Real-Time Emissions of Telecom Core Networks

Alharbi, Hatem A.; Musa, Mohamed O. I.; El-Gorashi, Taisir E. H.; Elmirghani, Jaafar M. H.

doi:10.1109/icton.2018.8474000

Cited by 5 publications

(5 citation statements)

References 17 publications

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“…The access network is accessed via an ethernet switch connected to an OLT, which supports ONUs that allow users to access the network. Figure 4 indicates the varying traffic quantity over a day period obtained in 2016 [28]. According to [29], a list of networking vendors provide networking equipment for the BT 21 CN.…”

Section: Resultsmentioning

confidence: 99%

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Energy Efficient Virtual Machines Placement Over Cloud-Fog Network Architecture

2020

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Fog computing is an emerging paradigm that aims to improve the efficiency and QoS of cloud computing by extending the cloud to the edge of the network. This paper develops a comprehensive energy efficiency analysis framework based on mathematical modeling and heuristics to study the offloading of virtual machine (VM) services from the cloud to the fog. The analysis addresses the impact of different factors including the traffic between the VM and its users, the VM workload, the workload versus number of users profile and the proximity of fog nodes to users. Overall, the power consumption can be reduced if the VM users' traffic is high and/or the VMs have a linear power profile. In such a linear profile case, the creation of multiple VM replicas does not increase the computing power consumption significantly (there may be a slight increase due to idle / baseline power consumption) if the number of users remains constant, however the VM replicas can be brought closer to the end users, thus reducing the transport network power consumption. In our scenario, the optimum placement of VMs over a cloud-fog architecture significantly decreased the total power consumption by 56% and 64% under high user data rates compared to optimized distributed clouds placement and placement in the existing AT&T network cloud locations, respectively.

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Section: Resultsmentioning

confidence: 99%

“…Constraints (27)(28)(29)(30)(31)(32) simulate the placement of a VM in a metro, PON and core networks…”

Section: Variablesmentioning

confidence: 99%

Energy Efficient Virtual Machines Placement Over Cloud-Fog Network Architecture

2020

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“…The British Telecom (BT) network topology, which is introduced in Fig. 2, consists of 20 nodes (cities) and 68 bidirectional links [22]. In this work, we aim to achieve a green fog-cloud architecture by optimizing the placement of cloud/fog applications over the BT network, considering several factors: data rates, carbon intensity, and the proximity of data center locations.…”

Section: E British Telecom Network Topologymentioning

confidence: 99%

Towards a Green Approach for Minimizing Carbon Emissions in Fog-Cloud Architecture

Aldossary

Alharbi²

2021

IEEE Access

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Fog computing is developed to complement cloud computing by extending the cloud services (computing, storage, networking, and management) to the edge of the network in order to reduce service latency. With the rapid growth of cloud users and the emergence of fog computing, the demand for cloud/fog resources has increased dramatically. Also, the incremental use of the cloud/fog resources and their applications has increased energy consumption and carbon emitted, which caused significant environmental challenges. Optimizing the placement of requested applications (e.g., in the form of virtual machines) is one of the main solutions, which has a primary effect in reducing the energy consumption of cloud/fog architecture and consequently their carbon emissions. However, due to the geographic distribution of cloud and fog data centers, there is a variety of carbon emission levels to consider, which makes optimizing the placement of applications in distributed cloud/fog more challenging than in centralized clouds in terms of carbon efficiency. In this paper, we propose a multi-level approach using a mixed-integer linear programming (MILP) model to minimize carbon emissions (CO2) by optimizing the usage of cloud/fog resources. These resources are managed by virtual machines (VMs), which can be optimally and virtually used. In our model, we used the British Telecom (BT) as a telecom network example with an aim to minimize the CO2 emission, considering several scenarios of traffic demand during different times of the day and year (seasons). The results show that the optimal location to host applications highly relies on the carbon intensity and traffic demands. The results also show there is a trade-off between CO2 emission reduced by shortening network journey, and CO2 increased by hosting more applications into the fog nodes. In addition, the results demonstrate that the proposed green fog-cloud architecture outperforms the central cloud and the distributed clouds in terms of reducing the total CO2 emission by up to 91% and 71%, respectively. Finally, we develop a heuristic algorithm to mimic and validate the presented work, and it shows comparable results to the MILP model.INDEX TERMS Cloud computing, fog computing, green fog-cloud architecture, applications placement, energy-efficiency, carbon emissions CO2.

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“…Significant research efforts in the literature have focused on cloud computing and communication networks energy efficiency [14]- [34]. In this paper, we optimize the network and processing energy efficiency by developing a framework for VMs placement over cloud-fog architecture.…”

Section: Takedownmentioning

confidence: 99%

Energy Efficient Virtual Machine Services Placement in Cloud-Fog Architecture

Alharbi

El-Gorashi

Elmirghani

2019

2019 21st International Conference on Transparent Optical Networks (ICTON)

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The proliferation in data volume and processing requests calls for a new breed of on-demand computing. Fog computing is proposed to address the limitations of cloud computing by extending processing and storage resources to the edge of the network. Cloud and fog computing employ virtual machines (VMs) for efficient resource utilization. In order to optimize the virtual environment, VMs can be migrated or replicated over geo-distributed physical machines for load balancing and energy efficiency. In this work, we investigate the offloading of VM services from the cloud to the fog considering the British Telecom (BT) network topology. The analysis addresses the impact of different factors including the VM workload and the proximity of fog nodes to users considering the data rate of state-of-the-art applications. The results show that the optimum placement of VMs significantly decreases the total power consumption by up to 75% compared to a single cloud placement.

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Real-Time Emissions of Telecom Core Networks

Cited by 5 publications

References 17 publications

Energy Efficient Virtual Machines Placement Over Cloud-Fog Network Architecture

Energy Efficient Virtual Machines Placement Over Cloud-Fog Network Architecture

Towards a Green Approach for Minimizing Carbon Emissions in Fog-Cloud Architecture

Energy Efficient Virtual Machine Services Placement in Cloud-Fog Architecture

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