An analysis of selected cases

Funding Information: This work was supported by Project CESME (Collaborative & Evolvable Smart Manufacturing Ecosystem) and the Portuguese FCT program UIDB/00066/2020. Publisher Copyright: © 2022 The Author(s)The rapid proliferation of renewable energy communities/ecosystems is an indication of their potential contribution to the ongoing energy transition. A common characteristic of these ecosystems is their complex composition, which often involves the interaction of multiple actors. Currently, the notions of "networking", "collaboration", "coordination", and "cooperation", although having different meanings, are often loosely used to describe these interactions, which creates a sense of ambiguity and confusion. To better characterize the nature of interactions in current and emerging ecosystems, this article uses the systematic literature review method to analyse 34 emerging cases. The objective is threefold (a) to study the interactions and engagements between the involved actors, aiming at identifying elements of collaboration. (b) Identify the adopted technological enablers, and (c) ascertain how the composition and functions of these ecosystems compare to virtual power plants. The outcome revealed that the interactions between the members of these ecosystems can be described as cooperation and not necessarily as collaboration, except in a few cases. Regarding technological enablers, a vast panoply of technologies, such as IoT devices, smart meters, intelligent software agents, peer-to-peer networks, distributed ledger systems/blockchain technology (including smart contracts, blockchain as a platform service, and cryptocurrencies) were found. In comparison with virtual power plants, these ecosystems have similar composition, thus, having multiple actors, comprised of decentralized and heterogeneous technologies, and are formed by aggregating various distributed energy resources. They are also supported by ICT and are characterized by the simultaneous flow of information and energy.publishersversionpublishe

ARTA: An economic middleware to exchange pervasive energy and computing resources

Studies reveal that an integrated system of smart grid and cloud computing ecosystems can better attain the energy efficiency objectives, considering all the aspects. To facilitate the integration, in this paper, we introduce an agent-oriented economic middleware architecture (ARTA) to exchange pervasive energy and computing resources in different layers of the service provisioning platform, from the edge layer of micro-grid and P2P-cloud to the mass production layer of the giant power plants and data centers. ARTA follows a semi-decentralized economic model by operating through partial system view in the edge-layer negotiations and considers system dynamics and uncertainties in the agents decisions.Peer ReviewedPostprint (author's final draft

A Property Rights Enforcement and Pricing Model for IIoT Data Marketplaces

학위논문(석사)--서울대학교 대학원 :공과대학 협동과정 기술경영·경제·정책전공,2019. 8. Jörn 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.산업용 사물 인터넷 (IIoT) 데이터가 제품과 서비스를 위한 중요한 고급 데이터 소스로 여겨지고 있지만, 여전히 수 많은 기업들은 불충분한 산업용 사물 인터넷 데이터 공유 시스템으로 인하여 고충을 겪고 있다. 방대한 분량의 산업용 데이터가 제대로 거래되지 못하고 있으며, 이는 데이터의 커다란 가치 손실로 이어지고 있다. 본 연구에서는 서비스로서의 센싱 (Sensing as a Service) 비지니스 모델이 한정적으로 적용되고 있는 원인이 해당 정보의 경제적, 기술적 특징들을 반영하는 디지털 권리 시스템의 부재에 기인한다고 보고 있다. 따라서 본 연구에서는 산업용 사물 인터넷 데이터에 대한 지적재산권 집행 시스템과 데이터 가격산정 모델을 제안하여 산업용 사물 인터넷 데이터 공유 인센티브 문제를 해결하고자 한다.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

Towards Free Market Cloud Computing

Although cloud computing has made great inroads in terms of consumer adoption, we argue that the paradigm still has a long way to go to reach an economically efficient free market state. We highlight four key problems with the current cloud computing approach. These are (1) coarse granularity of service provision, (2) limited control of resources, (3) inadequate support for small providers and prosumers, and (4) vendor lockin via APIs. In this position paper, we briefly outline interesting work that may lead to a solution, in terms of moving towards a more market-based approach to cloud resource allocation

The integrity of digital technologies in the evolving characteristics of real-time enterprise architecture

Advancements in interactive and responsive enterprises involve real-time access to the information and capabilities of emerging technologies. Digital technologies (DTs) are emerging technologies that provide end-to-end business processes (BPs), engage a diversified set of real-time enterprise (RTE) participants, and institutes interactive DT services. This thesis offers a selection of the author’s work over the last decade that addresses the real-time access to changing characteristics of information and integration of DTs. They are critical for RTEs to run a competitive business and respond to a dynamic marketplace. The primary contributions of this work are listed below. • Performed an intense investigation to illustrate the challenges of the RTE during the advancement of DTs and corresponding business operations. • Constituted a practical approach to continuously evolve the RTEs and measure the impact of DTs by developing, instrumenting, and inferring the standardized RTE architecture and DTs. • Established the RTE operational governance framework and instituted it to provide structure, oversight responsibilities, features, and interdependencies of business operations. • Formulated the incremental risk (IR) modeling framework to identify and correlate the evolving risks of the RTEs during the deployment of DT services. • DT service classifications scheme is derived based on BPs, BP activities, DT’s paradigms, RTE processes, and RTE policies. • Identified and assessed the evaluation paradigms of the RTEs to measure the progress of the RTE architecture based on the DT service classifications. The starting point was the author’s experience with evolving aspects of DTs that are disrupting industries and consequently impacting the sustainability of the RTE. The initial publications emphasized innovative characteristics of DTs and lack of standardization, indicating the impact and adaptation of DTs are questionable for the RTEs. The publications are focused on developing different elements of RTE architecture. Each published work concerns the creation of an RTE architecture framework fit to the purpose of business operations in association with the DT services and associated capabilities. The RTE operational governance framework and incremental risk methodology presented in subsequent publications ensure the continuous evolution of RTE in advancements of DTs. Eventually, each publication presents the evaluation paradigms based on the identified scheme of DT service classification to measure the success of RTE architecture or corresponding elements of the RTE architecture

Data Spaces

This open access book aims to educate data space designers to understand what is required to create a successful data space. It explores cutting-edge theory, technologies, methodologies, and best practices for data spaces for both industrial and personal data and provides the reader with a basis for understanding the design, deployment, and future directions of data spaces. The book captures the early lessons and experience in creating data spaces. It arranges these contributions into three parts covering design, deployment, and future directions respectively. The first part explores the design space of data spaces. The single chapters detail the organisational design for data spaces, data platforms, data governance federated learning, personal data sharing, data marketplaces, and hybrid artificial intelligence for data spaces. The second part describes the use of data spaces within real-world deployments. Its chapters are co-authored with industry experts and include case studies of data spaces in sectors including industry 4.0, food safety, FinTech, health care, and energy. The third and final part details future directions for data spaces, including challenges and opportunities for common European data spaces and privacy-preserving techniques for trustworthy data sharing. The book is of interest to two primary audiences: first, researchers interested in data management and data sharing, and second, practitioners and industry experts engaged in data-driven systems where the sharing and exchange of data within an ecosystem are critical

CloudAnchor Smart Contracts

The CloudAnchor platform allows the negotiation of IaaS Cloud resources for Small and Medium Sized Enterprises (SME), either as resource providers or consumers. This project entails the research, design, and implementation of a solution based on smart contracts, with the goal of permanently recording and managing the contracts on a blockchain network. The usage of smart contracts enables safe contract code execution and raises the level of trust, integrity, and traceability of the platform contracts by keeping the data stored in a decentralised manner. To do so, a method to coordinate and submit transactions to the blockchain network must be implemented. The tests carried out indicate that the solution has been successfully implemented, with contract registration saved in a decentralised and safe manner. As a result, there was an increase in the platform’s execution time, caused by the new transactions made to the blockchain.A plataforma CloudAnchor permite a negociação e contratualização de recursos Cloud do tipo IaaS a pequenas e médias empresas, sejam elas fornecedoras ou clientes. Este trabalho inclui o estudo, projeto e implementação de uma solução baseada em smart contracts, com o objetivo de administrar e registar de forma permanente os contratos celebrados numa rede blockchain. A utilização de smart contracts permite executar o respetivo código de forma segura e aumentar o nível de confiança, integridade e rastreabilidade dos contratos celebrados na plataforma, guardando-os de forma descentralizada. Para tal, é necessário implementar um mecanismo de coordenação e submissão de transações para a rede blockchain. Os testes realizados permitiram concluir que a implementação da solução foi bem sucedida, passando os contratos a ficar guardados de forma descentralizada e segura. Em consequência, verificou-se um aumento do tempo de execução da plataforma provocado pelas novas transações com a blockchain

Integration of Blockchain and Auction Models: A Survey, Some Applications, and Challenges

In recent years, blockchain has gained widespread attention as an emerging technology for decentralization, transparency, and immutability in advancing online activities over public networks. As an essential market process, auctions have been well studied and applied in many business fields due to their efficiency and contributions to fair trade. Complementary features between blockchain and auction models trigger a great potential for research and innovation. On the one hand, the decentralized nature of blockchain can provide a trustworthy, secure, and cost-effective mechanism to manage the auction process; on the other hand, auction models can be utilized to design incentive and consensus protocols in blockchain architectures. These opportunities have attracted enormous research and innovation activities in both academia and industry; however, there is a lack of an in-depth review of existing solutions and achievements. In this paper, we conduct a comprehensive state-of-the-art survey of these two research topics. We review the existing solutions for integrating blockchain and auction models, with some application-oriented taxonomies generated. Additionally, we highlight some open research challenges and future directions towards integrated blockchain-auction models