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Thursday, July 12, 2012

Just submitted CMG'12 papers abstracts: Very preliminary analysis

Abstracts are published anonymously here: http://www.cmg.org/cgi-bin/abstract_view.pl 
Apparently one of the  papers was inspired by me: 

Time-Series: Forecasting + Regression: “And” or “Or”?
At CMG’11, I had a fascinating discussion with Dr. I.Trubin. We talked about Uncertainty, Second Law of Thermodynamics, and other high matters in relation to IT. That discussion prompted this paper. We propose a method to get better predictions when we have a forecast of independent variable and a regression. It works for any scenarios where performance can be linked with business metrics. A real-world example is worked through that demonstrates how this technique works to improve the performance metric prediction and highlight trends that would have been overlooked otherwise.
 I guess that relates to my other posting about other paper that use "entropy" :  
Quantifying Imbalance in Computer Systems: CMG'11 Trip Report, Part 2
The following are abstracts of some other papers from the list that potentially could relate to the main topics of this blog. I cannot wait when I can read them!
Methods for Identifying Anomalous Server Behavior
Identifying anomalous server behavior in large server farms is often overlooked for a variety of reasons. The anomalous behavior does not breach alerting thresholds, or perhaps the behavior is subtle and is simply missed. Whatever the case, it is important to identify such behavior before it becomes more severe. In this paper we discuss methods of identifying server behavior that is anomalous or otherwise or uncharacteristic. Methods include statistical techniques such as multidimensional scaling, and machine learning methods such as isolation forests and self organizing maps.

Software Performance Antipatterns for Identifying and Correcting Performance Problems
Performance antipatterns document common software performance problems as well as their solutions. These problems are often introduced during the architectural or design phases of software development, but not detected until later in testing or deployment. Solutions usually require software changes as opposed to system tuning changes. This tutorial covers five performance antipatterns and gives examples to illustrate them. These antipatterns will help developers and performance engineers avoid common performance problems.


Introduction to Wavelets and their Application for Computer Performance Trend and Anomaly Detection
In this paper I will present a technique to identify trends and anomalies in Performance data using wavelets. I will answer the following questions: Why use Wavelets? What are Wavelets? How do I use them?

Application Invariants: Finding constants amidst all the change
This paper presents a method for deriving and utilizing Application Invariants. An Application Invariant is a metric that quantifies the behavior or performance of an application in such a way that its value is immune to changes in workload volume. Several sample Application Invariants are developed and presented. One of the primary benefits of an Application Invariant is that it provides a simple (flat) shape that can readily be used to track changes in application performance or behavior in an automated manner.
Couple other papers could be found there with the obvious interest for this blog.... Will post them later here.

All in all, based on the 1st glance, looks like this year CMG conference (http://www.cmg.org/ ) will have a great success.