Delta Dataflow Networks for Event Stream Processing

Rajit Manohar and K. Mani Chandy

We present a design of a new class of dataflow-like networks suitable for detecting complex conditions in systems in which parameters change rapidly. Such networks are helpful for detecting conditions that signal threats or opportunities in areas such as logistics, finance, and public health. Examples of such applications are detection of money laundering, epidemics, and unauthorized intrusion into systems. We call these networks delta-dataflow networks because nodes in the network propagate only changes in data values. We show how ultra low power asynchronous architectures that have been developed for sensor networks can provide an extremely efficient platform for executing such networks.

 
  
Yale