Swarm Intelligence-Based Dynamic Virtual Machine Placement Optimization in Cloud Data Centers Sanjay Mishra, Monisha Awasthi Proceedings IEEE 2024 1st International Conference on Advances in Computing Communication and Networking Icac2n 2024, 2024 Virtual machine (VM) deployment is a critical aspect of cloud data center resource management that directly impacts performance, energy efficiency, and quality of service. Efficient VM deployment ensures optimal resource utilization, reduces power consumption, and lowers operating costs. However, the dynamic nature of cloud environments poses significant challenges to achieving optimal VM deployment. This study presents various intelligences, especially partial swarm optimization (PSO), as a powerful optimization technique for dynamic VM deployment. Many cognitive algorithms mimic the collective behavior of social organisms and provide an efficient approach to solving complex optimization problems. This study addresses the issue of deploying virtual machines to maximize resource utilization while reducing power consumption and ensuring quality of service. Extensive simulation shows that the proposed PSO-based method significantly outperforms conventional static and heuristic approaches regarding energy efficiency, resource utilization, and SLA compliance. The results show the potential of multiple intelligences in improving the operational efficiency of cloud data centers, leading to future research and practical implementation in dynamic cloud environments.
A Comparison and Analysis of Various Cloud Computing Deployment Models Sanjay Mishra, Monisha Awasthi, Ayush Chandrol, Garvit Singh, Ayapal Lande 2024 IEEE 1st Karachi Section Humanitarian Technology Conference Khi Htc 2024, 2024 A study and comparison of several cloud computing presentation models, including cloud computing, are provided in this research report. To enable businesses to make wise choices regarding their cloud strategy, it is important to comprehend the features, advantages, and factors related to each deployment option. In this post, we’ll look at some important ideas including availability, cost, scalability, security, control, flexibility, vendor loyalty, durability, redundancy, and administrative simplicity. Cloud deployment models provide businesses a variety of options to benefit from cloud computing while also taking into account their unique requirements by examining these Cost, scalability, security, control, flexibility, complexity, and vendor loyalty are the main topics of the analysis. The paper also highlights future research for cloud computing deployment models, including sophisticated integration and multi-cloud designs, performance. Optimization, security and privacy, cost and pricing, energy efficiency, interoperability and standards, and evolving market process are all integrated across many contexts. Organizations can decide which climate model is most suitable for their unique needs by understanding the traits and trade-offs of several climate models. The organizations and researchers in the climate industry may find the analysis and comparison presented in this publication to be helpful. Based on their unique requirements, organizations can determine the viability of various distribution models. Variables different cloud deployment models are reviewed and compared in this document
Automated Cricket Score Prediction Polepaka Sanjeeva, Jampana Ajith Varma, Valaparla Sathvik, Attemla Abhinav Sai Ratan, Sanjay Mishra E3s Web of Conferences, 2023 Cricket is a popular sport that involves a high degree of variability in terms of game conditions and player performance. The ability to accurately predict cricket scores could provide valuable insights for coaches, analysts, and fans, as well as offer opportunities for sports betting and fantasy games. This paper explores the use of machine learning techniques to predict cricket scores based on a variety of contextual and historical factors. The publicly available cricket dataset is used to build and evaluate several regression models that predict the total runs scored by a team in a limited-overs cricket match. This analysis includes feature engineering to extract and transform relevant input variables, model selection to compare and choose among different regression algorithms, and performance evaluation to assess the accuracy and robustness of the models. This paper also conducts sensitivity analysis to identify the most influential predictors and explore the potential biases and limitations of the models. The results indicate that machine learning techniques can effectively predict cricket scores and provide valuable insights into the factors that contribute to team performance. Automated cricket prediction is useful for cricket teams, coaches, and analysts who seek to improve their game strategies and player selection, as well as for sports betting and fantasy game platforms that seek to provide more accurate experiences for users.
Performance analysis of 4-bit ternary adder and multiplier using CNTFET for high speed arithmetic circuits Venkataiah C., Mallikarjuna Rao Y., Manjula Jayamma, Rambabu S., Linga Murthy M.K., Laith H. Alzubaidi, Sanjay Mishra E3s Web of Conferences, 2023 Multiple valued logic (MVL) can represent an exponentially higher number of data/information compared to the binary logic for the same number of logic bits. Compared to the conventional devices, the emerging device technologies such as Graphene Nano Ribbon Field Effect Transistor (GNRFET) and carbon nanotube field effect transistor (CNTFET) appears to be very promising for designing MVL logic gates and arithmetic circuits due to some exceptional electrical properties such as the ability to control the threshold voltage. This variation of the threshold voltage is one of the prescribed techniques to achieve multiple voltage levels to implement the MVL circuit.This work presents a 4-input ternary adder using carbon nanotube field effect transistor (CNTFET). Many researchers have been done work on implementation of ternary adders and multipliers. But no one has done the comparison of this proposed ternary adder with different types of nano transistors. Hence this work has been proposed a design of low power and high speed 4-input adder which will be useful for designing of fast ternary multipliers. All the proposed designs have been simulated using emerging device such as CNTFET at 32nm technology node. From the simulations, we have calculated the power consumptions of the proposed designs, carry propagation delay and power delay product for the CNTFET circuits. It has been observed that CNTFET based proposed logic circuits given a better performance than the conventional logical circuits.
Design and Development of Embedded Controller with Wireless Sensor for Power Monitoring through Smart Interface Design Models S M Ramesh, S Rajeshkannan, Sumit Pundir, Navdeep Dhaliwal, Sanjay Mishra, B Shanthi Saravana Proceedings of the 2023 2nd International Conference on Augmented Intelligence and Sustainable Systems Icaiss 2023, 2023 The advanced innovation in the power electronics system paved a numerous ways in the development and monitoring of power consumption. This helps to maintain the demand side management to adopt several measures in limiting the consumption of power. This is implemented through embedded system with artificial intelligence techniques. These systems are highly reliable and stable in performing operations. The important objective of the proposed system includes the power monitoring and controlling through embedded controllers. These systems are integrated with wireless sensor network for enabling data storage in the network with higher security concerns. The stored data are used for optimization process. This includes image processing techniques with feature extraction. The power monitoring system is implemented by automatically evaluating the environmental conditions through sensors and functions based upon the priority. They are implemented with remote monitoring and control systems with providing real time information to the user’s mobile phone. The communication network are enhanced through the internet of things. This is enhanced through priority scheduling techniques through random forest algorithm. Thus, the overall system helps in enabling optimum power consumption through machine learning.
Design and Development of Exploratory Model in AI for Addressing CO2 Emission for a Sustainable Future Parminder Singh, Saurabh Dhyani, Harish Dutt Sharma, Sanjay Mishra, Yogesh Juyal, Amarjeet Rawat 2023 4th International Conference on Computation Automation and Knowledge Management Iccakm 2023, 2023 The global challenge of carbon dioxide (CO2) emissions and their environmental impact form the core focus of this research endeavor. Through an exploration of various visualizations and analyses, this study delves into the intricate dynamics surrounding CO2 emissions, providing insights into global trends, country-specific trajectories, and the imperative for sustainable practices. Beginning with an overview of worldwide CO2 emissions, the study uncovers the exponential growth trajectory, highlighting the urgency for proactive measures to address this issue. The research further dissects the top 10 CO2 emitting countries over the last decade, emphasizing the importance of collective efforts in emission reduction. Shifting the lens to India's emissions, the study examines the century-long journey of CO2 emissions, capturing the nuanced shifts from the early 20th century to the present day. The graph's portrayal underscores the pivotal role of industrialization, urbanization, and demographic changes in shaping India's carbon footprint. The turning point around 1960 signifies a transformational moment that propelled emissions on a steep upward trajectory. Economic growth emerges as both a driving force and a challenge. The narrative concludes with an exploration of future research avenues, spanning alternative energy sources, policy frameworks, technological innovations, behavioral changes, and inclusive strategies. This study underscores the complexity of the emissions landscape, weaving together historical insights, present-day challenges, and a visionary perspective for the future. As societies navigate the intricate balance between development and environmental responsibility, this research serves as a compass, guiding us toward a world where CO2 emissions are not just numbers but a collective call to action for a sustainable and harmonious future.
