True and Reliable Information Sharing in VANET Environment

VANET is a special class of mobile ad hoc network. Data dissemination in VANET is a challenge due to its dynamically changing topology, and researcher's works very hard to minimize this problem and new approaches from them have done this. Now data dissemination in VANET is easy as compared to five years back. But now a new challenge comes in front of researchers that how they decide that information which has to be forwarded into the network is valid and how can they make the network trustworthy. In this paper, we proposed a new approach in which a vehicle can check that information that comes to it for forwarding is true or not and, on its decision, data disseminated in the network. By this, we can make the VANET network trustworthy, and our experimental results show the same

Review of SDN-based load-balancing methods, issues, challenges, and roadmap

The development of the Internet and smart end systems, such as smartphones and portable laptops, along with the emergence of cloud computing, social networks, and the Internet of Things, has brought about new network requirements. To meet these requirements, a new architecture called software-defined network (SDN) has been introduced. However, traffic distribution in SDN has raised challenges, especially in terms of uneven load distribution impacting network performance. To address this issue, several SDN load balancing (LB) techniques have been developed to improve efficiency. This article provides an overview of SDN and its effect on load balancing, highlighting key elements and discussing various load-balancing schemes based on existing solutions and research challenges. Additionally, the article outlines performance metrics used to evaluate these algorithms and suggests possible future research directions

Exploring Path Computation Techniques in Software-Defined Networking: A Review and Performance Evaluation of Centralized, Distributed, and Hybrid Approaches

Software-Defined Networking (SDN) is a networking paradigm that allows network administrators to dynamically manage network traffic flows and optimize network performance. One of the key benefits of SDN is the ability to compute and direct traffic along efficient paths through the network. In recent years, researchers have proposed various SDN-based path computation techniques to improve network performance and reduce congestion. This review paper provides a comprehensive overview of SDN-based path computation techniques, including both centralized and distributed approaches. We discuss the advantages and limitations of each approach and provide a critical analysis of the existing literature. In particular, we focus on recent advances in SDN-based path computation techniques, including Dynamic Shortest Path (DSP), Distributed Flow-Aware Path Computation (DFAPC), and Hybrid Path Computation (HPC). We evaluate three SDN-based path computation algorithms: centralized, distributed, and hybrid, focusing on optimal path determination for network nodes. Test scenarios with random graph simulations are used to compare their performance. The centralized algorithm employs global network knowledge, the distributed algorithm relies on local information, and the hybrid approach combines both. Experimental results demonstrate the hybrid algorithm's superiority in minimizing path costs, striking a balance between optimization and efficiency. The centralized algorithm ranks second, while the distributed algorithm incurs higher costs due to limited local knowledge. This research offers insights into efficient path computation and informs future SDN advancements. We also discuss the challenges associated with implementing SDN-based path computation techniques, including scalability, security, and interoperability. Furthermore, we highlight the potential applications of SDN-based path computation techniques in various domains, including data center networks, wireless networks, and the Internet of Things (IoT). Finally, we conclude that SDN-based path computation techniques have the potential to significantly improvement in-order to improve network performance and reduce congestion. However, further research is needed to evaluate the effectiveness of these techniques under different network conditions and traffic patterns. With the rapid growth of SDN technology, we expect to see continued development and refinement of SDN-based path computation techniques in the future

An Optimised Shortest Path Algorithm for Network Rotuting & SDN: Improvement on Bellman-Ford Algorithm

Network routing algorithms form the backbone of data transmission in modern network architectures, with implications for efficiency, speed, and reliability. This research aims to critically investigate and compare three prominent routing algorithms: Bellman-Ford, Shortest Path Faster Algorithm (SPFA), and our novel improved variant of Bellman-Ford, the Space-efficient Cost-Balancing Bellman-Ford (SCBF). We evaluate the performance of these algorithms in terms of time and space complexity, memory utilization, and routing efficacy, within a simulated network environment. Our results indicate that while Bellman-Ford provides consistent performance, both SPFA and SCBF present improvements in specific scenarios with the SCBF showing notable enhancements in space efficiency. The innovative SCBF algorithm provides competitive performance and greater space efficiency, potentially making it a valuable contribution to the development of network routing protocols. Further research is encouraged to optimize and evaluate these algorithms in real-world network conditions. This study underscores the continuous need for algorithmic innovation in response to evolving network demands

An Improved Iris Recognition System with Template Security using CT and SVD

The Iris biometric system is the most prominent method for identification of individual. Many researchers have been presented iris recognition methods from decade but a fully suitable solution for real world scenario is not implemented yet. The two major issues are responsible for it. First is no accurate method to operate on non-ideal iris images with high recognition rate. Second one is deployment of system with high security on the existing real world situations. In this Paper, the above mentioned problems are solved to an extent. An accurate and secured iris template encoding method is used for generate highly secured encoded binary pattern for iris template. Contourlet transform and Singular Value decomposition is used for this purpose. Beside this security feature, the proposed method used best combinations of algorithm for provide high accuracy as compared to conventional system of iris recognition. In Our approach IIT Delhi iris database is used as input image. Iris region from eye image is extracted by canny edge detection and Hough transforms to achieve high recognition rate. Daugman’s rubber sheet model is used for normalization. Security for normalized template is provided by Contourlet transform and Singular Value Decomposition. At last stage the combination of Hamming Distance and Normalized Correlation coefficient is used to achieve high recognition rate. So at each stage of iris recognition system all methods and algorithms are performed very well and provide higher accuracy as compared to existing iris recognition system

Data Security Using Stegnography and Quantum Cryptography

Stegnography is the technique of hiding confidential information within any media. In recent years variousstegnography methods have been proposed to make data more secure. At the same time differentsteganalysis methods have also evolved. The number of attacks used by the steganalyst has only multipliedover the years. Various tools for detecting hidden informations are easily available over the internet, sosecuring data from steganalyst is still considered a major challenge. While various work have been done toimprove the existing algorithms and also new algorithms have been proposed to make data behind theimage more secure. We have still been using the same public key cryptography like Deffie-Hellman andRSA for key negotiation which is vulnerable to both technological progress of computing power andevolution in mathematics, so in this paper we have proposed use of quantum cryptography along withstegnography. The use of this combination will create key distribution schemes that are uninterceptable thusproviding our data a perfect security.Keywords: Stegnography, Steganalysis, Steganalyst, Quantum Cryptography

Microbiota Assessment of Pediatric Simple and Complex Acute Appendicitis

Funding Information: This study was funded by Latvian Academy of Science and Riga Stradins University. Publisher Copyright: © 2022 by the authors.Background and Objectives. The aim of this study is to determine the prevailing microbiota in samples from pediatric patients with acute appendicitis, as well as evaluate the antibacterial sensitivity of the isolated microorganisms, comparing the data obtained with the clinic's antibacterial therapy guidelines. Materials and Methods. The study group consisted of 93 patients between the ages of 7 and 18. All patients underwent a laparoscopic or conventional appendectomy. The children were hospitalized with signs and symptoms suggestive of acute appendicitis. Microbiological cultures from the appendix and abdominal cavity were collected intraoperatively. Results. E. coli was identified in most cases irrespective of the clinical presentation of acute appendicitis. Most strains were susceptible to ampicillin and amoxicillin/clavulanic acid. Five strains of E. coli produced extended spectrum beta-lactamase (ESBL). Pseudomonas aeruginosa (P. aeruginosa) was the second most commonly isolated causative agent. Furthermore, it was common in cases of acute complex appendicitis. Most strains of P. aeruginosa were resistant to amoxicillin/clavulanic acid, ertapenem, ampicillin and cefotaxime, yet were susceptible to ceftazidime. Regardless of the clinical presentation, the samples yielded mixed isolates. Conclusion. E. coli is the main causative agent of acute appendicitis in the pediatric population displaying susceptibility to various antibiotics. P. aeruginosa was more prevalent in cases of acute complex appendicitis. P. aeruginosa isolates were susceptible to ceftazidime; however, they were resistant to cefotaxime, which should, therefore, be removed from guidelines for empirical antibacterial treatment of acute appendicitis due to phenotypic resistance of P. aeruginosa. We recommend antibiotics with distinct implementation to avoid antibiotic resistance.publishersversionPeer reviewe

Case series of variable acute appendicitis in children with sars-cov-2 infection

Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.This case series study consists of six children, aged 5–16 years, admitted to a centralized tertiary paediatric hospital serving a population of 1.9 million with acute appendicitis in the setting of SARS-CoV-2 infection. From the beginning of the pandemic in March 2020 until August 2021, 121 COVID-19-positive children were admitted to the hospital. A total of 49 (40.5%) of these patients presented with gastrointestinal symptoms, of which six were diagnosed with acute appendicitis. Five underwent an appendectomy, while one was treated conservatively. To date, it has been reported that appendicitis may have a plausible association with SARS-CoV-2 infection in children. With COVID-19 cases rising, every medical specialist, including all paediatric surgeons, must be ready to treat common acute diseases with SARS-CoV-2 infection as a comorbidity. Providers should consider testing for this infection in paediatric patients with severe gastrointestinal symptoms. Non-surgical treatment of acute appendicitis in children may gain new importance during and after the COVID-19 pandemic. Further studies are needed to prove the link of causality between COVID-19 and acute appendicitis in children.publishersversionPeer reviewe

Culture Based Evaluation of Microbiota in Children with Acute Appendicitis

Treatment strategies for acute uncomplicated appendicitis have evolved and now conservative antibacterial treatment is recommended over surgical treatment, especially for paediatric patients. The aim of this study was to evaluate microbiota in paediatric patients with acute uncomplicated and complicated appendicitis, and antibacterial susceptibility of the causative microorganisms. Bacteriological identification was conducted using the VITEK2 analyser. Antibacterial susceptibility tests were performed and the results were evaluated in accordance with the recommendations of the European Committee on Antimicrobial Susceptibility Testing (EUCAST) “Clinical breakpoints and dosing of antibiotics” (Version 7.0, January 2019). Serodiagnosis of Yersinia enterocolitica was performed using indirect haemagglutination. The results revealed differences in microbiota in cases of acute complicated and acute uncomplicated appendicitis. Pseudomonas aeruginosa was identified more frequently in cases of acute complicated appendicitis. Mixed culture was prevalent in cases of both acute complicated and acute uncomplicated appendicitis. Very few positive extended spectrum beta-lactamase (ESBL) Escherichia coli cultures were identified. Most of strains of Pseudomonas aeruginosa were resistant to amoxicillin with clavulanic acid, ertapenem, ampicillin and cefotaxime. Some of E. coli isolates were resistant to ampicillin and to amoxicillin with clavulanic acid.publishersversionPeer reviewe

Serum and Urine Biomarker Leucine-Rich Alpha-2 Glycoprotein 1 Differentiates Pediatric Acute Complicated and Uncomplicated Appendicitis

Funding Information: This research received grant support from the Latvian Council of Science and Riga?s Stradins University. Grant support was used for the laboratory materials for biological specimen collection. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Purpose: This prospective, single-center cohort study analyzes the potential of inflammatory protein mediator leucine-rich alpha-2 glycoprotein 1 (LRG1) for the early and accurate diagnosis of acute appendicitis (AA), and differentiation of acute complicated (AcA) from uncomplicated appendicitis (AuA). Methods: Participants were divided into the AcA, AuA, and control groups, and their serum (s-LRG1) and urine LRG1 (u-LRG1) levels were assayed preoperatively on the second and fifth postoperative days. Results: 153 patients participated, 97 had AA. Preoperative u-LRG1 with a cut-off value of 0.18 µg/mL generated an area under the receiver operated characteristic (AUC) curve of 0.70 (95% CI 0.62–0.79) for AA versus control (p < 0.001), while the results for AcA versus AuA were not significant (AUC 0.60, 95% CI 0.49–0.71, p = 0.089). The s-LRG1 levels of AA versus the control with a cut-off value of 51.69 µg/mL generated an AUC of 0.94 (95% CI 0.91–0.99, p < 0.001). The cut-off value of s-LRG1 was 84.06 µg/mL for diagnosis of AcA from AuA, and therefore, significant (AUC 0.69, 95% CI 0.59–0.80, p = 0.001). Conclusions: LRG1 exhibited excellent diagnostic performance as an inexpensive, non-invasive, rapid, and accurate biomarker able to reflect the pathogenesis of AA. LRG1 has the potential to replace advanced imaging to diagnose clinically ambiguous AA cases.publishersversionPeer reviewe