Article
Computer Science, Information Systems
Suyel Namasudra
Summary: This article proposes a novel DNA computing based secure and fast Access Control Model (ACM) to improve data security and solve access control issues in a cloud environment. The theoretical analysis and experimental results demonstrate the efficiency and effectiveness of the proposed model over some well-known existing models.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Satya Deo Kumar Ram, Shashank Srivastava, K. K. Mishra
Summary: Teaching-Learning-Based Optimization (TLBO) algorithm is developed to solve single-objective optimization problems, but it performs poorly on multi-modal problems. To provide fair exploration, this study redefines the learning strategy of basic TLBO, resulting in a variant called MT-TLBO. Tested on the latest optimization benchmark functions, CEC-C06, 2019, MT-TLBO exhibits superior performance. Additionally, it successfully solves workflow scheduling problems in a cloud environment by minimizing execution cost and maximizing workload distribution on computing resources.
APPLIED SOFT COMPUTING
(2023)
Article
Engineering, Chemical
Aroosa Mubeen, Muhammad Ibrahim, Nargis Bibi, Mohammad Baz, Habib Hamam, Omar Cheikhrouhou
Summary: The study introduces an adaptive load-balanced task scheduling algorithm that reduces the makespan, maximizes resource utilization, and adaptively minimizes SLA violation. Compared to other task scheduling methods, the proposed algorithm shows significant improvements in reducing makespan, SLA violation, and resource utilization.
Article
Computer Science, Hardware & Architecture
Kashav Ajmera, Tribhuwan Kumar Tewari
Summary: Cloud data center serves tremendous workload demand due to the ever-increasing usage of internet services. Scheduling these workloads over physical servers is a combinatorial problem similar to an NP-complete problem. Dynamic workload changes result in high power consumption and SLA violation. This paper proposes a novel algorithm, ICSA-ROPE, which finds optimal VM schedules at each scheduling interval to minimize power consumption and ensure SLA. The implementation on a CloudSim simulator shows significant performance efficiency improvement compared to other algorithms.
Article
Computer Science, Information Systems
Monika Yadav, Atul Mishra
Summary: Efficient utilization of computing resources is a challenging problem in Cloud computing. An efficient task-scheduling strategy is crucial for the overall performance of the cloud system, especially in dynamic scenarios. This paper proposes an improved ordinal optimization technique to reduce the search space and achieve a minimum makespan. The technique allocates the load to the most promising schedules, resulting in optimal schedules and minimum makespan.
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Huafeng Yu
Summary: In this study, an improved particle swarm optimization (IPSO) algorithm was proposed to improve the efficiency of resource scheduling in cloud computing. Experimental results showed that the IPSO algorithm was more efficient in exploring globally optimal solutions and prevented premature convergence.
COMPLEX & INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Software Engineering
Satya Deo K. Ram, Shashank Srivastava, Krishn Kumar Mishra
Summary: The GTLBO algorithm is an improved version of the TLBO algorithm, which performs better in solving multimodal problems and has been validated through multiple tests for its performance.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2021)
Article
Computer Science, Hardware & Architecture
Suyel Namasudra
Summary: A novel cryptosystem using DNA cryptography and DNA steganography is proposed in this paper to enhance data security in cloud-based IoT infrastructure. The system encrypts and hides data, resisting various security attacks in the cloud-based IoT infrastructure.
COMPUTERS & ELECTRICAL ENGINEERING
(2022)
Article
Multidisciplinary Sciences
Muhammad Ibrahim, Muhammad Imran, Faisal Jamil, Yun-Jung Lee, Do-Hyeun Kim
Summary: The proposed Efficient Adaptive Migration Algorithm (EAMA) effectively reduces the number of migrations and SLA violation, increases resource utilization, and decreases energy consumption compared to the PACPA and RUAEE algorithms.
Article
Computer Science, Software Engineering
Satya Deo Kumar Ram, Shashank Srivastava, Krishn Kumar Mishra
Summary: Workflow scheduling is an important way to manage the execution of a workflow by providing suitable resources. Balancing conflicting objectives such as minimizing execution cost and maximizing load distribution poses a complex challenge. Developing an intelligent scheduling algorithm can identify an optimal mapping, resulting in reduced costs and fair workload distribution.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2022)
Article
Computer Science, Software Engineering
Satya Deo Kumar Ram, Shashank Srivastava, Krishn Kumar Mishra
Summary: The teaching-learning-based optimization (TLBO) algorithm is a population-based meta-heuristic algorithm inspired by the teaching-learning mechanism in a classroom. However, TLBO lacks exploration capability and performs poorly for solving multimodal problems. To address this issue, we propose a modified version called Intelligent-Teaching-Learning-Based Optimization (I-TLBO) algorithm which produces more diverse solutions and performs better for solving multimodal problems. Experimental results show that I-TLBO outperforms other algorithms and achieves significant reduction in flowtime and cost for workflow executions in a cloud datacenter.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Michael R. Jennings, Colin Turner, Raymond R. Bond, Alan Kennedy, Ranul Thantilage, Mohand Tahar Kechadi, Nhien-An Le-Khac, James McLaughlin, Dewar D. Finlay
Summary: The study aims to provide a service for processing biomedical data via a code-free interface, supporting multiple file formats and processing languages. The system developed using Python-based Django framework is effective in handling various input data types, potentially reducing bottlenecks in cross-platform development of bio-signal processing algorithms.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2021)
Article
Computer Science, Software Engineering
Tharindu B. Hewage, Shashikant Ilager, Maria A. Rodriguez, Rajkumar Buyya
Summary: Cloud computing environment simulators allow for cost-effective experimentation of infrastructure designs. Existing simulators compromise on usability and extensibility. We propose an architectural framework called CloudSim Express that enables human-readable script-based simulations while minimizing the impact on simulator extensibility. The framework achieves significant reductions in code complexity and lines of code.
SOFTWARE-PRACTICE & EXPERIENCE
(2023)
Article
Computer Science, Information Systems
Fang Fang, Xiaolun Wu
Summary: This article explores the complementarity and coexistence of 5G networks and edge computing, proposing a win-win mode for their cooperation. It summarizes applicable scenarios and potential challenges, providing valuable insights for research and development in integration deployment.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Suyel Namasudra, Rupak Chakraborty, Seifedine Kadry, Gunasekaran Manogaran, Bharat S. Rawal
Summary: This paper presents a solution to access control and security issues in a cloud environment, proposing a novel access control model that improves data access efficiency by maintaining temporary tables and significantly reducing data access time.
PEER-TO-PEER NETWORKING AND APPLICATIONS
(2021)
Article
Computer Science, Software Engineering
Sravankumar Bethi, Nageswara Rao Moparthi
Summary: The MLDC-WSN has advantages such as increasing node life, saving node power, and improving network reliability, but the sleeping features and mobility of MLDC-WSN result in topology changes that restrict the speed of neighbor node discovery. The proposed improved Bayesian clock synchronization-gossip routing protocol effectively reduces end-to-end delay and clock drift problems, while also enhancing clock synchronization by predicting the distance and movement speed of neighbors for neighbor node discovery. Simulation and analytical results showed that the proposed routing protocol significantly decreases end-to-end delay and energy consumption compared to existing algorithms.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Pratima Sharma, Nageswara Rao Moparthi, Suyel Namasudra, Vimal Shanmuganathan, Ching-Hsien Hsu
Summary: The integration of blockchain technology with the Internet of Things (IoT) can significantly impact the healthcare industry by improving efficiency, security, transparency, and providing more business opportunities. This article proposes a blockchain-based IoT architecture to enhance the security of healthcare data using Identity-Based Encryption (IBE) algorithm. The smart contract defines basic operations of the healthcare system for the benefit of stakeholders, and experiments show the proposed scheme outperforms existing renowned schemes.
Article
Biochemistry & Molecular Biology
Janaki Ramaiah Mekala, Prasanna Srinivasan Ramalingam, Sivagami Mathavan, Rajesh B. R. D. Yamajala, Nageswara Rao Moparthi, Rohil Kumar Kurappalli, Rajasekhar Reddy Manyam
Summary: This study synthesized various SAHA analogs and tested their cytotoxicity against different cancer cells. Among them, 3-Chloro-SAHA and 3-Chloro-4-fluoro SAHA showed effective cytotoxicity in all cancer cells, with the ability to inhibit specific enzyme activity and regulate gene expression. These analogs have the potential to be used in the treatment of glioblastoma.
CHEMICO-BIOLOGICAL INTERACTIONS
(2022)
Article
Computer Science, Artificial Intelligence
Joy Lal Sarkar, Abhishek Majumder
Summary: Tourism is crucial for a country's economy, as tourists face challenges in selecting suitable trips. The gTour algorithm is proposed to suggest multiple itineraries for a group, performing better than other baseline algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Joy Lal Sarkar, Abhishek Majumder, Chhabi Rani Panigrahi, Sudipta Roy, Bibudhendu Pati
Summary: A Recommendation System (RS) is an intelligent computer based system that provides valuable suggestions to users in various domains. In the tourism industry, Tourism Recommendation Systems (TRS) play a crucial role in helping tourists plan their trips by considering multiple factors such as transportation, accommodation, and tourist attractions. This paper examines various techniques, including Artificial Intelligence (AI), for solving the tourist recommendation problem and proposes future research directions to improve the Quality of Service (QoS) of RS in the tourism industry.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Gunaganti Sravanthi, Nageswara Rao Moparthi
Summary: Job scheduling is crucial in cloud computing to enhance the effectiveness of the system. Existing techniques for job scheduling lack efficiency, hence a new method called DIWGAN is proposed. This method accurately predicts future workload in the dynamic cloud environment and utilizes the AOA algorithm to optimize weight parameters, resulting in reduced power consumption at cloud data centers.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
Suyel Namasudra, S. Dhamodharavadhani, R. Rathipriya, Ruben Gonzalez Crespo, Nageswara Rao Moparthi
Summary: Big data is a combination of structured, semistructured, and unstructured data from various sources that needs to be processed before using it. Anomalies in big data refer to unusual occurrences of data that don't fit general patterns, which is a major problem. The Data Trust Method (DTM) is a technique that identifies and replaces untrustworthy data in big data using interpolation. This article discusses the application of DTM in improving the forecast quality of univariate time series (UTS) in big data using a neural network (NN) model.
Article
Computer Science, Artificial Intelligence
Sujit Kumar Das, Suyel Namasudra, Awnish Kumar, Nageswara Rao Moparthi
Summary: This paper presents an efficient approach based on Convolutional Neural Network (CNN) called AESPNet for the identification of Diabetic Foot Ulcer (DFU). Compared with other standard CNN-based schemes, AESPNet demonstrates better performance in DFU classification.
IMAGE AND VISION COMPUTING
(2023)
Article
Computer Science, Hardware & Architecture
Piyush Kumar, Mobashshirur Rahman, Suyel Namasudra, Nageswara Rao Moparthi
Summary: The advancement in technology has led to an increase in security attacks, which has resulted in the need for innovative security algorithms. In the healthcare system, the security of medical images sent over the internet is crucial. This paper proposes a novel GAN model to enhance the security of medical images by using a 2D chaotic map, hash-table, and DL. The proposed model has been tested on various medical images and outperforms other related schemes.
MOBILE NETWORKS & APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Vadipina Amarnadh, Nageswara Rao Moparthi
Summary: The rapid advancement of technologies has led to the need for additional improvements in banking and credit platforms. This paper proposes a new method for credit risk assessment in the banking sector using an Adaptive Binarized Spiking Marine Predators Neural Network, which achieves high accuracy and a short evaluation period.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Review
Computer Science, Artificial Intelligence
Vadipina Amarnadh, Nageswara Rao Moparthi
Summary: Credit risk is a significant problem in the banking and financial sectors. Continuous monitoring of payments and other assessment patterns can reduce non-performing assets and fraud risks. Artificial intelligence technology is focused on to handle the large amount of data. This review examines different learning methods to improve the performance and issues in banking and finance sectors.
INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS
(2023)
Article
Computer Science, Information Systems
Sandeep Kumar, MohdAnul Haq, Arpit Jain, C. Andy Jason, Nageswara Rao Moparthi, Nitin Mittal, Zamil S. Alzamil
Summary: This paper presents an intelligent assistant that utilizes voice recognition to identify emotions and provide support through alert actions. The proposed system successfully detects seven emotions and achieves better accuracy and faster processing time compared to existing technologies.
CMC-COMPUTERS MATERIALS & CONTINUA
(2023)
Proceedings Paper
Computer Science, Information Systems
Abhishek Majumder, Joy Lal Sarkar, Bibudhendu Pati, Chhabi Rani Panigrahi, V Ramasamy, Sudipta Roy, Vikas Kumar
Summary: The expansion and usage of the Industrial Internet of Things (IIoT) in commercial industries and technologies provide numerous possibilities for companies and businesses to expand, and intelligent devices incorporating sensors and data analysis can offer better tourist recommendations for travelers.
IEEE INFOCOM 2022 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS)
(2022)
Article
Education, Special
Monika Agrawal, Nageswara Rao Moparthi
Summary: A hybrid cross domain classification based feature selection method is proposed in this paper to improve the efficiency of aspect sentiment classification on large databases. Experimental results show that the proposed method has better overall true positive than conventional methods.
INTERNATIONAL JOURNAL OF EARLY CHILDHOOD SPECIAL EDUCATION
(2022)
