Holistic Quota Management

Michael Gilfix

mgilfix@eecs.tufts.edu

November 6th, 2002

LISA 2002

Why Quotas? Users expect guaranteed access to

resources Finite resources Ensures that users “play nice”

Well understood paradigm “Gets the job done” Widely applicable to resource management:

Disk Space Bandwidth Quality of Service

Traditional Systems

Individuals assigned usage limits Soft Limits vs. Hard Limits Groups as a solution to mass management

Limited facilities for analysis Manipulation limited to user-level or group-level No easy way to determine efficiency of current

quota policies No easy way of working with the “bigger picture”

“Bigger Picture” is Key

Some vital questions: How much am I promising compared to how

much I have available? How effective are, or how much is wasted by, my

current policies? How much “headroom” do I have to work with? Who needs less and who needs more?

All difficult to answer without global analysis

In Search of Inspiration

Resource management as a scheduling problem Dynamic resource management based on

“competitive counterforce” A control-theoretic model

Value of the whole is greater than the sum of its parts

Fusion

“Competitive Counterforce”: Emphasize relative share Increase for one means less for others

The control-theoretic model: Operating curves as an effective means of

defining system behavior Encourages a much more dynamic system

Value of the whole: Suggests a “fuzzy” visual interface

Towards a New Model Resource is treated as finite and continuous Each user is given a fraction of that resource System Administrator defines a distribution curve to

define the resource sharing policy Area constrained to one-to-one correlation with total

amount of resource Distribution curve is divided into slices whose widths

are proportional to the number of users of the resource

Users are either assigned or compete for a slice Operations are global: Giving more to one takes

from everyone else

The New Model Illustrated

The New Model IllustratedA Current Quota Implementation

in the New Model

Benefits

Separation of policy from implementation Closer to a service model Makes policy easier to understand

Encourages informed changes to individual limits Changes for individuals do not compromise the

general policy Puts perspective on over-subscription:

User shares decrease as user-base increases Allows for a stronger service guarantee

Scales “automatically” as underlying resource amount changes

Creating a Proof-of-Concept

A meta-management approach Biggest concern is adoption for POC Must be able to interoperate with existing

quota systems Implementation is a compromise between

model and inter-operability Implementation is consistent in interface Interface focuses on the “global picture”

Faithful Visualization

Chaining step functions as an accurate and scalable depiction

Avoids visual artifacts

A Plot at Full View A Zoomed Sub-Section

Exposing trends

Hierarchical sorting as a powerful tool for trend analysis Exposes categories of users, or service levels

automatically Exposes trends within population categories User groupings presented reflect reality Renders displays with meaningful distributions

Some Interesting Conclusions

The new model helps answer the “bigger picture” questions: Over-Subscription Effectiveness Working room User need satisfaction

Enables global operations Pareto distribution may play an important role

in modeling file size distributions in networks

Where to now?

Evaluation of the proof of concept Building a full implementation

Implementation of the privilege mechanism will eliminate many inherent problems in the POC

Direct support for explicit over-subscription Applying the Qualm concepts to other areas

of resource management Experimenting with dynamic schemes using

this framework

Qualm is freely available at:http://qualm.sourceforge.net

Orhttp://www.sourceforge.net/projects/qualm

Contact Information

Michael GilfixTufts University

mgilfix@eecs.tufts.edu

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