Oscillations and chaos in a flow model of a switching system

Field data from digital switching systems in an access tandem environment indicate unexpectedly large queuing delays at moderate occupancies. It is shown that these delays are caused by an effect called traffic synchronization, which is the batching of a system's workload caused by interactions between the system and incident traffic. The authors develop a flow model to study this effect and show that a momentary overload can cause sustained oscillations in the system's queues. There are several steady-state modes of operation, and it is shown that for certain parameter ranges the system is chaotic. Such oscillatory behavior can significantly lower the real-time capacity of the switching system, and controls to limit the synchronization effect are suggested. These controls are incorporated into the flow model and analyzed. The results described are validated by numerical studies, simulations, and field data     

A fully integrated micromachined magnetic particle separator

A prototype micromachined magnetic particle separator that can separate magnetic particles from suspended liquid solutions has been realized on a silicon wafer. The requisite magnetic field gradients are generated by integrated inductive components in place of permanent magnets, which yields several advantages in design flexibility, compactness, electrical and optical monitoring, and integration feasibility (thus enabling mass production). Preliminary experiments have been performed on aqueous suspensions of magnetic beads. At 500 mA of dc current, approximately 0.03 Tesla of magnetic flux density is achieved at the gap between the quadrupoles, and the magnetic particles rapidly move toward the quadrupoles, separate from the buffer solution, and clump on the poles. The magnetic particles clumped on the poles are also easily released when the dc current is removed, achieving the primary purpose of a separator. The device shows that micromachined magnetic components have a high potential in biological or biomedical applications, especially in separating small amounts of cells or DNA that are marked with magnetic beads, especially when close monitoring and control of the process is important     

Mid-infrared photothermal heterodyne spectroscopy in a liquid crystal using a quantum cascade laser

We report a technique to measure the mid-infrared photothermal response induced by a tunable quantum cascade laser in the neat liquid crystal 4-octyl-4'-cyanobiphenyl (8CB), without any intercalated dye. Heterodyne detection using a Ti:sapphire laser of the response in the solid, smectic, nematic and isotropic liquid crystal phases allows direct detection of a weak mid-infrared normal mode absorption using an inexpensive photodetector. At high pump power in the nematic phase, we observe an interesting peak splitting in the photothermal response. Tunable lasers that can access still stronger modes will facilitate photothermal heterodyne mid-infrared vibrational spectroscopy.     

Experimental queueing analysis with long-range dependent packettraffic

Traffic measurement studies from a wide range of working packet networks have convincingly established the presence of significant statistical features that are characteristic of fractal traffic processes, in the sense that these features span many time scales. Of particular interest in packet traffic modeling is a property called long-range dependence (LRD), which is marked by the presence of correlations that can extend over many time scales. We demonstrate empirically that, beyond its statistical significance in traffic measurements, long-range dependence has considerable impact on queueing performance, and is a dominant characteristic for a number of packet traffic engineering problems. In addition, we give conditions under which the use of compact and simple traffic models that incorporate long-range dependence in a parsimonious manner (e.g., fractional Brownian motion) is justified and can lead to new insights into the traffic management of high speed networks     

Self-similar traffic and network dynamics

One of the most significant findings of traffic measurement studies over the last decade has been the observed self-similarity in packet network traffic. Subsequent research has focused on the origins of this self-similarity, and the network engineering significance of this phenomenon. This paper reviews what is currently known about network traffic self-similarity and its significance. We then consider a matter of current research, namely, the manner in which network dynamics (specifically, the dynamics of transmission control protocol (TCP), the predominant transport protocol used in today's Internet) can affect the observed self-similarity. To this end, we first discuss some of the pitfalls associated with applying traditional performance evaluation techniques to highly-interacting, large-scale networks such as the Internet. We then present one promising approach based on chaotic maps to capture and model the dynamics of TCP-type feedback control in such networks. Not only can appropriately chosen chaotic map models capture a range of realistic source characteristics, but by coupling these to network state equations, one can study the effects of network dynamics on the observed scaling behavior We consider several aspects of TCP feedback, and illustrate by examples that while TCP-type feedback can modify the self-similar scaling behavior of network traffic, it neither generates it nor eliminates it