A review on orchestration distributed systems for IoT smart services in fog computing

This paper provides a review of orchestration distributed systems for IoT smart services in fog computing. The cloud infrastructure alone cannot handle the flow of information with the abundance of data, devices and interactions. Thus, fog computing becomes a new paradigm to overcome the problem. One of the first challenges was to build the orchestration systems to activate the clouds and to execute tasks throughout the whole system that has to be considered to the situation in the large scale of geographical distance, heterogeneity and low latency to support the limitation of cloud computing. Some problems exist for orchestration distributed in fog computing are to fulfil with high reliability and low-delay requirements in the IoT applications system and to form a larger computer network like a fog network, at different geographic sites. This paper reviewed approximately 68 articles on orchestration distributed system for fog computing. The result shows the orchestration distribute system and some of the evaluation criteria for fog computing that have been compared in terms of Borg, Kubernetes, Swarm, Mesos, Aurora, heterogeneity, QoS management, scalability, mobility, federation, and interoperability. The significance of this study is to support the researcher in developing orchestration distributed systems for IoT smart services in fog computing focus on IR4.0 national agend

Edge-Cloud Polarization and Collaboration: A Comprehensive Survey for AI

Influenced by the great success of deep learning via cloud computing and the rapid development of edge chips, research in artificial intelligence (AI) has shifted to both of the computing paradigms, i.e., cloud computing and edge computing. In recent years, we have witnessed significant progress in developing more advanced AI models on cloud servers that surpass traditional deep learning models owing to model innovations (e.g., Transformers, Pretrained families), explosion of training data and soaring computing capabilities. However, edge computing, especially edge and cloud collaborative computing, are still in its infancy to announce their success due to the resource-constrained IoT scenarios with very limited algorithms deployed. In this survey, we conduct a systematic review for both cloud and edge AI. Specifically, we are the first to set up the collaborative learning mechanism for cloud and edge modeling with a thorough review of the architectures that enable such mechanism. We also discuss potentials and practical experiences of some on-going advanced edge AI topics including pretraining models, graph neural networks and reinforcement learning. Finally, we discuss the promising directions and challenges in this field.Comment: 20 pages, Transactions on Knowledge and Data Engineerin

Improving the Reliability of Optimised Link State Routing Protocol in Smart Grid’s Neighbour Area Network

A reliable and resilient communication infrastructure that can cope with variable application traffic types and delay objectives is one of the prerequisites that differentiates a Smart Grid from the conventional electrical grid. However, the legacy communication infrastructure in the existing electrical grid is insufficient, if not incapable of satisfying the diverse communication requirements of the Smart Grid. The IEEE 802.11 ad hoc Wireless Mesh Network (WMN) is re-emerging as one of the communication networks that can significantly extend the reach of Smart Grid to backend devices through the Advanced Metering Infrastructure (AMI). However, the unique characteristics of AMI application traffic in the Smart Grid poses some interesting challenges to conventional communication networks including the ad hoc WMN. Hence, there is a need to modify the conventional ad hoc WMN, to address the uncertainties that may exist in its applicability in a Smart Grid environment. This research carries out an in-depth study of the communication of Smart Grid application traffic types over ad hoc WMN deployed in the Neighbour Area Network (NAN). It begins by conducting a critical review of the application characteristics and traffic requirements of several Smart Grid applications and highlighting some key challenges. Based on the reviews, and assuming that the application traffic types use the internet protocol (IP) as a transport protocol, a number of Smart Grid application traffic profiles were developed. Through experimental and simulation studies, a performance evaluation of an ad hoc WMN using the Optimised Link State Routing (OLSR) routing protocol was carried out. This highlighted some capacity and reliability issues that routing AMI application traffic may face within a conventional ad hoc WMN in a Smart Grid NAN. Given the fact that conventional routing solutions do not consider the traffic requirements when making routing decisions, another key observation is the inability of link metrics in routing protocols to select good quality links across multiple hops to a destination and also provide Quality of Service (QoS) support for target application traffic. As with most routing protocols, OLSR protocol uses a single routing metric acquired at the network layer, which may not be able to accommodate different QoS requirements for application traffic in Smart Grid. To address these problems, a novel multiple link metrics approach to improve the reliability performance of routing in ad hoc WMN when deployed for Smart Grid is presented. It is based on the OLSR protocol and explores the possibility of applying QoS routing for application traffic types in NAN based ad hoc WMN. Though routing in multiple metrics has been identified as a complex problem, Multi-Criteria Decision Making (MCDM) techniques such as the Analytical Hierarchy Process (AHP) and pruning have been used to perform such routing on wired and wireless multimedia applications. The proposed multiple metrics OLSR with AHP is used to offer the best available route, based on a number of considered metric parameters. To accommodate the variable application traffic requirements, a study that allows application traffic to use the most appropriate routing metric is presented. The multiple metrics development is then evaluated in Network Simulator 2.34; the simulation results demonstrate that it outperforms existing routing methods that are based on single metrics in OLSR. It also shows that it can be used to improve the reliability of application traffic types, thereby overcoming some weaknesses of existing single metric routing across multiple hops in NAN. The IEEE 802.11g was used to compare and analyse the performance of OLSR and the IEEE 802.11b was used to implement the multiple metrics framework which demonstrate a better performance than the single metric. However, the multiple metrics can also be applied for routing on different IEEE wireless standards, as well as other communication technologies such as Power Line Communication (PLC) when deployed in Smart Grid NAN

Toward Software-Defined Networking-Based IoT Frameworks: A Systematic Literature Review, Taxonomy, Open Challenges and Prospects

Internet of Things (IoT) is characterized as one of the leading actors for the next evolutionary stage in the computing world. IoT-based applications have already produced a plethora of novel services and are improving the living standard by enabling innovative and smart solutions. However, along with its rapid adoption, IoT technology also creates complex challenges regarding the management of IoT networks due to its resource limitations (computational power, energy, and security). Hence, it is urgently needed to refine the IoT-based application’s architectures to robustly manage the overall IoT infrastructure. Software-defined networking (SDN) has emerged as a paradigm that offers software-based controllers to manage hardware infrastructure and traffic flow on a network effectively. SDN architecture has the potential to provide efficient and reliable IoT network management. This research provides a comprehensive survey investigating the published studies on SDN-based frameworks to address IoT management issues in the dimensions of fault tolerance, energy management, scalability, load balancing, and security service provisioning within the IoT networks. We conducted a Systematic Literature Review (SLR) on the research studies (published from 2010 to 2022) focusing on SDN-based IoT management frameworks. We provide an extensive discussion on various aspects of SDN-based IoT solutions and architectures. We elaborate a taxonomy of the existing SDN-based IoT frameworks and solutions by classifying them into categories such as network function virtualization, middleware, OpenFlow adaptation, and blockchain-based management. We present the research gaps by identifying and analyzing the key architectural requirements and management issues in IoT infrastructures. Finally, we highlight various challenges and a range of promising opportunities for future research to provide a roadmap for addressing the weaknesses and identifying the benefits from the potentials offered by SDN-based IoT solutions

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Sensor Networks and Their Applications: Investigating the Role of Sensor Web Enablement

The Engineering Doctorate (EngD) was conducted in conjunction with BT Research on state-of-the-art Wireless Sensor Network (WSN) projects. The first area of work is a literature review of WSN project applications, some of which the author worked on as a BT Researcher based at the world renowned Adastral Park Research Labs in Suffolk (2004-09). WSN applications are examined within the context of Machine-to-Machine (M2M); Information Networking (IN); Internet/Web of Things (IoT/WoT); smart home and smart devices; BT’s 21st Century Network (21CN); Cloud Computing; and future trends. In addition, this thesis provides an insight into the capabilities of similar external WSN project applications. Under BT’s Sensor Virtualization project, the second area of work focuses on building a Generic Architecture for WSNs with reusable infrastructure and ‘infostructure’ by identifying and trialling suitable components, in order to realise actual business benefits for BT. The third area of work focuses on the Open Geospatial Consortium (OGC) standards and their Sensor Web Enablement (SWE) initiative. The SWE framework was investigated to ascertain its potential as a component of the Generic Architecture. BT’s SAPHE project served as a use case. BT Research’s experiences of taking this traditional (vertical) stove-piped application and creating SWE compliant services are described. The author’s findings were originally presented in a series of publications and have been incorporated into this thesis along with supplementary WSN material from BT Research projects. SWE 2.0 specifications are outlined to highlight key improvements, since work began at BT with SWE 1.0. The fourth area of work focuses on Complex Event Processing (CEP) which was evaluated to ascertain its potential for aggregating and correlating the shared project sensor data (‘infostructure’) harvested and for enabling data fusion for WSNs in diverse domains. Finally, the conclusions and suggestions for further work are provided

Edge AI for Internet of Energy: Challenges and Perspectives

The digital landscape of the Internet of Energy (IoE) is on the brink of a revolutionary transformation with the integration of edge Artificial Intelligence (AI). This comprehensive review elucidates the promise and potential that edge AI holds for reshaping the IoE ecosystem. Commencing with a meticulously curated research methodology, the article delves into the myriad of edge AI techniques specifically tailored for IoE. The myriad benefits, spanning from reduced latency and real-time analytics to the pivotal aspects of information security, scalability, and cost-efficiency, underscore the indispensability of edge AI in modern IoE frameworks. As the narrative progresses, readers are acquainted with pragmatic applications and techniques, highlighting on-device computation, secure private inference methods, and the avant-garde paradigms of AI training on the edge. A critical analysis follows, offering a deep dive into the present challenges including security concerns, computational hurdles, and standardization issues. However, as the horizon of technology ever expands, the review culminates in a forward-looking perspective, envisaging the future symbiosis of 5G networks, federated edge AI, deep reinforcement learning, and more, painting a vibrant panorama of what the future beholds. For anyone vested in the domains of IoE and AI, this review offers both a foundation and a visionary lens, bridging the present realities with future possibilities

Building the Future Internet through FIRE

The Internet as we know it today is the result of a continuous activity for improving network communications, end user services, computational processes and also information technology infrastructures. The Internet has become a critical infrastructure for the human-being by offering complex networking services and end-user applications that all together have transformed all aspects, mainly economical, of our lives. Recently, with the advent of new paradigms and the progress in wireless technology, sensor networks and information systems and also the inexorable shift towards everything connected paradigm, first as known as the Internet of Things and lately envisioning into the Internet of Everything, a data-driven society has been created. In a data-driven society, productivity, knowledge, and experience are dependent on increasingly open, dynamic, interdependent and complex Internet services. The challenge for the Internet of the Future design is to build robust enabling technologies, implement and deploy adaptive systems, to create business opportunities considering increasing uncertainties and emergent systemic behaviors where humans and machines seamlessly cooperate

Empowering the 6G Cellular Architecture with Open RAN

Innovation and standardization in 5G have brought advancements to every facet of the cellular architecture. This ranges from the introduction of new frequency bands and signaling technologies for the radio access network (RAN), to a core network underpinned by micro-services and network function virtualization (NFV). However, like any emerging technology, the pace of real-world deployments does not instantly match the pace of innovation. To address this discrepancy, one of the key aspects under continuous development is the RAN with the aim of making it more open, adaptive, functional, and easy to manage. In this paper, we highlight the transformative potential of embracing novel cellular architectures by transitioning from conventional systems to the progressive principles of Open RAN. This promises to make 6G networks more agile, cost-effective, energy-efficient, and resilient. It opens up a plethora of novel use cases, ranging from ubiquitous support for autonomous devices to cost-effective expansions in regions previously underserved. The principles of Open RAN encompass: (i) a disaggregated architecture with modular and standardized interfaces; (ii) cloudification, programmability and orchestration; and (iii) AI-enabled data-centric closed-loop control and automation. We first discuss the transformative role Open RAN principles have played in the 5G era. Then, we adopt a system-level approach and describe how these Open RAN principles will support 6G RAN and architecture innovation. We qualitatively discuss potential performance gains that Open RAN principles yield for specific 6G use cases. For each principle, we outline the steps that research, development and standardization communities ought to take to make Open RAN principles central to next-generation cellular network designs.Comment: This paper is part of the IEEE JSAC SI on Open RAN. Please cite as: M. Polese, M. Dohler, F. Dressler, M. Erol-Kantarci, R. Jana, R. Knopp, T. Melodia, "Empowering the 6G Cellular Architecture with Open RAN," in IEEE Journal on Selected Areas in Communications, doi: 10.1109/JSAC.2023.333461