Computational Science in IoT and Smart Systems (IoTSS) Session 1
Time and Date: 16:50 - 18:30 on 12th June 2019
Room: 0.6
Chair: Vaidy Sunderam
131 | Fog computing architecture based blockchain for industrial IoT [abstract] Abstract: Industry 4.0 is also referred to as the fourth industrial revolution and is the vision of a smart factory built with CPS. The ecosystem of the manufacturing industry is expected to be activated through autonomous and intelligent systems such as self-organization, self-monitoring and self-healing.
The Fourth Industrial Revolution is beginning with an attempt to combine the myriad elements of the industrial system with Internet communication technology to form a future smart factory. The related technologies derived from these attempts are creating new value. However, the existing Internet has no effective way to solve the problem of cyber security and data information protection against new technology of future industry. In a future industrial environment where a large number of IoT devices will be supplied and used, if the security problem is not resolved, it is hard to come to a true industrial revolution.
Therefore, in this paper, we propose block chain based fog system architecture for Industiral IoT. In this paper, we propose a new block chain based fog system architecture for industial IoT. In order to guarantee fast performance, And the performance is evaluated and analyzed by applying a proper fog system-based permission block chain. |
Jang Su Hwan, Jongpil Jeong and Jo Guejong |
492 | Exploration of Data from Smart Bands in the Cloud and on the Edge - the Impact on the Data Storage Space [abstract] Abstract: Smart bands are wearable devices that are frequently used in monitoring people's activity, fitness, and health state. They can be also used in early detection of possibly dangerous health-related problems. The increasing number of wearable devices frequently transmitting data to scalable monitoring centers located in the Cloud may raise the Big Data challenge and cause network congestion.
In this paper, we focus on the storage space consumed while monitoring people with smart IoT devices and performing classification of their health state and detecting possibly dangerous situations with the use of machine learning models in the Cloud and on the Edge. We also test two different repositories for storing sensor data in the Cloud monitoring center - a relational Azure SQL Database and the Cosmos DB document store. |
Mateusz Gołosz and Dariusz Mrozek |
209 | Security of Low Level IoT Protocols [abstract] Abstract: Application of formal methods in security is demonstrated. Formalism for description of security properties of low level IoT protocols is proposed. It is based on timed process algebra and on security concept called infinite step opacity. We prove some of its basic properties as well as we show its relation to other security notions. Finally, complexity issues of verification and security enforcement are discussed. |
Damas Gruska and M.Carmen Ruiz |
569 | FogFlow - computation organization for heterogeneous Fog computing environments [abstract] Abstract: With the arising amounts of devices and data that Internet of Things systems are processing nowadays, solutions for computational applications are in a high demand. Many concepts targeting at more efficient data processing are arising and among them edge and fog computing are the ones gaining significant interest since they reduce cloud load. In consequence Internet of Things systems are becoming more and more diverse in terms of architecture. In this paper we present FogFlow - model and execution environment allowing for organization of data-flow applications to be run on the heterogeneous environments. We propose unified interface for data-flow creation, graph model and we evaluate our concept in the use case of production line model that mimic real-world factory scenario. |
Joanna Sendorek, Tomasz Szydlo, Robert Brzoza-Woch and Mateusz Windak |