Light Fidelity (Li-Fi) is an emerging technology that has been in transferring data packets in Internet of Things (IoT) applications. During the COVID-19 pandemic, healthcare institutes try to manage the rapid increase of patients’ numbers. The healthcare team may not have the ability to monitor patients’ stats around the clock with the conventional techniques. In this paper, a healthcare monitoring framework to exchange health data between biosensors and terminals employing Li-Fi technology is proposed. It exploits Li-Fi to transmit data towards a terminal then to a cloud platform. It is intended for use in highly dense healthcare institutes where the number of patients is high. Exploiting Li-Fi to establish connection to cut high cost of other transmission technologies including Wi-Fi and provides less complexity and shorter latency. We evaluate the framework in a real-life environment using biosensors and Li-Fi communication model (for network infrastructure), these two components are connected to a computing terminal to help health staff monitor patients. The computing terminal is connected to a cloud platform to provide remote monitoring and computing resilience. The framework shows superior performance in real-world scenarios compared to Wi-Fi. A comprehensive analysis has been conducted to show the differences between Li-Fi and Wi-Fi.
Abstract-Networks performance is traditionally evaluated using packet delivery ratio (PDR) and latency (delay). We propose an addition mechanism the drop-burst length (DBL). Many traffic classes display varying application-level performance according to the pattern of drops, even if the PDR is similar. In this paper we study a number of VANET scenarios and evaluate them with these three metrics.Vehicular Ad-hoc Networks (VANETs) are an emerging class of Mobile Ad-hoc Network (MANETs) where nodes include both moving vehicles and fixed infrastructure. VANETs aim to make transportation systems more intelligent by sharing information to improve safety and comfort. Efficient and adaptive routing protocols are essential for achieving reliable and scalable network performance. However, routing in VANETs is challenging due to the frequent, high-speed movement of vehicles, which results in frequent network topology changes.Our simulations are carried out using NS2 (for network traffic) and SUMO (for vehicular movement) simulators, with scenarios configured to reflect real-world conditions. The results show that OLSR is able to achieve a best DBL performance and demonstrates higher PDR performance comparing to AODV and GPSR under low network load. However, with GPSR, the network shows more stable PDR under medium and high network load. In term of delay OLSR is outperformed by GPSR.
Mobile ad-hoc network (MANET) is a collection of wireless mobile hosts forming a temporary network without the centralized administration or base station. Mobile ad-hoc network have the attributes such as wireless connection, continuously changing topology, ease of deployment. This study has compared the performance of two MANET routing protocol DSDV and TORA by using random mobility model. In this study two performance metrics have been chosen, such as Average Performance Evaluation of MANET Routing Protocols for Varying … 83 Delay and throughput. The simulations are carried out on NS-2. The performance differentials are analyzed using varying network size (20 and 50 nodes) and simulation time was 100s. Simulation results confirm that DSDV performs well in terms of Average Delay. But TORA performs better than DSDV in terms of throughput and changing in network topology.
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