Search Results for author: Rajkumar Buyya

Found 18 papers, 5 papers with code

Metaverse: A Vision, Architectural Elements, and Future Directions for Scalable and Realtime Virtual Worlds

no code implementations21 Aug 2023 Leila Ismail, Rajkumar Buyya

With the emergence of Cloud computing, Internet of Things-enabled Human-Computer Interfaces, Generative Artificial Intelligence, and high-accurate Machine and Deep-learning recognition and predictive models, along with the Post Covid-19 proliferation of social networking, and remote communications, the Metaverse gained a lot of popularity.

Cloud Computing Marketing

Reinforcement Learning (RL) Augmented Cold Start Frequency Reduction in Serverless Computing

no code implementations15 Aug 2023 Siddharth Agarwal, Maria A. Rodriguez, Rajkumar Buyya

It features serverless attributes by eliminating resource management responsibilities from developers and offers transparent and on-demand scalability of applications.

Cloud Computing Management +3

A Deep Recurrent-Reinforcement Learning Method for Intelligent AutoScaling of Serverless Functions

no code implementations11 Aug 2023 Siddharth Agarwal, Maria A. Rodriguez, Rajkumar Buyya

Therefore, in this paper, we investigate a model-free Recurrent RL agent for function autoscaling and compare it against the model-free Proximal Policy Optimisation (PPO) algorithm.

Anomaly Detection reinforcement-learning

Classification of Methods to Reduce Clinical Alarm Signals for Remote Patient Monitoring: A Critical Review

no code implementations8 Feb 2023 Teena Arora, Venki Balasubramanian, Andrew Stranieri, Shenhan Mai, Rajkumar Buyya, Sardar Islam

This study aims to critically review the existing literature to identify the causes of these false-positive alarms and categorize the various interventions used in the literature to eliminate these causes.

Clinical Knowledge

A Distributed Deep Reinforcement Learning Technique for Application Placement in Edge and Fog Computing Environments

no code implementations24 Oct 2021 Mohammad Goudarzi, Marimuthu Palaniswami, Rajkumar Buyya

Fog/Edge computing is a novel computing paradigm supporting resource-constrained Internet of Things (IoT) devices by the placement of their tasks on the edge and/or cloud servers.

Edge-computing

Energy and Thermal-aware Resource Management of Cloud Data Centres: A Taxonomy and Future Directions

no code implementations6 Jul 2021 Shashikant Ilager, Rajkumar Buyya

This paper investigates the existing resource management approaches in Cloud Data Centres for energy and thermal efficiency.

Management

Machine Learning-based Orchestration of Containers: A Taxonomy and Future Directions

no code implementations24 Jun 2021 Zhiheng Zhong, Minxian Xu, Maria Alejandra Rodriguez, Chengzhong Xu, Rajkumar Buyya

Containerization is a lightweight application virtualization technology, providing high environmental consistency, operating system distribution portability, and resource isolation.

BIG-bench Machine Learning Management

STOPPAGE: Spatio-temporal Data Driven Cloud-Fog-Edge Computing Framework for Pandemic Monitoring and Management

no code implementations4 Apr 2021 Shreya Ghosh, Anwesha Mukherjee, Soumya K Ghosh, Rajkumar Buyya

Several researches and evidence show the increasing likelihood of pandemics (large-scale outbreaks of infectious disease) which has far reaching sequels in all aspects of human lives ranging from rapid mortality rates to economic and social disruption across the world.

Edge-computing Management

SAED: Edge-Based Intelligence for Privacy-Preserving Enterprise Search on the Cloud

1 code implementation26 Feb 2021 Sakib M Zobaed, Mohsen Amini Salehi, Rajkumar Buyya

We propose Smartness At Edge (SAED mechanism that offers intelligence in the form of semantic and personalized search at the edge tier while maintaining privacy of the search on the cloud tier.

Privacy Preserving

Dynamic Scheduling for Stochastic Edge-Cloud Computing Environments using A3C learning and Residual Recurrent Neural Networks

1 code implementation1 Sep 2020 Shreshth Tuli, Shashikant Ilager, Kotagiri Ramamohanarao, Rajkumar Buyya

The ubiquitous adoption of Internet-of-Things (IoT) based applications has resulted in the emergence of the Fog computing paradigm, which allows seamlessly harnessing both mobile-edge and cloud resources.

Cloud Computing Scheduling

Artificial Intelligence (AI)-Centric Management of Resources in Modern Distributed Computing Systems

no code implementations9 Jun 2020 Shashikant Ilager, Rajeev Muralidhar, Rajkumar Buyya

Contemporary Distributed Computing Systems (DCS) such as Cloud Data Centres are large scale, complex, heterogeneous, and distributed across multiple networks and geographical boundaries.

Distributed Computing Management

APEX: Adaptive Ext4 File System for Enhanced Data Recoverability in Edge Devices

2 code implementations3 Oct 2019 Shreshth Tuli, Shikhar Tuli, Udit Jain, Rajkumar Buyya

We demonstrate the effectiveness of APEX through a case study of overwriting surveillance videos by CryPy malware on Raspberry-Pi based Edge deployment and show 678% and 32% higher recovery than Ext4 and current state-of-the-art File Systems.

Operating Systems

FogBus: A Blockchain-based Lightweight Framework for Edge and Fog Computing

2 code implementations29 Nov 2018 Shreshth Tuli, Redowan Mahmud, Shikhar Tuli, Rajkumar Buyya

The requirement of supporting both latency sensitive and computing intensive Internet of Things (IoT) applications is consistently boosting the necessity for integrating Edge, Fog and Cloud infrastructure.

Distributed, Parallel, and Cluster Computing

Task Runtime Prediction in Scientific Workflows Using an Online Incremental Learning Approach

no code implementations10 Oct 2018 Muhammad H. Hilman, Maria A. Rodriguez, Rajkumar Buyya

In this paper, we propose an online incremental learning approach to predict the runtime of tasks in scientific workflows in clouds.

Incremental Learning Management +3

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