Browsing by Author "Shetty D, P.D."

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A Quantitative Method for Measuring Health of Authoritative Name Servers
(IGI Global, 2022) Adiwal, S.; Rajendran, B.; Shetty D, P.D.
The domain name system (DNS) is regarded as one of the critical infrastructure components of the global internet because a large-scale DNS outage would effectively take a typical user offline. Therefore, the internet community should ensure that critical components of the DNS ecosystem—that is, root name servers, top-level domain registrars and registries, authoritative name servers, and recursive resolvers—function smoothly. To this end, the community should monitor them periodically and provide public alerts about abnormal behavior. The authors propose a novel quantitative approach for evaluating the health of authoritative name servers – a critical, core, and a large component of the DNS ecosystem. The performance is typically measured in terms of response time, reliability, and throughput for most of the internet components. This research work proposes a novel list of parameters specifically for determining the health of authoritative name servers: DNS attack permeability, latency comparison, and DNSSEC validation. The aim is to understand the general behavior of authoritative name servers, detect sluggishness in their performance, and arrive at a score of their health through the aforesaid parameters. The effectiveness of identified parameters is evaluated by devising the corresponding probing algorithms and experimented with them among the authoritative name servers serving the world’s top 500 domains. This approach could be used periodically to assess and take necessary measures to protect authoritative domain name servers from abuse. © © 2022, IGI Global.
Analyzing Information Flow of Hashtag Networks during Elections using Sentiment Analysis and Graph Algorithms
(Institute of Electrical and Electronics Engineers Inc., 2022) Patra, C.; Shetty D, P.D.; Chakraborty, S.
An exponential increase in the usage of social media across the world creates a lot of unstructured data and cross-communication between individuals. These platforms provides opportunity to the political parties to spread their word out. The information is spread using several hashtags in the form of user-generated tagging that facilitates cross-referencing of content. These hashtag-generated networks serve as a huge reservoir of data and if analyzed systematically can help in understanding the agenda-setting of each party and how successful or unsuccessful they are. This in turn helps in predicting the outcome of the election looking from the prism of social media. In the present study, a model is proposed by combining sentiment analysis and graph techniques to look into the trending hashtag networks propagated by political parties using Twitter. The sentiment analysis gives us a sense of inclination of each tweet and thereafter it's extrapolated onto the hashtag's user network to get insights as to how the information is diffusing and how one party propagates its favorable hashtag and how the others try to counter it. The major aim of the present work is to find out the intricacies that go on in the social media space before a major election. Â© 2022 IEEE.
FLAG: fuzzy logic augmented game theoretic hybrid hierarchical clustering algorithm for wireless sensor networks
(Springer, 2022) Naik, C.; Shetty D, P.D.
Stability of the wireless sensor network (WSN) is the most critical factor in real-time and data-sensitive applications like military and surveillance systems. Many energy optimization techniques and algorithms have been proposed to extend the stability of a wireless sensor network. Clustering is a well regarded method in the research communities among them. Hence, this paper presents hybrid hierarchical artificial intelligence based clustering techniques, named FLAG and I-FLAG. The first phase of these algorithms use game-theoretic technique to elect suitable cluster heads (CHs) and later phase of the algorithms use fuzzy inference system to select appropriate super cluster heads (SCHs) among CHs. The I-FLAG is an improved version of FLAG where additional parameters like energy and distance are considered to elect CHs. Simulations are performed to check superiority of the proposed algorithms over the existing protocols like LEACH, CHEF, and CROSS. Simulation results show that the average stability period of WSN is better in FLAG and I-FLAG compared to other protocols, and so is the throughput of WSN during the stability period. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Graph energy centrality: a new centrality measurement based on graph energy to analyse social networks
(Inderscience Publishers, 2022) Mahadevi, S.; Kamath, S.S.; Shetty D, P.D.
Critical node identification, one of the key issues in social network analysis, is addressed in this article with the development of a new centrality metric termed graph energy centrality (GEC). The fundamental idea underlying this GEC measure is to give each vertex a centrality value based on the graph energy that results from vertex elimination. We show that the GEC of each vertex is asymptotically equal to two for cycle graphs and exactly equal to two for complete graphs. We further demonstrate that star graphs can be ranked using only two GEC values, whereas path graphs can be ranked using a maximum of ⌈n+12 ⌉ values. The proposed algorithm takes O(n3) time complexity to rank all vertices; hence an optimised algorithm is also being proposed considering only a few classes of graphs. The proposed algorithm ranks the nodes based on the collaborative measure of eigenvalues. © 2022 Inderscience Enterprises Ltd.. All rights reserved.