INCITE: Traffic Processing Techniques for Network Inference and Control Effort 1: Chirp Probing Objective : Reduced complexity, multiscale link models with known accuracy Innovative Ideas Multifractal analysis Multiplicative modeling Multiscale queuing Chirps for probing Rice University. INCITE. Baraniuk, Riedi, Nowak, Knightly

INCITE: Traffic Processing Techniques for Network Inference and Control Chirp Probing: Impact Congestion control Workload balancing at servers Dynamical streaming Pricing on connection basis New Ideas Probing multiple hops Probing buffer at core router Technical transfer Stanford (SLAC) Los Alamos (LANL) Sprint Labs

INCITE: Traffic Processing Techniques for Network Inference and Control Effort 2: Connection level analysis Objective : Understand the causes of Traffic Burstiness Overall traffic  :Residual traffic  : 1 Strongest connection per time window = + Innovative Ideas: Traffic separation into - dominant “alpha connections” and - residual “beta” background traffic

INCITE: Traffic Processing Techniques for Network Inference and Control Connection level analysis. New results Alpha traffic: –few (1%) connections, small (3%) load –Responsible for all non-Gaussian burstiness Beta traffic: –Gaussian, rules LRD Origins / physical explanation: –Alpha = High bandwidth + large load –Beta = Limited bandwidth traffic

INCITE: Traffic Processing Techniques for Network Inference and Control Connection level analysis Impact of alpha-beta model: –Queuing: large delays caused by few alpha connections –Simulation: bandwidth variability for realism Future work: –Mathematical modeling of alpha traffic –New queuing theory –New control mechanisms Technical risk: –Realism of simulation, modeling and analysis –Effectiveness of control of bursty traffic