CompSci Self-Managing Systems Shivnath Babu

2 Reminder Slides and 2-page writeup due today Thursday: Control-theory paper Student presentations from next month Feb 21 (next Tuesday): Progress talk, <= 5 minutes Feb 23: Speaker from Cisco Feb 28: Speaker from IBM Tivoli

3 Oceano Setting: Computing utility Goal: Automatic SLA management Challenges: Peak load >> average load, shared Simple solution: overprovision Solution: –Domain –Events: Monitoring, correlation –Control actions: Dynamic server allocation, throttling

4 Oceano: Mechanisms Figure 2 Monitoring: detect events Aggregation and correlation of events Events  control actions

5 Discussion Strong points? Weak points? How does Oceano differ from related work? How does Oceano deal with overload? Content-based throttling Allocating a Dolphin Experiments

6 Autonomic Reservoir Optimization on Grids Prototype application: placement and operation of oil wells to maximize revenue Proof of concept for: –New paradigm of application deployment –Peer-to-peer interactions among application modules, Grid services, resources, and data –Autonomic optimization Self-optimizing behavior within and across components

7 Components Reservoir simulation (IPARS) Optimization services (VFSA) Economic modeling Real-time data Historical archives Experts (collaborative portals)

8 Interactions and Implementation Figure 3 Pawn: Figure 5 Implementing reservoir optimization using Pawn

9 Discussion What does this work show? –Did they pick the right application? How “autonomic” is this work?