Energy Efficient IoT Virtualization Framework With Peer to Peer Networking and Processing

Al-Azez, Zaineb T.; Lawey, Ahmed Q.; El-Gorashi, Taisir E. H.; Elmirghani, Jaafar M. H.

doi:10.1109/access.2019.2911117

Cited by 47 publications

(30 citation statements)

References 28 publications

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“…The OLT acts as a controller unit [68] that collects processing requests from mobile units present in the same room. These requests can be generated from applications in the mobile units.…”

Section: Optimum Placement Of Processing To Minimize Power Consumptionmentioning

confidence: 99%

Optimum resource allocation in optical wireless systems with energy-efficient fog and cloud architectures

Alsulami

Alahmadi

Saeed

et al. 2020

Phil. Trans. R. Soc. A.

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Optical wireless communication (OWC) is a promising technology that can provide high data rates while supporting multiple users. The optical wireless (OW) physical layer has been researched extensively, however, less work was devoted to multiple access and how the OW front end is connected to the network. In this paper, an OWC system which employs a wavelength division multiple access (WDMA) scheme is studied, for the purpose of supporting multiple users. In addition, a cloud/fog architecture is proposed for the first time for OWC to provide processing capabilities. The cloud/fog-integrated architecture uses visible indoor light to create high data rate connections with potential mobile nodes. These OW nodes are further clustered and used as fog mini servers to provide processing services through the OW channel for other users. Additional fog-processing units are located in the room, the building, the campus and at the metro level. Further processing capabilities are provided by remote cloud sites. Two mixed-integer linear programming (MILP) models were proposed to numerically study networking and processing in OW systems. The first MILP model was developed and used to optimize resource allocation in the indoor OWC systems, in particular, the allocation of access points (APs) and wavelengths to users, while the second MILP model was developed to optimize the placement of processing tasks in the different fog and cloud nodes available. The optimization of tasks placement in the cloud/fog-integrated architecture was analysed using the MILP models. Multiple scenarios were considered where the mobile node locations were varied in the room and the amount of processing and data rate requested by each OW node was varied. The results help to identify the optimum colour and AP to use for communication for a given mobile node location and OWC system configuration, the optimum location to place processing and the impact of the network architecture. This article is part of the theme issue ‘Optical wireless communication’.

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“…The OLT acts as a controller unit [68] that collects processing requests from mobile units present in the same room. These requests can be generated from applications in the mobile units.…”

Section: Optimum Placement Of Processing To Minimize Power Consumptionmentioning

confidence: 99%

Optimum resource allocation in optical wireless systems with energy-efficient fog and cloud architectures

Alsulami

Alahmadi

Saeed

et al. 2020

Phil. Trans. R. Soc. A.

Self Cite

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“…Virtualization abstracts the server resources including the CPU, RAM, hard disk and I/O network to create an isolated virtual entity that can run its operating system and applications. The existence of such a virtual environment allows the scaling up and down of server resources in a dynamic manner based on the variation in user demands [31]. Further dynamism can be achieved by migrating or replicating VMs over geo-distributed servers to achieve different features such as load balancing [32] and energy efficiency [33].…”

Section: Energy Efficient Placement Of Virtual Machines Over Cloumentioning

confidence: 99%

“…In [26]- [28] the problem of energy-efficient VM placement over a core network is formulated as a MILP model. Finally, [29]- [31] present a MILP model for energyefficient network virtualization.…”

Section: Introductionmentioning

confidence: 99%

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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“…In this paper, a techno-economic Mixed Integer Linear Programming (MILP) model is built to study the potential profit ISPs can achieve by a differentiated pricing scheme under the repeal of net neutrality. We build on our MILP optimization, network, cloud and fog modelling background [35]- [39] and consider ISPs that offer the CP service classes, which represent different data rate requirements. The model optimizes the pricing scheme of differentiated service classes to maximize the ISP profit based on price elasticity of demand (PED).…”

Section: Related Workmentioning

confidence: 99%

Impact of the Net Neutrality Repeal on Communication Networks

2020

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Network neutrality (net neutrality) is the principle of treating equally all Internet traffic regardless of its source, destination, content, application or other related distinguishing metrics. Under net neutrality, ISPs are compelled to charge all content providers (CPs) the same per Gbps rate despite the growing profit achieved by CPs. In this paper, we study the impact of the repeal of net neutrality on communication networks by developing a techno-economic Mixed Integer Linear Programming (MILP) model to maximize the potential profit ISPs can achieve by offering their services to CPs. We focus on video delivery as video traffic accounts for 78% of the cloud traffic. We consider an ISP that offers CPs different classes of service representing typical video content qualities including standard definition (SD), high definition (HD) and ultra-high definition (UHD) video. The MILP model maximizes the ISP profit by optimizing the prices of the different classes according to the users demand sensitivity to the change in price, referred to as Price Elasticity of Demand (PED). We analyze how PED impacts the profit in different CP delivery scenarios in cloud-fog architectures. The results show that the repeal of net neutrality can potentially increase ISPs profit by a factor of 8 with a pricing scheme that discriminates against data intensive content. Also, the repeal of net neutrality positively impacts the network energy efficiency by reducing the core network power consumption by 55% as a result of suppressing data intensive content compared to the net neutrality scenario.Index Terms-Net neutrality, AT&T, IP over WDM networks, profit, power consumption.

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Energy Efficient IoT Virtualization Framework With Peer to Peer Networking and Processing

Cited by 47 publications

References 28 publications

Optimum resource allocation in optical wireless systems with energy-efficient fog and cloud architectures

Optimum resource allocation in optical wireless systems with energy-efficient fog and cloud architectures

Energy Efficient Virtual Machines Placement Over Cloud-Fog Network Architecture

Impact of the Net Neutrality Repeal on Communication Networks

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