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S. Nandhini

Bio: S. Nandhini is an academic researcher from VIT University. The author has contributed to research in topics: Fair queuing & Weighted fair queueing. The author has an hindex of 2, co-authored 6 publications receiving 17 citations.

Papers
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Journal ArticleDOI
TL;DR: This paper neatly summarized with the comparison and prediction of epidemic curve of the first and second waves of COVID-19 pandemic to picturize the transmission rate in the both times.
Abstract: The coronavirus disease 2019 (COVID-19) pandemic has fatalized 216 countries across the world and has claimed the lives of millions of people globally. Researches are being carried out worldwide by scientists to understand the nature of this catastrophic virus and find a potential vaccine for it. The most possible efforts have been taken to present this paper as a form of contribution to the understanding of this lethal virus in the first and second wave. This paper presents a unique technique for the methodical comparison of disastrous virus dissemination in two waves amid five most infested countries and the death rate of the virus in order to attain a clear view on the behaviour of the spread of the disease. For this study, the data set of the number of deaths per day and the number of infected cases per day of the most affected countries, the USA, Brazil, Russia, India, and the UK, have been considered in the first and second waves. The correlation fractal dimension has been estimated for the prescribed data sets of COVID-19, and the rate of death has been compared based on the correlation fractal dimension estimate curve. The statistical tool, analysis of variance, has also been used to support the performance of the proposed method. Further, the prediction of the daily death rate has been demonstrated through the autoregressive moving average model. In addition, this study also emphasis a feasible reconstruction of the death rate based on the fractal interpolation function. Subsequently, the normal probability plot is portrayed for the original data and the predicted data, derived through the fractal interpolation function to estimate the accuracy of the prediction. Finally, this paper neatly summarized with the comparison and prediction of epidemic curve of the first and second waves of COVID-19 pandemic to visualize the transmission rate in the both times.

34 citations

Journal Article
TL;DR: An Enhanced Core Stateless Fair Queuing with multiple queue priority scheduler is proposed and it is shown that this technique improves the throughput of real time flows by reducing the packet loss and delay.
Abstract: The Core Stateless Fair Queuing (CSFQ) is a distributed approach of Fair Queuing (FQ). The limitations include its inability to estimate fairness during large traffic flows, which are short and bursty (VoIP or video), and also it utilizes the single FIFO queue at the core router. For improving the fairness and efficiency, we propose an Enhanced Core Stateless Fair Queuing (ECSFQ) with multiple queue priority scheduler. Initially priority scheduler is applied to the flows entering the ingress edge router. If it is real time flow i.e., VoIP or video flow, then the packets are given higher priority else lower priority. In core router, for higher priority flows the Multiple Queue Fair Queuing (MQFQ) is applied that allows a flow to utilize multiple queues to transmit the packets. In case of lower priority, the normal max1min fairness criterion of CSFQ is applied to perform probabilistic packet dropping. By simulation results, we show that this technique improves the throughput of real time flows by reducing the packet loss and delay.

8 citations

Journal ArticleDOI
TL;DR: A fuzzy based congestion detection technique for queuing in IP networks that eradicates unsolicited packet drops and improves packet delivery ratio is proposed.
Abstract: Internet Protocol (IP) has brought rapid development in many applications such as video and audio streaming, Voice-over-IP (VoIP) and e-commerce. However, these applications suffer from congestion problem, which severely worsens the network performance of real time data transmissions. In this paper, we propose a fuzzy based congestion detection technique for queuing in IP networks. This technique classifies the flow as real time and non real time and the priority scheduler prioritizes the classified flows as high and low, respectively. The congestion level of high priority flows is detected by means of fuzzy logic system. The queue delay and arrival rate are considered as input for Fuzzy logic and the level of congestion is estimated. According to the congestion level of flows, they are scheduled in two different queuing mechanisms. We simulate our technique using NS-2 and simulation results prove the efficiency of our approach. It eradicates unsolicited packet drops and improves packet delivery ratio.

2 citations

Journal ArticleDOI
S. Nandhini1
TL;DR: An improved round robin IRR queue management algorithm for elastic and inelastic traffic flows is proposed to enhance the situation of congestion and shows consistent improvement in the performance of the network.
Abstract: In current scenario, network traffic flows need a start-time fair queuing algorithm which is computationally efficient and also which can achieve maximum fairness regardless of variation in a network capacity. To enhance the situation of congestion, an improved round robin IRR queue management algorithm for elastic and inelastic traffic flows is proposed. In this approach, the traffic flows are categorised into elastic traffic flows and in-elastic traffic flows. The scheduling process in the inelastic flows is handled by the BRR scheduler algorithm since they have large capacity requirements and delay constraints and elastic flows will be scheduled using DRR-SFF. The results are simulated with NS-2 and they show consistent improvement in the performance of the network.

2 citations

Journal ArticleDOI
TL;DR: Virtual Private Network (VPN) as mentioned in this paper is a great way to secure devices and information from hackers, as described in this article, it is a rapidly developing technology that plays a critical role in WLAN by enabling safe data transmission over the Internet.
Abstract: Network security has become a big concern in the modern age. And in the last few years we have seen so many different invalid uses of our data there is many prompt for the government to control the data exploiting sites but we have to detect such VPN and delete with it so in future our data network is secure network. In almost all areas, such as online banking, online shopping, communications, companies, and organizations, the internet offers tremendous convenience. As a result, the communication network necessitates the protection of sensitive data that is stored or transferred over the internet. Because of the rapid growth of computerized devices and their widespread use the internet has resulted in data protection issues for users. Security and privacy risks have become increasingly complex in recent years, highlighting the need for a modernized secured medium to safeguard valuable data on the internet. Virtual Private Network (VPN) is a great way to secure devices and information from hackers, as described in this article. A virtual private network (VPN) is a network device that runs more than a network connection and sends encrypted data. data to prevent attackers from accessing it. The aim of a VPN is to provide vari ous security elements such as authenticity, confidentiality, and data integrity, which is why they are becoming increasingly popular, low-cost, and simple to use. Smartphones, laptops, and tablets will all use VPN services. The creation, protocols, tunneling, and protection of VPNs are also discussed in this paper. It is a rapidly developing technology that plays a critical role in WLAN by enabling safe data transmission over the Internet.

1 citations


Cited by
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Journal ArticleDOI
TL;DR: In this article , the seven-day moving average of most affected Omicron variant countries Denmark, Germany, India, Netherlands, South Africa and UK has been investigated and compared with each other.
Abstract: Omicron (B.1.1.529), a highly mutated SARS-CoV-2 variant, has emerged in the south of African continent in the November 2021. The spike protein of Omicron has 26 amino acid mutations, which makes it distinct from the other variants of concern. Researches are underway to know the virulence and transmission rate of Omicron variant. In this letter, the seven-day moving average of most affected Omicron variant countries Denmark, Germany, India, Netherlands, South Africa and UK has been investigated and compared with each other. Further, the seven-day average of daily positive Omicron cases of the prescribed countries has been predicted for the months of December 2021, January 2022 and February 2022 using the fractal interpolation method. Results elucidate that the curve of daily positive case follows the same pattern even though the new variant of concern, Omicron added in the existing variants.

59 citations

Journal ArticleDOI
TL;DR: In this article , the seven-day moving average of most affected Omicron variant countries Denmark, Germany, India, Netherlands, South Africa and UK has been investigated and compared with each other.
Abstract: Omicron (B.1.1.529), a highly mutated SARS-CoV-2 variant, has emerged in the south of African continent in the November 2021. The spike protein of Omicron has 26 amino acid mutations, which makes it distinct from the other variants of concern. Researches are underway to know the virulence and transmission rate of Omicron variant. In this letter, the seven-day moving average of most affected Omicron variant countries Denmark, Germany, India, Netherlands, South Africa and UK has been investigated and compared with each other. Further, the seven-day average of daily positive Omicron cases of the prescribed countries has been predicted for the months of December 2021, January 2022 and February 2022 using the fractal interpolation method. Results elucidate that the curve of daily positive case follows the same pattern even though the new variant of concern, Omicron added in the existing variants.

52 citations

Journal ArticleDOI
TL;DR: In this paper, the concept of SIR and fractal interpolation models is applied to predict the number of positive cases in India by approximating the epidemic curve, where the epidemic graph denotes the two-dimensional graphical representation of COVID-19-positive cases in which the abscissa denotes the time, while the ordinate provides the number.
Abstract: An unprecedented upsurge of COVID-19-positive cases and deaths is currently being witnessed across India. According to WHO, India reported an average of 3.9 lakhs of new cases during the first week of May 2021 which equals 47% of new cases reported globally and 276 daily cases per million population. In this letter, the concept of SIR and fractal interpolation models is applied to predict the number of positive cases in India by approximating the epidemic curve, where the epidemic curve denotes the two-dimensional graphical representation of COVID-19-positive cases in which the abscissa denotes the time, while the ordinate provides the number of positive cases. In order to estimate the epidemic curve, the fractal interpolation method is implemented on the prescribed data set. In particular, the vertical scaling factors of the fractal function are selected from the SIR model. The proposed fractal and SIR model can also be explored for the assessment and modeling of other epidemics to predict the transmission rate. This letter investigates the duration of the second and third waves in India, since the positive cases and death cases of COVID-19 in India have been highly increasing for the past few weeks, and India is in a midst of a catastrophizing second wave. The nation is recording more than 120 million cases of COVID-19, but pandemics are still concentrated in most states. In order to predict the forthcoming trend of the outbreaks, this study implements the SIR and fractal models on daily positive cases of COVID-19 in India and its provinces, namely Delhi, Karnataka, Tamil Nadu, Kerala and Maharashtra.

51 citations

Journal ArticleDOI
TL;DR: The experiments’ results show that NR method is more comprehensive and accurate than other method based on single metric (e.g. K-shell and closeness method).
Abstract: Node importance evaluation is of great importance in the defense and attack of aviation network, most current studies did not consider the dynamic change and specific characteristics of aviation network. On the basis of complex network theory and node deletion method, a method customized for node importance evaluation in aviation network was proposed. The main feature of the method proposed is that the node will not be returned to the network after being removed, so it is called NR method, short for “No Return”. Network efficiency, largest component size and network flow were used as the indicators of network performance. In order to quantify the three indicators, multi-attribute decision-making method was introduced, which takes individual network removed of different nodes as a solution, takes the evaluation indicators of network as the attributes of each solution. To demonstrate the method proposed, a randomly generated network, Chinese aviation network and American aviation network were chosen as test beds. The experiments’ results show that NR method is more comprehensive and accurate than other method based on single metric (e.g. K-shell and closeness method). Compared with R- strategy, NR method shows its accuracy, some potential key nodes can be discovered along with nodes deletion.

29 citations

Journal ArticleDOI
TL;DR: In this paper, a mathematical model for the co-interaction of COVID-19 and dengue transmission dynamics is formulated and analyzed using MATLAB and the fitting was done using the fmincon function in the Optimization Toolbox of MATLAB.
Abstract: A mathematical model for the co-interaction of COVID-19 and dengue transmission dynamics is formulated and analyzed. The sub-models are shown to be locally asymptotically stable when the respective reproduction numbers are below unity. Using available data sets, the model is fitted to the cumulative confirmed daily COVID-19 cases and deaths for Brazil (a country with high co-endemicity of both diseases) from February 1, 2021 to September 20, 2021. The fitting was done using the fmincon function in the Optimization Toolbox of MATLAB. Parameters denoting the COVID-19 contact rate, death rate and loss of infection acquired immunity to COVID-19 were estimated using the two data sets. The model is then extended to include optimal control strategies. The appropriate conditions for the existence of optimal control and the optimality system for the co-infection model are established using the Pontryagin's Principle. Different control strategies and their cost-effectiveness analyses were considered and simulated for the model, which include: controls against incident dengue and COVID-19 infections, control against co-infection with a second disease and treatment controls for both dengue and COVID-19. Highlights of the simulation results show that: (1) dengue prevention strategy could avert as much as 870,000 new COVID-19 infections; (2) dengue only control strategy or COVID-19 only control strategy significantly reduces new co-infection cases; (3) the strategy implementing control against incident dengue infection is the most cost-effective in controlling dengue and COVID-19 co-infections.

23 citations