1. University of Nottingham Introduction to Thermal Management Naisan Benatar Supervisors: Prof. Uwe Aickelin & Dr. Milena Radenkovic

2. IMA -University of Nottingham 2 Outline Introduction to WSNs Problem Domain Solution Outline Future Work

3. IMA -University of Nottingham 3 Introduction – Who Am I? Undergraduate Degree in CS – University of Nottingham 2002-2005 Software Engineer – Thales Avionics – Worked on SatCom system mainly for Airbus Returned to UoN for PhD Studies in Sept

4. IMA -University of Nottingham 4 Areas of Research Wireless Sensor Networks (WSNs) Their Applications Protocols related to their applications

5. IMA -University of Nottingham 5 What are Wireless Sensor Networks? Constructed from inexpensive nodes with a sensor (or multiple sensors) and a wireless networking device Power is a concern – limited battery Resource Constraints (CPU, Memory)

6. IMA -University of Nottingham 6 Applications of WSNs Many Sizes and Applications: Military Conservation Urban Monitoring (Traffic)

7. IMA -University of Nottingham 7 What I’m currently Interested In Thermal Challenges in Data Centres – Lots of Heat producing objects (mainly servers,storage etc ) Few cooling units (Active Air Conditioning Units) Varying Loads mean varying temperatures Each piece of equipment must not exceed its operating conditions (Usually around 75 degrees Celsius) Very heterogeneous environment – many manufacturers. Changes in data centers are not uncommon (Often a 3 year upgrade cycle)

8. IMA -University of Nottingham 8

9. 9 Current Solution Very Brute Force All Coolers set so no piece of equipment goes above a set level (approx 75 degrees Celsius) Not very Intelligent Wastes Energy Does not adapt to varying workloads No one system that handles all aspects of the thermal environment

10. IMA -University of Nottingham 10 How can it improve? Using a wireless sensor network composed of numerous nodes equipped with temperature sensor. Gather Data from nodes Make Decisions. Be flexible, resilient and quick to respond or predictive.

11. IMA -University of Nottingham 11 Problems with this approach Lots of data – Possibly thousands of nodes in a large DC. Unordered/Unstructured data Heterogeneous Environment

12. IMA -University of Nottingham 12 Potential Algorithm Inspiration “Bio-inspired” Artificial Endocrine System Traditional WSN approaches

13. IMA -University of Nottingham 13 Bio Inspired Approach The human endocrine system regulates processes in the body E.g. Rate of breakdown of stored energy to useable form controlled by 2 hormones (insulin & glucagon) Can something similar be used to regulate cooling requirements in a DC?

14. IMA -University of Nottingham 14 Traditional Solutions Directed Diffusion is a data centric protocol sometimes used with WSNs. Uses named data pairs, along with interests to specify where data should be sent in the network. Most useful for applications where all data ends up in a single place for processing – not what we have here

15. IMA -University of Nottingham 15 How to test: A model Need to build a Model (or 2) to simulate the various algorithms: Networking Model Each node in the network will be individually modelled -> Agent Based Modelling Thermal Model Thermal Environment will alter all nodes gradually - >System Dynamics?

16. IMA -University of Nottingham 16 Software Using Anylogic (V 6.4) Allows Combinations of Modelling Paradigms Uses java for behaviour specification Provides good foundation frameworks

17. IMA -University of Nottingham 17 How to get some confidence in the model? Performed experiments with real equipment – measured temperature changes at varying levels of load Used as basis of thermal model

18. IMA -University of Nottingham 18 Measuring Performance Metrics for Measurement of Performance of an algorithm: Packets sent Time to respond to peaks Energy Usage of cooling system

19. IMA -University of Nottingham 19 Real Life

20. IMA -University of Nottingham 20 Simulation

21. IMA -University of Nottingham 21 Comparisons Not very similar! Many Reasons for this Experimental Data not perfectly controlled Many Simplifications in model An ongoing topic in modelling research

22. IMA -University of Nottingham 22 Future Work – Short term Improve Accuracy of model (CFD for thermal?). Comparisons of different approaches to solving the problem.

23. IMA -University of Nottingham 23 Future Work – Long term Possible Experiments with small data centres More Intelligence - predicative load based on prior knowledge (e.g. Weekly peaks)

24. IMA -University of Nottingham 24 Questions?