Fog as a Service Technology

Chen, Nanxi; Yang, Yang; Zhang, Tao; Zhou, Ming-Tuo; Luo, Xiliang; Zao, John K.

doi:10.1109/mcom.2017.1700465

Cited by 82 publications

(25 citation statements)

References 9 publications

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“…Fog as a Service (FaaS) is a new business model which allows small, medium and large service providers to seamlessly deploy and operate computing, storage and control services at different scales [24]. However, such a novel business model requires the appropriate supporting infrastructure, platform, software and evaluation metrics [25]. The proliferation of edge computing nodes such as hyper-converged infrastructure in enterprises is due to performance or regulation requirements.…”

Section: Fog As a Service And Server Disaggregationmentioning

confidence: 99%

Disaggregation for Improved Efficiency in Fog Computing Era

Ajibola

El-Gorashi

Elmirghani

2019

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

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This paper evaluates the impact of using disaggregated servers in the near-edge of telecom networks (metro central offices, radio cell sites and enterprise branch office which form part of a Fog as a Service system) to minimize the number of fog nodes required in the far-edge of telecom networks. We formulated a mixed integer linear programming (MILP) model to this end. Our results show that replacing traditional servers with disaggregated servers in the near-edge of the telecom network can reduce the number of far-edge fog nodes required by up to 50% if access to near-edge computing resources is not limited by network bottlenecks. This improved efficiency is achieved at the cost of higher average hop count between workload sources and processing locations and marginal increases in overall metro and access networks traffic and power consumption.

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Section: Fog As a Service And Server Disaggregationmentioning

confidence: 99%

Disaggregation for Improved Efficiency in Fog Computing Era

Ajibola

El-Gorashi

Elmirghani

2019

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

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“…FNs have the capability to receive raw data from WSNs, aggregate, perform preprocessing, and store them temporarily instead of sensor nodes forwarding all the raw data to the cloud computing, thus reducing network bandwidth and latency [9]. The integration of fog computing with the WSNs and IoT creates a new type of service called fog as a service (FaaS) [10]. However, for fog computing to fully deploy its service, each fog node should meet the following requirements: (i) concurrent data collection from low-end nodes, (ii) high processing power and performance to support real-time data processing and analysis, (iii) high service reliability, and (iv) low power consumption, to achieve long time utilization.…”

Section: Introductionmentioning

confidence: 99%

Energy-efficient hierarchical routing in wireless sensor networks based on Fog Computing

Abidoye

Kabaso

2020

Preprint

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Wireless sensor networks (WSNs) have been recognized as one of the most essential technologies of the 21st century. The applications of WSNs are rapidly increasing in almost every sector because they can be deployed in areas where cable and power supply are difficult to use. In the literature, different methods have been proposed to minimize energy consumption of sensor nodes so as to prolong WSNs utilization. In this article, we propose an efficient routing protocol for data transmission in WSNs; it is called Energy-Efficient Hierarchical routing protocol for wireless sensor networks based on Fog Computing (EEHFC). Fog computing is integrated into the proposed scheme due to its capability to optimize the limited power source of WSNs and its ability to scale up to the requirements of the Internet of Things applications. In addition, we propose an improved ant colony optimization (ACO) algorithm that can be used to construct optimal path for efficient data transmission for sensor nodes. The performance of the proposed scheme is evaluated in comparison with P-SEP, EDCF, and RABACO schemes. The results of the simulations show that the proposed approach can minimize sensor nodes’ energy consumption, data packet losses and extends the network lifetime

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“…Pedestrians can also access VeFN via RSUs. To this end, VeFN combines the concepts of fog-as-a-service [3] and vehicle as the infrastructures [1], and is promising in the era of artificial intelligence (AI), which calls for computing anytime and everywhere.…”

Section: Introductionmentioning

confidence: 99%

Exploiting Moving Intelligence: Delay-Optimized Computation Offloading in Vehicular Fog Networks

et al. 2019

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Future vehicles will have rich computing resources to support autonomous driving and be connected by wireless technologies. Vehicular fog networks (VeFN) have thus emerged to enable computing resource sharing via computation task offloading, providing wide range of fog applications. However, the high mobility of vehicles makes it hard to guarantee the delay that accounts for both communication and computation throughout the whole task offloading procedure. In this article, we first review the state-of-the-art of task offloading in VeFN, and argue that mobility is not only an obstacle for timely computing in VeFN, but can also benefit the delay performance. We then identify machine learning and coded computing as key enabling technologies to address and exploit mobility in VeFN. Case studies are provided to illustrate how to adapt learning algorithms to fit for the dynamic environment in VeFN, and how to exploit the mobility with opportunistic computation offloading and task replication.

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Fog as a Service Technology

Cited by 82 publications

References 9 publications

Disaggregation for Improved Efficiency in Fog Computing Era

Disaggregation for Improved Efficiency in Fog Computing Era

Energy-efficient hierarchical routing in wireless sensor networks based on Fog Computing

Exploiting Moving Intelligence: Delay-Optimized Computation Offloading in Vehicular Fog Networks

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