1. Introduction Network Quality Assurance (and Simulation!) Read Chapters 1, 2, 3

2. Quality Assurance A planned and systematic set of activities to ensure that variances in system performance are clearly identified, assessed, and evaluated to fulfill (or not) some requirements.(After a SixSigma definition related to software engineering). In this class, a system will be a computer network, a networking protocol, a network element (switch, interconnection network)..

3. Techniques for Quality Assurance Formal modeling and analysis –Queueing models –Probability models Experimentation/measurements –Measure some keys metrics Simulation –Encode a behavior/system (write code that mimicks the system) –Measure key metrics

4. Examples Consider the evaluation of medium access control protocols: Aloha, slotted Aloha, CSMA/CD… –Formal analysis yields bounds on maximum medium utilization (during design phase), but often requires some simplifications –Experimentation/measurements could yield similar results (no guarantees!), but requires that system exists –Simulation could yield similar results (no guarantees!), does not require that system exists

5. Examples (2) Quality assurance may require a mix of formal analysis, simulation, and experimentation. Why a mix? Consider the Aloha protocol

6. Pure Aloha Designed by Abramson (wireless) A station emits whenever it has something to send If other station emits, a collision happens If collision, frame must be resent Best possible utilization at high load 18%

7. Example: Aloha Protocol Input (workload) Output (Metrics)

8. Example: Aloha Protocol Input (Packet generated per unit time) Output (Medium utilisation/ throughput)

9. Simplifications for Formal Analysis Stations have always one packet to send Packets have the same size Generated traffic is a Poisson process Propagation time negligible.

10. Tools for the 3 Techniques Networking knowledge Probability Statistiques

11. Mixing the Techniques Formal analysis provide some approximation of the expected performance Simulation may validate the formal analysis and will allow the evaluation of the model when simplifications are removed (“real workload” with packets of different sizes, real world traffic…) Experimentation/measurements may validate the formal analysis and the simulation.

12. Read Chapter 1, 2, 3