Service-Oriented Architecture for IoT Home Area Networking in 5G

Rahim, Mohd. Rozaini Abd.; Rashid, Rozeha A.; Rateb, Ahmad M.; Sarijari, Mohd Adib; Abdullah, Ahmad Shahidan; Hamid, Mohd. Kamaruddin Abd.; Sayuti, Hamdan; Fisal, Norsheila

doi:10.1002/9781119333142.ch16

Cited by 7 publications

(4 citation statements)

References 15 publications

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“…Future extensions of this work include adapting FCE to deal with realistic implementation challenges, especially large CS measurements errors and invalid measurements caused by wireless channel impairments [59], [60]. In addition, developing a hardware implementation of an FCE-based ECG monitoring system within a smart-home framework [61]. Realistic ECG reconstruction performance and energy consumption are then measured, evaluated and compared.…”

Section: Discussionmentioning

confidence: 99%

A Fast Compressed Sensing Decoding Technique for Remote ECG Monitoring Systems

Rateb

2020

IEEE Access

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Compressed Sensing (CS) has been proposed as a low-complexity ECG data compression scheme for wearable wireless bio-sensor devices. However, CS decoding is characterized by high computational complexity. As a result, it represents a burden to the computational and energy resources of the network gateway node, where decoding is performed. In this article, we propose a Fast Compressive Electrocardiography (FCE) technique to address this problem. CS decoding in FCE is based on Weighted Regularized Least-Squares (WRLS), rather than the standard approach based on 1 norm minimization. The WRLS formulation takes into account prior knowledge of ECG signal properties to estimate an optimally compact and accurate representation of ECG signals. Numerical results show that decoding by FCE is on average 33 times faster than the fastest tested CS-based ECG decoding technique. In addition, highquality ECG signal reconstruction by FCE is achieved at 32% higher compression ratio. Therefore, FCE can contribute to improving the overall energy and computational resource efficiency of CS-based remote ECG monitoring systems.INDEX TERMS Compressed sensing (CS), electrocardiogram (ECG), random demodulator, remote health monitoring, wireless body-sensor network (WBSN).

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Section: Discussionmentioning

confidence: 99%

A Fast Compressed Sensing Decoding Technique for Remote ECG Monitoring Systems

Rateb

2020

IEEE Access

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“…On the other hand, Service Oriented architecture (SOA) has been used by literature to address IoT challenges such as interoperability as well as Middle-ware design and implementations [25], [26] and [27].…”

Section: Related Workmentioning

confidence: 99%

“…In [25] a Service Oriented architecture for Home Area Network (SoHAN) has been introduced to facilitate and abstract a network of sensors and/or actuators for application developer over 5G networks. they based on a Sensor node that has a processing capabilities to process the sensor data and send it to a gateway hosted in Home premises which send it to the Cloud/server for processing.…”

Section: Related Workmentioning

confidence: 99%

Towards a Dynamic Scalable IoT Computing Platform Architecture

Abdelqawy¹,

Kamel²,

Makady³

2020

IJACSA

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Internet of Things (IoT) has become an interesting topic among technology titans and different business groups. IoT platforms have been introduced to support the development of IoT applications and services. Such platforms connect the real and virtual worlds of objects, systems and people. Even though IoT platforms increasingly target various domains, they still suffer from various limitations. (1) Integrating hardware devices from different providers/vendors (thereafter referenced as heterogeneous hardware) is still a subtle task. (2) Providing a scalable solution without altering the end user privacy (e.g., through the use of cloud platforms) is hard to achieve. (3) Handling IoT Applications reliability as well as platform reliability is still not fully supported. (4) Addressing Safety-critical applications needs are still not covered by such platforms. A novel scalable dynamic computing platform architecture is proposed to address such limitations and provide simultaneous support for five non-functional requirements. The supported non-functional requirements are scalability, reliability, privacy, timing for real-time systems and safety. The proposed architecture uses a novel network topology design, virtualization and containerization concepts, along with a service-oriented architecture. We present and use a smart home case study to evaluate how traditional IoT platform architectures are compared to the proposed architecture, in terms of supporting the five non-functional requirements.

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“…Furthermore, drones can be on-demand disposed above the desired area in order to assist communications at any given time and according to their dynamic requirements [1]. In the 5G and 6G networks, one of the main objectives is the creation of a fully integrated heterogeneous network [2] [3] following the Service-Oriented Architecture (SOA) paradigm [4]. SOA is an approach that addresses the requirements of loosely cou-pled, protocol-independent, and standards-based distributed computing.…”

Section: Introductionmentioning

confidence: 99%

Metropolitan Quantum-Drone Networking and Computing: A Software-Defined Perspective

2022

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Swarms of drones are utilized in a wide range of applications, considering that they can be deployed on-demand and are economically affordable. Furthermore, they can also have a significant role in the creation of future Quantum Networks (QNs). As a matter of fact, the use of drones allows deploying a non terrestrial Quantum Metropolitan Area Network (QMAN), overcoming Optical Fibers' (OFs) limits, due to the large percentage of photons that scatters before reaching the receiver. However, random fluctuations of drones' positions and atmospheric turbulence can affect the quality of the Free Space Optic (FSO) link with a significant impact on performance. Considering that Quantum Drone Networks (QDNs) require significant control, Software-Defined Networking (SDN) paradigm can play a key role in their provisioning. Specifically, an SDN Controller is responsible for managing the global strategies for the distribution of end-to-end (E2E) entangled pairs. Therefore, this paper provides the design of an SDN-based architecture for supporting high-performance Metropolitan Quantum Drone Networks (MQDNs) with a specific protocol for creating entanglement between two Ground Stations (GSs) through the swarm of drones. The proposed architecture can be employed for distributed quantum computing applications and entanglement-based Quantum Key Distribution (QKD) services. Moreover, a suited objective function to optimize the planning and operation of the swarm mission has been proposed. Finally, the paper provides a performance evaluation considering the most relevant metrics, such as fidelity, entanglement rate, and the overhead of the proposed protocol, pointing out that even higher performance than OFs is achievable.

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Service-Oriented Architecture for IoT Home Area Networking in 5G

Cited by 7 publications

References 15 publications

A Fast Compressed Sensing Decoding Technique for Remote ECG Monitoring Systems

A Fast Compressed Sensing Decoding Technique for Remote ECG Monitoring Systems

Towards a Dynamic Scalable IoT Computing Platform Architecture

Metropolitan Quantum-Drone Networking and Computing: A Software-Defined Perspective

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