TITLE:
RISN: An Efficient Sensor Network Overlay with Support for Autonomous and Distributed Applications
AUTHORS:
Evens Jean, Ingmar Rauschert, Robert T. Collins, Ali R. Hurson, Sahra Sedigh, Yu Jiao
KEYWORDS:
Pervasive Computing, Mobile Computing, RISN, Service Overlays, Overlay Architecture, Sensor Network, Embedded Systems, Mobile Agents, Target Tracking, Reconfigurable Hardware, Interoperability
JOURNAL NAME:
International Journal of Communications, Network and System Sciences,
Vol.4 No.1,
January
28,
2011
ABSTRACT: Once deployed, sensor networks are capable of providing a comprehensive view of their environment. However, since the current sensor network paradigm promotes isolated networks that are statically tasked, the full power of the harnessed data has yet to be exploited. In recent years, users have become mobile enti-ties that require constant access to data for efficient and autonomous processing. Under the current limita-tions of sensor networks, users would be restricted using only a subset of the vast amount of data being col-lected; depending on the networks they are able to access. Through reliance on isolated networks, prolifera-tion of sensor nodes can easily occur in any area that has high appeals to users. Furthermore, support for dy-namic tasking of nodes and efficient processing of data is contrary to the general view of sensor networks as subject to severe resource constraints. Addressing the aforementioned challenges requires the deployment of a system that allows users to take full advantage of data collected in the area of interest to their tasks. Such a system must enable interoperability of surrounding networks, support dynamic tasking, and swiftly react to stimuli. In light of these observations, we introduce a hardware-overlay system designed to allow users to efficiently collect and utilize data from various heterogeneous sensor networks. The hardware-overlay takes advantage of FPGA devices and the mobile agent paradigm in order to efficiently collect and process data from cooperating networks. The computational and power efficiency of the prototyped system are herein demonstrated. Furthermore, as a proof-of-concept, we present the implementation of a distributed and autonomous visual object tracker implemented atop the Reconfigurable and Interoperable Sensor Network (RISN) showcasing the network’s ability to support ad-hoc agent networks dedicated to user’s tasks.