List of Titles

5G for Vehicular Communications

- Shah, Syed, Ahmed, Ejaz, Imran, Muhammad, Zeadally, Sherali

Authors: Shah, Syed , Ahmed, Ejaz , Imran, Muhammad , Zeadally, Sherali
Date: 2018
Type: Text , Journal article
Relation: IEEE Communications Magazine Vol. 56, no. 1 (2018), p. 111-117
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Description: 5G is ongoing, and it is an emerging platform that not only aims to augment existing but also introduce a plethora of novel applications that require ultra-reliable low-latency communication. It is a new radio access technology that provides building blocks to retrofit existing platforms (e.g., 2G, 3G, 4G, and WiFi) for greater coverage, accessibility, and higher network density with respect to cells and devices. It implies that 5G aims to satisfy a diverse set of communication requirements of the various stakeholders. Among the stakeholders, vehicles, in particular, will benefit from 5G at both the system and application levels. The authors present a tutorial perspective on vehicular communications using the building blocks provided by 5G. First, we identify and describe key requirements of emerging vehicular communications and assess existing standards to determine their limitations. Then we provide a glimpse of the adopted 5G architecture and identify some of its promising salient features for vehicular communications. Finally, key 5G building blocks (i.e., proximity services, mobile edge computing and network slicing) are explored in the context of vehicular communications, and associated design challenges are highlighted. © 1979-2012 IEEE.

A hybrid precoding- and filtering-based uplink MC-LNOMA scheme for 5G cellular networks with reduced PAPR

- Baig, Imran, Farooq, Umer, Ahmed, Ejaz, Imran, Muhammad, Shoaib, Muhammad

Authors: Baig, Imran , Farooq, Umer , Ahmed, Ejaz , Imran, Muhammad , Shoaib, Muhammad
Date: 2018
Type: Text , Journal article
Relation: Transactions on Emerging Telecommunications Technologies Vol. 29, no. 10 (2018), p.
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Description: Uplink multicarrier localized nonorthogonal multiple access (MC-LNOMA) is a variant of hybrid nonorthogonal multiple access, where subcarrier mapping is performed in localized mode. MC-LNOMA is one of the most prominent emerging schemes and likely to be employed in the forthcoming fifth-generation cellular networks due to its massive connectivity, spectral efficiency, better cell coverage capability, and higher data rate. It may employ orthogonal frequency-division multiple access due to the technical ripeness. However, schemes based on orthogonal frequency-division multiple access all suffer from the high peak-to-average power ratio problem. Therefore, in this paper, a new finite impulse response filter–based discrete cosine transform–precoded uplink MC-LNOMA scheme is presented for peak-to-average power ratio reduction. MATLAB simulations demonstrate the performance supremacy of the proposed scheme compared to contemporary schemes such as discrete cosine transform–precoded uplink MC-LNOMA and nonprecoded uplink MC-LNOMA. © 2018 John Wiley & Sons, Ltd.

Big data analytics in industrial IoT using a concentric computing model

- Rehman, Muhammad, Ahmed, Ejaz, Yaqoob, Ibrar, Hashem, Ibrahim, Imran, Muhammad, Ahmad, Shafiq

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.

Bringing Computation Closer toward the User Network: Is Edge Computing the Solution?

- Ahmed, Ejaz, Ahmed, Arif, Yaqoob, Ibrar, Shuja, Junaid, Imran, Muhammad

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**

Clustering-based real-time anomaly detection—a breakthrough in big data technologies

- Habeeb, Riyaz, Nasaruddin, Fariza, Gani, Abdullah, Amanullah, Mohamed, Hashem, Ibrahim, Ahmed, Ejaz, Imran, Muhammad

Authors: Habeeb, Riyaz , Nasaruddin, Fariza , Gani, Abdullah , Amanullah, Mohamed , Hashem, Ibrahim , Ahmed, Ejaz , Imran, Muhammad
Date: 2022
Type: Text , Journal article
Relation: Transactions on Emerging Telecommunications Technologies Vol. 33, no. 8 (2022), p.
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Description: Off late, the ever increasing usage of a connected Internet-of-Things devices has consequently augmented the volume of real-time network data with high velocity. At the same time, threats on networks become inevitable; hence, identifying anomalies in real time network data has become crucial. To date, most of the existing anomaly detection approaches focus mainly on machine learning techniques for batch processing. Meanwhile, detection approaches which focus on the real-time analytics somehow deficient in its detection accuracy while consuming higher memory and longer execution time. As such, this paper proposes a novel framework which focuses on real-time anomaly detection based on big data technologies. In addition, this paper has also developed streaming sliding window local outlier factor coreset clustering algorithms (SSWLOFCC), which was then implemented into the framework. The proposed framework that comprises BroIDS, Flume, Kafka, Spark streaming, SparkMLlib, Matplot and HBase was evaluated to substantiate its efficacy, particularly in terms of accuracy, memory consumption, and execution time. The evaluation is done by performing critical comparative analysis using existing approaches, such as K-means, hierarchical density-based spatial clustering of applications with noise (HDBSCAN), isolation forest, spectral clustering and agglomerative clustering. Moreover, Adjusted Rand Index and memory profiler package were used for the evaluation of the proposed framework against the existing approaches. The outcome of the evaluation has substantially proven the efficacy of the proposed framework with a much higher accuracy rate of 96.51% when compared to other algorithms. Besides, the proposed framework also outperformed the existing algorithms in terms of lesser memory consumption and execution time. Ultimately the proposed solution enable analysts to precisely track and detect anomalies in real time. © 2019 John Wiley & Sons, Ltd.

Deep learning and big data technologies for IoT security

- Amanullah, Mohamed, Habeeb, Riyaz, Nasaruddin, Fariza, Gani, Abdullah, Ahmed, Ejaz, Nainar, Abdul, Akim, Nazihah, Imran, Muhammad

Authors: Amanullah, Mohamed , Habeeb, Riyaz , Nasaruddin, Fariza , Gani, Abdullah , Ahmed, Ejaz , Nainar, Abdul , Akim, Nazihah , Imran, Muhammad
Date: 2020
Type: Text , Journal article , Review
Relation: Computer Communications Vol. 151, no. (2020), p. 495-517
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Description: Technology has become inevitable in human life, especially the growth of Internet of Things (IoT), which enables communication and interaction with various devices. However, IoT has been proven to be vulnerable to security breaches. Therefore, it is necessary to develop fool proof solutions by creating new technologies or combining existing technologies to address the security issues. Deep learning, a branch of machine learning has shown promising results in previous studies for detection of security breaches. Additionally, IoT devices generate large volumes, variety, and veracity of data. Thus, when big data technologies are incorporated, higher performance and better data handling can be achieved. Hence, we have conducted a comprehensive survey on state-of-the-art deep learning, IoT security, and big data technologies. Further, a comparative analysis and the relationship among deep learning, IoT security, and big data technologies have also been discussed. Further, we have derived a thematic taxonomy from the comparative analysis of technical studies of the three aforementioned domains. Finally, we have identified and discussed the challenges in incorporating deep learning for IoT security using big data technologies and have provided directions to future researchers on the IoT security aspects. © 2020 Elsevier B.V.

Green industrial networking : recent advances, taxonomy, and open research challenges

- Ahmed, Ejaz, Yaqoob, Ibrar, Ahmed, Ahmed, Gani, Abdullah, Imran, Muhammad, Guizani, Sghaier

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.

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Heterogeneity-aware task allocation in mobile ad hoc cloud

- Yaqoob, Ibrar, Ahmed, Ejaz, Gani, Abdullah, Mokhtar, Salimah, Imran, Muhammad

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

- Yaqoob, Ibrar, Ahmed, Ejaz, Hashem, Ibrahim, Ahmed, Abdelmuttlib, Gani, Abdullah, Imran, Muhammad, Guizani, Mohsen

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 environments : state of the art, taxonomy, and open research challenges

- Ahmed, Ejaz, Yaqoob, Ibrar, Gani, Abdullah, Imran, Muhammad, Guizani, Mohsen

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.

Mobile ad hoc cloud : a survey

- Yaqoob, Ibra, Ahmed, Ejaz, Gani, Abdullah, Mokhtar, Salimah, Imran, Muhammad, Guizani, Sghaier

Authors: Yaqoob, Ibra , Ahmed, Ejaz , Gani, Abdullah , Mokhtar, Salimah , Imran, Muhammad , Guizani, Sghaier
Date: 2016
Type: Text , Journal article
Relation: Wireless Communications and Mobile Computing Vol. 16, no. 16 (2016), p. 2572-2589
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Description: The unabated flurry of research activities to augment various mobile devices in terms of compute-intensive task execution by leveraging heterogeneous resources of available devices in the local vicinity has created a new research domain called mobile ad hoc cloud (MAC) or mobile cloud. It is a new type of mobile cloud computing (MCC). MAC is deemed to be a candidate blueprint for future compute-intensive applications with the aim of delivering high functionalities and rich impressive experience to mobile users. However, MAC is yet in its infancy, and a comprehensive survey of the domain is still lacking. In this paper, we survey the state-of-the-art research efforts carried out in the MAC domain. We analyze several problems inhibiting the adoption of MAC and review corresponding solutions by devising a taxonomy. Moreover, MAC roots are analyzed and taxonomized as architectural components, applications, objectives, characteristics, execution model, scheduling type, formation technologies, and node types. The similarities and differences among existing proposed solutions by highlighting the advantages and disadvantages are also investigated. We also compare the literature based on objectives. Furthermore, our study advocates that the problems stem from the intrinsic characteristics of MAC by identifying several new principles. Lastly, several open research challenges such as incentives, heterogeneity-ware task allocation, mobility, minimal data exchange, and security and privacy are presented as future research directions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Overcoming the key challenges to establishing vehicular communication : is SDN the answer?

- Yaqoob, Ibrar, Ahmad, Iftikhar, Ahmed, Ejaz, Gani, Abdullah, Imran, Muhammad, Guizani, Nadra

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 state synchronization-based application execution management for mobile edge/cloud computing

- Ahmed, Ejaz, Naveed, Anjum, Gani, Abdullah, Hamid, Siti, Imran, Muhammad, Guizani, Mohsen

Authors: Ahmed, Ejaz , Naveed, Anjum , Gani, Abdullah , Hamid, Siti , Imran, Muhammad , Guizani, Mohsen
Date: 2019
Type: Text , Journal article
Relation: Future Generation Computer Systems Vol. 91, no. (2019), p. 579-589
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Description: Mobile cloud computing (MCC) and mobile edge computing (MEC) facilitate the mobile devices to augment their capabilities by utilizing the resources and services offered by Cloud and Edge Cloud, respectively. However, due to mobility, network connection becomes unstable that causes application execution disruption. Such disruption increases the execution time and in some cases restrain the mobile devices from getting execution results from the cloud. This research work analyzes the impact of user mobility on the execution of cloud-based mobile applications. We propose a Process State Synchronization (PSS)-based execution management to solve the aforementioned problem. We analytically compute a sufficient condition on synchronization interval that ensure reduction in mobile application execution time under PSS in case of disconnection. Similarly, we compute the upper bound on synchronization interval whereby a larger synchronization interval did not result in significant benefits in terms of execution time for the mobile application. The analytical results were confirmed by the sample implementation of PSS with the computed synchronization intervals. Moreover, we also compare the performance of proposed solution with the state-of-the-art solutions. The results show that the PSS-based execution outperforms the other contemporary solutions. © 2018 Elsevier B.V.

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Real-time big data processing for anomaly detection : a survey

- Ariyaluran Habeeb, Riyaz, Nasaruddin, Fariza, Gani, Abdullah, Targio Hashem, Ibrahim, Ahmed, Ejaz, Imran, Muhammad

Authors: Ariyaluran Habeeb, Riyaz , Nasaruddin, Fariza , Gani, Abdullah , Targio Hashem, Ibrahim , Ahmed, Ejaz , Imran, Muhammad
Date: 2019
Type: Text , Journal article , Review
Relation: International Journal of Information Management Vol. 45, no. (2019), p. 289-307
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Description: The advent of connected devices and omnipresence of Internet have paved way for intruders to attack networks, which leads to cyber-attack, financial loss, information theft in healthcare, and cyber war. Hence, network security analytics has become an important area of concern and has gained intensive attention among researchers, off late, specifically in the domain of anomaly detection in network, which is considered crucial for network security. However, preliminary investigations have revealed that the existing approaches to detect anomalies in network are not effective enough, particularly to detect them in real time. The reason for the inefficacy of current approaches is mainly due the amassment of massive volumes of data though the connected devices. Therefore, it is crucial to propose a framework that effectively handles real time big data processing and detect anomalies in networks. In this regard, this paper attempts to address the issue of detecting anomalies in real time. Respectively, this paper has surveyed the state-of-the-art real-time big data processing technologies related to anomaly detection and the vital characteristics of associated machine learning algorithms. This paper begins with the explanation of essential contexts and taxonomy of real-time big data processing, anomalous detection, and machine learning algorithms, followed by the review of big data processing technologies. Finally, the identified research challenges of real-time big data processing in anomaly detection are discussed. © 2018 Elsevier Ltd

Recent advances and challenges in mobile big data

- Ahmed, Ejaz, Yaqoob, Ibrar, Hashem, Ibrahim, Shuja, Junaid, Imran, Muhammad

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**

SDN-Based load balancing service for cloud servers

- Abdelaziz, Ahmed, Ahmed, Ejaz, Fong, Ang, Gani, Abdullah, Imran, Muhammad

Authors: Abdelaziz, Ahmed , Ahmed, Ejaz , Fong, Ang , Gani, Abdullah , Imran, Muhammad
Date: 2018
Type: Text , Journal article
Relation: IEEE Communications Magazine Vol. 56, no. 8 (2018), p. 106-111
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Description: With the continuous growth, heterogeneity, and ever increasing demand of services, load balancing of cloud servers is an emerging challenge to meet highly demanding requirements (e.g., data rates, latency, quality of service) of 5G network applications. Although various load balancing techniques have been proposed, some of these techniques either require installation of dedicated additional load balancers for each service, or manual reconfiguration of the device to handle new services is desired. These techniques are expensive, time-consuming, and impractical. Moreover, most of the existing load balancing schemes do not consider service types. This article presents an SDN-based load balancing (SBLB) service for cloud servers to maximize resource utilization and minimize response time of users. The constituents of the proposed scheme are an application module that runs on top of an SDN controller and server pools that connect to the controller through OpenFlow switches. The application module consists of a service classification module, a dynamic load balancing module, and a monitoring module. The controller handles all messages, manages host pools, and maintains the load of host in real time. Experimental results validate the performance of the proposed scheme. Through experimental results, SBLB demonstrates significant decrease in average response time and reply time. © 1979-2012 IEEE.

Securing IoTs in distributed blockchain : analysis, requirements and open issues

- Moin, Sana, Karim, Ahmad, Safdar, Zanab, Safdar, Kalsoom, Ahmed, Ejaz, Imran, Muhammad

Authors: Moin, Sana , Karim, Ahmad , Safdar, Zanab , Safdar, Kalsoom , Ahmed, Ejaz , Imran, Muhammad
Date: 2019
Type: Text , Journal article
Relation: Future Generation Computer Systems Vol. 100, no. (2019), p. 325-343
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Description: IoTs are integrated, interconnected concepts of things or objects in our surroundings, with an essence of virtualization. The interconnectivity of the business world, health environments, smart home devices, and daily use gadgets takes place through the networks based on cloud infrastructure which is not restricted to jurisdictional, geographic, and national boundaries. However, the light-weight IoT devices come with a limited storage and processing capacity. Due to this limitation, the need for separate data storage arises so that data can be utilized in the future. These third-party storage services are provided at the cost of a user's privacy. Furthermore, the storage relies on a centralized database which is more open to attack due to its single point security breach chances. Furthermore, present IoT data is not trustworthy in the external environment, as data manipulation is lacking when data is shared with other parties. To overcome the above-mentioned limitations of IoT, the emerging secure decentralized storage technology; Blockchain, have begun to abandon the significant impact in the IoT with the enhancement of security and incorporating a large number of devices in the today's ecosystems. In this paper, we have performed a comprehensive literature review to show how well blockchain has transformed the smart environments connected with IoT sensors and the underlying issues for its adaptation. Further, a well-organized taxonomy is presented by highlighting the strengths, weaknesses, opportunities, and threats (SWOT) of blockchain based IoT environment. In addition to that, we have clearly presented the verities of blockchain applications such as bitcoin (earlier cryptocurrency used in blockchain) or ethereum (establish smart contracts) based works and pinpoint the necessities and security challenges. Moreover, we have highlighted the essential implementation requirements of blockchain in the IoTs. This paper is also equipped with a state-of-the-art framework of IoT while adopting security features and decentralized storage requirements of the blockchain. In the end, we have presented insightful challenges need to be addressed to obtain efficient, secure, and effective communication goals and to provide private and secure services for users as per their requirements. © 2019 Elsevier B.V.

Social-aware resource allocation and optimization for D2D communication

- Ahmed, Ejaz, Yaqoob, Ibrar, Gani, Abdullah, Imran, Muhammad, Guizani, Mohsen

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.

The rise of ransomware and emerging security challenges in the internet of things

- Yaqoob, Ibrar, Ahmed, Ejaz, Rehman, Muhammad, Ahmed, Abdelmuttlib, Imran, Muhammad

Authors: Yaqoob, Ibrar , Ahmed, Ejaz , Rehman, Muhammad , Ahmed, Abdelmuttlib , Imran, Muhammad
Date: 2017
Type: Text , Journal article
Relation: Computer Networks Vol. 129, no. (2017), p. 444-458
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Description: With the increasing miniaturization of smartphones, computers, and sensors in the Internet of Things (IoT) paradigm, strengthening the security and preventing ransomware attacks have become key concerns. Traditional security mechanisms are no longer applicable because of the involvement of resource-constrained devices, which require more computation power and resources. This paper presents the ransomware attacks and security concerns in IoT. We initially discuss the rise of ransomware attacks and outline the associated challenges. Then, we investigate, report, and highlight the state-of-the-art research efforts directed at IoT from a security perspective. A taxonomy is devised by classifying and categorizing the literature based on important parameters (e.g., threats, requirements, IEEE standards, deployment level, and technologies). Furthermore, a few credible case studies are outlined to alert people regarding how seriously IoT devices are vulnerable to threats. We enumerate the requirements that need to be met for securing IoT. Several indispensable open research challenges (e.g., data integrity, lightweight security mechanisms, lack of security software's upgradability and patchability features, physical protection of trillions of devices, privacy, and trust) are identified and discussed. Several prominent future research directions are provided. © 2017 Elsevier B.V. **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**

The role of big data analytics in internet of things

- Ahmed, Ejaz, Yaqoob, Ibrar, Hashem, Ibrahim, Khan, Imran, Imran, Muhammad

Authors: Ahmed, Ejaz , Yaqoob, Ibrar , Hashem, Ibrahim , Khan, Imran , Imran, Muhammad
Date: 2017
Type: Text , Journal article
Relation: Computer Networks Vol. 129, no. (2017), p. 459-471
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Description: The explosive growth in the number of devices connected to the Internet of Things (IoT) and the exponential increase in data consumption only reflect how the growth of big data perfectly overlaps with that of IoT. The management of big data in a continuously expanding network gives rise to non-trivial concerns regarding data collection efficiency, data processing, analytics, and security. To address these concerns, researchers have examined the challenges associated with the successful deployment of IoT. Despite the large number of studies on big data, analytics, and IoT, the convergence of these areas creates several opportunities for flourishing big data and analytics for IoT systems. In this paper, we explore the recent advances in big data analytics for IoT systems as well as the key requirements for managing big data and for enabling analytics in an IoT environment. We taxonomized the literature based on important parameters. We identify the opportunities resulting from the convergence of big data, analytics, and IoT as well as discuss the role of big data analytics in IoT applications. Finally, several open challenges are presented as future research directions. © 2017 Elsevier B.V. **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**

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