The challenge

• Objectives:

Design, implementation, and operation of integral solutions for “Large-Scale Data Management to build Software Services in Smart Cities through Edge-to-Cloud orchestration.”

• Challenges:

The stress of urban growth and citizens’ requirements makes it complex to build software services in a smart city. Some key points of these complexities go beyond large-scale IoT management in a smart city in terms of management of data and IoT resources as well as assessment and mitigation cybersecurity threats/risks to validate security requirements for building software services in a smart city.

• Introduction:

As cities change and overgrow, smart city services contribute potent tools for enhancing livability, sustainability, and overall efficiency. Internet of Things (IoT) technology is considered as the heart of a smart city environment to develop the lives of the citizens within it. The IoT-enabled smart city may help to reroute traffic around congestion in real-time, automatically schedule repairs for failed infrastructure like street lighting, and intelligently organize energy and pollution consumption right across the constructed environment. It can defend citizens and businesses from violations as well as safeguard vulnerable citizens in their homes.
By 2021, Gartner envisages that 25 billion IoT devices will be connected and in use as well as assuming prominent business possibilities. However, to benefit fully from capabilities of IoT and thriving innovations in application domains such as applications of the energy management system (EMS), human health applications, etc. in the smart city, it is critical to facilitate the creation and operation of large-scale IoT systems management in the smart city. IoT systems are known to be complex, large scale, and distributed. Coordinated behavior across IoT, edge, and cloud infrastructures require to be organized and structured. Furthermore, the trustworthiness of such systems is critical, ranging from business-critical to safety-critical. The capacity to continuously grow and conform to these systems is crucial to assure and develop their trustworthiness, quality, and user experience.
Edge-to-Cloud orchestration can offer a splendid solution for building Software Services across the city as well as management of the large-scale IoT in smart cities. With regard to focus on designing large-scale software services, we should consider data as the most precious resource for service development in smart cities. Without data, services cannot be launched for smart city citizens. Therefore, to build efficient smart city services, we should consider large-scale IoT data management architecture from data collection to data consumption as well as assessment and mitigation cybersecurity threats/risks to validate security requirements for building software services in the smart city.
Building Software Services in Smart City through Edge-to-Cloud orchestration (3SC-E2C) workshop focuses on software-assisted environments for urban environments. We welcome strong papers exploring the theme of “Large-Scale Data Management to build Software Services in Smart Cities” mainly concentrating on Edge-to-Cloud orchestration. This workshop brings together researchers, developers, practitioners, and stakeholders interested in the advances and applications for smart cities. In addition to this, we look forward to novel proposals for the large-scale management of data, software/service, and cybersecurity in the smart city environment.

Organization

Keynote speakers

Industry Talk

Phu H. Nguyen, Ph.D., Sintef Digital, Oslo, Norway

Title of Keynote Speaker: “Edge-to-Cloud orchestration: a case study of building a scalable Cooperative-Intelligent Transport System (C-ITS)”

Ask him about “Software Engineering” and “IoT Security and Privacy”

Phu H. Nguyen, Ph.D. is a Research Scientist at the Department of Software and Service Innovation, SINTEF, Oslo, Norway. He conducts research in Software Engineering, with a focus on tools and methodologies for software development and operation of heterogeneous and autonomous, yet secure and privacy-aware systems spanning across the Cloud, the Edge, and the IoT. He has experience from working in international research projects in the EU as well as research and development projects with industry. He has a very international education and research background, from Vietnam (BSc) to the Netherlands (MSc), Luxembourg (Ph.D.), and Norway. Phu is active in contributing to the peer-review tasks of high-impact journals such as IEEE Transactions on Software Engineering (TSE), Springer Journal on Software and System Modeling (SoSyM), Elsevier Journal on Information and Software Technology (INFSOF), Journal of Systems and Software (JSS) as well as conferences and workshops. He is a PC member of the International Workshop on Designing and Measuring CyberSecurity in Software Architecture (DeMeSSA 2019), Co-PC Chair of the 11th A-TEST (Automated Testing) workshop 2020. He was awarded a certificate for exceptional contributions, support, and commitment in the organization of the Sixth IEEE International Conference on Software Testing, Verification and Validation (ICST 2013), IBM award for displaying exceptional personal dedication, teamwork and contribution to the ibm.com project 2007, and the first prize at the LuxDoc Science Slam 2014 for communicating research to the public.

His current research interest includes IoT, Microservices Architecture, Cloud to Fog/Edge, C-ITS, and IoT Security and Privacy.

His publication lists> Google Scholar

Title: “Edge-to-Cloud orchestration: a case study of building a scalable Cooperative-Intelligent Transport System (C-ITS)”

Researcher Talk

Ali Dorri, School of Electrical Engineering and Computer Science at Queensland University of Technology (QUT), Brisbane, Australia

Title of Keynote Speaker: “Blockchain: A distributed secure and anonymous solution for smart cities”

Ask him about “Blockchain Applied in IoT” and “Smart Grid”

Ali Dorri, Ph.D., is a Research Fellow in the School of Electrical Engineering and Computer Science at Queensland University of Technology (QUT), Brisbane, Australia. He received his Ph.D. degree from the University of New South Wales (UNSW), Sydney, Australia. He was also a Postgraduate research student at CSIRO, Australia. He has published over 23 peer-reviewed papers. His publications in blockchain are being ranked among most popular in IEEE and ACM digital library as well as top-cited papers in their respective venues.

His current research interest includes blockchain optimization for IoT, blockchain applications in IoT, security and privacy in smart cities, smart grids, e-health, and applied Machine learning

His publication lists> Google Scholar

Young Researcher Talk

Souvik Sengupta, Department of Computer Architecture (DAC), Universitat Politècnica de Catalunya (UPC), Barcelona, Spain

Title of Keynote Speaker: “Prospect of Federated Learning in the combined Fog-to-Cloud Computing paradigm”

Ask him about “Fog/Edge Computing” and “Database Management”

Souvik is a Researcher of CRAAX Lab, Universitat Politechnica da Catalunya (UPC BarcelonaTech) and currently pursuing PhD from the Department of Computer Architecture (DAC) at the UPC BarcelonaTech.  He is working in the area of Resource Management strategy in Fog-to-Cloud computing by using Machine Learning strategies. He has a fellowship from FPI, which is provided by the Ministry of Science and Innovation, Spain. In the past he had been awarded by the Erasmus Mundus Scholarship, which has been provided by the European Commission for the “c-LINK-centre of excellence for Learning, Innovation, Networking and Knowledge”, Erasmus Mundus Action 2 project (372242-1-2012-1-UK-ERA MUNDUS-EMA21).

His current research interest includes Fog/Edge computing, Cloud Computing, IoT, Database Management, and Machine Learning

His publication lists: https://orcid.org/0000-0002-0056-1540

Submission

Building Software Services in Smart City through Edge-to-Cloud orchestration (3SC-E2C) workshop focuses on software-assisted environments for urban environments. We welcome strong papers exploring the theme of “Large-Scale Data Management to build Software Services in Smart Cities” mainly concentrating on Edge-to-Cloud orchestration. This workshop brings together researchers, developers, practitioners, and stakeholders interested in the advances and applications for smart cities. In addition to this, we look forward to novel proposals for the large-scale management of data, software/service, and cybersecurity in the smart city environment.

Program

Start the video-workshop at 11:00 am – Central European Time (CET), 30 June 2020 (Tuesday)

11:00 – 11.15 Welcome message by the Program Chair (Amir Sinaeepourfard, Norwegian University of Science and Technology (NTNU), Norway)

Session 1> Vehicular Networks and Smart Transportation System

11.15 – 11.45 Keynote Talk 1

Presenter: Phu Nguyen, SINTEF, Norway

Title: “Edge-to-Cloud orchestration: a case study of building a scalable Cooperative-Intelligent Transport System (C-ITS)”

Abstract: The development of Cooperative Intelligent Transport Systems (C-ITS) was primarily driven by applications for improving traffic safety and efficiency. More recently, C-ITS applications have focused on not only improving traffic safety and efficiency but also making better use of the digitisation of transport under Cooperative, Connected, and Automated Mobility (CCAM). Indeed, the vision of C-ITS is beyond addressing road safety issues. CCAM is meant for enhanced traffic management and even supporting various business-driven “ecosystems” around C-ITS. For example, besides traffic safety and efficiency scenarios such as intersection collision warning, overtaking warning, cooperative lane change, there will be “business-oriented” scenarios such as miles-traveled-fees, a request for cheap fuel, requirements for customs declarations, diesel bans in city streets and offers for charging stations. This talk presents the challenges and possible solutions of Edge-to-Cloud orchestration in building a scalable C-ITS platform that can realise the vision of CCAM and support for “ecosystems” around C-ITS.

11.45 – 12.00 Accepted Paper Presentation

Title: “A Smart Fog-to-Cloud System in Airport: Challenges and Lessons Learnt”

Authors: Antonio Salis (Engineering Sardegna SRL, Italy), Jens Jensen(UK Research and Innovation-Science and Technology Facilities Council, UK)

Abstract: Airports are one relevant environment in the smart cities implementation. Recent progresses in IoT have made it possible to develop advanced real-time services and assistance tools for travelers, making use of fog computing as an architectural model that places itself between the Cloud and the IoT, in the Cloud-to-Things Continuum, fulfilling requirements for strict real-time responses. The main tool exploits the concept of proximity marketing and
covers the essential experience through the airport onto the flight, but also allows travelers to spend their waiting time by discovering the facilities of the airport, supported by a recommendation system using machine learning. The system provides also the airport planners an aggregated and anonymized view, like heat maps, of travelers behavior that highlight bottlenecks in the infrastructure, or highlight situations that require intervention, such as emergencies. The app in based on Android and makes use of the fog-to-cloud platform developed by the Horizon2020-funded mF2C project,
giving evidence that the adoption of the fog-to-cloud approach brings significant benefits in terms of performance and
optimization of resource usage, giving an objective evidence of the impact of the mF2C framework.

Keywords—Cloud computing, fog computing, fog-to-cloud, distributed systems, IoT, machine learning, proximity marketing

12.00 – 12.30 Lunch break

Session 2> Data Management and Machine Learning

12.30 – 13.00 Keynote talk 2

Title: “Prospect of Federated Learning in the combined Fog-to-Cloud Computing paradigm”

Presenter: Souvik Sengupta, Universitat Politècnica de Catalunya (UPC), Spain

Abstract: The rapid emergence of the Internet of Things (IoT) technology has significantly fueled up the development of ubiquitous computing, and driving the whole society into a new smart computing world. As a matter of course, every surrounding thing is getting connected with the network. Importantly, all of these connected devices are continuously capturing various events from the environments and generating a massive amount of data. Interestingly, the International Data Corporation (IDC), predicts that by 2025 more than forty-two (42) billions of various smart connected devices or things would be activated across the globe, and these devices would produce almost seventy-nine (79) zettabytes (ZB) of data in the same year [1]. Thus, managing those massive amounts of data and devices poses an enormous challenge for any existing computing system. Notably, one of the critical features of any modern smart computing system is to provide latency-sensitive context-aware services efficiently among the end-users. For ensuring this facility, it is essential to distribute the computation and secure storage facilities all over the network. Realizing this fact, Xavi et al. [2] proposed a coordinated and hierarchical Fog-to-Cloud (F2C) computing platform by integrating the Cloud, Fog, and IoT functionalities. One of the most significant nature of the F2C is that it helps to bring more intelligence on the verge of the network. Significantly, intelligence is closely related to the adaption of knowledge from history. Based on the learning from past incidents, a device can able to perform quick and wise action. Thus, in the F2C scenario, local data storing and processing with global coordination is essential for bringing the smartness at the end-users site. Therefore, Federated Learning [3] is going to play a crucial role in any large-scale distributed computing paradigm, i.e., F2C-enabled Smart Computing system. Local data processing – is the biggest advantage of the Federated Learning technique. As the data is locally processing, there is no further requirement to send the data to the centralized server. That means, the Federated Learning not only reduces the bandwidth consumption as well as ensures the currently coined-up data-privacy issues (ex. GDPR) [4].
In many aspects and scenarios, Federated Learning can be beneficial for the F2C, and it helps the F2C to keep its promises for bringing the smartness to the verge of the network. For example, in the real-time traffic management system to e-Health emergency services, Federated Learning can be productive for F2C. Especially for offering any real-time context-aware services, F2C can grant the better quality of facilities by adopting the Federated Learning techniques. Thus the adoption of the Federated Learning concept in the F2C is still in the infancy stage. So, many more aspects are still open to be addressed. In this talk, will focus on identifying the prospects and the open issues for implementing the Federated Learning concept in the combined and hierarchical Fog-to-Cloud (F2C) paradigm.
REFERENCES>
[1] M. Shirer and C. MacGillivray. (2019, jun) The growth in connected iot devices is expected to generate 79.4zb of data in 2025, according to a new idc
forecast. [Online]. Available: https://www.idc.com/getdoc.jsp?containerId=prUS45213219
[2] X. Masip-Bruin, E. Marın-Tordera, A. Juan-Ferrer, A. Queralt, A. Jukan, J. Garcia, D. Lezzi, J. Jensen, C. Cordeiro, A. Leckey et al., “mf2c: towards
a coordinated management of the iot-fog-cloud continuum,” in Proceedings of the 4th ACM MobiHoc Workshop on Experiences with the Design and
Implementation of Smart Objects. ACM, 2018, p. 8.
[3] H. B. McMahan, E. Moore, D. Ramage, S. Hampson et al., “Communication-efficient learning of deep networks from decentralized data,” arXiv preprint
arXiv:1602.05629, 2016.
[4] K. Bonawitz, H. Eichner, W. Grieskamp, D. Huba, A. Ingerman, V. Ivanov, C. Kiddon, J. Konecny, S. Mazzocchi, H. B. McMahan et al., “Towards
federated learning at scale: System design,” arXiv preprint arXiv:1902.01046, 2019.

13.00 – 13.15 Accepted Paper Presentation

Title: “A Cost Model for Data Discovery in Large-Scale ICT Networks of Smart Cities”

Authors: Torbjørn Soltvedt, Amir Sinaeepourfard, Dirk Ahlers (Norwegian University of Science and Technology (NTNU), Norway))

Abstract: A smart city with huge numbers of physical (e.g., sensors and actuators) and non-physical (e.g., external databases) data sources will continuously produce high amounts of massive city-data. Distributed data storage across the city may store the produced city-data. City managers through different update mechanisms may send the produced city-data from distributed data storage to centralized data storage (e.g., Cloud data storage). Hence, the data discovery issues are in a vital position in the smart city concepts because the produced city-data may exist in different data storage platforms from distributed to centralized data. In this paper, we will first present our proposed Distributed-to-Centralized Information and Communications Technology (D2C-ICT) architecture for the Zero Emission Neighborhoods (ZEN) center. This proposed D2C-ICT architecture can provide multiple facilities from the joined benefits of distributed and centralized technologies in smart cities. Second, we will show how the Multi-Attribute Utility Theory (MAUT) cost model can be beneficial to find the appropriate data for building city services across the different storage platforms on the city scale as well as can be applied in the ZEN center and its pilots.
Keywords—Smart City; Cost Model; Data Discovery; Distributed-to-Centralized ICT Architecture

13.15 – 13.30 Accepted Paper Presentation

Title: “Bridging MQTT and Kafka to support C-ITS: a feasibility study”

Authors: Åsmund Hugo, Brice Morin, Karl Svantorp (SINTEF, Norway)

Abstract: Nowadays, every vehicle is wirelessly connected, often by both itself and its passengers. The same goes for all the continuously growing amount of devices alongside the transportation infrastructure. This induces an abundance of data that can be used to direct traffic efficiently, optimize the transportation infrastructure, avoid accidents, lower emissions from transportation and so forth. To create coherence among the messages related to a Cooperative and Intelligent Transportation System (C-ITS), an ETSI message type standard has been developed. The next hurdle is how to facilitate receiving and processing millions of C-ITS messages in real-time.
We present a feasibility study on how these C-ITS messages can be received, processed and distributed. Our novel approach is to bridge C-ITS message types over MQTT, to Apache Kafka, with fault-tolerance, horizontal scalability and low latency. We have engineered both an MQTT-Kafka source connector and a Kafka-MQTT sink connector, by utilizing the Kafka Connector API. These facilitate an easy configurable topic mapping between MQTT and Kafka, from vehicles and road side units to a central application, and in the opposite direction. Our experiments with this bridging technology, performed on a modest desktop computer with a single instance Kafka setup, show the feasibility by managing to source and sink CAM messages with low latency.

Keywords—C-ITS, Kafka, Smart Mobility, MQTT, Distributed Message Delivery

Session 3>  Security and Software Services Platform

13.30 – 14.00 Keynote talk 3

Title: “Blockchain: A distributed secure and anonymous solution for smart cities”

Presenter: Ali Dorri, Queensland University of Technology (QUT), Australia

Abstract: Smart city incorporates a broad range of sensors and devices that capture various aspects of the users’ day life and transfer the data to centralized service providers (SPs). The latter offer personalized services to the users which in turn increases user satisfaction and automates multiple everyday tasks. The huge volume of information collected by SPs may potentially compromise the user privacy as the SP can build a virtual profile about the user. Additionally, conventional centralized solutions are not scalable in network with millions of devices.  Blockchain has received tremendous attention to address security, anonymity, and centralization challenges in smart cities. Blockchain is a distributed database that records transactions, i.e., communications between nodes, in the form of blocks. Appending new blocks to the blockchain involves following a consensus algorithm that ensures blockchain security and establishes a trusted network without relying on central authorities.

In this talk, I will discuss the core concepts and the key features of blockchain that made it attractive for smart cities. I will also discuss applications of blockchain in smart connected vehicles and energy management as representative applications of smart cities. Finally, I will discuss the challenges and limitations associated with adopting blockchain in smart cities.

14.00 – 14.15 Accepted Paper Presentation

Title: “A Novel Edge-to-Cloud-as-a-Service (E2CaaS) Model for Building Software Services in Smart Cities”

Authors: Jaro Robberechts (Ghent University, Belgium), Amir Sinaeepourfard (Norwegian University of Science and Technology (NTNU), Norway), Tom Goethals (Ghent University, Belgium), Bruno Volckaert (Ghent University, Belgium)

Abstract: The main goal of a smart city is to enhance the quality of life of its inhabitants by providing services using Information and Communications Technology (ICT) components in a city. ICT components include not only Internet of Things (IoT) data sources spread across the city, but also traditional non-IoT data sources. Managing all ICT components in a smart city can be challenging and results in many complexities. Consequently, there is a need for ICT management architectures. Traditional solutions are often based on a centralized ICT architecture using Cloud technologies. Recently, the number of ICT components, services, and their corresponding complexities are growing, leading to large-scale ICT architectures. Centralized Cloud solutions cannot cope with the ever-expanding demands of this kind of architectures. The limitations of the centralized approaches necessitate the design of a new ICT architecture, using distributed technologies, for every layer and element of the city. Many solutions for management from Edge-to-Cloud (E2C) through distributed technologies are forthcoming, including Decentralized-to-Centralized ICT (DC2C-ICT) and Distributed-to-Centralized ICT (D2C-ICT) architectures. The DC2C-ICT architecture and its components work on their own tasks and are solely communicating with a centralized platform. On the other hand, components of the D2C-ICT architecture can work together to provide the services for the citizens across different layers from E2C. Therefore, the D2C-ICT architecture is less dependent on the central Cloud-based entity, but harder to design and manage. In this paper, an “Edge-to-Cloud-as-a-Service (E2CaaS)” model is proposed together with a model on how to build efficient software services in smart cities through different layers of E2C. The most important tasks for building these services are the management of “Data/Database,” “Resources,” and “Network Communication and Cybersecurity issues.”

Keywords—Smart City, IoT, Edge-to-Cloud, Distributed-to-Centralized ICT architecture, Edge-to-Cloud-as-a-Service

14.15 – 14.30 Accepted Paper Presentation

Title: “Towards a Simulation Framework for Edge-to-Cloud Orchestration in C-ITS”

Authors: Phu Nguyen (SINTEF, Norway), Åsmund Hugo (SINTEF, Norway), Karl Svantorp (Aventi, Norway), Bjørn Magne Elnes (Aventi, Norway)

Abstract: Cooperative Intelligent Transport Systems (C-ITS) are essential for smart cities. To realise the vision of C-ITS in the European Strategy to implement smart mobility towards Cooperative, Connected and Automated Mobility (CCAM), there must be advanced infrastructures for message exchange between connected and autonomous vehicles (CAVs), road-side units (RSUs), and transport management centres. One of the most challenges to build such infrastructures is to ensure the scalability to support for millions of vehicles on roads at the same time. In this short paper, we aim to discuss the challenge of ensuring the scalability of a C-ITS platform and describe our simulation framework to test its scalability. First, we give a high-level description of a C-ITS platform that is based on Edge-Cloud orchestration for message exchange between CAVs, RSUs, and transportation data centres. Then, we present our simulation framework that is based on Eclipse SUMO and Veins to test the scalability of the C-ITS platform. We have initially worked in two main tasks for the simulation framework: build simulation scenarios and integrate MQTT clients into the simulation tools to test our C-ITS platform. These are two fundamental steps towards a full simulation framework for our C-ITS platform.

Keywords— Smart Mobility, Edge-to-Cloud, Simulation, Connected Vehicles, Autonomous Vehicles, C-ITS, CCAM

14.30 – 15.00 Final Technical Discussion Panel by the committee members and keynote speakers (Amir Sinaeepourfard, Antonio Salis, Phu Nguyen, Souvik Sengupta, Ali Dorri), including “Main outcomes and open challenges in the design of complex Software Services in Smart Cities”

15.00  End of Workshop

Venue

Please visit this link for further information.

Contact

For further information, please contact us at a.sinaee@ntnu.no. Please put the title of your email “3SCity-E2C 2020 Workshop-Question”.