Cloud Storage Systems: Latency Characterization and Extensions

Table of Contents

Seminars-2-2024 - This article is part of a series.

Part 1: The Dawn of an Immersive Internet: XR, Generative AI and the Road to 6G

Part 2: AGI Chips - The Next Frontier

Part 3: Generalist vs Specialist Language Models

Part 4: From Intelligent Surfaces to Noise-Driven Communication: Innovative Technologies for 6G and Beyond

Part 5: An Overview of Evolutionary Multi-Objective Optimization

Part 6: Packet Trimming at the Edge for Low Latency in 6G Environments

Part 7: Scientific Machine Learning and Quantum Utility: A Near Future Perspective

Part 8: This Article

Part 9: Let the Plants do the Talking: Climate-Smart Agriculture by the Messages Received from Plants and Soil

Part 10: More is different: How the Science of Complex Systems can inspire Future Autonomous Networks

Abstract #

Consumers are engaged in more social networking and E-commerce activities these days and are increasingly storing their documents and media in the online storage. Businesses are relying on Big Data analytics for business intelligence and are migrating their traditional IT infrastructure to the cloud. These trends cause the online data storage demand to rise faster than Moore’s Law. Erasure coding techniques are used widely for distributed data storage since they provide space-optimal data redundancy to protect against data loss. Cost-effective, network-accessible storage is a strategic infrastructural capability that can serve many businesses. These customers, however, have very diverse requirements of latency, cost, security etc. In this talk, I will describe how to characterize latency. In order to characterize latency, we give and analyze a novel scheduling algorithm. We will also present extensions for video streaming, and applications for stragglers in cloud computing.

Bio of Vaneet Aggarwal #

Vaneet Aggarwal received the B.Tech. degree in 2005 from Indian Institute of Technology, Kanpur, India and the M.A. and Ph.D. degrees in 2007 and 2010, respectively from Princeton University, Princeton, NJ, USA, all in Electrical Engineering. He is currently a University Faculty Scholar and Professor and in the Edwardson School of Industrial Engineering, the Elmore Family School of Electrical and Computer Engineering (by courtesy), and the Department of Computer Science (by courtesy) at Purdue University, where he has been since Jan 2015. Prior to this, he worked as a researcher at AT&T Labs-Research, Florham Park (2010-2014). He was Adjunct Assistant Professor at Columbia University (EE, 2013-2014), VAJRA Adjunct Professor at IISc Bangalore (ECE, 2018-2019), Adjunct Faculty at IIIT Delhi (CS, 2022-2023), and Visiting Faculty at KAUST, Saudi Arabia (CS, 2022-2023). His research interests are in classical and quantum machine learning. Dr. Aggarwal was the recipient of Princeton University’s Porter Ogden Jacobus Honorific Fellowship in 2009 and Purdue’s Most Impactful Faculty Innovator Award in 2020. He also received the 2017 Jack Neubauer Memorial Award recognizing the Best Systems Paper published in the IEEE Transactions on Vehicular Technology, the 2018 IEEE Infocom Workshop Best Paper Award, the 2021 NeurIPS Workshop Best Paper Award, and the 2024 IEEE William Bennett Prize Award recognizing the Best Paper published in IEEE/ACM Transactions on Networking. He was on the Editorial Board of the IEEE Transactions on Green Communications and Networking and the IEEE Transactions on Communications. He is currently serving on the Editorial Board of the IEEE/ACM Transactions on Networking and IEEE Transactions on Network Science and Engineering, and is co-Editor-in-Chief of the ACM Journal on Transportation Systems. He is also IEEE ComSoc Distinguished Lecturer (2024-2025).