MAC Layer Architecture

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Chenyang Lu (PI), Mo Sha

Alumni: Octav Chipara, Greg Hackmann, Kevin Klues, Guoliang Xing


News

MLA (MAC Layer Architecture) has been upgraded for TinyOS 2.1.1. The component-based MAC architecture originally presented in the SenSys'07 paper is implemented as a tinyos-2.x contribs project and is now compatible with the recent tinyos-2.1.1 release.


The MAC Layer Architecture (MLA) provides a component-based architecture for MAC protocols in wireless sensor networks. MLA extends the Unified Power Management Architecture to provide the hardware-independent interfaces required by timing sensitive MAC protocols, and defines platform-independent reusable components that implement MAC layer logic on top of them. The MLA architecture can be used to develop a large number of platform-independent MAC implementations, with little or no further effort required to adapt these implementations to new hardware platforms.

Our current implementation of MLA is built on top of TinyOS 2.1.1. It currently supports platforms which use the CC2420 radio stack and has been tested on TelosB motes. In addition to providing interfaces and components for building new MAC layer implementations, MLA includes implementations of five representative MAC layers:

  • bmac: a port of the BMAC-like NOACK monolithic LPL layer to MLA
  • boxmac2: a port of the BoXmac2-like ACK monolithic LPL layer to MLA
  • scp-wustl: a reimplementation of the SCP-MAC protocol (currently excludes some optimizations)
  • pure-tdma: a single-hop TDMA protocol
  • ss-tdma: a TDMA/CSMA hybrid protocol which implements Z-MAC's "slot-stealing" optimization

Publications


Software

MLA is available from the wustl/upma directory in the tinyos-2.x-contrib CVS repository. Instructions for accessing the repository are available here. Please read the included README file for instructions on set up and use MLA.

If you have any questions or comments, feel free to email Mo Sha at msha@wustl.edu.

Acknowledgements

This work is supported by the NSF under NeTS-NOSS Grant CNS-0627126.