Advances in Science and Technology Vol. 124

Abstract: Today's and tomorrow's secret data exchange relies heavily on cryptography. Cryptographic applications offer a secure communication channel for safely transferring data. It provides individuals, groups, and organizations with greater privacy and access to communication and other information, as well as the opportunity to restore personal privacy. Nowadays, online users desire to create an account in order to get access to certain websites, such as online tutorials, online purchases, online resource access, hosting services, social networking sites, and so on. However, unless the service provider or authority person ensures that the registration and login processes are genuine, there is a potential that the account might be hacked by a third party using the ordinary user access method. With the growing usage of cloud emails and frequent reports of large-scale leakage occurrences, a security attribute known as forward secrecy becomes desired and necessary for both users and cloud service providers to improve the security of cloud email systems.

Abstract: The Self-Sovereign Identity (SSI) strategy provides user identities that the SSI system cannot serve its purpose without considering user privacy at the network level. The existing systems work to the best of its ability but lack in allowing for a smooth transition of network input/output. This paper addresses the above issue by optimising the Network Discovery Strategy and creating a new Bootstrapper configuration.

Abstract: Over the last several years, vehicular ad-hoc networks (VANETs) technology booming as significant research topic. Vehicular Ad-hoc Networks (VANETs) are a component of Intelligent Transportation Systems (ITS) that are in charge of communication between moving vehicles in a specific environment. VANETs are increasingly recognised as dependable networks that vehicles engage for communication between moving or stationary vehicles (V2V), Road side unit (RSU).The idea of enabling vehicle communication over a cellular connection prompted the creation of the new protocols, equipment, also different application scenarios. Various simulators were created at the time due to the inherent difficulties of evaluating these research contributions on a real-world test platform. The introduction of autonomous cars and the proliferation of new technology have created new research challenges in VANETs (e.g., 5G and edge computing). As a result, VANET simulators must be assessed to determine whether they are still capable of analysing these novel ideas. This study delivers a comprehensive assessment of Vehicular simulators such as Veins, EstiNet, ezCar2X, Eclipse MOSAIC, VanetSim, NetSim, VENTOS,demonstrating their current condition and capabilities for evaluating innovative situations in Vehicular network research. Depends on this demonstration, we highlight the unresolved research issues need to be resolved in current and future Vehicular network simulations.

Abstract: Innovative environments such as fog computing, which offer computation, data management, and other applications at the network edge, are gaining prominence. Fog networks with Wi-Fi offloading determined to be among the most acceptable methods for combating significant data increases in cellular networks. Fog nodes used to relay traffic and computations are situated nearby, making them excellent relay points. So, why networks have grown as rapidly as they have, and it's left its imprint on their performance. On the other hand, fog computing has recently developed to help Content-Centric Networking (CCN) decrease the amount of traffic. It has shown to be an effective method to reduce network latency and process time in industries and traffic. The use of Vehicle to Device technology for transferring network data in the mobile environment is expected to take off, particularly for autonomous cars. This study considers how to balance energy usage and service delay while allocating mobile traffic among vehicle networks. This article proposes a new paradigm for describing users' desire to provide their mobile vehicle resources to the public. The suggested methods are evaluated via comprehensive simulations, using various mobile movement traces. Additionally, Deep learning algorithm with how an online traffic monitoring for training and how important it is to know that train is possible. In conclusion, this methods proved to be better than previous benchmark techniques for fog networks.

Abstract: With the development in the technologies and modern equipment the level of the pollution has increased significantly. Air pollution caused due to the factories and the automobiles contributes a large share in this pollution and also one of the most challenging because the Particulate matters are released directly in to the air. So, this project is based on solving the global problem of air pollution by designing an air purifier that brings the increased level of air pollution to its lowest level. In this air purifier HEPA filters is used to purify the air and to make it smart sensors and IOTs are used. To make this whole process automatic Arduino based microcontroller (Node MCU ESP12e) is used which makes this whole system self-operating .This model will also use air quality sensor (MQ135 ),temperature sensor (DHT11) and humidity sensor (DHT11) for its working. Along-with this for energy requirements solar panels are used but for future scope electricity generation using piezo-electric plates has also been suggested.

Abstract: Smart grids add software and sensors to the existing power grids that will give utilities and individual’s access to information that they can understand and react to make changes quickly. They employ bi-directional communication between electricity endpoints and power stations. They help power stations with managing electricity demand and perform dynamic pricing. For instance, by using smart meters at home, consumers can view the price of electricity throughout the day and schedule tasks such that their energy bills are minimized. Deploying a smart grid comes with its own challenges. Managing the network of a smart grid is very complex and time consuming. The communication system comprises of devices that use different protocols for communication. This leads to interoperability problems and frequent intervention of the network administrator to make changes to the network configuration. By using the software-defined networking architecture, the control plane is separated from the data-forwarding plane. It allows network administrators to make configuration changes to the network from a device that centrally controls network components. One of the major challenges in SDN is the placement of controller (s) in the network. It affects the primary objective of setting up a network – fast and reliable communication of data. In this paper, we introduce the networking paradigm of smart grids and SDN architecture and go on to propose a method to find the optimal solution for the placement of controller (s) in a smart grid that uses SDN architecture.

Abstract: Body Area Networks (BAN) consists of sensors, microcontrollers interfaced with the wireless transceivers. BAN sensors are implanted or placed on the body's surface which allows for continuous monitoring of patients' health parameters. According to recent studies, BAN is a viable option for an effective transmission of detected parameters to the nearby health care centers. This transmission helps in energy consumption for further better diagnosis. With the advent of machine learning and Internet of Things (IoT), BAN has taken the dimension in achieving the better performance with limited threshold. Although, BANs are light weight implanted nodes, the problem in improving the performance still remains demur for researchers. This paper proposes the edge based BAN which integrates the powerful Bi layered feed forward (BLFF) learning models for efficient data transmission with lower consumption of energy. The proposed model works on the adaptive distance principle of Extreme Learning Machines (ELM) which detects the cluster head BAN network. The extensive experimentation has been carried out to find the consumption of energy in the network. Additionally, the performance of the proposed ELM-BLFF learning model has been compared with the other machine learning models which are integrated in BAN-IoT frameworks. An experimental result demonstrates that the proposed ELM-BLFF model outperforms the traditional learning model with 30% lesser in terms of energy consumption.

Abstract: Distribution Transformers performs a critical role and is one of the maximum critical electric gadget in electricity device network. For the reliability of the electricity device network, protection and tracking of transformer will become our first precedence. But sometimes due to overloading, leakages in transformer oil, overheating and overcurrent faults occurs in distribution transformer. To overcome such problems proper tracking of distribution transformer will become essential. This paper gives the one of the approach used for tracking of distribution transformer that's primarily based totally on IoT. This proposed device is designed and manufactured to screen and locate the faults of distribution transformer and straight away dispatched the message concerning fault to authenticated or related person. This approach may be very green and correct for tracking of fitness of distribution transformer.

Abstract: This portal represents the implementation of a car rental & pooling system. High traffic congestion is one of the issue which is faced by people in their day to day life. Carpooling system may help in reducing unnecessary traffic on roads. Sometime higher authorities encourages people to use carpool system during the period whenever there is a hike in the prices of petroleum products or when the pollution level of that state is going beyond the maximum limits. The main objective of this carpooling system will to enable different persons living in an area to use this system to minimize monthly expenses, no tension of hiring a car at higher cost. The portal aims to create a hybrid link between Car sharing services and Car rental services under the same roof. The car-sharing service enables you to connect and organize passengers for a shared ride in a very short time. Arrangements to combine cars among 2 or even more unrelated people traveling to work or school have not changed in the past. Real-Time Carpooling is based on the use and integration of multiple technologies and provides for more flexible shared trips by allowing riders and drivers to agree on sharing journeys in advance or in the short term. Dijkstra’s shortest path algorithm have been used in a separate route tab.

Abstract: Edge computing is a decentralized way of computation and storing data near to the edge performing device so that necessary physical proximity can be provided to the device and the computational data produced by that device. Previous works were focused on work in relation to Edge Computing for several anonymous sectors. Edge computing developed with the growth of various IoT devices which are present in connection with the internet for give and take of data from the cloud. In case of Edge computing data is now not needed to be directly transmit to the cloud. It is only needed to be sent to the cloud after much of its processing at the edge only. Therefore the better processing of the edge requires regular efficient improvements in the parameters which are concerned with the improved functioning of the edge devices. In this paper, we have studied existing architectures of edge computing within the IOT and Mobile edge computing to throw light on various issues like Network bandwidth capacity, throughput, response time, resource utilization, cost, execution time, energy consumption, scalability, reliability, availability etc which can be further improved for efficiency in edge computing.