Rajkumar Buyya

The anatomy of big data computing

2015 · Software Practice and Experience

Summary Advances in information technology and its widespread growth in several areas of business, engineering, medical, and scientific studies are resulting in information/data explosion. Knowledge discovery and decision‐making from such rapidly growing voluminous data are …

Service Level Agreement(SLA) Based SaaS Cloud Management System

2015

Cloud computing has emerged as a new computing paradigm which has revolutionized the IT industry. It has particularly transformed the licensing of software products which are now being offered as a Service on pay-as-you-go basis. …

The interplay between timeliness and scalability in cloud monitoring systems

2015

Cloud computing is a groundbreaking solution to acquire computational resources on demand. To deliver high quality cloud services and provide features such as reduced costs and availability to customers, a cloud, like any other computational …

Ensuring Security and Privacy Preservation for Cloud Data Services

2016 · ACM Computing Surveys

With the rapid development of cloud computing, more and more enterprises/individuals are starting to outsource local data to the cloud servers. However, under open networks and not fully trusted cloud environments, they face enormous security …

Monitoring of cloud computing environments

2016

Cloud computing is a technology that companies, universities, and research centers use to acquire computational resources on demand to improve availability and scalability of applications while reducing operational costs. In this context, resource management is …

Heterogeneous Job Allocation Scheduler for Hadoop MapReduce Using Dynamic Grouping Integrated Neighboring Search

2017 · IEEE Transactions on Cloud Computing

MapReduce is a crucial framework in the cloud computing architecture, and is implemented by Apache Hadoop and other cloud computing platforms. The resources required for executing jobs in a large data center vary according to …

Task-Based Budget Distribution Strategies for Scientific Workflows with Coarse-Grained Billing Periods in IaaS Clouds

2017

The use of cloud computing, particularly of Infrastructure as a Service clouds, for the execution of largescale scientific workflows has been a topic of interest in recent years. These environments offer on-demand access to all …

Sustainable Cloud Computing: Foundations and Future Directions

2018 · arXiv (Cornell University)

Major cloud providers such as Microsoft, Google, Facebook and Amazon rely heavily on datacenters to support the ever-increasing demand for their computational and application services. However, the financial and carbon footprint related costs of running …

J-OPT: A Joint Host and Network Optimization Algorithm for Energy-Efficient Workflow Scheduling in Cloud Data Centers

2019

Workflows are a popular application model used for representing scientific as well as commercial applications, and cloud data centers are increasingly used in the execution of workflow applications. Existing approaches to energy-efficient workflow scheduling in …

Unequal‐interval based loosely coupled control method for auto‐scaling heterogeneous cloud resources for web applications

2020 · Concurrency and Computation Practice and Experience

Summary Most existing quality of service (QoS) control algorithms of Web applications take into account Web Server or database connections which can be released immediately. However, many applications are deployed on virtual machines (VMs) or …

Prepartition: Load Balancing Approach for Virtual Machine Reservations in a Cloud Data Center

2021 · arXiv (Cornell University)

Load balancing is vital for the efficient and long-term operation of cloud data centers. With virtualization, post (reactive) migration of virtual machines after allocation is the traditional way for load balancing and consolidation. However, reactive …

Thermal Prediction for Efficient Energy Management of Clouds using\n Machine Learning

2020 · arXiv (Cornell University)

Thermal management in the hyper-scale cloud data centers is a critical\nproblem. Increased host temperature creates hotspots which significantly\nincreases cooling cost and affects reliability. Accurate prediction of host\ntemperature is crucial for managing the resources effectively. Temperature\nestimation …

Energy-Efficiency and Sustainability in New Generation Cloud Computing: A Vision and Directions for Integrated Management of Data Centre Resources and Workloads

2023 · arXiv (Cornell University)

Cloud computing has become a critical infrastructure for modern society, like electric power grids and roads. As the backbone of the modern economy, it offers subscription-based computing services anytime, anywhere, on a pay-as-you-go basis. Its …

iQuantum: A Case for Modeling and Simulation of Quantum Computing Environments

2023

Today’s quantum computers are primarily accessible through the cloud and are expected to be deployed in edge networks in the near future. With the rapid advancement and proliferation of quantum computing research worldwide, there has …

CloudSim express: A novel framework for rapid low code simulation of cloud computing environments

2023 · Software Practice and Experience

Abstract Cloud computing environment simulators enable cost‐effective experimentation of novel infrastructure designs and management approaches by avoiding significant costs incurred from repetitive deployments in real Cloud platforms. However, widely used Cloud environment simulators compromise on …

Service Colonies: A Novel Architectural Style for Developing Software Systems with Autonomous and Cooperative Services

2026 · ACM Transactions on Software Engineering and Methodology

This paper introduces the concept of a service colony , a novel architectural style for developing software systems. A service colony organizes a system as a group of autonomous software services that cooperate to achieve …

Federated Learning Architectures: A Performance Evaluation with Crop Yield Prediction Application

2024 · arXiv (Cornell University)

Federated learning has become an emerging technology for data analysis for IoT applications. This paper implements centralized and decentralized federated learning frameworks for crop yield prediction based on Long Short-Term Memory Network. For centralized federated …