6G wireless systems : a vision, architectural elements, and future directions
- Authors: Khan, Latif , Yaqoob, Ibrar , Imran, Muhammad , Han, Zhu , Hong, Choong
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 147029-147044
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- Description: Internet of everything (IoE)-based smart services are expected to gain immense popularity in the future, which raises the need for next-generation wireless networks. Although fifth-generation (5G) networks can support various IoE services, they might not be able to completely fulfill the requirements of novel applications. Sixth-generation (6G) wireless systems are envisioned to overcome 5G network limitations. In this article, we explore recent advances made toward enabling 6G systems. We devise a taxonomy based on key enabling technologies, use cases, emerging machine learning schemes, communication technologies, networking technologies, and computing technologies. Furthermore, we identify and discuss open research challenges, such as artificial-intelligence-based adaptive transceivers, intelligent wireless energy harvesting, decentralized and secure business models, intelligent cell-less architecture, and distributed security models. We propose practical guidelines including deep Q-learning and federated learning-based transceivers, blockchain-based secure business models, homomorphic encryption, and distributed-ledger-based authentication schemes to cope with these challenges. Finally, we outline and recommend several future directions. © 2013 IEEE.
A novel countermeasure technique for reactive jamming attack in internet of things
- Authors: Fadele, Alaba , Othman, Mazliza , Hashem, Ibrahim , Yaqoob, Ibrar , Imran, Muhammad , Shoaib, Muhammad
- Date: 2019
- Type: Text , Journal article
- Relation: Multimedia Tools and Applications Vol. 78, no. 21 (2019), p. 29899-29920
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- Description: In recent years, Internet of Things (IoT) has attracted significant attention because of its wide range of applications in various domains. However, security is a growing concern as users of small devices in an IoT network are unable to defend themselves against reactive jamming attacks. These attacks negatively affect the performance of devices and hinder IoT operations. To address such an issue, this paper presents a novel countermeasure detection and consistency algorithm (CDCA), which aims to fight reactive jamming attacks on IoT networks. The proposed CDCA uses a change in threshold value to detect and treat an attack. The algorithm employs channel signal strength to check packet consistency by determining if the data transmission value contradicts the threshold value. The node that sends the threshold value is periodically checked and the threshold value is compared with the current value after data transmission to find out if an attack has occurred in the network. Based on realistic simulation scenarios (e.g., with varying traffic interval, number of malicious nodes, and random mobility patterns), the performance of the proposed CDCA is evaluated using a Cooja simulator. Simulation results demonstrate the superiority of the proposed technique compared with contemporary schemes in terms of performance metrics such as energy consumption, traffic delay, and network throughput. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.
An application development framework for internet-of-things service orchestration
- Authors: Rafique, Wajid , Zhao, Xuan , Yu, Shui , Yaqoob, Ibrar , Imran, Muhammad , Dou, Wanchun
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Internet of Things Journal Vol. 7, no. 5 (2020), p. 4543-4556
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- Description: Application development for the Internet of Things (IoT) poses immense challenges due to the lack of standard development frameworks, tools, and techniques to assist end users in dealing with the complexity of IoT systems during application development. These challenges invoke the use of model-driven development (MDD) along with the representational state transfer (REST) architecture to develop IoT applications, supporting model generation at different abstraction levels while generating software implementation artifacts for heterogeneous platforms and ensuring loose coupling in complex IoT systems. This article proposes an IoT application development framework, named IADev, which uses attribute-driven design and MDD to address the above-mentioned challenges. This framework is composed of two major steps, including iterative architecture development using attribute-driven design and generating models to guide the transformation using MDD. IADev uses attribute-driven design to transform the requirements into a solution architecture by considering the concerns of all involved stakeholders, and then, MDD metamodels are generated to hierarchically transform the design components into the software artifacts. We evaluate IADev for a smart vehicle scenario in an intelligent transportation system to generate an executable implementation code for a real-world system. The case study experiments proclaim that IADev achieves higher satisfaction of the participants for the IoT application development and service orchestration, as compared to conventional approaches. Finally, we propose an architecture that uses IADev with the Siemens IoT cloud platform for service orchestration in industrial IoT. © 2014 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.
Big data analytics in industrial IoT using a concentric computing model
- Authors: Rehman, Muhammad , Ahmed, Ejaz , Yaqoob, Ibrar , Hashem, Ibrahim , Imran, Muhammad , Ahmad, Shafiq
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Communications Magazine Vol. 56, no. 2 (2018), p. 37-43
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- Description: The unprecedented proliferation of miniaturized sensors and intelligent communication, computing, and control technologies have paved the way for the development of the Industrial Internet of Things. The IIoT incorporates machine learning and massively parallel distributed systems such as clouds, clusters, and grids for big data storage, processing, and analytics. In IIoT, end devices continuously generate and transmit data streams, resulting in increased network traffic between device-cloud communication. Moreover, it increases in-network data transmissions. requiring additional efforts for big data processing, management, and analytics. To cope with these engendered issues, this article first introduces a novel concentric computing model (CCM) paradigm composed of sensing systems, outer and inner gateway processors, and central processors (outer and inner) for the deployment of big data analytics applications in IIoT. Second, we investigate, highlight, and report recent research efforts directed at the IIoT paradigm with respect to big data analytics. Third, we identify and discuss indispensable challenges that remain to be addressed for employing CCM in the IIoT paradigm. Lastly, we provide several future research directions (e.g., real-Time data analytics, data integration, transmission of meaningful data, edge analytics, real-Time fusion of streaming data, and security and privacy). © 1979-2012 IEEE.
Blockchain for digital twins : recent advances and future research challenges
- Authors: Yaqoob, Ibrar , Salah, Khaled , Uddin, Mueen , Jayaraman, Raja , Omar, Mohammed , Imran, Muhammad
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Network Vol. 34, no. 5 (2020), p. 290-298
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- Description: The advent of blockchain technology can refine the concept of DTs by ensuring transparency, decentralized data storage, data immutability, and peer-to-peer communication in industrial sectors. A DT is an integrated multiphysics, multiscale, and probabilistic simulation, representation, and mirroring of a real-world physical component. The DTs help to visualize designs in 3D, perform tests and simulations virtually prior to creation of any physical component, and consequently play a vital role in sustaining and maintaining Industry 4.0. It is anticipated that DTs will become prevalent in the foreseeable future because they can be used for configuration, monitoring, diagnostics, and prognostics. This article envisages how blockchain can reshape and transform DTs to bring about secure manufacturing that guarantees traceability, compliance, authenticity, quality, and safety. We discuss several benefits of employing blockchain in DTs. We taxonomize the DTs literature based on key parameters (e.g., DTs levels, design phases, industrial use cases, key objectives, enabling technologies, and core applications). We provide insights into ongoing progress made towards DTs by presenting recent synergies and case studies. Finally, we discuss open challenges that serve as future research directions. © 1986-2012 IEEE.
Bringing Computation Closer toward the User Network: Is Edge Computing the Solution?
- Authors: Ahmed, Ejaz , Ahmed, Arif , Yaqoob, Ibrar , Shuja, Junaid , Imran, Muhammad
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Communications Magazine Vol. 55, no. 11 (2017), p. 138-144
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- Description: The virtually unlimited available resources and wide range of services provided by the cloud have resulted in the emergence of new cloud-based applications, such as smart grids, smart building control, and virtual reality. These developments, however, have also been accompanied by a problem for delay-sensitive applications that have stringent delay requirements. The current cloud computing paradigm cannot realize the requirements of mobility support, location awareness, and low latency. Hence, to address the problem, an edge computing paradigm that aims to extend the cloud resources and services and enable them to be nearer the edge of an enterprise's network has been introduced. In this article, we highlight the significance of edge computing by providing real-life scenarios that have strict constraint requirements on application response time. From the previous literature, we devise a taxonomy to classify the current research efforts in the domain of edge computing. We also discuss the key requirements that enable edge computing. Finally, current challenges in realizing the vision of edge computing are discussed. © 1979-2012 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “ Muhammad Imran” is provided in this record**
Channel clustering and QoS level identification scheme for multi-channel cognitive radio networks
- Authors: Ali, Amjad , Yaqoob, Ibrar , Ahmed, Adnan , Imran, Muhammad , Kwak, Kyung
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Communications Magazine Vol. 56, no. 4 (2018), p. 164-171
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- Description: The increasing popularity of wireless services and devices necessitates high bandwidth requirements; however, spectrum resources are not only limited but also heavily underutilized. Multiple license channels that support the same levels of QoS are desirable to resolve the problems posed by the scarcity and inefficient use of spectrum resources in multi-channel cognitive radio networks (MCRNs). One reason is that multimedia services and applications have distinct, stringent QoS requirements. However, due to a lack of coordination between primary and secondary users, identifying the QoS levels supported over available licensed channels has proven to be problematic and has yet to be attempted. This article presents a novel Bayesian non-parametric channel clustering scheme, which identifies the QoS levels supported over available license channels. The proposed scheme employs the infinite Gaussian mixture model and collapsed Gibbs sampler to identify the QoS levels from the feature space of the bit rate, packet delivery ratio, and packet delay variation of licensed channels. Moreover, the real measurements of wireless data traces and comparisons with baseline clustering schemes are used to evaluate the performance of the proposed scheme. © 1979-2012 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**
Complementing IoT services through software defined networking and edge computing : a comprehensive survey
- Authors: Rafique, Wajid , Qi, Lianyong , Yaqoob, Ibrar , Imran, Muhammad , Rasool, Raojan , Dou, Wanchun
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Communications Surveys and Tutorials Vol. 22, no. 3 (2020), p. 1761-1804
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- Description: Millions of sensors continuously produce and transmit data to control real-world infrastructures using complex networks in the Internet of Things (IoT). However, IoT devices are limited in computational power, including storage, processing, and communication resources, to effectively perform compute-intensive tasks locally. Edge computing resolves the resource limitation problems by bringing computation closer to the edge of IoT devices. Providing distributed edge nodes across the network reduces the stress of centralized computation and overcomes latency challenges in the IoT. Therefore, edge computing presents low-cost solutions for compute-intensive tasks. Software-Defined Networking (SDN) enables effective network management by presenting a global perspective of the network. While SDN was not explicitly developed for IoT challenges, it can, however, provide impetus to solve the complexity issues and help in efficient IoT service orchestration. The current IoT paradigm of massive data generation, complex infrastructures, security vulnerabilities, and requirements from the newly developed technologies make IoT realization a challenging issue. In this research, we provide an extensive survey on SDN and the edge computing ecosystem to solve the challenge of complex IoT management. We present the latest research on Software-Defined Internet of Things orchestration using Edge (SDIoT-Edge) and highlight key requirements and standardization efforts in integrating these diverse architectures. An extensive discussion on different case studies using SDIoT-Edge computing is presented to envision the underlying concept. Furthermore, we classify state-of-the-art research in the SDIoT-Edge ecosystem based on multiple performance parameters. We comprehensively present security and privacy vulnerabilities in the SDIoT-Edge computing and provide detailed taxonomies of multiple attack possibilities in this paradigm. We highlight the lessons learned based on our findings at the end of each section. Finally, we discuss critical insights toward current research issues, challenges, and further research directions to efficiently provide IoT services in the SDIoT-Edge paradigm. © 1998-2012 IEEE.
Green industrial networking : recent advances, taxonomy, and open research challenges
- Authors: Ahmed, Ejaz , Yaqoob, Ibrar , Ahmed, Ahmed , Gani, Abdullah , Imran, Muhammad , Guizani, Sghaier
- Date: 2016
- Type: Text , Journal article
- Relation: IEEE Communications Magazine Vol. 54, no. 10 (2016), p. 38-45
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- Description: The consciousness of environmental problems has attracted the industry's attention toward the reduction of unnecessary energy emission by enabling green industrial networking. The reduction of unnecessary energy emitted by industrial networks can be a possible solution to many environmental issues. Green industrial networking is in its infancy, and an overview of the domain is still lacking. In this article, we discuss recent advances in industrial and green networking paradigms to investigate the impact on global communities. We also classify the literature by devising a taxonomy based on networking technologies, machines, network types, topologies, field bus types, transmission media, and hierarchical levels. Moreover, we identify and discuss key enablers (adaptive links, resource-based energy conservation, energy-efficient scheduling, energy-aware systems, energy-aware proxying, energy-conservative approaches, and low-power wireless protocols) for green industrial networking. Furthermore, we discuss challenges that remain to be addressed as future research directions. © 2016 IEEE.
Heterogeneity-aware task allocation in mobile ad hoc cloud
- Authors: Yaqoob, Ibrar , Ahmed, Ejaz , Gani, Abdullah , Mokhtar, Salimah , Imran, Muhammad
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Access Vol. 5, no. (2017), p. 1779-1795
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- Description: Mobile Ad Hoc Cloud (MAC) enables the use of a multitude of proximate resource-rich mobile devices to provide computational services in the vicinity. However, inattention to mobile device resources and operational heterogeneity-measuring parameters, such as CPU speed, number of cores, and workload, when allocating task in MAC, causes inefficient resource utilization that prolongs task execution time and consumes large amounts of energy. Task execution is remarkably degraded, because the longer execution time and high energy consumption impede the optimum use of MAC. This paper aims to minimize execution time and energy consumption by proposing heterogeneity-aware task allocation solutions for MAC-based compute-intensive tasks. Results of the proposed solutions reveal that incorporation of the heterogeneity-measuring parameters guarantees a shorter execution time and reduces the energy consumption of the compute-intensive tasks in MAC. A system model is developed to validate the proposed solutions' empirical results. In comparison with random-based task allocation, the proposed five solutions based on CPU speed, number of core, workload, CPU speed and workload, and CPU speed, core, and workload reduce execution time up to 56.72%, 53.12%, 56.97%, 61.23%, and 71.55%, respectively. In addition, these heterogeneity-aware task allocation solutions save energy up to 69.78%, 69.06%, 68.25%, 67.26%, and 57.33%, respectively. For this reason, the proposed solutions significantly improve tasks' execution performance, which can increase the optimum use of MAC. © 2013 IEEE.
Internet of things architecture : recent advances, taxonomy, requirements, and open challenges
- Authors: Yaqoob, Ibrar , Ahmed, Ejaz , Hashem, Ibrahim , Ahmed, Abdelmuttlib , Gani, Abdullah , Imran, Muhammad , Guizani, Mohsen
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Wireless Communications Vol. 24, no. 3 (2017), p. 10-16
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- Description: Recent years have witnessed tremendous growth in the number of smart devices, wireless technologies, and sensors. In the foreseeable future, it is expected that trillions of devices will be connected to the Internet. Thus, to accommodate such a voluminous number of devices, scalable, flexible, interoperable, energy-efficient, and secure network architectures are required. This article aims to explore IoT architectures. In this context, first, we investigate, highlight, and report premier research advances made in IoT architecture recently. Then we categorize and classify IoT architectures and devise a taxonomy based on important parameters such as applications, enabling technologies, business objectives, architectural requirements, network topologies, and IoT platform architecture types. We identify and outline the key requirements for future IoT architecture. A few prominent case studies on IoT are discovered and presented. Finally, we enumerate and outline future research challenges. © 2002-2012 IEEE.
Internet-of-things-based smart cities : recent advances and challenges
- Authors: Mehmood, Yasir , Ahmad, Farhan , Yaqoob, Ibrar , Adnane, Asma , Imran, Muhammad , Guizani, Sghaier
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Communications Magazine Vol. 55, no. 9 (2017), p. 16-24
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- Description: The Internet of Things is a novel cutting edge technology that proffers to connect a plethora of digital devices endowed with several sensing, actuation, and computing capabilities with the Internet, thus offering manifold new services in the context of a smart city. The appealing IoT services and big data analytics are enabling smart city initiatives all over the world. These services are transforming cities by improving infrastructure and transportation systems, reducing traffic congestion, providing waste management, and improving the quality of human life. In this article, we devise a taxonomy to best bring forth a generic overview of the IoT paradigm for smart cities, integrated ICT, network types, possible opportunities and major requirements. Moreover, an overview of the up-to-date efforts from standard bodies is presented. Later, we give an overview of existing open source IoT platforms for realizing smart city applications followed by several exemplary case studies. In addition, we summarize the latest synergies and initiatives worldwide taken to promote IoT in the context of smart cities. Finally, we highlight several challenges in order to give future research directions. © 1979-2012 IEEE.
Internet-of-things-based smart environments : state of the art, taxonomy, and open research challenges
- Authors: Ahmed, Ejaz , Yaqoob, Ibrar , Gani, Abdullah , Imran, Muhammad , Guizani, Mohsen
- Date: 2016
- Type: Text , Journal article
- Relation: IEEE Wireless Communications Vol. 23, no. 5 (2016), p. 10-16
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- Description: The rapid advancements in communication technologies and the explosive growth of the Internet of Things have enabled the physical world to invisibly interweave with actuators, sensors, and other computational elements while maintaining continuous network connectivity. The continuously connected physical world with computational elements forms a smart environment. A smart environment aims to support and enhance the abilities of its dwellers in executing their tasks, such as navigating through unfamiliar space and moving heavy objects for the elderly, to name a few. Researchers have conducted a number of efforts to use IoT to facilitate our lives and to investigate the effect of IoT-based smart environments on human life. This article surveys the state-of-the-art research efforts to enable IoT-based smart environments. We categorize and classify the literature by devising a taxonomy based on communication enablers, network types, technologies, local area wireless standards, objectives, and characteristics. Moreover, the article highlights the unprecedented opportunities brought about by IoT-based smart environments and their effect on human life. Some reported case studies from different enterprises are also presented. Finally, we discuss open research challenges for enabling IoT-based smart environments. © 2016 IEEE.
Managing big RDF data in clouds : challenges, opportunities, and solutions
- Authors: Elzein, Nahla , Majid, Mazlina , Hashem, Ibaker , Yaqoob, Ibrar , Alaba, Fadele , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: Sustainable Cities and Society Vol. 39, no. (2018), p. 375-386
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- Description: The expansion of the services of the Semantic Web and the evolution of cloud computing technologies have significantly enhanced the capability of preserving and publishing information in standard open web formats, such that data can be both human-readable and machine-processable. This situation meets the challenge in the current big data era to effectively store, retrieve, and analyze resource description framework (RDF) data in swarms. This paper presents an overview of the existing challenges, evolving opportunities, and current developments towards managing big RDF data in clouds and provides guidance and substantial lessons learned from research in big data management. In particular, it highlights the basic principles of RDF data management, which allow researchers to know the most recent stage in developing RDF graphs and its achievement. Additionally, the research provides comparative studies among current storage systems and query processing approaches in understanding their efficiency. The paper also provides a vision for long-term future research directions by providing highlights on future challenges and opportunities in RDF domain. © 2018 Elsevier Ltd
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.
Process migration-based computational offloading framework for IoT-supported mobile edge/cloud computing
- Authors: Yousafzai, Abdullah , Yaqoob, Ibrar , Imran, Muhammad , Gani, Abdullah , Md Noor, Rafidah
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Internet of Things Journal Vol. 7, no. 5 (2020), p. 4171-4182
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- Description: Mobile devices have become an indispensable component of Internet of Things (IoT). However, these devices have resource constraints in processing capabilities, battery power, and storage space, thus hindering the execution of computation-intensive applications that often require broad bandwidth, stringent response time, long-battery life, and heavy-computing power. Mobile cloud computing and mobile edge computing (MEC) are emerging technologies that can meet the aforementioned requirements using offloading algorithms. In this article, we analyze the effect of platform-dependent native applications on computational offloading in edge networks and propose a lightweight process migration-based computational offloading framework. The proposed framework does not require application binaries at edge servers and thus seamlessly migrates native applications. The proposed framework is evaluated using an experimental testbed. Numerical results reveal that the proposed framework saves almost 44% of the execution time and 84% of the energy consumption. Hence, the proposed framework shows profound potential for resource-intensive IoT application processing in MEC. © 2014 IEEE.
Recent advances and challenges in mobile big data
- Authors: Ahmed, Ejaz , Yaqoob, Ibrar , Hashem, Ibrahim , Shuja, Junaid , Imran, Muhammad
- Date: 2018
- Type: Text , Journal article
- Relation: IEEE Communications Magazine Vol. 56, no. 2 (2018), p. 102-108
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- Description: The unabated flurry of research activities dedicated to gaining business insights from a flood of data generated by heterogeneous mobile sources, such as the Internet of Vehicles, sensors, and smartphones, has instigated a new research domain called MBD. At the core of this mobile environment, scalability, cost effectiveness, reliability, analytics, and security are important concerns. Coping with these issues in handling MBD requires understanding the challenges associated with it. Mobile computing and big data have been widely studied separately; however, very few studies have explored the convergence of these two domains. In this article, we critically review recent research efforts directed at MBD. We also classify the MBD by devising a thematic taxonomy that is based on source, analytics, applications, characteristics, security, and data type. Furthermore, we discuss the opportunities offered by MBD in terms of analytics. Some potential uses of MBD in healthcare, telecommunication, digital advertising, and transportation are also presented. Several open research challenges are discussed as future research directions. © 1979-2012 IEEE. **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “Muhammad Imran” is provided in this record**
Resource optimized federated learning-enabled cognitive internet of things for smart industries
- Authors: Khan, Latif , Alsenwi, Madyan , Yaqoob, Ibrar , Imran, Muhammad , Han, Zhu , Hong, Choong
- Date: 2020
- Type: Text , Journal article
- Relation: IEEE Access Vol. 8, no. (2020), p. 168854-168864
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- Description: Leveraging the cognitive Internet of things (C-IoT), emerging computing technologies, and machine learning schemes for industries can assist in streamlining manufacturing processes, revolutionizing operational analytics, and maintaining factory efficiency. However, further adoption of centralized machine learning in industries seems to be restricted due to data privacy issues. Federated learning has the potential to bring about predictive features in industrial systems without leaking private information. However, its implementation involves key challenges including resource optimization, robustness, and security. In this article, we propose a novel dispersed federated learning (DFL) framework to provide resource optimization, whereby distributed fashion of learning offers robustness. We formulate an integer linear optimization problem to minimize the overall federated learning cost for the DFL framework. To solve the formulated problem, first, we decompose it into two sub-problems: association and resource allocation problem. Second, we relax the association and resource allocation sub-problems to make them convex optimization problems. Later, we use the rounding technique to obtain binary association and resource allocation variables. Our proposed algorithm works in an iterative manner by fixing one problem variable (for example, association) and compute the other (for example, resource allocation). The iterative algorithm continues until convergence of the formulated cost optimization problem. Furthermore, we compare the proposed DFL with two schemes; namely, random resource allocation and random association. Numerical results show the superiority of the proposed DFL scheme. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
Social-aware resource allocation and optimization for D2D communication
- Authors: Ahmed, Ejaz , Yaqoob, Ibrar , Gani, Abdullah , Imran, Muhammad , Guizani, Mohsen
- Date: 2017
- Type: Text , Journal article
- Relation: IEEE Wireless Communications Vol. 24, no. 3 (2017), p. 122-129
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- Description: The undiminished growth of research activities to converge social awareness with D2D communication has paved the way for facilitating and providing significant benefits to users. Realizing these benefits depends on efficiently addressing several main technical challenges associated with the convergence. Although there are many research studies related to social networks and D2D communication, convergence of these two areas leads to further research efforts to implement social-aware D2D communication. In this article, we discuss recent advances in the domain of D2D communication from the perspective of social-aware resource allocation and optimization. We also categorize and classify the literature by devising a taxonomy based on channel-centric attributes, objectives, solving approaches, networking technologies, characteristics, and communication types. Moreover, we also outline the key requirements with the aim of providing guidelines for the domain researchers and designers to enable the social-aware resource allocation for D2D communication. Several open research challenges are presented as future research directions. © 2002-2012 IEEE.