Fuzzy Logic Approach for Routing in Internet of Things Network

A performance of network is evaluated by considering different parameters. The network lifetime depends on many factors Residual energy, Link lifetime and Delay. The Major Challenge in IoT is to the increased lifetime of low power and lossy network (RPL).The process considering input and output to evaluate Network performance by considering the above factors. The proposed system makes use of FIS (Fuzzy Inference System) for selecting the best path to maximize network lifetime. The outcome obtained by using MATLAB and Network performance is increased. The excellent route is selected if Residual Energy is 194, Link quality is 51.2 and Delay is 1.05 then excellent route quality is 73.4%

Business Process Model for IOT Based Systems Operations

The internet of things (IoT) is an innovative and advanced high-level IT development that provides the connection between a large network of devices equipped with numerous computing capabilities, actuation, and sensing with the help of internet connection, consequently providing multifarious novel services regarding smart systems. All around the globe the attractive big data analytics and IoT services are allowing initiatives regarding smart systems. Business processes are commonly executed inside the application systems where computers, objects of IoT as well as humans participate. However, for the system-supported processes, the use of IoT technology is still facing the problem of the absence of a standard system architecture that is essential to manage the coordination in a smart IoT environment. Business process management (BPM) is regarded as a substantial technique for designing, controlling, and improving the processes of a system. This article introduces a BPM modeling approach for IoT-based systems operation exploits IoT using BPM by adopting an IoT framework architecture and considering IoT data for interaction in a defined process model. The methodology has been carried out on top of current BPM modeling notions and system techniques for formal representations of the system and also to get through the challenges of collaboration and connection

Increasing the Use of Home Automation Technology Using IoT Application

The Internet of Things (IoT) is the webworking of physical contraptions and different articles which include an introduced structure with model availability that connect to gather and exchange information. Home automation is a theme which picks up ubiquity step by step, because of large advantages. By just associating home apparatus electrical devices to the web or cloud storage, anyone can accomplish home automation. The purpose behind this surge demand of system empowered home computerization is to achieve the peak as of late for its effortlessness and comparable affordability. Stages dependent on cloud computing help to interface with the things surrounding everybody, so one can think that it's simple to get to everything without exception whenever and place in an easy way to use exceptionally characterized entries. Subsequently, cloud goes about as a front end to get to IoT. After few years, this framework which can control devices through remote based system or cloud based methodology. This model will use IoT based home computerization framework whose target is to make a home automation model that gives the users unlimited oversight over all control by remote bits of their home requiring little to no effort. It will give smarter process and services and reduce human effort. This model focused on framework of smart home automation. This model will further be extended with discuss about IoT security, and yet few challenges which will also be addressed. I likewise portrayed about persistent verification system which incorporates relevant data for client confirmation in structure of smart home

A REVIEW ON INTERNET OF THINGS ARCHITECTURE FOR BIG DATA PROCESSING

The importance of big data implementations is increased due to large amount of gathered data via the online gates. The businesses and organizations would benefit from the big data analysis i.e. analyze the political, market, and social interests of the people. The Internet of Things (IoT) presents many facilities that support the big data transfer between various Internet objects. The integration between the big data and IoT offer a lot of implementations in the daily life like GPS, Satellites, and airplanes tracking. There are many challenges face the integration between big data transfer and IoT technology. The main challenges are the transfer architecture, transfer protocols, and the transfer security. The main aim of this paper is to review the useful architecture of IoT for the purpose of big data processing with the consideration of the various requirements such as the transfer protocol. This paper also reviews other important issues such as the security requirements and the multiple IoT applications. In addition, the future directions of the IoT-Big data are explained in this paper

Lightweight novel trust based framework for IoT enabled wireless network communications

For IoT enabled networks, the security and privacy is one of the important research challenge due to open nature of wireless communications, especially for the networks like Vehicular Ad hoc Networks (VANETs). The characteristics like heterogeneity, constrained resources, scalability requirements, uncontrolled environment etc. makes the problems of security and privacy even more challenging. Additionally, the high degree of availability needs of IoT networks may compromise the integrity and confidentially of communication data. The security threats mainly performed during the operations of data routing, hence designing the secure routing protocol main research challenge for IoT networks. In this paper, to design the lightweight security algorithm the use of Named Data Networking (NDN) which provides the benefits applicable for IoT applications like built-in data provenance assurance, stateful forwarding etc. Therefore the novel security framework NDN based Cross-layer Attack Resistant Protocol (NCARP) proposed in this paper. In NCARP, we designed the cross-layer security technique to identify the malicious attackers in network to overcome the problems like routing overhead of cryptography and trust based techniques. The parameters from the physical layer, Median Access Control (MAC) layer, and routing/network layer used to compute and averages the trust score of each highly mobility nodes while detecting the attackers and establishing the communication links. The simulation results of NCARP is measured and compared in terms of precision, recall, throughput, packets dropped, and overhead rate with state-of-art solutions

A lightweight blockchain based framework for underwater ioT

The Internet of Things (IoT) has facilitated services without human intervention for a wide range of applications, including underwater monitoring, where sensors are located at various depths, and data must be transmitted to surface base stations for storage and processing. Ensuring that data transmitted across hierarchical sensor networks are kept secure and private without high computational cost remains a challenge. In this paper, we propose a multilevel sensor monitoring architecture. Our proposal includes a layer-based architecture consisting of Fog and Cloud elements to process and store and process the Internet of Underwater Things (IoUT) data securely with customized Blockchain technology. The secure routing of IoUT data through the hierarchical topology ensures the legitimacy of data sources. A security and performance analysis was performed to show that the architecture can collect data from IoUT devices in the monitoring region efficiently and securely. © 2020 by the authors. Licensee MDPI, Basel, Switzerland

Three Branch Diversity Systems for Multi-Hop IoT Networks

Internet of Things (IoT) is an emerging technological paradigm connecting numerous smart objects for advanced applications ranging from home automation to industrial control to healthcare. The rapid development of wireless technologies and miniature embedded devices has enabled IoT systems for such applications, which have been deployed in a variety of environments. One of the factors limiting the performance of IoT devices is the multipath fading caused by reflectors and attenuators present in the environment where these devices are deployed. Leveraging polarization diversity is a well-known technique to mitigate the deep signal fades and depolarization effects caused by multipath. However, neither experimental validation of the performance of polarization diversity antenna with more than two branches nor the potency of existing antenna selection techniques on such antennas in practical scenarios has received much attention. The objectives of this dissertation are threefold. First, to demonstrate the efficacy of a tripolar antenna, which is specifically designed for IoT devices, in harsh environments through simulations and experimental data. Second, to develop antenna selection strategies to utilize polarized signals received at the antenna, considering the restrictions imposed due to resource limitations of the IoT devices. Finally, to conduct comparative analyses on the existing standard diversity techniques and proposed approaches, in conjunction with experimental data. Accordingly, this dissertation presents the testing results of tripolar antenna integrated with Arduino based IoT devices deployed in environments likely to be experienced by IoT devices in real life applications. Both simulation and experimental results from single point-to-point wireless links demonstrate the advantage of utilizing tripolar antennas in harsh propagation conditions over single branch antenna. Motivated by these empirical results, we deploy a small-scale IoT network with tripolar antenna based nodes to analyze the impact of tripolar antenna on neighbor nodes performance as well as to investigate end-to-end network performance. This work illustrates that the selection of antenna branches, while considering network architecture and the level of congestion on the repeater nodes, minimizes excessive antenna switching and energy consumption. Similar results are shown for IoT networks with predetermined and dynamic routing protocols, where the proposed techniques yielded lower energy consumption than the conventional diversity schemes. Furthermore, a probabilistic, low complexity antenna selection approach based on Hidden Markov model is proposed and implemented on wireless sensor nodes aiming to reduce energy consumption and improve diversity gain. Finally, we develop a dual-hop based technique where a node selects the antenna element for optimal performance based on its immediate network neighbors antenna configuration status during selection. The performance of the proposed technique, which is verified through simulation and measured data, illustrates the importance of considering network-wide evaluations of antenna selection techniques

A patient agent controlled customized blockchain based framework for internet of things

Although Blockchain implementations have emerged as revolutionary technologies for various industrial applications including cryptocurrencies, they have not been widely deployed to store data streaming from sensors to remote servers in architectures known as Internet of Things. New Blockchain for the Internet of Things models promise secure solutions for eHealth, smart cities, and other applications. These models pave the way for continuous monitoring of patient’s physiological signs with wearable sensors to augment traditional medical practice without recourse to storing data with a trusted authority. However, existing Blockchain algorithms cannot accommodate the huge volumes, security, and privacy requirements of health data. In this thesis, our first contribution is an End-to-End secure eHealth architecture that introduces an intelligent Patient Centric Agent. The Patient Centric Agent executing on dedicated hardware manages the storage and access of streams of sensors generated health data, into a customized Blockchain and other less secure repositories. As IoT devices cannot host Blockchain technology due to their limited memory, power, and computational resources, the Patient Centric Agent coordinates and communicates with a private customized Blockchain on behalf of the wearable devices. While the adoption of a Patient Centric Agent offers solutions for addressing continuous monitoring of patients’ health, dealing with storage, data privacy and network security issues, the architecture is vulnerable to Denial of Services(DoS) and single point of failure attacks. To address this issue, we advance a second contribution; a decentralised eHealth system in which the Patient Centric Agent is replicated at three levels: Sensing Layer, NEAR Processing Layer and FAR Processing Layer. The functionalities of the Patient Centric Agent are customized to manage the tasks of the three levels. Simulations confirm protection of the architecture against DoS attacks. Few patients require all their health data to be stored in Blockchain repositories but instead need to select an appropriate storage medium for each chunk of data by matching their personal needs and preferences with features of candidate storage mediums. Motivated by this context, we advance third contribution; a recommendation model for health data storage that can accommodate patient preferences and make storage decisions rapidly, in real-time, even with streamed data. The mapping between health data features and characteristics of each repository is learned using machine learning. The Blockchain’s capacity to make transactions and store records without central oversight enables its application for IoT networks outside health such as underwater IoT networks where the unattended nature of the nodes threatens their security and privacy. However, underwater IoT differs from ground IoT as acoustics signals are the communication media leading to high propagation delays, high error rates exacerbated by turbulent water currents. Our fourth contribution is a customized Blockchain leveraged framework with the model of Patient-Centric Agent renamed as Smart Agent for securely monitoring underwater IoT. Finally, the smart Agent has been investigated in developing an IoT smart home or cities monitoring framework. The key algorithms underpinning to each contribution have been implemented and analysed using simulators.Doctor of Philosoph