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Hardware-Software Architecture of the SWAN Wireless ATM Network

  • Prathima Agrawal
  • Eoin Hyden
  • Paul Krzyzanowski
  • Mani B. Srivastava
  • John A. Trotter

Abstract

The SWAN (Seamless Wireless ATM Network) system provides end-to-end ATM connectivity to mobile end-points equipped with RF transceivers for wireless access. Users carrying laptops and multimedia terminals can seamlessly access multimedia data over a backbone wired network while roaming among room-sized cells that are equipped with basestations. The research focus on how to make ATM mobile and wireless distinguishes SWAN from present day mobile-IP based wireless LANs. This paper describes the design and implementation of the ATM-based wireless last-hop, the primary components of which are the air-interface control, the medium access control, and the low-level ATM transport and signalling.

The design is made interesting by its interplay with ATM; in particular, by the need to meaningfully extend over the wireless last-hop the service quality guarantees made by the higher level ATM layers. The implementation, on the other hand, is an example of hardware-software co-design and partitioning. A key component of the wireless hop implementation is a custom designed reconfigurable wireless adapter card called FAWN (Flexible Adapter for Wireless Networking) which is used at the mobiles as well as at the basestations. The functionality is partitioned three-way amongst dedicated reconfigurable hardware on FAWN, embedded firmware on FAWN, and device driver software on a host processor. Using an off-the-shelf 625 Kbps per channel radio, several of which can be supported by a single FAWN adapter to provide multiple channels, per-channel unidirectional TCP data throughput of 227 Kbps (or, 454 Kbps bidirectional) and per-channel unidirectional native ATM data throughput of 210 Kbps (or, 420 Kbps bidirectional) have been obtained.

Keywords

Medium Access Control Medium Access Control Protocol Mobile Host Frequency Slot Connection Manager 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • Prathima Agrawal
    • 1
  • Eoin Hyden
    • 1
  • Paul Krzyzanowski
    • 1
  • Mani B. Srivastava
    • 1
  • John A. Trotter
    • 1
  1. 1.Bell LaboratoriesLucent TechnologiesMurray HillUSA

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