Enabling Communication Technologies for Automated Unmanned Vehicles in Industry 4.0

Within the context of Industry 4.0, mobile robot systems such as automated guided vehicles (AGVs) and unmanned aerial vehicles (UAVs) are one of the major areas challenging current communication and localization technologies. Due to stringent requirements on latency and reliability, several of the existing solutions are not capable of meeting the performance required by industrial automation applications. Additionally, the disparity in types and applications of unmanned vehicle (UV) calls for more flexible communication technologies in order to address their specific requirements. In this paper, we propose several use cases for UVs within the context of Industry 4.0 and consider their respective requirements. We also identify wireless technologies that support the deployment of UVs as envisioned in Industry 4.0 scenarios.Comment: 7 pages, 1 figure, 1 tabl

Role of artificial intelligence in cloud computing, IoT and SDN: Reliability and scalability issues

Information technology fields are now more dominated by artificial intelligence, as it is playing a key role in terms of providing better services. The inherent strengths of artificial intelligence are driving the companies into a modern, decisive, secure, and insight-driven arena to address the current and future challenges. The key technologies like cloud, internet of things (IoT), and software-defined networking (SDN) are emerging as future applications and rendering benefits to the society. Integrating artificial intelligence with these innovations with scalability brings beneficiaries to the next level of efficiency. Data generated from the heterogeneous devices are received, exchanged, stored, managed, and analyzed to automate and improve the performance of the overall system and be more reliable. Although these new technologies are not free of their limitations, nevertheless, the synthesis of technologies has been challenged and has put forth many challenges in terms of scalability and reliability. Therefore, this paper discusses the role of artificial intelligence (AI) along with issues and opportunities confronting all communities for incorporating the integration of these technologies in terms of reliability and scalability. This paper puts forward the future directions related to scalability and reliability concerns during the integration of the above-mentioned technologies and enable the researchers to address the current research gaps

On the Integration of Blockchain and SDN: Overview, Applications, and Future Perspectives

Blockchain (BC) and software-defined networking (SDN) are leading technologies which have recently found applications in several network-related scenarios and have consequently experienced a growing interest in the research community. Indeed, current networks connect a massive number of objects over the Internet and in this complex scenario, to ensure security, privacy, confidentiality, and programmability, the utilization of BC and SDN have been successfully proposed. In this work, we provide a comprehensive survey regarding these two recent research trends and review the related state-of-the-art literature. We first describe the main features of each technology and discuss their most common and used variants. Furthermore, we envision the integration of such technologies to jointly take advantage of these latter efficiently. Indeed, we consider their group-wise utilization—named BC–SDN—based on the need for stronger security and privacy. Additionally, we cover the application fields of these technologies both individually and combined. Finally, we discuss the open issues of reviewed research and describe potential directions for future avenues regarding the integration of BC and SDN. To summarize, the contribution of the present survey spans from an overview of the literature background on BC and SDN to the discussion of the benefits and limitations of BC–SDN integration in different fields, which also raises open challenges and possible future avenues examined herein. To the best of our knowledge, compared to existing surveys, this is the first work that analyzes the aforementioned aspects in light of a broad BC–SDN integration, with a specific focus on security and privacy issues in actual utilization scenarios

Intrusion Detection Framework for Industrial Internet of Things Using Software Defined Network

The Industrial Internet of Things (IIoT) refers to the employment of the Internet of Things in industrial management, where a substantial number of machines and devices are linked and synchronized with the help of software programs and third platforms to improve the overall productivity. The acquisition of the industrial IoT provides benefits that range from automation and optimization to eliminating manual processes and improving overall efficiencies, but security remains to be forethought. The absence of reliable security mechanisms and the magnitude of security features are significant obstacles to enhancing IIoT security. Over the last few years, alarming attacks have been witnessed utilizing the vulnerabilities of the IIoT network devices. Moreover, the attackers can also sink deep into the network by using the relationships amidst the vulnerabilities. Such network security threats cause industries and businesses to suffer financial losses, reputational damage, and theft of important information. This paper proposes an SDN-based framework using machine learning techniques for intrusion detection in an industrial IoT environment. SDN is an approach that enables the network to be centrally and intelligently controlled through software applications. In our framework, the SDN controller employs a machine-learning algorithm to monitor the behavior of industrial IoT devices and networks by analyzing traffic flow data and ultimately determining the flow rules for SDN switches. We use SVM and Decision Tree classification models to analyze our framework’s network intrusion and attack detection performance. The results indicate that the proposed framework can detect attacks in industrial IoT networks and devices with an accuracy of 99.7%

Single-Board-Computer Clusters for Cloudlet Computing in Internet of Things

The number of connected sensors and devices is expected to increase to billions in the near future. However, centralised cloud-computing data centres present various challenges to meet the requirements inherent to Internet of Things (IoT) workloads, such as low latency, high throughput and bandwidth constraints. Edge computing is becoming the standard computing paradigm for latency-sensitive real-time IoT workloads, since it addresses the aforementioned limitations related to centralised cloud-computing models. Such a paradigm relies on bringing computation close to the source of data, which presents serious operational challenges for large-scale cloud-computing providers. In this work, we present an architecture composed of low-cost Single-Board-Computer clusters near to data sources, and centralised cloud-computing data centres. The proposed cost-efficient model may be employed as an alternative to fog computing to meet real-time IoT workload requirements while keeping scalability. We include an extensive empirical analysis to assess the suitability of single-board-computer clusters as cost-effective edge-computing micro data centres. Additionally, we compare the proposed architecture with traditional cloudlet and cloud architectures, and evaluate them through extensive simulation. We finally show that acquisition costs can be drastically reduced while keeping performance levels in data-intensive IoT use cases.Ministerio de Economía y Competitividad TIN2017-82113-C2-1-RMinisterio de Economía y Competitividad RTI2018-098062-A-I00European Union’s Horizon 2020 No. 754489Science Foundation Ireland grant 13/RC/209

On the Integration of Blockchain and SDN: Overview, Applications, and Future Perspectives

Blockchain (BC) and Software-Defined Networking (SDN) are leading technologies which have recently found applications in several network-related scenarios and have consequently experienced a growing interest in the research community. Indeed, current networks connect a massive number of objects over the Internet and in this complex scenario, to ensure security, privacy, confidentiality, and programmability, the utilization of BC and SDN have been successfully proposed. In this work, we provide a comprehensive survey regarding these two recent research trends and review the related state-of-the-art literature. We first describe the main features of each technology and discuss their most common and used variants. Furthermore, we envision the integration of such technologies to jointly take advantage of these latter efficiently. Indeed, we consider their group-wise utilization -- named BC-SDN -- based on the need for stronger security and privacy. Additionally, we cover the application fields of these technologies both individually and combined. Finally, we discuss the open issues of reviewed research and describe potential directions for future avenues regarding the integration of BC and SDN. To summarize, the contribution of the present survey spans from an overview of the literature background on BC and SDN to the discussion of the benefits and limitations of BC-SDN integration in different fields, which also raises open challenges and possible future avenues examined herein. To the best of our knowledge, compared to existing surveys, this is the first work that analyzes the aforementioned aspects in light of a broad BC-SDN integration, with a specific focus on security and privacy issues in actual utilization scenarios.Comment: 42 pages, 14 figures, to be published in Journal of Network and Systems Management - Special Issue on Blockchains and Distributed Ledgers in Network and Service Managemen