PON-Based Connectivity for Fog Computing

Alqahtani, Abdullah M.; Mohamed, Sanaa Hamid; El-Gorashi, Taisir E. H.; Elmirghani, Jaafar M. H.

doi:10.1109/icton51198.2020.9203425

Cited by 6 publications

(13 citation statements)

References 47 publications

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“…As shown in Fig. 1, we consider three distributed fog computing cells connected to each other through WDM-PON in the access network [1]. Each PON cell has two racks of servers, each of which has four servers for hosting the VMs, and each server is equipped with an Optical Network Unit (ONU) acting as a transceiver to send and receive traffic.…”

Section: A the Federated Fog Computing Over Pon Architecturementioning

confidence: 99%

“…To make use of the WDM-PON connectivity, each cell has arrayed waveguide grating routers (AWGRs) to achieve full connectivity between racks of servers located within the same fog cell or between racks in different fog cells. The details of the WDM PON connectivity is given in our previous work in [1]. The inter-VM traffic, which flows between VMs placed in different servers, could be traffic flow within the same rack or traffic flow between different racks.…”

Section: A the Federated Fog Computing Over Pon Architecturementioning

confidence: 99%

“…However, Fog Computing is characterized by limited computational resources in terms of processing cycles and storage capacity. Therefore, it faces many challenges such as performance, resource allocation and orchestration, and reliability [1]- [8]. Therefore, the capacity of fog units should be addressed to process the intensive end-users demands.…”

Section: Introductionmentioning

confidence: 99%

“…We benefit from our previous work in energy efficiency that tackled areas such as distributed processing in the IoT/Fog layer [21]- [24], green core and data centre (DC) networks [25]- [34], [35]- [40], network virtualization and service embedding in core and IoT networks [41]- [44] and machine learning and network optimization for healthcare systems [45]- [48] and network coding in the core network [49], [50]. Our previous work in [1] optimized connectivity among distributed fog units to facilitate the communication between different servers. Also, our work in [51] extended the available capacity in fog units by enabling the borrowing of data processing capabilities from nearby fog units to serve intensive VM demands originating from the end user devices.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Energy Efficient Resource Allocation in Federated Fog Computing Networks

Alqahtani¹,

Yosuf²,

Mohamed³

et al. 2021

2021 IEEE Conference on Standards for Communications and Networking (CSCN)

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There is a continuous growth in demand for time sensitive applications which has shifted the cloud paradigm from a centralized computing architecture towards distributed heterogeneous computing platforms where resources located at the edge of the network are used to provide cloud-like services. This paradigm is widely known as fog computing. Virtual machines (VMs) have been widely utilized in both paradigms to enhance the network scalability, improve resource utilization, and energy efficiency. Moreover, Passive Optical Networks (PONs) are a technology suited to handling the enormous volumes of data generated in the access network due to their energy efficiency and large bandwidth. In this paper, we utilize a PON to provide the connectivity between multiple distributed fog units to achieve federated (i.e., cooperative) computing units in the access network to serve intensive demands. We propose a mixed integer linear program (MILP) to optimize the VM placement in the federated fog computing units with the objective of minimizing the total power consumption while considering inter-VM traffic. The results show a significant power saving as a result of the proposed optimization model by up to 52%, in the VM-allocation compared to a baseline approach that allocates the VM requests while neglecting the power consumption and inter-VMs traffic in the optimization framework.

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Section: A the Federated Fog Computing Over Pon Architecturementioning

confidence: 99%

Section: A the Federated Fog Computing Over Pon Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Energy Efficient Resource Allocation in Federated Fog Computing Networks

Alqahtani¹,

Yosuf²,

Mohamed³

et al. 2021

2021 IEEE Conference on Standards for Communications and Networking (CSCN)

Self Cite

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“…Several previous studies have used PONs in edge computing [12]- [14], but few studies have examined their support of real-time motion control. Reference [15] describes the maximum permissible number of branches in a direct connection between a factory control center and a factory machine using a PON with ultra-high branching numbers.…”

Section: Introductionmentioning

confidence: 99%

Demonstration of Real-Time Motion Control Method for Access Edge Computing in PONs

et al. 2022

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In the remote motion control of IoT devices, the delay adversely affects control performance. In our access edge concept, in which motion control is performed from a central office, the delay becomes large due to Dynamic Bandwidth Allocation (DBA) when the Passive Optical Network (PON) is adopted as the access system. No existing motion control method considers the delay changes of the DBA algorithm. We rectify this omission by proposing a novel real-time and high-precision motion control method that links the PON device and the controller. The proposed method can improve the control performance while maintaining the bandwidth utilization efficiency without changing the DBA delay specified to meet the requirements. In the proposed method, the delay in the PON system is calculated by using a delay model based on the setting parameter received from the communication device, and is used for delay compensation control. An experiment shows that, unlike the conventional method which becomes unstable and fails to realize control, the proposed method achieves high resolution control within 4 s, which demonstrates the feasibility of motion control for factory automation using edge computing in PON systems.

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A systematic review on resource provisioning in fog computing

Κaur

Singh

Sharma

2023

Trans Emerging Tel Tech

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Resource provisioning is allocating resources to clients over the Internet and plays a prominent role in cloud computing infrastructure-as-a-service (IaaS).The main issues of resource provisioning are meeting user demands like bandwidth, response time, throughput, availability, and so on. The cloud computing framework uses virtualization technology to provide on-demand access to computer system resources, specifically computation and storage. In cloud computing, computing resources are shared across another communication network using virtualization. However, the cloud computing mechanism cannot meet the needs of a large number of Internet of Things (IoT) services. To consider this, fog computing was introduced as a modified mechanism of the cloud paradigm by providing cloud services for the end devices. Fog computing is a decentralized computing model placed between devices, edges, data centers or the cloud. In this way, it helps to meet the demands initiated by IoT services, such as reduced latency, wide mobility coverage, and so on. Several solutions regarding resource allocation in fog computing are available in the research field, but such solutions have not achieved satisfactory results. Therefore, finding a solution by analyzing recent problems is open research. Therefore, this paper reviews different methods established for resource provisioning in fog computing using different parameters from 2015 to 2021 and introduces the limitations, advantages and future directions related to different resource provisioning techniques.

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PON-Based Connectivity for Fog Computing

Abstract: This is a repository copy of PON-Based Connectivity for Fog Computing.

Cited by 6 publications

References 47 publications

Energy Efficient Resource Allocation in Federated Fog Computing Networks

Energy Efficient Resource Allocation in Federated Fog Computing Networks

Demonstration of Real-Time Motion Control Method for Access Edge Computing in PONs

A systematic review on resource provisioning in fog computing

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