 46,47,66,129,[134][135][136] For example, Akoush et al introduced a software framework that supports the migration of virtual machines between data centers according to "green" power availability, 47 whereas Qi et al proposed scheduling algorithms for optimal VM migration. 66 Zhang et al, introduced the "GreenWare" middleware, which takes into account both the availability of renewable energy of a network of cooperating data centers and the desired cost of the Internet service operator to decide dynamically where to dispatch incoming tasks so as to maximize the total use of "green" energy.…”

Section: Benchmarking Experimentsmentioning

confidence: 99%

“…Geographical load balancing tries to exploit spatio‐temporal differences in environmental conditions, in power‐grid and on‐site electricity prices, and in excess computing capacity of remote data centers in order to achieve overall better reliability, increased availability, and lower end‐user latency with lower cost and reduced carbon footprint 130‐133 . These efforts often pursue the concept of “follow‐the‐sun” (for solar‐powered facilities) or “follow‐the‐renewables” (for wind and/or solar) computation, wherein computing workloads migrate dynamically towards sites that have larger availability of renewable energy 46,47,66,129,134‐136 . For example, Akoush et al introduced a software framework that supports the migration of virtual machines between data centers according to “green” power availability, 47 whereas Qi et al proposed scheduling algorithms for optimal VM migration 66 .…”

Section: Energy‐efficient Data Centers: Status and Trendsmentioning

confidence: 99%

See 1 more Smart Citation

A cyber‐physical management system for medium‐scale solar‐powered data centers

Dikaiakos

Chatzigeorgiou

Tryfonos

et al. 2023

Concurrency and Computation

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Summary The effort to reduce the environmental impact and carbon footprint of data‐center operations has led to the emergence of “green” data centers, which are designed to reduce energy consumption and to increase their use of Renewable Energy Sources (RES). Despite the advances demonstrated by hyper‐scale facilities in energy efficiency and the use of green energy, small and medium‐scale data centers, which contribute to over 50% of the total electricity consumption and carbon emissions of the sector, face significant challenges in the adoption and exploitation of RES. In this article, we present the steps taken to transform a medium‐scale, academic data center into a “green” one that uses solar power. In particular, we describe the design and implementation of: (i) a collocated photovoltaic facility and (ii) a cyber‐physical system comprising IoT sensor devices, a microservices platform, and a visualization and analytics dashboard that supports the configuration and monitoring of the infrastructure. Using data collected from the platform and dashboard, we show the environmental and financial advantages derived from this transformation, and the potential that arises from the availability of integrated operational data.

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Section: Benchmarking Experimentsmentioning

confidence: 99%

Section: Energy‐efficient Data Centers: Status and Trendsmentioning

confidence: 99%

A cyber‐physical management system for medium‐scale solar‐powered data centers

Dikaiakos

Chatzigeorgiou

Tryfonos

et al. 2023

Concurrency and Computation

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“…Thus, cloud networks require reliability and fall-back options. CSCs are also unevenly distributed across the globe, and parallel servers must be provided to reduce issues such as latency, traffic load balancing, non-repudiation of data, and primarily balancing the allocation of resources offered to users [61,62]. 8…”

Section: Comparative Analysis Of Zero-trust Cloud Network Technologiesmentioning

confidence: 99%

Security of Zero Trust Networks in Cloud Computing: A Comparative Review

et al. 2022

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Recently, networks have shifted from traditional in-house servers to third-party-managed cloud platforms due to its cost-effectiveness and increased accessibility toward its management. However, the network remains reactive, with less accountability and oversight of its overall security. Several emerging technologies have restructured our approach to the security of cloud networks; one such approach is the zero-trust network architecture (ZTNA), where no entity is implicitly trusted in the network, regardless of its origin or scope of access. The network rewards trusted behaviour and proactively predicts threats based on its users’ behaviour. The zero-trust network architecture is still at a nascent stage, and there are many frameworks and models to follow. The primary focus of this survey is to compare the novel requirement-specific features used by state-of-the-art research models for zero-trust cloud networks. In this manner, the features are categorized across nine parameters into three main types: zero-trust-based cloud network models, frameworks and proofs-of-concept. ZTNA, when wholly realized, enables network administrators to tackle critical issues such as how to inhibit internal and external cyber threats, enhance the visibility of the network, automate the calculation of trust for network entities and orchestrate security for users. The paper further focuses on domain-specific issues plaguing modern cloud computing networks, which leverage choosing and implementing features necessary for future networks and incorporate intelligent security orchestration, automation and response. The paper also discusses challenges associated with cloud platforms and requirements for migrating to zero-trust architecture. Finally, possible future research directions are discussed, wherein new technologies can be incorporated into the ZTA to build robust trust-based enterprise networks deployed in the cloud.

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“…To offer qualitative insight about the scalability's gain of data center-enabled HAP, we compare the system electricity cost; which represents the main operational expenditure source in data centers; according to the deployment scenarios shown in Fig 3 [15]. In the first scenario, a terrestrial data center is considered to process all the incoming workload.…”

Section: Deployment Scenariosmentioning

confidence: 99%

Latency-Aware Offloading in Integrated Satellite Terrestrial Networks

Abderrahim¹,

Amin²,

Alouini³

et al. 2020

Preprint

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Next-generation communication networks are expected to integrate newly-used technologies in a smart way to ensure continuous connectivity in rural areas and to alleviate the traffic load in dense regions. The prospective access network in 6G should hinge on satellite systems to take advantage of their wide coverage and high capacity. However, adopting satellites in 6G could be hindered because of the additional latency introduced, which is not tolerable by all traffic types. Therefore, we propose a traffic offloading scheme that integrates both the satellite and terrestrial networks to smartly allocate the traffic between them while satisfying different traffic requirements. Specifically, the proposed scheme offloads the Ultra-Reliable Low Latency Communication (URLLC) traffic to the terrestrial backhaul to satisfy its stringent latency requirement. However, it offloads the enhanced Mobile Broadband (eMBB) traffic to the satellite since eMBB needs high data rates but is not always sensitive to delay. Our scheme is shown to reduce the transmission delay of URLLC packets, decrease the number of dropped eMBB packets, and hence improve the network's availability. Our findings highlight that the inter-working between satellite and terrestrial networks is crucial to mitigate the expected high load on the limited terrestrial capacity.

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Energy and Network Aware Workload Management for Geographically Distributed Data Centers

Cited by 26 publications

References 31 publications

A cyber‐physical management system for medium‐scale solar‐powered data centers

A cyber‐physical management system for medium‐scale solar‐powered data centers

Security of Zero Trust Networks in Cloud Computing: A Comparative Review

Latency-Aware Offloading in Integrated Satellite Terrestrial Networks

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