Jaypee Institute of Information Technology

About: Jaypee Institute of Information Technology is a education organization based out in Noida, Uttar Pradesh, India. It is known for research contribution in the topics: Cluster analysis & Wireless sensor network. The organization has 2136 authors who have published 3435 publications receiving 31458 citations. The organization is also known as: JIIT Noida.

Blockchain for 5G: A Prelude to Future Telecommunication

Abstract: 5G and Blockchain are potentially revolutionizing future technologies. 5G promises high rates and QoS to the users and blockchain guarantees a high level of trust and security among the peers. Applications that would be using 5G have varying needs in terms of speed, bandwidth, latency and various other factors. Augmented reality, self-driving vehicles and other ioT applications tend to use 5G for reliable and fast communication. To work seamlessly and securely in such scenarios a more specialized and efficient approach would be required. in this article, we have identified the specific areas where blockchain could be utilized to enhance the security and privacy of the 5G services offered to the users. The current challenges faced in deployment and upliftment of 5G and their related solutions based on blockchain are discussed. A model for Multi-Operator Network Slicing in 5G using blockchain is also presented along with 5G blockchain implementation.

Wearable Devices and IoT

Abstract: Wearable devices are the significant ubiquitous technology of the Internet of Things in day-to-day life. The efficient data processing in various devices such as smart clothes, smart wristwear and medical wearables along with consumer-oriented service of the IoT technology becomes inevitable in smart healthcare systems. The wearable market is currently dominated by health, safety, interaction, tracker, identity, fitness etc. Wearables increase the convergence of physical and digital world which automatically bring people into the IoT. The popularity of wearable devices is growing exponentially since it entirely changes the way how the consumers interact with the environment. 74% people believe that the wearable sensors assist them in interacting with the physical objects around them. Henceforth, one out of three smartphone users will wear minimum 5 wearables in 2020. Moreover, 60% believe that wearables in the next five years will be used not only to track health related information, although it can be used to control objects, unlock doors, authenticate identity and transactions. Wearables must be evolved to cope with the future to meet the expectations of consumers, where the users will wear many devices that is connected with the internet to interact with the physical surroundings and receive data in a seamless secure way. By 2021, smartwatches are estimated to be sold to nearly 81 million units which signifies 16% sales of total wearable device. According to the latest figure of Gartner report, the global shipment of wearable devices are anticipated to raise by 25.8% every year to $225 million (GBP 176.3 million) in 2019. Researchers also forecasted that the usage of wearable devices by the end users will increase to $42 billion (GBP 32.9 million) in 2019. In recent years, the IoT based Smart Healthcare system has influenced greatly on growing demand of wearable devices. In fact, the Wearable IoT (WIoT) devices are generating huge volume of personal health data. Enabling technologies such as cloud computing, Fog computing and Big Data play vital role in leveraging WIoT services. These enabling services over the voluminous health data enhance clinical process at health care system at remote or local servers. The traditional remote healthcare information system involves data transfer, signal processing mechanism and naive machine learning models deployed on remote server to process the medical data of patients. This technique has several demerits like they are not suitable for resource constrained wearable IoT devices. The resources such as processing, memory, energy, networking capability are limited in WIoT devices. Traditional mechanism lacks optimization of resource usage, prediction of medical condition, and dynamic assessment based on available information. Further, the naive machine learning techniques does not perform knowledge generation, decision making and discover hidden valuable patterns from the available medical data. The integrated platform in which cloud computing serves as backend computing systems, Fog computing as edge computing and Big data as platform for data analysis, knowledge generation promise to provide valid solution to several issues of Wearable IoT devices. Next, the health data generated through WIoT devices are personal and sensitive. Hence, the security and privacy of such delicate data at all level of WIoT ecosystem is essential. This part of chapter will contribute towards understanding the recent research work, issues, challenges, and opportunities in applying enabling technologies for WIoT. Also, how well the security and privacy can be incorporated is also discussed.

SVM classifier based feature selection using GA, ACO and PSO for siRNA design

Abstract: Recently there has been considerable interest in applying evolutionary and natural computing techniques for analyzing large datasets with large number of features In particular, efficacy prediction of siRNA has attracted a lot of researchers, because of large number of features involved In the present work, we have applied the SVM based classifier along with PSO, ACO and GA on Huesken dataset of siRNA features as well as on two other wine and wdbc breast cancer gene benchmark dataset and achieved considerably high accuracy and the results have been presented We have also highlighted the necessary data size for better accuracy in SVM for selected kernel Both groups of features (sequential and thermodynamic) are important in the efficacy prediction of siRNA The results of our study have been compared with other results available in the literature

Photonic-crystal-based all-optical NOT logic gate

Abstract: In the present paper, we have utilized the concept of photonic crystals for the implementation of an optical NOT gate inverter. The designed structure has a hexagonal arrangement of silicon rods in air substrate. The logic function is based on the phenomenon of the existence of the photonic bandgap and resulting guided modes in defect photonic crystal waveguides. We have plotted the transmission, extinction ratio, and tolerance analysis graphs for the structure, and it has been observed that the maximum output is obtained for a telecom wavelength of 1.554 μm. Dispersion curves are obtained using the plane wave expansion method, and the transmission is simulated using the finite element method. The proposed structure is applicable for photonic integrated circuits due to its simple structure and clear operating principle.