Thurs, 13 Oct
405 Soda
11:30am - 1:00pm

Title: "HiFi: An Architecture for Large-Scale Sensor Data Processing"

Speaker: Shawn Jeffery, UC Berkeley

Abstract: Advances in wireless sensors, RFID technology, and mobile
devices have enabled the development of information systems that
monitor and react to events in the real world. When deployed on a
large (e.g., national) scale, these systems assume a high fan-in
architecture, in which vast numbers of events measured at the edges of
the network are continually refined, summarized, augmented, and
aggregated as they flow towards the interior. These systems present a
wealth of new research problems reflecting the different concerns and
priorities at each level of the system as well as the interactions
between the levels.

The solutions will require insights from recent efforts in data stream
processing, sensor databases, event systems, data warehousing, and
spatio-temporal data management. In this talk, I will identify the key
characteristics and challenges presented by high fan-in systems, and
argue for a uniform, query-based approach towards addressing them. I
will then present our initial thoughts on the design of HiFi, the
system we are building to embody these ideas, and describe an initial
proof-of-concept prototype that is capable of combining data from RFID
readers, clusters of sensor motes, and other devices.

Bio: Shawn Jeffery is a Ph.D. student at the University of California,
Berkeley.  As part of the HiFi project led by Professor Michael
Franklin, his research focus is on "bridging the physical-digital
divide": integrating data captured by physical receptor devices into
traditional data processing infrastructures.  He received his
undergraduate degree in computer science in 2002 from the University
of Wisconsin, Madison.