Securing smart cities through blockchain technology : architecture, requirements, and challenges
- Authors: Hakak, Saqib , Khan, Wazir , Gilkar, Gulshan , Imran, Muhammad , Guizani, Nadra
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Network Vol. 34, no. 1 (2020), p. 8-14
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- Description: In recent years, unprecedented work has been done in the area of smart cities. The purpose of developing smart cities is to enhance quality of life factors for people dwelling within them. To achieve that purpose, technologies such as IoT and cloud computing have been utilized. Blockchain technology is also among the promising technologies that can offer countless valuable services to its end users. It is a immutable programmable digital register for the purpose of recording virtual assets having some value and was primarily developed for digital currencies like Bitcoin. To fully utilize the services of blockchain technology within smart cities, characteristics of blockchain technology, and its key requirements and research challenges need to be identified. Hence, in this article, an attempt has been made to identify the characteristics of blockchain technology. Furthermore, indispensable requirements for incorporating blockchain technology within smart cities are enumerated. A conceptual architecture for securing smart city using blockchain technology is proposed and explained using a possible use case study. An overview of a real-world three-blockchain- based smart city case study is also presented. Finally, several imperative research challenges are identified and discussed. © 2019 IEEE.
Wireless powering internet of things with UAVs : challenges and opportunities
- Authors: Liu, Yalin , Dai, Hong-Ning , Wang, Qubeijian , Imran, Muhammad , Guizani, Nadra
- Date: 2022
- Type: Text , Journal article , Review
- Relation: IEEE Network Vol. 36, no. 2 (2022), p. 146-152
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- Description: Unmanned aerial vehicles (UAVs) have the potential to overcome the deployment constraint of The Internet of Things (IoT) in remote or rural areas. Wirelessly powered communications (WPC) can address the battery limitation of IoT devices through transferring wireless power to IoT devices. The integration of UAVs and WPC, namely UAV-enabled wireless powering IoT (Ue-WPI-o T) can greatly extend the IoT applications from cities to remote or rural areas. In this article, we present a state-of-the-art overview of Ue-WPIoT by first illustrating the working flow of Ue-WPIoT and discussing the challenges. We then introduce the enabling technologies in realizing Ue-WPI-oT. Simulation results validate the effectiveness of the enabling technologies in Ue-WPIoT. We finally outline the future directions and open issues. © 1986-2012 IEEE.
Autonomous driving cars in smart cities : recent advances, requirements, and challenges
- Authors: Yaqoob, Ibrar , Khan, Latif , Kazmi, S. , Imran, Muhammad , Guizani, Nadra , Hong, Choong
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Network Vol. 34, no. 1 (2020), p. 174-181
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- Description: An unprecedented proliferation of autonomous driving technologies has been observed in recent years, resulting in the emergence of reliable and safe transportation services. In the foreseeable future, millions of autonomous cars will communicate with each other and become prevalent in smart cities. Thus, scalable, robust, secure, fault-tolerant, and interoperable technologies are required to support such a plethora of autonomous cars. In this article, we investigate, highlight, and report premier research advances made in autonomous driving by devising a taxonomy. A few indispensable requirements for successful deployment of autonomous cars are enumerated and discussed. Furthermore, we discover and present recent synergies and prominent case studies on autonomous driving. Finally, several imperative open research challenges are identified and discussed as future research directions. © 2019 IEEE.
Overcoming the key challenges to establishing vehicular communication : is SDN the answer?
- Authors: Yaqoob, Ibrar , Ahmad, Iftikhar , Ahmed, Ejaz , Gani, Abdullah , Imran, Muhammad , Guizani, Nadra
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Communications Magazine Vol. 55, no. 7 (2017), p. 128-135
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- Description: Considerable development in software-based configurable hardware has paved the way for a new networking paradigm called software-defined vehicular networks (SDVNs). The distinctive features of SDN, such as its flexibility and programmability, can help fulfill the performance and management requirements for VANETs. Although several studies exist on VANET and SDN, a tutorial on SDVNs is still lacking. In this article, we initially investigate recent premier research advances in the SDVN paradigm. Then we categorize and classify SDVN concepts and establish a taxonomy based on important characteristics, such as services, access technologies, network architectural components, opportunities, operational modes, and system components. Furthermore, we identify and outline the key requirements for SDVNs. Finally, we enumerate and outline future research challenges. © 2017 IEEE.
Improving cognitive ability of edge intelligent IIoT through machine learning
- Authors: Chen, Baotong , Wan, Jiafu , Lan, Yanting , Imran, Muhammad , Li, Di , Guizani, Nadra
- Date: 2019
- Type: Text , Journal article
- Relation: IEEE Network Vol. 33, no. 5 (2019), p. 61-67
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- Description: Computer-integrated manufacturing is a notable feature of Industry 4.0. Integrating machine learning (ML) into edge intelligent Industrial Internet of Things (IIoT) is a key enabling technology to achieve intelligent IIoT. To realize novel intelligent applications of edge-enhanced IIoT, ML methods are proposed to improve the cognitive ability of edge intelligent IIoT in this article. First, an ML-enabled framework of the cognitive IIoT is proposed. Second, the ML methods are presented to enhance the cognitive ability of IIoT including the ML model of IIoT, data-driven learning and reasoning, and coordination with cognitive methods. Finally, with a focus on the reconfigurable production line, a scenario-aware dynamic adaptive planning (DAP) with deep reinforcement learning (DRL) was conducted. The experimental results show that the DRL-based dynamic adaptive planning (DRL-based DAP) had good performance in an observable IIoT environment. The main purpose of this work is to point out the effects of ML-based optimization methods on the analysis of industrial IoT from the macroscopic view. © 1986-2012 IEEE.