Internet Of Things Reliability Research Articles

Sensor Self-Declaration of Numeric Data Reliability in Internet of Things

Sensor Self-Declaration of Numeric Data Reliability in Internet of Things

Bipolar Fuzzy PROMETHEE‐based Decision‐Making Trust Model for guaranteeing data dissemination reliability in Internet of Things

SummaryInternet of Things (IoT) is the rapidly growing domain that facilitates seamless connectivity to physical objects that makes them suitable and ideal entity of smart environment. The enforcement of trust between the physical objects is essential for completely utilizing the significant potentiality of these connected IoT objects. The traditional security strategies are not potent enough in provisioning comprehensive protection to the smart world. In this paper, Bipolar Fuzzy PROMETHEE‐based Decision‐Making Trust Model (BFPSMTM) is proposed for determining the outranking class that aids in superior trust estimation of interconnected IoT objects to guarantee reliable data dissemination. This BFPSMTM adopted different preference functions depending on the nature and type of criteria or attributes considered for evaluating the trust of the IoT objects during data dissemination. It utilized bipolar fuzzy number for assessing trust that represents an asymmetrical associated between the different judgmental factors considered for decision making. It represented the bipolar linguistic terms into trapezoidal bipolar fuzzy numbers to handle the issue of imprecise and vague knowledge during trust computation. It utilized a trapezoidal bipolar fuzzy number‐based ranking function and identified the crisp real preferences of trusted IoT objects during data dissemination. It incorporated an entropy weighting information and computed the attribute weights based on the normality condition to prevent bias during trust estimation. The results of BFPSMTM confirmed improved throughput of 22.18%, reduced delay of 20.86%, minimized energy consumption of 19.32%, and better packet forwarding rate of 19.84%, with different number of IoT objects in the environment.

Exploring edge computing in artificial intelligence using service aggregation standards

Edge computing is to support physical impairment evaluation, execution monitoring, alarm message filter based on an On-board artificial intelligence approach. Now a day a smart approach called Artificial Intelligence is being developed to pretend thinking and learning ability of human beings. Since Machine Learning is incorporated with an advanced tool it has several industrial applications such as manufacturing, petrochemical, and power plants. An artificial intelligence which is a development of edge computing (EC) in fifth-generation (5G) networks can be meet the needs of everything as a service in the networks edge. Since the theory of edge-artificial intelligence is much useful in fulfillment of AI service. Cloud computing has more computational complexity and delay, so edge computing will be preferred in terms of back-up & restore data and reliability in internet of things (IoT) based industrial applications. In industrial devices the computational speed and range of internet of things (IoT) at edge can be enhanced with aid of artificial intelligence. In this paper an AI-based service aggregation problem using edge computing in various industrial applications will be implemented. The energy efficiency, good duty cycle, storage capacity and reliability can be achieved by using Service Aggregation Edge Computing (SAEC).

Reliability in Internet of Things: Current Status and Future Perspectives

The Internet of Things (IoT) aims to transform the human society toward becoming intelligent, convenient, and efficient with potentially enormous economic and environmental benefits. Reliability is one of the main challenges that must be addressed to enable this revolutionized transformation. Based on the layered IoT architecture, this article first identifies reliability challenges posed by specific enabling technologies of each layer. This article then presents a systematic synthesis and review of IoT reliability-related literature. Reliability models and solutions at four layers (perception, communication, support, and application) are reflected and classified. Despite the rich body of works performed, the IoT reliability research is still in its early stage. Challenging research problems and opportunities are then discussed in relation to current underexplored behaviors and future new aspects of evolving IoT system complexity and dynamics.

Reliability Evaluation System and its Application of Internet of Things

This paper studies the general model of Internet of Things reliability, investigated factors affecting the reliability Internet of Things, the reliability evaluation method proposed Internet of Things from network connectivity and networking information transfer material aspects, and for the general model make reliability simulation. Research results can be used to guide the planning Internet of Things, layout and construction stages of the reliability of the forecast; reference can be used to improve the overall reliability of the study; also provides guidance on the management of network reliability.