Thapar University

About: Thapar University is a education organization based out in Patiāla, Punjab, India. It is known for research contribution in the topics: Computer science & Cloud computing. The organization has 2944 authors who have published 8558 publications receiving 130392 citations.

Blockchain-Based Mutual-Healing Group Key Distribution Scheme in Unmanned Aerial Vehicles Ad-Hoc Network

Abstract: A dynamic group key is required for secure communication in the Unmanned Aerial Vehicles Ad-Hoc Network (UAANET). However, due to the unreliable wireless channel and high-dynamic topology of UAANET, the situation that a node is missing certain group key broadcast messages occurs frequently. Existing group key distribution schemes cannot be directly applied to the UAANET, because of their poor security or real-time. Therefore, we present a mutual-healing group key distribution scheme based on the blockchain. Firstly, the Ground Control Station (GCS) builds a private blockchain where the group keys distributed by GCS are recorded. Meanwhile, through the blockchain, a dynamic list of UAANET membership certificates is also managed. According to different attack models, a basic mutual-healing protocol and an enhanced one are designed based on the Longest-Lost-Chain mechanism to recover the node's lost group keys with the aid of its neighbors. Security analysis and extensive experiments show that, compared with the existing mutual-healing schemes, our proposed solution can effectively resist various attacks with small overhead on time and storage.

Improved possibility degree method for ranking intuitionistic fuzzy numbers and their application in multiattribute decision-making

Abstract: In the present paper, we define an improved possibility degree method to rank the different intuitionistic fuzzy numbers (IFNs). To achieve it, we first present some shortcomings of the existing possibility degree method and score function of IFNs. The existing shortcomings are overcome by proposing a new possibility degree measure for IFNs. The desirable properties of it are analyzed in details. Afterward, based on proposed possibility degree measure, a decision-making approach presents to solve the multiattribute decision-making (MADM) problem under the intuitionistic fuzzy set environment. Finally, a real-life case is studied to manifest the practicability and feasibility of the proposed decision-making method.

A Novel UAV-Enabled Data Collection Scheme for Intelligent Transportation System Through UAV Speed Control

Abstract: The rapid and convenient travel of people and the timely transportation of goods depend on the correct decision of the Intelligent Transportation Systems (ITS). Due to the decision-making of ITS requires a large amount of data to support, UAV-enabled periodic data collection is an effective method. However, due to the limited resources of UAV, UAV cannot directly collect data from all storage devices, resulting in unfair data collection. Therefore, we propose a UAV Speed Control based Fairness Data Collection (USCFDC) scheme. First, since the fairness of data collection will affect the decision-making of ITS, a framework for controlling the flight speed of the UAV is proposed to improve the fairness of data collection. The flight speed of UAV will slow down in areas with a large number of nodes, thereby improving the fairness of data collection. Second, a novel method is proposed to maximize the amount of data collected by UAV from each node. With this method, the value of the amount of data will be used as the dichotomous value in the dichotomy algorithm, and the UAV must collect a certain amount of data from each node. The upper and lower limits of the dichotomy algorithm are adjusted according to the time duration for UAV to collect data. Compared with previous schemes, the fairness of data collection can be improved by a maximum of 15.89% under the same flight time of UAV. Besides, the energy consumption is reduced by 49.31%–52.55% and the flight time of the UAV is reduced by 48%–62.38% when the amount of collected data is the same.

Reusability assessment for software components

Abstract: Software reuse has been used as a tool to reduce the development cost and time of the software. Nowadays, in fact, majority of software systems are being developed from an assembly of existing reusable components. In order to assess the reuse of components effectively, it is necessary to measure the reusability of these components. Paper proposes Artificial Neural Network based approach to assess the reusability of software component. This work will help developers to select the best component in terms of its reusability, which will improve the maintainability of the overall system.

Generalised Pythagorean fuzzy geometric interactive aggregation operators using Einstein operations and their application to decision making

Abstract: In this paper, we investigate the decision-making problem under the Pythagorean fuzzy environment by proposing some generalised aggregation operators. For it, we improve the existing aggregation op...