NDLI: Model building for dynamic multi-tenant provider environments

Please wait, while we are loading the content...

Model building for dynamic multi-tenant provider environments

Content Provider	ACM Digital Library
Author	Narayanamurthy, Srinivasan Voruganti, Kaladhar Basak, Jayanta Nandi, Siddhartha Wadhwani, Kushal Mathur, Vipul
Abstract	Increasingly, storage vendors are finding it difficult to leverage existing white-box and black-box modeling techniques to build robust system models that can predict system behavior in the emerging dynamic and multi-tenant data centers. White-box models are becoming brittle because the model builders are not able to keep up with the innovations in the storage system stack, and black-box models are becoming brittle because it is increasingly difficult to a priori train the model for the dynamic and multi-tenant data center environment. Thus, there is a need for innovation in system model building area. In this paper we present a machine learning based blackbox modeling algorithm called M-LISP that can predict system behavior in untrained region for these emerging multitenant and dynamic data center environments. We have implemented and analyzed M-LISP in real environments and the initial results look very promising. We also provide a survey of some common machine learning algorithms and how they fare with respect to satisfying the modeling needs of the new data center environments.
Starting Page	20
Ending Page	31
Page Count	12
File Format	PDF
ISSN	01635980
DOI	10.1145/2421648.2421653
Journal	ACM SIGOPS Operating Systems Review (OPSR)
Volume Number	46
Issue Number	3
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1975-04-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Black-box Storage management Machine learning Resource modeling
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Hardware and Architecture Information Systems

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Fairness and isolation in multi-tenant storage as optimization decomposition

Predictive performance modeling for distributed batch processing using black box monitoring and machine learning

Modeling the relative fitness of storage

Trouble Management for Multimedia Services in Multi-Provider Environments

DYVERSE: DYnamic VERtical Scaling in multi-tenant Edge environments

Joint Dynamic Resource Allocation for QoS Provisioning in Multi-Access and Multi-Service Wireless Systems

Energy-Aware Autonomic Resource Allocation in Multitier Virtualized Environments

A multi-service storage architecture

Dynamic storage partitioning

Model building for dynamic multi-tenant provider environments

Similar Documents

Fairness and isolation in multi-tenant storage as optimization decomposition

Predictive performance modeling for distributed batch processing using black box monitoring and machine learning

Modeling the relative fitness of storage

Trouble Management for Multimedia Services in Multi-Provider Environments

DYVERSE: DYnamic VERtical Scaling in multi-tenant Edge environments

Joint Dynamic Resource Allocation for QoS Provisioning in Multi-Access and Multi-Service Wireless Systems

Energy-Aware Autonomic Resource Allocation in Multitier Virtualized Environments

A multi-service storage architecture

Dynamic storage partitioning

Model building for dynamic multi-tenant provider environments