Energy Efficient QoS-Based Access Point Selection in Hybrid WiFi and LiFi IoT Networks

Asad, Muhammad; Qaisar, Saad

doi:10.1109/tgcn.2021.3115729

Cited by 20 publications

(8 citation statements)

References 27 publications

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“…The related work shows that the current focus of optimizing energy efficiency in LiFi networks is in the downlink direction at APs. Our previous work presented a first-of-its-kind client-based energy minimization technique for QoS provisioning in hybrid WiFi and LiFi networks [12]. This paper extends our previous work, and presents a novel adaptive uplink transmit power mechanism to optimize energy efficiency distributively at the client-side.…”

Section: Contributionsupporting

confidence: 56%

“…However, energy is more limited at IoT nodes, and hence energy-efficient uplink communications are even more vital. Our previous work proposes a novel client-side technique for energy efficiency in hybrid WiFi and LiFi networks [12]. To the best of the authors' knowledge, extending our previous work, this paper presents a first-of-its-kind adaptive uplink transmit power mechanism to improve energy efficiency in IRbased LiFi IoT networks.…”

Section: Introductionmentioning

confidence: 92%

“…The Algorithm 1 is presented for the proposed adaptive uplink transmission power selection for energy efficiency, and is derived from our earlier proposed algorithm [12]. The algorithm runs distributively at all nodes.…”

Section: Algorithmmentioning

confidence: 99%

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Adaptive Uplink Transmit Power Mechanism for Energy Efficiency in Infrared-Based LiFi IoT Networks

Asad

Qaisar

2022

Preprint

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The continuously increasing number of Wireless Fidelity (WiFi) access points have resulted in increased congestion in already congested indoor networks. In recent years, Light Fidelity (LiFi) has presented itself as upcoming access technology to complement WiFi owing to its vast spectrum, high data rates, and secrecy. Infrared (IR) is widely adopted in the uplink of LiFi-based systems. Due to the limited availability of energy in the Internet of Things (IoT) nodes, energy efficiency is vital. This paper presents a client-based adaptive IR uplink transmit power algorithm to enhance energy efficiency while satisfying the data rate requirement of IoT nodes. With hardware-based experimentation with LZ1 IR-LED and Heidi lens, the need for such an adaptive transmit power mechanism is first demonstrated. Simulation-based evaluation is then performed, showing that the proposed algorithm outperforms random and fixed uplink optical powers in terms of energy efficiency and satisfaction of data rate requirements of IoT nodes. The results clearly show the need for hardware design of IR-based IoT nodes with integrated adaptive uplink transmit power algorithms for LiFi IoT networks.

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Section: Contributionsupporting

confidence: 56%

Section: Introductionmentioning

confidence: 92%

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Adaptive Uplink Transmit Power Mechanism for Energy Efficiency in Infrared-Based LiFi IoT Networks

Asad

Qaisar

2022

Preprint

Self Cite

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“…Series of batteries have been developed as self‐powered wearable devices, such as those that utilize wireless power supply, [ 1 ] piezoelectricity, [ 2 ] triboelectricity, [ 3 ] and even biomass fuel cells. [ 4 ] However, the output power from these energy sources is often lower than the normal operating power required for the key electronic components, such as Bluetooth [ 3b,5 ] (>10 mW), Wi‐Fi [ 6 ] (>20 mW), and some low‐power microcontroller unit (MCU) [ 7 ] (>5 mW). Self‐powering can only serve as a secondary energy supply in certain equipment that requires the maintenance of stable operations for a long period.…”

Section: Introductionmentioning

confidence: 99%

Material Choice and Structure Design of Flexible Battery Electrode

et al. 2022

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With the development of flexible electronics, the demand for flexibility is gradually put forward for its energy supply device, i.e., battery, to fit complex curved surfaces with good fatigue resistance and safety. As an important component of flexible batteries, flexible electrodes play a key role in the energy density, power density, and mechanical flexibility of batteries. Their large‐scale commercial applications depend on the fulfillment of the commercial requirements and the fabrication methods of electrode materials. In this paper, the deformable electrode materials and structural design for flexible batteries are summarized, with the purpose of flexibility. The advantages and disadvantages of the application of various flexible materials (carbon nanotubes, graphene, MXene, carbon fiber/carbon fiber cloth, and conducting polymers) and flexible structures (buckling structure, helical structure, and kirigami structure) in flexible battery electrodes are discussed. In addition, the application scenarios of flexible batteries and the main challenges and future development of flexible electrode fabrication are also discussed, providing general guidance for the research of high‐performance flexible electrodes.

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“…3,4 Sensors, actuators, hardware, software, and storage are all included in the objects and are incorporated in a wide domain of applicability including medical care, education, transportation industry, and agriculture. 5,6 The basic goal of the IoT is to increase the connection between hardware items and the edge computing environment, along with data transformation in meaningful information without human intervention. 7,8 Hardware, middleware, and presentation are the three components of the IoT.…”

Section: Introductionmentioning

confidence: 99%

Energy efficient IoT‐based informative analysis for edge computing environment

Bhatia

2022

Trans Emerging Tel Tech

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Internet of Things (IoT) is an intelligent technology that interconnection of everything at any time over an edge computing network. Because of pervasiveness and ubiquity, IoT technology is exhausting energy resources over edge computing platforms. As a result, IoT energy efficiency has become a prominent research domain. Conspicuously, an energy-efficient IoT framework for the edge computing paradigm has been proposed in the present research. Specifically, the proposed framework comprises three layers including perception and control layer, data processing layer, and application and visualization layer.The presented framework predicts inactive sensor intervals based on respective battery percentage, historical utility, and data accuracy needed for edge-based service delivery. Specifically, when the sensing nodes are in inactivity mode, the predicted value increases edge resource usage by re-provisioning the allotted resources. Moreover, the presented technique enables energy-efficient utilization of IoT resources. For validation purposes, the performance comparison is performed with state-of-the-art techniques. It shows that the presented framework is significantly enhanced in terms of energy consumption efficacy (30.45 mJ/K nodes), packet loss ratio (0.51%), statistical performance, and system stability (84.69%).

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Energy Efficient QoS-Based Access Point Selection in Hybrid WiFi and LiFi IoT Networks

Cited by 20 publications

References 27 publications

Adaptive Uplink Transmit Power Mechanism for Energy Efficiency in Infrared-Based LiFi IoT Networks

Adaptive Uplink Transmit Power Mechanism for Energy Efficiency in Infrared-Based LiFi IoT Networks

Material Choice and Structure Design of Flexible Battery Electrode

Energy efficient IoT‐based informative analysis for edge computing environment

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