| 1. |
- Dayo, Zaheer Ahmed, et al.
(författare)
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A Compact High-Gain Coplanar Waveguide-Fed Antenna for Military RADAR Applications
- 2020
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Ingår i: International Journal of Antennas and Propagation. - : HINDAWI LTD. - 1687-5869 .- 1687-5877. ; 2020
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Tidskriftsartikel (refereegranskat)abstract
- This paper presents a new design of a compact, high-gain coplanar waveguide-fed antenna and proposes a multielement approach to attain enhanced characteristics. The proposed method overcomes the simulation and geometrical complexity and achieves optimal performance features. The antenna prototype is carefully designed, and simulation results have been analyzed. The proposed antenna was fabricated on a new WangLing TP-2 laminate with dimensions (0.195 lambda x 0.163 lambda x 0.0052 lambda) at the lowest resonance of 9.78 GHz. The results have been tested and experimentally verified. The antenna model achieved excellent performance including a peak realized gain better than 9.0 dBi, optimal radiation efficiency better than 87.6% over the operating band, and a good relative bandwidth of 11.48% at 10 dB return loss. Symmetrical stable far-field radiation pattern in orthogonal planes and strong distribution of current are observed. Moreover, a comparative analysis with state-of-the-artwork is presented. The measured and simulation result shows a good agreement. The high-performance antenna results reveal that the proposed model is a good contender of military airborne, land, and naval radar applications.
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| 2. |
- Muzammal, Muhammad, et al.
(författare)
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A Multi-sensor Data Fusion Enabled Ensemble Approach for Medical Data from Body Sensor Networks
- 2020
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Ingår i: Information Fusion. - : Elsevier. - 1566-2535 .- 1872-6305. ; 53:2020, s. 155-164
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Tidskriftsartikel (refereegranskat)abstract
- Wireless Body Sensor Network (BSNs) are wearable sensors with varying sensing, storage, computation, and transmission capabilities. When data is obtained from multiple devices, multi-sensor fusion is desirable to transform potentially erroneous sensor data into high quality fused data. In this work, a data fusion enabled Ensemble approach is proposed to work with medical data obtained from BSNs in a fog computing environment. Daily activity data is obtained from a collection of sensors which is fused together to generate high quality activity data. The fused data is later input to an Ensemble classifier for early heart disease prediction. The ensembles are hosted in a Fog computing environment and the prediction computations are performed in a decentralised manners. The results from the individual nodes in the fog computing environment are then combined to produce a unified output. For the classification purpose, a novel kernel random forest ensemble is used that produces significantly better quality results than random forest. An extensive experimental study supports the applicability of the solution and the obtained results are promising, as we obtain 98% accuracy when the tree depth is equal to 15, number of estimators is 40, and 8 features are considered for the prediction task.
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| 3. |
- Nisar, Kashif, et al.
(författare)
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A survey on the architecture, application, and security of software defined networking: Challenges and open issues
- 2020
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Ingår i: INTERNET OF THINGS. - : ELSEVIER. - 2543-1536 .- 2542-6605. ; 12
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Forskningsöversikt (refereegranskat)abstract
- Software Defined Networking (SDN) is a new technology that makes computer networks farther programmable. SDN is currently attracting significant consideration from both academia and industry. SDN is simplifying organisations to implement applications and assist flexible delivery, offering the capability of scaling network resources in lockstep with application and data. This technology allows the user to manage the network easily by permitting the user to control the applications and operating system. SDN not only introduces new ways of interaction within network devices, but it also gives more flexibility for the existing and future networking designs and operations. SDN is an innovative approach to design, implement, and manage networks that separate the network control (control plane) and the forwarding process (data plane) for a better user experience. The main differentiation between SDN and Traditional Networking is that SDN removes the decision-making part from the routers and it provides, logically, a centralised Control-Plane that creates a network view for the control and management applications. Through the establishment of SDN, many new network capabilities and services have been enabled, such as Software Engineering, Traffic Engineering, Network Virtualisation and Automation, and Orchestration for Cloud Applications. This paper surveys the state-of-the-art contribution such as a comparison between SDN and traditional networking. Also, comparison with other survey works on SDN, new information about controller, details about OpenFlow architecture, configuration, comprehensive contribution about SDN security threat and countermeasures, SDN applications, benefit of SDN, and Emulation & Tested for SDN. In addition, some existing and representative SDN tools from both industry and academia are explained. Moreover, future direction of SDN security solutions is discussed in detail. (C) 2020 Elsevier B.V. All rights reserved.
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| 4. |
- Sodhro, Ali, et al.
(författare)
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AI-Enabled Reliable Channel Modelling Architecture for FoG Computing Vehicular Networks’
- 2020
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Ingår i: IEEE Wireless Communication Magazine. - IEEE : IEEE. - 1536-1284 .- 1558-0687. ; 27:2, s. 14-21
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Tidskriftsartikel (refereegranskat)abstract
- Artificial intelligence (AI)-driven fog computing (FC) and its emerging role in vehicular networks is playing a remarkable role in revolutionizing daily human lives. Fog radio access networks are accommodating billions of Internet of Things devices for real-time interactive applications at high reliability. One of the critical challenges in today's vehicular networks is the lack of standard wireless channel models with better quality of service (QoS) for passengers while enjoying pleasurable travel (i.e., highly visualized videos, images, news, phone calls to friends/relatives). To remedy these issues, this article contributes significantly in four ways. First, we develop a novel AI-based reliable and interference-free mobility management algorithm (RIMMA) for fog computing intra-vehicular networks, because traffic monitoring and driver's safety management are important and basic foundations. The proposed RIMMA in association with FC significantly improves computation, communication, cooperation, and storage space. Furthermore, its self-adaptive, reliable, intelligent, and mobility-aware nature, and sporadic contents are monitored effectively in highly mobile vehicles. Second, we propose a reliable and delay-tolerant wireless channel model with better QoS for passengers. Third, we propose a novel reliable and efficient multi-layer fog driven inter-vehicular framework. Fourth, we optimize QoS in terms of mobility, reliability, and packet loss ratio. Also, the proposed RIMMA is compared to an existing competitive conventional method (i.e., baseline). Experimental results reveal that the proposed RIMMA outperforms the traditional technique for intercity vehicular networks.
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| 5. |
- Sodhro, Ali Hassan, et al.
(författare)
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Power Management Strategies for Medical Information Transmission in Wireless Body Sensor Networks
- 2020
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Ingår i: IEEE Consumer Electronics Magzine. - USA. ; 9:2, s. 47-51
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Tidskriftsartikel (refereegranskat)abstract
- To minimize and manage the power drain, and extend battery lifetime of wireless body sensor networks (WBSN) is one of the major challenges. There are three key purposes of this survey article, first, to examine the downsides of the classical power-management methods in WBSNs; second, considering the life-critical applications and emergency contexts that are encompassed by WBSN; and, third, studying the impact of power-management techniques on resource-confined networks for economical healthcare. A specific power-management solution is also discussed.
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| 6. |
- Sodhro, Ali Hassan, et al.
(författare)
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Towards Blockchain-Enabled Security Technique for Industrial Internet of Things Based Decentralized Applications
- 2020
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Ingår i: Journal of Grid Computing. - Springer : Springer. - 1570-7873 .- 1572-9184. ; 18:2020, s. 615-628
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Tidskriftsartikel (refereegranskat)abstract
- As the Industrial Internet of Things (IIoT) is one of the emerging trends and paradigm shifts to revolutionize the traditional industries with the fourth wave of evolution or transform it into Industry 4.0. This all is merely possible with the sensor-enabled technologies, e.g., wireless sensor networks (WSNs) in various landscapes, where security provisioning is one of the significant challenges for miniaturized power hungry networks. Due to the increasing demand for the commercial Internet of things (IoT) devices, smart devices are also extensively adopted in industrial applications. If these devices are compromising the date/information, then there will be a considerable loss and critical issues, unlike information compromising level by the commercial IoT devices. So emerging industrial processes and smart IoT based methods in medical industries with state-of-the-art blockchain security techniques have motivated the role of secure industrial IoT. Also, frequent changes in android technology have increased the security of the blockchain-based IIoT system management. It is very vital to develop a novel blockchain-enabled cyber-security framework and algorithm for industrial IoT by adopting random initial and master key generation mechanisms over long-range low-power wireless networks for fast encrypted data processing and transmission. So, this paper has three remarkable contributions. First, a blockchain-driven secure, efficient, reliable, and sustainable algorithm is proposed. It can be said that the proposed solution manages keys randomly by introducing the chain of blocks with less power drain, a small number of cores, will slightly more communication and computation bits. Second, an analytic hierarchy process (AHP) based intelligent decision-making approach for the secure, concurrent, interoperable, sustainable, and reliable blockchain-driven IIoT system. AHP based solution helps the industry experts to select the more relevant and critical parameters such as (reliability in-line with a packet loss ratio), (convergence in mapping with delay), and (interoperability in association with throughput) for improving the yield of the product in the industry. Third, sustainable technology-oriented services are supporting to propose the novel cloud-enabled framework for the IIoT platform for regular monitoring of the products in the industry. Moreover, experimental results reveal that proposed approach is a potential candidate for the blockchain-driven IIoT system in terms of reliability, convergence, and interoperability with a strong foundation to predict the techniques and tools for the regulation of the adaptive system from Industry 4.0 aspect.
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| 7. |
- Sodhro, Ali Hassan, et al.
(författare)
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Towards Wearable Sensing Enabled Healthcare Framework for Elderly Patients
- 2020
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Ingår i: ICC 2020 - 2020 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC). - : IEEE. - 9781728150895
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Konferensbidrag (refereegranskat)abstract
- The pervasive and smart healthcare is important for elderly patients which has revolutionized the medical world and caught the attention from industry and academia with the help of portable sensor-enabled devices. Tiny size and resource-constrained nature restricts them to perform several tasks at a time. Thus, energy drain, limited battery lifetime, and high packet loss ratio (PLR) are the key challenges to be tackled carefully for ubiquitous healthcare. Energy efficiency, reliability and longer battery cycle are the vital ingredients for wearable devices to empower cost-effective and pervasive medical environment. Thus,this research work has three key contributions. First, a novel transmission power control driven energy efficient algorithm (EEA) is proposed to enhance energy, battery lifetime and reliability while monitoring the health status of elderly patients. Proposed EEA and conventional constant transmission power control (TPC) are evaluated by adopting real-time datasets of static (i.e., wheelchair sitting) and dynamic (i.e., wheelchair moving) body postures of elderly patients. Second, smart healthcare framework is proposed. Third, performance metrics such as, energy drain, battery lifetime and reliability are introduced and calculated by considering average and threshold RSSI and TPC values. Finally, it is observed through experimental analysis that the proposed EEA enhances energy efficiency with acceptable PLR than the constant TPC during data transmission.
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| 8. |
- Talat, Romana, et al.
(författare)
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A decentralised approach to privacy preserving trajectory mining
- 2020
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Ingår i: Future Generation Computer Application. - : Elsevier. - 0167-739X .- 1872-7115. ; 102:2020, s. 382-392
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Tidskriftsartikel (refereegranskat)abstract
- Large volumes of mobility data is collected in various application domains. Enterprise applications are designed on the notion of centralised data control where the proprietary of the data rests with the enterprise and not with the user. This has consequences as evident by the occasional privacy breaches. Trajectory mining is an important data mining problem, however, trajectory data can disclose sensitive location information about users. In this work, we propose a decentralised blockchain-enabled privacy-preserving trajectory data mining framework where the proprietary of the data rests with the user and not with the enterprise. We formalise the privacy preservation in trajectory data mining settings, present a proposal for privacy preservation, and implement the solution as a proof-of-concept. A comprehensive experimental evaluation is conducted to assess the applicability of the system. The results show that the proposed system yields promising results for blockchain-enabled privacy preservation in user trajectory data.
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| 9. |
- Zhang, Tianle, et al.
(författare)
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A Joint Deep Learning and Internet of Medical Things Driven Framework for Elderly Patients
- 2020
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Ingår i: IEEE Access. - : IEEE. - 2169-3536. ; 8:2020, s. 75822-75832
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Tidskriftsartikel (refereegranskat)abstract
- Deep learning (DL) driven cardiac image processing methods manage and monitor the massive medical data collected by the internet of things (IoT) based on wearable devices. A Joint DL and IoT platform are known as Deep-IoMT that extracts the accurate cardiac image data from noisy conventional devices and tools. Besides, smart and dynamic technological trends have caught the attention of every corner such as, healthcare, which is possible through portable and lightweight sensor-enabled devices. Tiny size and resource-constrained nature restrict them to perform several tasks at a time. Thus, energy drain, limited battery lifetime, and high packet loss ratio (PLR) are the keys challenges to be tackled carefully for ubiquitous medical care. Sustainability (i.e., longer battery lifetime), energy efficiency, and reliability are the vital ingredients for wearable devices to empower a cost-effective and pervasive healthcare environment. Thus, the key contribution of this paper is the sixth fold. First, a novel self-adaptive power control-based enhanced efficient-aware approach (EEA) is proposed to reduce energy consumption and enhance the battery lifetime and reliability. The proposed EEA and conventional constant TPC are evaluated by adopting real-time data traces of static (i.e., sitting) and dynamic (i.e., cycling) activities and cardiac images. Second, a novel joint DL-IoMT framework is proposed for the cardiac image processing of remote elderly patients. Third, DL driven layered architecture for IoMT is proposed. Forth, the battery model for IoMT is proposed by adopting the features of a wireless channel and body postures. Fifth, network performance is optimized by introducing sustainability, energy drain, and PLR and average threshold RSSI indicators. Sixth, a Use-case for cardiac image-enabled elderly patient's monitoring is proposed. Finally, it is revealed through experimental results in MATLAB that the proposed EEA scheme performs better than the constant TPC by enhancing energy efficiency, sustainability, and reliability during data transmission for elderly healthcare.
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