GeoBlockchain: The Analysis, Design, and Evaluation of a Spatially Enabled Blockchain

Land ownership and supply chain use cases are an enormous business challenge for both the public and private sectors. Every organization has different needs and wants, and they are researching and exploring ways to add value and impact their ownership tracing processes. Geospatial and Blockchain technologies are two emerging trends that could help an organization add value in this manner. The combination of blockchain and geospatial technologies would result in the new concept of GeoBlockchain, defined here as an artifact that could be used to study the trends and behaviours of participants (users) geographically and spatially, based on distributed nodes, transactions, and geo-locations through the blockchain technology. GeoBlockchain can also be used to visually display geo-ownership tracing processes (points, lines, and polygons) demonstrating the importance of geography. The result of this research was the design, development, implementation, and evaluation of a Spatially Enabled Blockchain ICT artifacts. Each prototype artifact was built using ArcGIS Enterprise and Hyperledger Fabric. The architecture designs were implemented with on-premises and cloud environments and evaluated based on users’ usability and sociotechnical metrics. This research indicates that blockchain technology can be integrated with geospatial technology, resulting in the GeoBlockchain framework along with its attendant implementation criteria in the age of GeoBlockchain

Selecting Implementation Criteria in the Age of GeoBlockchain

Today, the growing use of public blockchain, private blockchain, and hybrid blockchain advances in geospatial technology. Geography is a significant factor in identifying locations and spatial trends related to blockchain activities through distributed and immutable networks. Besides that, as the understanding that blockchain and location intelligence has value for many organizations. Our study examined the merge of the two technologies and identified the implementation criteria in the age of GeoBlockchchain. Moreover, it will examine the rules and roles of participants within GeoBlockchain by using Q Methodology and Q set. The ICT artifact for a supply chain use case is the result of a solution proof of concept

Design Patterns for Ethereum Smart Contracts

The invention of Bitcoin in 2008 offered a solution for a digital currency that could be used without a trusted third-party settling disputes over transactions. Bitcoin relied on a technology known as the blockchain, which can be described as a distributed database that relies on a consensus mechanism (generally Proof Of Work is employed) to be resilient against tampering. Ethereum, launched in 2015, leveraged the blockchain technology to augment the initial proposal of Bitcoin, enabling computational statements to be executed as part of each block validation. The platform offers a Turing-complete runtime environment (the Ethereum Virtual Machine), which can run smart contracts - scripts that verify and enforce the execution of predefined legal contracts. The technical development of smart contracts present significant challenges that are not well modeled by the current body of knowledge and practices of software engineering. In fact, some of the characteristic of blockchain make the contract execution uncontrollable by the programmer and immutable after deployment. Also, the potential security risks are considerable, since there is a large incentive to exploit vulnerabilities in a smart contract for financial gain. Considering the concerns presented above, the establishment of well understood and welldefined design patterns for the development of smart contracts is of paramount importance. In the realm of software engineering, design patterns are defined as generic and reusable solutions to common problems in software design. In the context of this work, a survey of design patterns that target the Ethereum framework was performed, with an extensive analysis regarding the context in which they can be employed, as well as implementations, examples and consequences of their use. A total of 11 design patterns were analysed. The design patterns identified for the Ethereum framework focus on several concerns specific to this platform – most of these concerns revolve around safety, upgradeability, and the limitations inherent to the sandboxed approach of the Ethereum Virtual Machine. A Decentralized Application (dApp) was created to showcase the employment of several of the identified contracts, and to highlight the value they can provide. This dApp offers a framework for decentralized betting in a trustless environment, where neither the user needs to trust the owner nor vice-versa. The dApp implements several use cases that are reliant on the identified design patterns.A invenção da Bitcoin em 2018 disponibilizou uma solução para uma moeda digital que poderia ser usada sem a necessidade de envolver terceiros para a mediação de transações. A Bitcoin recorre a uma tecnologia conhecida como blockchain, que consiste numa base de dados distribuída, assente num mecanismo de consenso resistente a alterações não acordadas. Ethereum, lançada em 2015, utiliza a mesma tecnologia da blockchain para oferecer uma plataforma que se baseia na Bitcoin, mas que também permite a execução de instruções como parte do processo de validação de cada bloco. A plataforma permite correr contratos inteligentes (smart contracts) - scripts que verificam e garantem a correta execução de um contrato predefinido. O desenvolvimento técnico de contratos inteligentes apresenta desafios significativos que não são atualmente modelados pela área de engenharia de software. De facto, algumas das caraterísticas da blockchain fazem com que a execução de contratos não seja controlável pelo programador e também com que estes contratos sejam imutáveis após serem colocados na rede principal de Ethereum. Tendo em conta os pontos anteriores, é importante o estabelecimento de padrões de desenho (design patterns) bem definidos para serem usados em contratos inteligentes. No contexto deste trabalho, foi realizada uma análise dos padrões de desenho usados em Ethereum, tendo em conta o contexto em que são utilizados, as suas implementações e exemplos da sua utilização em contratos existentes. Um total de 11 padrões de desenho foram identificados e analisados. Uma Decentralized Application (dApp) foi desenvolvida para demonstrar o emprego dos padrões de desenho identificados. Esta dApp disponibiliza uma framework para se efetuar apostas de uma forma descentralizada, em que nem o utilizador necessita de confiar no dono do contrato, nem vice-versa

Orchestration in the Cloud-to-Things compute continuum: taxonomy, survey and future directions

IoT systems are becoming an essential part of our environment. Smart cities, smart manufacturing, augmented reality, and self-driving cars are just some examples of the wide range of domains, where the applicability of such systems have been increasing rapidly. These IoT use cases often require simultaneous access to geographically distributed arrays of sensors, heterogeneous remote, local as well as multi-cloud computational resources. This gives birth to the extended Cloud-to-Things computing paradigm. The emergence of this new paradigm raised the quintessential need to extend the orchestration requirements (i.e., the automated deployment and run-time management) of applications from the centralised cloud-only environment to the entire spectrum of resources in the Cloud-to-Things continuum. In order to cope with this requirement, in the last few years, there has been a lot of attention to the development of orchestration systems in both industry and academic environments. This paper is an attempt to gather the research conducted in the orchestration for the Cloud-to-Things continuum landscape and to propose a detailed taxonomy, which is then used to critically review the landscape of existing research work. We finally discuss the key challenges that require further attention and also present a conceptual framework based on the conducted analysis

Blockchain for secured IoT and D2D applications over 5G cellular networks : a thesis by publications presented in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer and Electronics Engineering, Massey University, Albany, New Zealand

Author's Declaration: "In accordance with Sensors, SpringerOpen, and IEEE’s copyright policy, this thesis contains the accepted and published version of each manuscript as the final version. Consequently, the content is identical to the published versions."The Internet of things (IoT) is in continuous development with ever-growing popularity. It brings significant benefits through enabling humans and the physical world to interact using various technologies from small sensors to cloud computing. IoT devices and networks are appealing targets of various cyber attacks and can be hampered by malicious intervening attackers if the IoT is not appropriately protected. However, IoT security and privacy remain a major challenge due to characteristics of the IoT, such as heterogeneity, scalability, nature of the data, and operation in open environments. Moreover, many existing cloud-based solutions for IoT security rely on central remote servers over vulnerable Internet connections. The decentralized and distributed nature of blockchain technology has attracted significant attention as a suitable solution to tackle the security and privacy concerns of the IoT and device-to-device (D2D) communication. This thesis explores the possible adoption of blockchain technology to address the security and privacy challenges of the IoT under the 5G cellular system. This thesis makes four novel contributions. First, a Multi-layer Blockchain Security (MBS) model is proposed to protect IoT networks while simplifying the implementation of blockchain technology. The concept of clustering is utilized to facilitate multi-layer architecture deployment and increase scalability. The K-unknown clusters are formed within the IoT network by applying a hybrid Evolutionary Computation Algorithm using Simulated Annealing (SA) and Genetic Algorithms (GA) to structure the overlay nodes. The open-source Hyperledger Fabric (HLF) Blockchain platform is deployed for the proposed model development. Base stations adopt a global blockchain approach to communicate with each other securely. The quantitative arguments demonstrate that the proposed clustering algorithm performs well when compared to the earlier reported methods. The proposed lightweight blockchain model is also better suited to balance network latency and throughput compared to a traditional global blockchain. Next, a model is proposed to integrate IoT systems and blockchain by implementing the permissioned blockchain Hyperledger Fabric. The security of the edge computing devices is provided by employing a local authentication process. A lightweight mutual authentication and authorization solution is proposed to ensure the security of tiny IoT devices within the ecosystem. In addition, the proposed model provides traceability for the data generated by the IoT devices. The performance of the proposed model is validated with practical implementation by measuring performance metrics such as transaction throughput and latency, resource consumption, and network use. The results indicate that the proposed platform with the HLF implementation is promising for the security of resource-constrained IoT devices and is scalable for deployment in various IoT scenarios. Despite the increasing development of blockchain platforms, there is still no comprehensive method for adopting blockchain technology on IoT systems due to the blockchain's limited capability to process substantial transaction requests from a massive number of IoT devices. The Fabric comprises various components such as smart contracts, peers, endorsers, validators, committers, and Orderers. A comprehensive empirical model is proposed that measures HLF's performance and identifies potential performance bottlenecks to better meet blockchain-based IoT applications' requirements. The implementation of HLF on distributed large-scale IoT systems is proposed. The performance of the HLF is evaluated in terms of throughput, latency, network sizes, scalability, and the number of peers serviceable by the platform. The experimental results demonstrate that the proposed framework can provide a detailed and real-time performance evaluation of blockchain systems for large-scale IoT applications. The diversity and the sheer increase in the number of connected IoT devices have brought significant concerns about storing and protecting the large IoT data volume. Dependencies of the centralized server solution impose significant trust issues and make it vulnerable to security risks. A layer-based distributed data storage design and implementation of a blockchain-enabled large-scale IoT system is proposed to mitigate these challenges by using the HLF platform for distributed ledger solutions. The need for a centralized server and third-party auditor is eliminated by leveraging HLF peers who perform transaction verification and records audits in a big data system with the help of blockchain technology. The HLF blockchain facilitates storing the lightweight verification tags on the blockchain ledger. In contrast, the actual metadata is stored in the off-chain big data system to reduce the communication overheads and enhance data integrity. Finally, experiments are conducted to evaluate the performance of the proposed scheme in terms of throughput, latency, communication, and computation costs. The results indicate the feasibility of the proposed solution to retrieve and store the provenance of large-scale IoT data within the big data ecosystem using the HLF blockchain

Edge Computing for Internet of Things

The Internet-of-Things is becoming an established technology, with devices being deployed in homes, workplaces, and public areas at an increasingly rapid rate. IoT devices are the core technology of smart-homes, smart-cities, intelligent transport systems, and promise to optimise travel, reduce energy usage and improve quality of life. With the IoT prevalence, the problem of how to manage the vast volumes of data, wide variety and type of data generated, and erratic generation patterns is becoming increasingly clear and challenging. This Special Issue focuses on solving this problem through the use of edge computing. Edge computing offers a solution to managing IoT data through the processing of IoT data close to the location where the data is being generated. Edge computing allows computation to be performed locally, thus reducing the volume of data that needs to be transmitted to remote data centres and Cloud storage. It also allows decisions to be made locally without having to wait for Cloud servers to respond