Volume
OASIcs, Volume 80
2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)
-
Part of:
Series:
Open Access Series in Informatics (OASIcs)
Conference: Workshop on Fog Computing and the IoT (Fog-IoT)
Event
Fog-IoT 2020, April 21, 2020, Sydney, AustraliaEditors
Publication Details
- published at: 2020-04-08
- Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
- ISBN: 978-3-95977-144-3
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Document
Complete Volume
OASIcs, Volume 80, Fog-IoT 2020, Complete Volume
Abstract
OASIcs, Volume 80, Fog-IoT 2020, Complete Volume
Cite as
2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 1-110, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
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@Proceedings{cervin_et_al:OASIcs.Fog-IoT.2020,
title = {{OASIcs, Volume 80, Fog-IoT 2020, Complete Volume}},
booktitle = {2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
pages = {1--110},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-144-3},
ISSN = {2190-6807},
year = {2020},
volume = {80},
editor = {Cervin, Anton and Yang, Yang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020},
URN = {urn:nbn:de:0030-drops-119933},
doi = {10.4230/OASIcs.Fog-IoT.2020},
annote = {Keywords: OASIcs, Volume 80, Fog-IoT 2020, Complete Volume}
}
Document
Front Matter
Front Matter, Table of Contents, Preface, Conference Organization
Abstract
Front Matter, Table of Contents, Preface, Conference Organization
Cite as
2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 0:i-0:viii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
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@InProceedings{cervin_et_al:OASIcs.Fog-IoT.2020.0,
author = {Cervin, Anton and Yang, Yang},
title = {{Front Matter, Table of Contents, Preface, Conference Organization}},
booktitle = {2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
pages = {0:i--0:viii},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-144-3},
ISSN = {2190-6807},
year = {2020},
volume = {80},
editor = {Cervin, Anton and Yang, Yang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.0},
URN = {urn:nbn:de:0030-drops-119944},
doi = {10.4230/OASIcs.Fog-IoT.2020.0},
annote = {Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Invited Talk
Fog and Edge Computing: Challenges and Emerging Trends (Invited Talk)
Abstract
Just as the trend of data and computing consolidation via cloud computing starts to fade out, new paradigms that can better handle the unique demand of Internet of Things (IoT) and Big Data emerged in the form of edge and fog computing. Although the literature provides different accounts for the differences between these emerging paradigms, they both rely on computing and storage devices that are closer to IoT devices and users than regular cloud data centers. With the advantage of smaller latencies, they introduce issues such as higher complexity for application development and deployment. In this talk, I will present the context in which these paradigms developed, challenges inhibiting their adoption, and emerging approaches to address some of these issues.
Cite as
Rodrigo N. Calheiros. Fog and Edge Computing: Challenges and Emerging Trends (Invited Talk). In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, p. 1:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
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@InProceedings{calheiros:OASIcs.Fog-IoT.2020.1,
author = {Calheiros, Rodrigo N.},
title = {{Fog and Edge Computing: Challenges and Emerging Trends}},
booktitle = {2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
pages = {1:1--1:1},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-144-3},
ISSN = {2190-6807},
year = {2020},
volume = {80},
editor = {Cervin, Anton and Yang, Yang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.1},
URN = {urn:nbn:de:0030-drops-119954},
doi = {10.4230/OASIcs.Fog-IoT.2020.1},
annote = {Keywords: Cloud computing, Fog computing, Edge computing, Internet of Things}
}
Document
Invited Talk
From Vehicular Networks to IoT for Smart Roads: How a Communication Engineer Can Help Solve Transportation Problems (Invited Talk)
Abstract
Intelligent transportation system (ITS) is an important development that applies advanced sensing, communication, big data analysis and control technologies to ground transportation in order to improve safety, mobility and efficiency. This talk will begin with a brief introduction to our work in vehicular networks, which started more than ten years ago. As we delve deeper into vehicular networks and interact more frequently with transportation stakeholders, we realize that ITS is a truly cross-disciplinary area, in order for vehicular networks to achieve its desired impact, we need to think beyond the traditional communication domain, and start to ponder the deeper-level questions of what fundamental changes can be brought by advanced sensing and communication techniques to transportation and how the applications of advanced sensing and communication techniques can help solve crucial transportation problems. To this end, we will introduce our more recent work of developing advanced IoT technology to transform our roads into smart roads, which in the shorter term, make our roads safer and more efficient while providing the fine-grained real-time traffic information for traffic management; in the longer term, provide the much-needed road infrastructure support for the future booming CAV revolution.
Cite as
Guoqiang Mao. From Vehicular Networks to IoT for Smart Roads: How a Communication Engineer Can Help Solve Transportation Problems (Invited Talk). In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, p. 2:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
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@InProceedings{mao:OASIcs.Fog-IoT.2020.2,
author = {Mao, Guoqiang},
title = {{From Vehicular Networks to IoT for Smart Roads: How a Communication Engineer Can Help Solve Transportation Problems}},
booktitle = {2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
pages = {2:1--2:1},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-144-3},
ISSN = {2190-6807},
year = {2020},
volume = {80},
editor = {Cervin, Anton and Yang, Yang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.2},
URN = {urn:nbn:de:0030-drops-119969},
doi = {10.4230/OASIcs.Fog-IoT.2020.2},
annote = {Keywords: Intelligent transportation systems, Vehicular networks, Internet of Things}
}
Document
Quality-Of-Control-Aware Scheduling of Communication in TSN-Based Fog Computing Platforms Using Constraint Programming
Abstract
In this paper we are interested in real-time control applications that are implemented using Fog Computing Platforms consisting of interconnected heterogeneous Fog Nodes (FNs). Similar to previous research and ongoing standardization efforts, we assume that the communication between FNs is achieved via IEEE 802.1 Time Sensitive Networking (TSN). We model the control applications as a set of real-time streams, and we assume that the messages are transmitted using time-sensitive traffic that is scheduled using the Gate Control Lists (GCLs) in TSN. Given a network topology and a set of control applications, we are interested to synthesize the GCLs for messages such that the quality-of-control of applications is maximized and the deadlines of real-time messages are satisfied. We have proposed a Constraint Programming-based solution to this problem, and evaluated it on several test cases.
Cite as
Mohammadreza Barzegaran, Bahram Zarrin, and Paul Pop. Quality-Of-Control-Aware Scheduling of Communication in TSN-Based Fog Computing Platforms Using Constraint Programming. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 3:1-3:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
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@InProceedings{barzegaran_et_al:OASIcs.Fog-IoT.2020.3,
author = {Barzegaran, Mohammadreza and Zarrin, Bahram and Pop, Paul},
title = {{Quality-Of-Control-Aware Scheduling of Communication in TSN-Based Fog Computing Platforms Using Constraint Programming}},
booktitle = {2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
pages = {3:1--3:9},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-144-3},
ISSN = {2190-6807},
year = {2020},
volume = {80},
editor = {Cervin, Anton and Yang, Yang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.3},
URN = {urn:nbn:de:0030-drops-119975},
doi = {10.4230/OASIcs.Fog-IoT.2020.3},
annote = {Keywords: TSN, Fog Computing, Constraint Programming, Quality of Control}
}
Document
Processing LiDAR Data from a Virtual Logistics Space
Abstract
We study computing solutions that can be used close to the network edge in I2oT systems (Industrial Internet of Things). As a specific use case, we consider a factory warehouse with AGVs (Automated Guided Vehicles). The computing services for such systems should be dependable, yield high performance, and have low latency. For understanding such systems, we have constructed a hybrid system that consists of a simulator yielding virtual LiDAR sensor data streams in real-time and a sensor data processor on a real cluster that acts as a fog computing node close to the warehouse. The processing merges the observations done from the individual sensor streams without using the vehicle-to-vehicle communication links for the complicated computing. We present our experimental results, which show the feasibility of the computing solution.
Cite as
Jaakko Harjuhahto, Anton Debner, and Vesa Hirvisalo. Processing LiDAR Data from a Virtual Logistics Space. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 4:1-4:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
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@InProceedings{harjuhahto_et_al:OASIcs.Fog-IoT.2020.4,
author = {Harjuhahto, Jaakko and Debner, Anton and Hirvisalo, Vesa},
title = {{Processing LiDAR Data from a Virtual Logistics Space}},
booktitle = {2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
pages = {4:1--4:12},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-144-3},
ISSN = {2190-6807},
year = {2020},
volume = {80},
editor = {Cervin, Anton and Yang, Yang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.4},
URN = {urn:nbn:de:0030-drops-119985},
doi = {10.4230/OASIcs.Fog-IoT.2020.4},
annote = {Keywords: simulation, hybrid systems, new control applications, fog computing}
}
Document
Addressing the Node Discovery Problem in Fog Computing
Abstract
In recent years, the Internet of Things (IoT) has gained a lot of attention due to connecting various sensor devices with the cloud, in order to enable smart applications such as: smart traffic management, smart houses, and smart grids, among others. Due to the growing popularity of the IoT, the number of Internet-connected devices has increased significantly. As a result, these devices generate a huge amount of network traffic which may lead to bottlenecks, and eventually increase the communication latency with the cloud. To cope with such issues, a new computing paradigm has emerged, namely: fog computing. Fog computing enables computing that spans from the cloud to the edge of the network in order to distribute the computations of the IoT data, and to reduce the communication latency. However, fog computing is still in its infancy, and there are still related open problems. In this paper, we focus on the node discovery problem, i.e., how to add new compute nodes to a fog computing system. Moreover, we discuss how addressing this problem can have a positive impact on various aspects of fog computing, such as fault tolerance, resource heterogeneity, proximity awareness, and scalability. Finally, based on the experimental results that we produce by simulating various distributed compute nodes, we show how addressing the node discovery problem can improve the fault tolerance of a fog computing system.
Cite as
Vasileios Karagiannis, Nitin Desai, Stefan Schulte, and Sasikumar Punnekkat. Addressing the Node Discovery Problem in Fog Computing. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 5:1-5:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
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@InProceedings{karagiannis_et_al:OASIcs.Fog-IoT.2020.5,
author = {Karagiannis, Vasileios and Desai, Nitin and Schulte, Stefan and Punnekkat, Sasikumar},
title = {{Addressing the Node Discovery Problem in Fog Computing}},
booktitle = {2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
pages = {5:1--5:10},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-144-3},
ISSN = {2190-6807},
year = {2020},
volume = {80},
editor = {Cervin, Anton and Yang, Yang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.5},
URN = {urn:nbn:de:0030-drops-119991},
doi = {10.4230/OASIcs.Fog-IoT.2020.5},
annote = {Keywords: Fog computing, Edge computing, Internet of Things, Node discovery, Fault tolerance}
}
Document
Routing Using Safe Reinforcement Learning
Abstract
The ever increasing number of connected devices has lead to a metoric rise in the amount data to be processed. This has caused computation to be moved to the edge of the cloud increasing the importance of efficiency in the whole of cloud. The use of this fog computing for time-critical control applications is on the rise and requires robust guarantees on transmission times of the packets in the network while reducing total transmission times of the various packets.
We consider networks in which the transmission times that may vary due to mobility of devices, congestion and similar artifacts. We assume knowledge of the worst case tranmssion times over each link and evaluate the typical tranmssion times through exploration. We present the use of reinforcement learning to find optimal paths through the network while never violating preset deadlines. We show that with appropriate domain knowledge, using popular reinforcement learning techniques is a promising prospect even in time-critical applications.
Cite as
Gautham Nayak Seetanadi and Karl-Erik Årzén. Routing Using Safe Reinforcement Learning. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 6:1-6:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
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@InProceedings{nayakseetanadi_et_al:OASIcs.Fog-IoT.2020.6,
author = {Nayak Seetanadi, Gautham and \r{A}rz\'{e}n, Karl-Erik},
title = {{Routing Using Safe Reinforcement Learning}},
booktitle = {2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
pages = {6:1--6:8},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-144-3},
ISSN = {2190-6807},
year = {2020},
volume = {80},
editor = {Cervin, Anton and Yang, Yang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.6},
URN = {urn:nbn:de:0030-drops-120007},
doi = {10.4230/OASIcs.Fog-IoT.2020.6},
annote = {Keywords: Real time routing, safe exploration, safe reinforcement learning, time-critical systems, dynamic routing}
}
Document
Real-Time Containers: A Survey
Abstract
Container-based virtualization has gained a significant importance in a deployment of software applications in cloud-based environments. The technology fully relies on operating system features and does not require a virtualization layer (hypervisor) that introduces a performance degradation. Container-based virtualization allows to co-locate multiple isolated containers on a single computation node as well as to decompose an application into multiple containers distributed among several hosts (e.g., in fog computing layer). Such a technology seems very promising in other domains as well, e.g., in industrial automation, automotive, and aviation industry where mixed criticality containerized applications from various vendors can be co-located on shared resources.
However, such industrial domains often require real-time behavior (i.e, a capability to meet predefined deadlines). These capabilities are not fully supported by the container-based virtualization yet. In this work, we provide a systematic literature survey study that summarizes the effort of the research community on bringing real-time properties in container-based virtualization. We categorize existing work into main research areas and identify possible immature points of the technology.
Cite as
Václav Struhár, Moris Behnam, Mohammad Ashjaei, and Alessandro V. Papadopoulos. Real-Time Containers: A Survey. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 7:1-7:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
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@InProceedings{struhar_et_al:OASIcs.Fog-IoT.2020.7,
author = {Struh\'{a}r, V\'{a}clav and Behnam, Moris and Ashjaei, Mohammad and Papadopoulos, Alessandro V.},
title = {{Real-Time Containers: A Survey}},
booktitle = {2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
pages = {7:1--7:9},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-144-3},
ISSN = {2190-6807},
year = {2020},
volume = {80},
editor = {Cervin, Anton and Yang, Yang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.7},
URN = {urn:nbn:de:0030-drops-120011},
doi = {10.4230/OASIcs.Fog-IoT.2020.7},
annote = {Keywords: Real-Time, Containers, Docker, LXC, PREEMPT\underlineRT, Xenomai, RTAI}
}
Document
Evaluation of Burst Failure Robustness of Control Systems in the Fog
Abstract
This paper investigates the robustness of control systems when a controller is run in a Fog environment. Control systems in the Fog are introduced and a discussion regarding relevant faults is presented. A preliminary investigation of the robustness properties of a MinSeg case study is presented and commented. The discussion is then used to outline future lines of research.
Cite as
Nils Vreman and Claudio Mandrioli. Evaluation of Burst Failure Robustness of Control Systems in the Fog. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 8:1-8:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
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@InProceedings{vreman_et_al:OASIcs.Fog-IoT.2020.8,
author = {Vreman, Nils and Mandrioli, Claudio},
title = {{Evaluation of Burst Failure Robustness of Control Systems in the Fog}},
booktitle = {2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
pages = {8:1--8:8},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-144-3},
ISSN = {2190-6807},
year = {2020},
volume = {80},
editor = {Cervin, Anton and Yang, Yang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.8},
URN = {urn:nbn:de:0030-drops-120025},
doi = {10.4230/OASIcs.Fog-IoT.2020.8},
annote = {Keywords: Networked Control Systems, Stability Analysis, Control over Internet, Fault Tolerance}
}
Document
Next-Generation SDN and Fog Computing: A New Paradigm for SDN-Based Edge Computing
Abstract
In the last few years, we have been able to see how terms like Mobile Edge Computing, Cloudlets, and Fog computing have arisen as concepts that reach a level of popularity to express computing towards network Edge. Shifting some processing tasks from the Cloud to the Edge brings challenges to the table that might have been non-considered before in next-generation Software-Defined Networking (SDN). Efficient routing mechanisms, Edge Computing, and SDN applications are challenging to deploy as controllers are expected to have different distributions. In particular, with the advances of SDN and the P4 language, there are new opportunities and challenges that next-generation SDN has for Fog computing. The development of new pipelines along with the progress regarding control-to-data plane programming protocols can also promote data and control plane function offloading. We propose a new mechanism of deploying SDN control planes both locally and remotely to attend different challenges. We encourage researchers to develop new ways to functionally deploying Fog and Cloud control planes that let cross-layer planes interact by deploying specific control and data plane applications. With our proposal, the control and data plane distribution can provide a lower response time for locally deployed applications (local control plane). Besides, it can still be beneficial for a centralized and remotely placed control plane, for applications such as path computation within the same network and between separated networks (remote control plane).
Cite as
Eder Ollora Zaballa, David Franco, Marina Aguado, and Michael Stübert Berger. Next-Generation SDN and Fog Computing: A New Paradigm for SDN-Based Edge Computing. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 9:1-9:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
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@InProceedings{ollorazaballa_et_al:OASIcs.Fog-IoT.2020.9,
author = {Ollora Zaballa, Eder and Franco, David and Aguado, Marina and Berger, Michael St\"{u}bert},
title = {{Next-Generation SDN and Fog Computing: A New Paradigm for SDN-Based Edge Computing}},
booktitle = {2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
pages = {9:1--9:8},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-144-3},
ISSN = {2190-6807},
year = {2020},
volume = {80},
editor = {Cervin, Anton and Yang, Yang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.9},
URN = {urn:nbn:de:0030-drops-120033},
doi = {10.4230/OASIcs.Fog-IoT.2020.9},
annote = {Keywords: SDN, P4, P4Runtime, control planes, Fog, Edge}
}
Document
Fog Network Task Scheduling for IoT Applications
Abstract
In the Internet of Things (IoT) networks, the data traffic would be very bursty and unpredictable. It is therefore very difficult to analyze and guarantee the delay performance for delay-sensitive IoT applications in fog networks, such as emergency monitoring, intelligent manufacturing, and autonomous driving. To address this challenging problem, a Bursty Elastic Task Scheduling (BETS) algorithm is developed to best accommodate bursty task arrivals and various requirements in IoT networks, thus optimizing service experience for delay-sensitive applications with only limited communication resources in time-varying and competing environments. To better describe the stability and consistence of Quality of Service (QoS) in realistic scenarios, a new performance metric "Bursty Service Experience Index (BSEI)" is defined and quantified as delay jitter normalized by the average delay. Finally, the numeral results shows that the performance of BETS is fully evaluated, which can achieve 5-10 times lower BSEI than traditional task scheduling algorithms, e.g. Proportional Fair (PF) and the Max Carrier-to-Interference ratio (MCI), under bursty traffic conditions. These results demonstrate that BETS can effectively smooth down the bursty characteristics in IoT networks, and provide much predictable and acceptable QoS for delay-sensitive applications.
Cite as
Chongchong Zhang, Fei Shen, Jiong Jin, and Yang Yang. Fog Network Task Scheduling for IoT Applications. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 10:1-10:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
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@InProceedings{zhang_et_al:OASIcs.Fog-IoT.2020.10,
author = {Zhang, Chongchong and Shen, Fei and Jin, Jiong and Yang, Yang},
title = {{Fog Network Task Scheduling for IoT Applications}},
booktitle = {2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
pages = {10:1--10:9},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-144-3},
ISSN = {2190-6807},
year = {2020},
volume = {80},
editor = {Cervin, Anton and Yang, Yang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.10},
URN = {urn:nbn:de:0030-drops-120049},
doi = {10.4230/OASIcs.Fog-IoT.2020.10},
annote = {Keywords: Task Scheduling, Internet of Things, fog network, delay sensitive}
}
Document
Realizing Video Analytic Service in the Fog-Based Infrastructure-Less Environments
Abstract
Deep learning has unleashed the great potential in many fields and now is the most significant facilitator for video analytics owing to its capability to providing more intelligent services in a complex scenario. Meanwhile, the emergence of fog computing has brought unprecedented opportunities to provision intelligence services in infrastructure-less environments like remote national parks and rural farms. However, most of the deep learning algorithms are computationally intensive and impossible to be executed in such environments due to the needed supports from the cloud. In this paper, we develop a video analytic framework, which is tailored particularly for the fog devices to realize video analytic service in a rapid manner. Also, the convolution neural networks are used as the core processing unit in the framework to facilitate the image analysing process.
Cite as
Qiushi Zheng, Jiong Jin, Tiehua Zhang, Longxiang Gao, and Yong Xiang. Realizing Video Analytic Service in the Fog-Based Infrastructure-Less Environments. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 11:1-11:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
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@InProceedings{zheng_et_al:OASIcs.Fog-IoT.2020.11,
author = {Zheng, Qiushi and Jin, Jiong and Zhang, Tiehua and Gao, Longxiang and Xiang, Yong},
title = {{Realizing Video Analytic Service in the Fog-Based Infrastructure-Less Environments}},
booktitle = {2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
pages = {11:1--11:9},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-144-3},
ISSN = {2190-6807},
year = {2020},
volume = {80},
editor = {Cervin, Anton and Yang, Yang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.11},
URN = {urn:nbn:de:0030-drops-120050},
doi = {10.4230/OASIcs.Fog-IoT.2020.11},
annote = {Keywords: Fog Computing, Convolution Neural Network, Infrastructure-less Environment}
}
Document
Detection of Fog Network Data Telemetry Using Data Plane Programming
Abstract
Fog computing has been introduced to deliver Cloud-based services to the Internet of Things (IoT) devices. It locates geographically closer to IoT devices than Cloud networks and aims at offering latency-critical computation and storage to end-user applications. To leverage Fog computing for computational offloading from end-users, it is important to optimize resources in the Fog nodes dynamically. Provisioning requires knowledge of the current network state, thus, monitoring mechanisms play a significant role to conduct resource management in the network. To keep track of the state of devices, we use P4, a data-plane programming language, to describe data-plane abstraction of Fog network devices and collect telemetry without the intervention of the control plane or adding a big amount of overhead. In this paper, we propose a software-defined architecture with a programmable data plane for data telemetry detection that can be integrated into Fog network resource management. After the implementation of detecting data telemetry based on In-Band Network Telemetry (INT) within a Mininet simulation, we show the available features and preliminary Fog resource management based on the collected data telemetry and future telemetry-based traffic engineering possibilities.
Cite as
Zifan Zhou, Eder Ollora Zaballa, Michael Stübert Berger, and Ying Yan. Detection of Fog Network Data Telemetry Using Data Plane Programming. In 2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020). Open Access Series in Informatics (OASIcs), Volume 80, pp. 12:1-12:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)
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@InProceedings{zhou_et_al:OASIcs.Fog-IoT.2020.12,
author = {Zhou, Zifan and Ollora Zaballa, Eder and Berger, Michael St\"{u}bert and Yan, Ying},
title = {{Detection of Fog Network Data Telemetry Using Data Plane Programming}},
booktitle = {2nd Workshop on Fog Computing and the IoT (Fog-IoT 2020)},
pages = {12:1--12:11},
series = {Open Access Series in Informatics (OASIcs)},
ISBN = {978-3-95977-144-3},
ISSN = {2190-6807},
year = {2020},
volume = {80},
editor = {Cervin, Anton and Yang, Yang},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Fog-IoT.2020.12},
URN = {urn:nbn:de:0030-drops-120062},
doi = {10.4230/OASIcs.Fog-IoT.2020.12},
annote = {Keywords: SDN, P4, P4Runtime, control planes, Fog, Edge}
}