Proportional fairness in wireless powered CSMA/CA based IoT networks

This paper considers the deployment of a hybrid wireless data/power access point in an 802.11-based wireless powered IoT network. The proportionally fair allocation of throughputs across IoT nodes is considered under the constraints of energy neutrality and CPU capability for each device. The joint optimization of wireless powering and data communication resources takes the CSMA/CA random channel access features, e.g. the backoff procedure, collisions, protocol overhead into account. Numerical results show that the optimized solution can effectively balance individual throughput across nodes, and meanwhile proportionally maximize the overall sum throughput under energy constraints.Comment: Accepted by Globecom 201

Connected OFCity Challenge: Addressing the Digital Divide in the Developing World

Over the past 50 years, the development of information and communications technology has provided unprecedented support to the steady economic growth of developed countries. In recent years, some of the largest growth has been reported in emerging economies, which, however, often lack adequate telecommunications infrastructure to further sustain their development. Although a number of service providers and system vendors have started to address the issue, the challenges they encounter are substantially different from those in the developed world, including an unreliable electricity grid, poor fiber infrastructure, low revenue expectations, and often a harsh climate environment. This paper reports use cases and solutions pertinent to the development of the networking infrastructure in emerging economies, provided by organizations directly involved in such activities. After providing some background information on the current state of network infrastructure and the main challenges for Africa and rural China, the paper provides details on two proposed solutions. The first focuses on the provisioning of services and network infrastructure through the development of low-cost data centers, whereas the second proposes cost-effective adaptation of both fiber and hybrid copper-fiber technology to rural areas. The article is concluded with a brief discussion on the complementarity of the two approaches

Explainable AI over the Internet of Things (IoT): Overview, State-of-the-Art and Future Directions

Explainable Artificial Intelligence (XAI) is transforming the field of Artificial Intelligence (AI) by enhancing the trust of end-users in machines. As the number of connected devices keeps on growing, the Internet of Things (IoT) market needs to be trustworthy for the end-users. However, existing literature still lacks a systematic and comprehensive survey work on the use of XAI for IoT. To bridge this lacking, in this paper, we address the XAI frameworks with a focus on their characteristics and support for IoT. We illustrate the widely-used XAI services for IoT applications, such as security enhancement, Internet of Medical Things (IoMT), Industrial IoT (IIoT), and Internet of City Things (IoCT). We also suggest the implementation choice of XAI models over IoT systems in these applications with appropriate examples and summarize the key inferences for future works. Moreover, we present the cutting-edge development in edge XAI structures and the support of sixth-generation (6G) communication services for IoT applications, along with key inferences. In a nutshell, this paper constitutes the first holistic compilation on the development of XAI-based frameworks tailored for the demands of future IoT use cases.Comment: 29 pages, 7 figures, 2 tables. IEEE Open Journal of the Communications Society (2022

Towards end-to-end resource provisioning in Fog Computing over Low Power Wide Area Networks

Recently, with the advent of the Internet of Things (IoT), Smart Cities have emerged as a potential business opportunity for most cloud service providers. However, centralized cloud architectures cannot sustain the requirements imposed by many IoT services. High mobility coverage and low latency constraints are among the strictest requirements, making centralized solutions impractical. In response, theoretical foundations of Fog Computing have been introduced to set up a distributed cloud infrastructure by placing computational resources close to end-users. However, the acceptance of its foundational concepts is still in its early stages. A key challenge still to answer is Service Function Chaining (SFC) in Fog Computing, in which services are connected in a specific order forming a service chain to fully leverage on network softwarization. Also, Low Power Wide Area Networks (LPWANs) have been getting significant attention. Opposed to traditional wireless technologies, LPWANs are focused on low bandwidth communications over long ranges. Despite their tremendous potential, many challenges still arise concerning the deployment and management of these technologies, making their wide adoption difficult for most service providers. In this article, a Mixed Integer Linear Programming (MILP) formulation for the IoT service allocation problem is proposed, which takes SFC concepts, different LPWAN technologies and multiple optimization objectives into account. To the best of our knowledge, our work goes beyond the current state-of-the-art by providing a complete end-to-end (E2E) resource provisioning in Fog-cloud environments while considering cloud and wireless network requirements. Evaluations have been performed to evaluate in detail the proposed MILP formulation for Smart City use cases. Results show clear trade-offs between the different provisioning strategies. Our work can serve as a benchmark for resource provisioning research in Fog-cloud environments since the model approach is generic and can be applied to a wide range of IoT use cases

Communication and Control in Collaborative UAVs: Recent Advances and Future Trends

The recent progress in unmanned aerial vehicles (UAV) technology has significantly advanced UAV-based applications for military, civil, and commercial domains. Nevertheless, the challenges of establishing high-speed communication links, flexible control strategies, and developing efficient collaborative decision-making algorithms for a swarm of UAVs limit their autonomy, robustness, and reliability. Thus, a growing focus has been witnessed on collaborative communication to allow a swarm of UAVs to coordinate and communicate autonomously for the cooperative completion of tasks in a short time with improved efficiency and reliability. This work presents a comprehensive review of collaborative communication in a multi-UAV system. We thoroughly discuss the characteristics of intelligent UAVs and their communication and control requirements for autonomous collaboration and coordination. Moreover, we review various UAV collaboration tasks, summarize the applications of UAV swarm networks for dense urban environments and present the use case scenarios to highlight the current developments of UAV-based applications in various domains. Finally, we identify several exciting future research direction that needs attention for advancing the research in collaborative UAVs