Improvement of light intensity and efficiency of n-ZnO/NiO/p-GaN heterojunction-based white light emitting diodes using micro-/nanolens array

Our study proposes a technique to enhance light extraction efficiency of light emitting diodes (LEDs) by incorporating various micro-/nanolens arrays (MNLAs) on the substrate layer, which in turn increases the external quantum efficiency (EQE) of the LEDs. To simulate the LEDs, we utilized the finite difference time domain method. To achieve a white LED, we inserted a thin layer of NiO at the interface between the n-type ZnO and the p-type GaN. The basic n-ZnO/NiO/p-GaN heterojunction-based LED exhibited an EQE of 10.99% where the effective refractive index of the LED structure was 1.48. The EQE was further increased by engraving various planoconvex or planoconcave MNLA on the top surface of the substrate layer. A maximum EQE of 12.4% was achieved for convex-1 type (lens height of 0.5  μm and radius of 0.4  μm) elliptical lens engraved LED where the effective refractive index was 1.4. In addition, the peak electroluminescence (EL) light intensity of convex-1 lens-based LED was twice than the light intensity observed in basic LED. Because of excellent EL spectrum and significant amount of light throughout the visible spectrum, the proposed convex-1 structure-based LED can be considered as a prospective candidate for white LED

Dynamic trust boundary identification for the secure communications of the entities via 6G

6G is more likely prone to a range of known and unknown cyber-attacks because of its highly distributive nature. Current literature and research prove that a trust boundary can be used as a security door (e.g., gateway/firewall) to validate entities and applications attempting to access 6G networks. Trust boundaries allow these entities to connect or work with entities of other trust boundaries via 6G by dynamically monitoring their interactions, behaviors, and data transmissions. The importance of trust boundaries in security protection mechanisms demands a dynamic multi-trust boundary identification. There exists an automatic trust boundary identification for IoT data. However, it is a binary trust boundary classification and the dataset used in the approach is not suitable for dynamic trust boundary identification. Motivated by these facts, to provide automatic security protection for entities in 6G, in this paper, we propose a mechanism to identify dynamic and multiple trust boundaries based on trust values and geographical location coordinates of 6G communication entities. Our proposed mechanism uses unsupervised clustering and splitting and merging techniques. The experimental results show that entities can dynamically change their boundary location if their trust values and locations change over time. We also analyze the trust boundary identification accuracy in terms of our defined two performance metrics, i.e., trust consistency and the degree of gateway coverage. The proposed scheme allows us to distinguish between entities and control their access to the 6G network based on their trust levels to ensure secure and resilient communication

Minimizing the number of IGMP report messages for receiver-driven layered video multicasting

International audienceTo manage multicast group in wired or wireless domain, the hosts need to send internet group management protocol (IGMP) report message when they are queried by the multicast routers. In fact, the bandwidth of wireless domain and mobile nodes' battery power are scarce resources; therefore, it can be big burden for the receiver-driven layered video multicasting (RLVM) receiving mobile hosts to follow the conventional report sending phenomenon, where a host needs to send a report message for subscribing each of the video layers. In this paper, we propose a mechanism for reducing the number of IGMP report messages for RLVM receiving hosts. The protocol overhead and efficiency are evaluated, and compared with conventional IGMPs. Our results show that applying proposed idea in IGMP the number of report messages can be minimized significantly for RLVM service

Human Face Detection Techniques: A Comprehensive Review and Future Research Directions

Face detection, which is an effortless task for humans, is complex to perform on machines. The recent veer proliferation of computational resources is paving the way for frantic advancement of face detection technology. Many astutely developed algorithms have been proposed to detect faces. However, there is little attention paid in making a comprehensive survey of the available algorithms. This paper aims at providing fourfold discussions on face detection algorithms. First, we explore a wide variety of the available face detection algorithms in five steps, including history, working procedure, advantages, limitations, and use in other fields alongside face detection. Secondly, we include a comparative evaluation among different algorithms in each single method. Thirdly, we provide detailed comparisons among the algorithms epitomized to have an all-inclusive outlook. Lastly, we conclude this study with several promising research directions to pursue. Earlier survey papers on face detection algorithms are limited to just technical details and popularly used algorithms. In our study, however, we cover detailed technical explanations of face detection algorithms and various recent sub-branches of the neural network. We present detailed comparisons among the algorithms in all-inclusive and under sub-branches. We provide the strengths and limitations of these algorithms and a novel literature survey that includes their use besides face detection

Efficient mobile IP location update mechanism for idle terminals in optical wireless integrated access networks

International audienceDuring an off-peak hour of a day, a Mobile Terminal (MT) can stay in idle mode for long time as there is no incoming or outgoing packet. An idle MT can move from one location to another and the wireless access network keeps tracking the idle MT. Idle MTs need to assist the wireless access network for location update; so that, on call arrival the network can route the call successfully. Mean while, Voice over IP (VoIP) got wide acceptance. To provide VoIP service in mobile environment or any IP packet based service, Mobile IP is very important protocol undeniably. However, Proxy Mobile IP was developed by IETF without considering the idle mode condition of MTs. Consequently, an idle MT needs to conduct Mobile IP binding (Layer 3 location update) whenever it moves to new area of a Foreign Agent although it does not have any incoming or outgoing packets during idle period. This phenomenon unnecessarily increases location update signaling cost. Here in this paper, based on optical wireless integrated access network we propose a mechanism that allows only Layer 2 location update when an MT is in idle mode and the Layer 3 location update is conducted after call arrives for an idle MT. Our numerical results show that proposed mechanism out performs than the existing solution

Light intensity and efficiency enhancement of n-ZnO/NiO/p-GaN heterojunction-based white light-emitting diodes using micro-pillar array

This study presents a unique method of enhancing light intensity and efficiency of light-emitting diodes (LEDs) by incorporating micro-pillars’ array on top of the substrate layer. The micro-pillars’ array on the substrate layer increases the light extraction efficiency, which in turn increases the external quantum efficiency (EQE) and output light intensity of the LEDs. The simulation works have been conducted using finite difference time domain method. To achieve white LED, we inserted a thin NiO layer inside the n-type ZnO and p-type GaN layers. The basic n-ZnO/NiO/p-GaN heterojunction-based LED showed an EQE of 10.99% as the effective refractive index of the LED structure was 1.48. The EQE of the basic LED was further increased by engraving micro-pillars’ array on the top of the substrate layer. A maximum EQE of 12.8% was achieved for Pillar-2 type micro-pillars array having pillars’ width and height of 2 µm and 0.2 µm where effective refractive index of the LED structure was 1.38. On the contrary, the peak electroluminescence light intensity was 2.22 times higher in Pillar–2 type micro-pillars’ array-based LED than the basic LED. Due to the excellent electroluminescence spectrum and intensity profile, the proposed Pillar–2 type micro-pillars’ array engraved LED can be considered as a potential candidate for white LED

Green Demand Aware Fog Computing: A Prediction-Based Dynamic Resource Provisioning Approach

Fog computing could potentially cause the next paradigm shift by extending cloud services to the edge of the network, bringing resources closer to the end-user. With its close proximity to end-users and its distributed nature, fog computing can significantly reduce latency. With the appearance of more and more latency-stringent applications, in the near future, we will witness an unprecedented amount of demand for fog computing. Undoubtedly, this will lead to an increase in the energy footprint of the network edge and access segments. To reduce energy consumption in fog computing without compromising performance, in this paper we propose the Green-Demand-Aware Fog Computing (GDAFC) solution. Our solution uses a prediction technique to identify the working fog nodes (nodes serve when request arrives), standby fog nodes (nodes take over when the computational capacity of the working fog nodes is no longer sufficient), and idle fog nodes in a fog computing infrastructure. Additionally, it assigns an appropriate sleep interval for the fog nodes, taking into account the delay requirement of the applications. Results obtained based on the mathematical formulation show that our solution can save energy up to 65% without deteriorating the delay requirement performance

Green Demand Aware Fog Computing: A Prediction-Based Dynamic Resource Provisioning Approach

Fog computing could potentially cause the next paradigm shift by extending cloud services to the edge of the network, bringing resources closer to the end-user. With its close proximity to end-users and its distributed nature, fog computing can significantly reduce latency. With the appearance of more and more latency-stringent applications, in the near future, we will witness an unprecedented amount of demand for fog computing. Undoubtedly, this will lead to an increase in the energy footprint of the network edge and access segments. To reduce energy consumption in fog computing without compromising performance, in this paper we propose the Green-Demand-Aware Fog Computing (GDAFC) solution. Our solution uses a prediction technique to identify the working fog nodes (nodes serve when request arrives), standby fog nodes (nodes take over when the computational capacity of the working fog nodes is no longer sufficient), and idle fog nodes in a fog computing infrastructure. Additionally, it assigns an appropriate sleep interval for the fog nodes, taking into account the delay requirement of the applications. Results obtained based on the mathematical formulation show that our solution can save energy up to 65% without deteriorating the delay requirement performance