System Maintenance:
There may be intermittent impact on performance while updates are in progress. We apologize for the inconvenience.
By Topic

A Bin Packing Heuristic for On-Line Service Placement and Performance Control

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Reynolds, M.B. ; Crane Div., Naval Surface Warfare Center, USA ; Hulce, D.R. ; Hopkinson, K.M. ; Oxley, M.E.
more authors

The ever-increasing size and complexity of cloud computing, data centers, virtualization, web services, and other forms of distributed computing make automated and effective service management increasingly important. This article treats the service placement problem as a novel generalization of the on-line vector packing problem. This generalization of the service placement problem does not require a priori knowledge of the service resource profiles, allows for resource profiles to change over time, and allows services to be moved once placed on a server. An on-line self-organizing model profiles resource supplies and demands arranging services in a placement based on their resulting quality rating. A policy-driven asymmetric matrix norm quantifies the quality of the placement allowing for administrative preferences regarding service performance versus service inclusion. Service resource usage profiles' variations cause changes in their assigned placement quality; forcing new, better server placements to be found. Because some placements perform better, a proportional integral derivative controller for performance feedback adjusts the services' actual profile according to service's individual response times. This large scale system autonomically organizes placement of services in response to changes in demand and network disruptions. This article presents theorems which demonstrate the theoretical basis for the model. The article includes empirical results from the implementation of this model in a self-organizing testbed of web servers and services.

Published in:

Network and Service Management, IEEE Transactions on  (Volume:10 ,  Issue: 3 )