13 research outputs found
Sensing as a service (S2aaS): buying and selling IoT data
The Internet of Things (IoT) envisions the creation of an environment where everyday objects (e.g. microwaves, fridges, cars, coffee machines, etc.) are connected to the internet and make users' lives more convenient. It will also lead users to consume resources more efficiently
A Property Rights Enforcement and Pricing Model for IIoT Data Marketplaces
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ผ๋ฌธ(์์ฌ)--์์ธ๋ํ๊ต ๋ํ์ :๊ณต๊ณผ๋ํ ํ๋๊ณผ์ ๊ธฐ์ ๊ฒฝ์ยท๊ฒฝ์ ยท์ ์ฑ
์ ๊ณต,2019. 8. Jรถrn Altmann.The Industrial Internet of Things (IIoT) has become a valuable data source for products and services based on advanced data analytics. However, evidence suggests that industries are suffering a significant loss of value creation from insufficient IIoT data sharing. We argue that the limited utilization of the Sensing as a Service business model is caused by the economic and technological characteristics of sensor data, and the corresponding absence of applicable digital rights management models. Therefore, we propose a combined property rights enforcement and pricing model to solve the IIoT data sharing incentive problem.์ฐ์
์ฉ ์ฌ๋ฌผ ์ธํฐ๋ท (IIoT) ๋ฐ์ดํฐ๊ฐ ์ ํ๊ณผ ์๋น์ค๋ฅผ ์ํ ์ค์ํ ๊ณ ๊ธ ๋ฐ์ดํฐ ์์ค๋ก ์ฌ๊ฒจ์ง๊ณ ์์ง๋ง, ์ฌ์ ํ ์ ๋ง์ ๊ธฐ์
๋ค์ ๋ถ์ถฉ๋ถํ ์ฐ์
์ฉ ์ฌ๋ฌผ ์ธํฐ๋ท ๋ฐ์ดํฐ ๊ณต์ ์์คํ
์ผ๋ก ์ธํ์ฌ ๊ณ ์ถฉ์ ๊ฒช๊ณ ์๋ค. ๋ฐฉ๋ํ ๋ถ๋์ ์ฐ์
์ฉ ๋ฐ์ดํฐ๊ฐ ์ ๋๋ก ๊ฑฐ๋๋์ง ๋ชปํ๊ณ ์์ผ๋ฉฐ, ์ด๋ ๋ฐ์ดํฐ์ ์ปค๋ค๋ ๊ฐ์น ์์ค๋ก ์ด์ด์ง๊ณ ์๋ค. ๋ณธ ์ฐ๊ตฌ์์๋ ์๋น์ค๋ก์์ ์ผ์ฑ (Sensing as a Service) ๋น์ง๋์ค ๋ชจ๋ธ์ด ํ์ ์ ์ผ๋ก ์ ์ฉ๋๊ณ ์๋ ์์ธ์ด ํด๋น ์ ๋ณด์ ๊ฒฝ์ ์ , ๊ธฐ์ ์ ํน์ง๋ค์ ๋ฐ์ํ๋ ๋์งํธ ๊ถ๋ฆฌ ์์คํ
์ ๋ถ์ฌ์ ๊ธฐ์ธํ๋ค๊ณ ๋ณด๊ณ ์๋ค. ๋ฐ๋ผ์ ๋ณธ ์ฐ๊ตฌ์์๋ ์ฐ์
์ฉ ์ฌ๋ฌผ ์ธํฐ๋ท ๋ฐ์ดํฐ์ ๋ํ ์ง์ ์ฌ์ฐ๊ถ ์งํ ์์คํ
๊ณผ ๋ฐ์ดํฐ ๊ฐ๊ฒฉ์ฐ์ ๋ชจ๋ธ์ ์ ์ํ์ฌ ์ฐ์
์ฉ ์ฌ๋ฌผ ์ธํฐ๋ท ๋ฐ์ดํฐ ๊ณต์ ์ธ์ผํฐ๋ธ ๋ฌธ์ ๋ฅผ ํด๊ฒฐํ๊ณ ์ ํ๋ค.1 Introduction 1
1.1 Background 1
1.2 Problem Description 6
1.3 Research Objective and Question 8
1.4 Methodology 8
1.5 Contributions 9
1.6 Structure 10
2 Literature Review 11
2.1 Sensing as a Service 11
2.2 Economic Characteristics of IIoT Data 14
2.2.1 Property Rights of Data 18
2.2.2 Licensing of IIoT Data 23
2.3 IIoT Data Marketplaces 25
2.3.1 Use-cases and Value Propositions 30
2.3.2 Market Structures and Pricing Models 34
2.4 Digital Rights Management for IIoT 36
3 Model 44
3.1 Assumptions 45
3.2 Watermarking Technique 47
3.2.1 Function 48
3.2.2 Example 50
3.2.3 Robustness 51
3.3 Economic Reasoning 54
3.3.1 The Quality Gap 55
3.3.2 Cost of Watermarking (CoW) 57
3.3.3 Cost of Attacking (CoA) 58
4 Analytical Analysis 60
4.1 Equilibrium Between CoW and CoA 60
4.2 Determining the Optimal Quality Gap 62
4.3 Applicability of the Quality Gap Function 64
5 Conclusion 66
5.1 Summary 66
5.2 Discussion 66
6 Limitations and Future Research 68
References 70
Abstract (Korean) 79Maste
Sensing as a Service for Internet of Things: A roadmap
Few years back, I wrote about the Sensing as a Service (S2aaS) in two scholarly publications. Since then, these publications have been well cited and discussed by different research communities. After receiving number of inquires from interested readers, I decided to write this book to explain the topic of S2aaS in detail, specially without being restricted into number of pages allowed by conferences and journals. This book aims to expand on previous ideas and to present a much detailed vision that would be useful to both general (non-scientific) and advance (scientific) readers. This book is written in a easy to understand non-technical language to help general readers to grasp the content quickly. However, I also wanted to make sure that this book useful for advance readers who are interested in additional reading material on the topic. In order to facilitate them, throughout this book, I have presented additional material using different types of notes
Using Blockchain to support Data & Service Monetization
Two required features of a data monetization platform are query and retrieval of the metadata of the resources to be monetized. Centralized platforms rely on the maturity of traditional NoSQL database systems to support these features. These databases, for example, MongoDB allows for very efficient query and retrieval of data it stores. However, centralized platforms come with a bag of security and privacy concerns, making them not the ideal approach for a data monetization platform. On the other hand, most existing decentralized platforms are only partially decentralized. In this research, I developed Cowry, a platform for publishing metadata describing available resources (data or services), discovery of published metadata including fast search and filtering. My main contribution is a fully decentralized architecture that combines blockchain and traditional distributed database to gain additional features such as efficient query and retrieval of metadata stored on the blockchain
Modeling and Analysis of Data Trading on Blockchain-based Market in IoT Networks
Mobile devices with embedded sensors for data collection and environmental
sensing create a basis for a cost-effective approach for data trading. For
example, these data can be related to pollution and gas emissions, which can be
used to check the compliance with national and international regulations. The
current approach for IoT data trading relies on a centralized third-party
entity to negotiate between data consumers and data providers, which is
inefficient and insecure on a large scale. In comparison, a decentralized
approach based on distributed ledger technologies (DLT) enables data trading
while ensuring trust, security, and privacy. However, due to the lack of
understanding of the communication efficiency between sellers and buyers, there
is still a significant gap in benchmarking the data trading protocols in IoT
environments. Motivated by this knowledge gap, we introduce a model for
DLT-based IoT data trading over the Narrowband Internet of Things (NB-IoT)
system, intended to support massive environmental sensing. We characterize the
communication efficiency of three basic DLT-based IoT data trading protocols
via NB-IoT connectivity in terms of latency and energy consumption. The model
and analyses of these protocols provide a benchmark for IoT data trading
applications.Comment: 10 pages, 8 figures, Accepted at IEEE Internet of Things Journa
The blockchain: a new framework for robotic swarm systems
Swarms of robots will revolutionize many industrial applications, from targeted material delivery to precision farming. However, several of the heterogeneous characteristics that make them ideal for certain future applications --- robot autonomy, decentralized control, collective emergent behavior, etc. --- hinder the evolution of the technology from academic institutions to real-world problems. Blockchain, an emerging technology originated in the Bitcoin field, demonstrates that by combining peer-to-peer networks with cryptographic algorithms a group of agents can reach an agreement on a particular state of affairs and record that agreement without the need for a controlling authority. The combination of blockchain with other distributed systems, such as robotic swarm systems, can provide the necessary capabilities to make robotic swarm operations more secure, autonomous, flexible and even profitable. This work explains how blockchain technology can provide innovative solutions to four emergent issues in the swarm robotics research field. New security, decision making, behavior differentiation and business models for swarm robotic systems are described by providing case scenarios and examples. Finally, limitations and possible future problems that arise from the combination of these two technologies are described