GRaNADA: A Network-Aware and Energy-Efficient PaaS Cloud Architecture

Cuadrado-Cordero, Ismael; Orgerie, Anne‐Cécile; Morin, Christine

doi:10.1109/dsdis.2015.65

Cited by 6 publications

(7 citation statements)

References 13 publications

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“…Our platform is semi-decentralized and extends the concept of microcloud proposed in [9] in order to support dynamic interactivity of multiple services with no replication. A microcloud is an overlay network that connects independent users working using the same service -for each service a microcloud is created.…”

Section: Architecture Designmentioning

confidence: 99%

“…It is launched by the user and extends the DEEPACC protocol presented in [9] to find the fastest path between the client and the SP. All services are listed in the BM, and the user selects one of them through a graphical interface.…”

Section: Join and Detach Processesmentioning

confidence: 99%

“…Once the SP obtains all the possible paths, they are sent to the service manager. The SM uses a Branch and Bound algorithm [9] to plan the microcloudś topology and communicates this topology to the SP and to the BM. The BM uses this information for inefficiency-triggered reconfigurations.…”

Section: Join and Detach Processesmentioning

confidence: 99%

See 2 more Smart Citations

Microcities: A Platform Based on Microclouds for Neighborhood Services

Cuadrado-Cordero

Cuadrado

Phillips

et al. 2016

Algorithms and Architectures for Parallel Processing

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Abstract:The current mobile Cloud computing trend has set the focus on the ubiquity of computation. However, the current architecture confines the cloud to datacenters, which are generally far from the user. Distance leads to increased utilization of the broadband Wide Area Network -WAN -and poor user experience, especially for interactive applications. Decentralized architectures are emerging as an alternative, but they still fail to adapt to situations where files are concurrently modified. A semi-decentralized approach which confines local traffic close to the user while still maintaining centralized characteristics, running on the users and network devices, can provide a better Quality of Experience (QoE) in large urban populations in mobile cloud networks. In this report, we propose a novel semi-centralized cloud architecture based on microclouds. Microclouds are dynamically created and allow users to contribute resources from their computers, mobile and network devices to the cloud. We present the process for building and reconfiguring the microclouds, whilst guaranteeing a high QoE to users of real-time applications. We also provide a description of a realistic mobile cloud use-case. Results from a simulation-based evaluation indicate that the microclouds architecture is able to sustain hundreds of mobile devices and provide a latency significantly lower than regular Clouds based on datacenters. Résumé : La tendance actuelle des applications mobiles dans les nuages informatiques (clouds) a mis láccent sur lómniprésence du calcul. Cependant, lárchitecture actuelle confine le cloud dans les centres de données qui sont généralement loin de lútilisateur. Cette distance conduit á une utilisation accrue de la bande passante des réseaux longue distance (Wide Area Network -WAN) et conduit á une expérience utilisateur médiocre, en particulier pour les applications interactives. Les architectures décentralisées apparaissent comme une alternative, mais elles ne parviennent pas toujours á s'adapter á des situations oú les fichiers sont modifiés de maniére concurrente. Une approche semi-décentralisée, mise en oeuvre sur les équipements des utilisateurs et du réseau et confinant le trafic local á proximité de lútilisateur tout en conservant les caractéristiques centralisées, peut fournir une meilleure qualité déxpérience (QoE) aux grandes populations urbaines utilisant les applications mobiles des clouds. Dans cet rapport, nous proposons une nouvelle architecture de cloud semi-centralisée fondée sur les "microclouds". Les microclouds sont créés dynamiquement et permettent aux utilisateurs de fournir au cloud des ressources de leurs ordinateurs, smartphones et équipements réseau. Nous présentons le processus de construction et de reconfiguration des microclouds, tout en garantissant un haut degré de QoE aux utilisateurs dápplications temps-réel. Nous donnons également une description dún cas d'utilisation réaliste de cloud mobile. Les résultats dúne évaluation menée par simulation indiquent que lárchitecture á base de m...

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Section: Architecture Designmentioning

confidence: 99%

Section: Join and Detach Processesmentioning

confidence: 99%

See 1 more Smart Citation

Microcities: A Platform Based on Microclouds for Neighborhood Services

Cuadrado-Cordero

Cuadrado

Phillips

et al. 2016

Algorithms and Architectures for Parallel Processing

Self Cite

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“…A typical server consumes power depending on its resource usage (generally CPU load) [10]. Similar behavior can be observed for network devices [6]. The idle power consumption of an IT device represents its static consumption when turned on but idle, so not performing any useful work.…”

Section: Our Metricmentioning

confidence: 99%

Glenda

Guyon

Orgerie

Morin

2017

Proceedings of the Eighth International Conference on Future Energy Systems

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As cloud services multiply rapidly, so does the computing centers dedicated to them, and consequently their power consumption. Although this consumption is hampering data centers' expansion, these infrastructures have not yet reached energy proportionality, thus wasting significant amounts of energy. Numerous energy metrics have been propose as incentives towards greener infrastructures, but none of them currently gives direct insights about the energy proportionality and green energy usage of data centers. In this paper, we propose GLENDA: a Green Label towards Energy pro-portioNality for IaaS DAta centers. We validate our metric by using traces from real infrastructures, and show that our label gets a better grade when increasing energy efficiency, increasing utilization rates, and using distributed renewable generation. We expect this new metric to become a useful reference for Cloud providers towards green data centers. CCS CONCEPTS • Computer systems organization → Cloud computing; • General and reference → Metrics; • Information systems → Retrieval efficiency; • Hardware → Power and energy;

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“…Modern cloud systems have numerous open research challenges including resource management, load balancing, security, privacy, and multi‐clouds 16–22. In this section, the recent works on load balancing are summarized as this study concentrates on multi‐objective load balancing.…”

Section: Related Workmentioning

confidence: 99%

Resource‐efficient load‐balancing framework for cloud data center networks

2020

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Cloud computing has drastically reduced the price of computing resources through the use of virtualized resources that are shared among users. However, the established large cloud data centers have a large carbon footprint owing to their excessive power consumption. Inefficiency in resource utilization and power consumption results in the low fiscal gain of service providers. Therefore, data centers should adopt an effective resource‐management approach. In this paper, we present a novel load‐balancing framework with the objective of minimizing the operational cost of data centers through improved resource utilization. The framework utilizes a modified genetic algorithm for realizing the optimal allocation of virtual machines (VMs) over physical machines. The experimental results demonstrate that the proposed framework improves the resource utilization by up to 45.21%, 84.49%, 119.93%, and 113.96% over a recent and three other standard heuristics‐based VM placement approaches.

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GRaNADA: A Network-Aware and Energy-Efficient PaaS Cloud Architecture

Cited by 6 publications

References 13 publications

Microcities: A Platform Based on Microclouds for Neighborhood Services

Microcities: A Platform Based on Microclouds for Neighborhood Services

Glenda

Resource‐efficient load‐balancing framework for cloud data center networks

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