1. CompSci 296.2 Self-Managing Systems
Shivnath Babu
In this talk my aims are:
- to give an overview of the work that we have been doing at Stanford on adaptive processing in the stream system and what we are doing now
[past and current work]
- facilitate some interesting discussion. Hope the title is provoking enough
I will not be comparing our system with eddies explicitly, although I am doing some work in that respect with DeWitt and one of his students.

2. Reminder Today: Progress talk <= 5 minutes
Send me slides + 2-page writeup by next Tuesday
Thursday: Speaker from Cisco
Next Tuesday: Speaker from IBM Tivoli

3. Adaptive Metric Attribution
Recap
Metric attribution
TANs
Balanced accuracy
Log-likelihood difference
Experimental results

4. Ensembles What are the different approaches they test in the paper?
Pros and cons
Are they depending on “past predicts future”?
Ensemble-based algorithm

5. Experiments Workloads Table 2 Figure 3(a) Learning surfaces
Rationale behind the workload selection?
Table 2
Figure 3(a)
Learning surfaces

6. Discussion Strong points? Weak points?
Root-cause detection Vs. metric attribution
Strange behavior with BURST workload
What are wrong with single models?
Does it make sense to disqualify models?
Bullet 3 on Page 3
Redundancy of metrics in Ensembles