An optimization framework for joint sensor deployment, link scheduling and routing in underwater sensor networks

Underwater sensor networks are a very interesting case of wireless communication in extreme conditions. They exploit acoustic communication in sea water and are nowadays used in surveillance and monitoring applications. These networks present very challenging aspects, such as low data rates and large delays, as well as the special propagation characteristics of the underwater medium. We propose an integer-linear programming approach to jointly optimize routing, link-scheduling and node placement in such a scenario. Accounting for these special aspects of underwater wireless communications leads to re-thinking traditional approaches; this results in original solutions, which highlight novel directions for further research in this area.

[1]  Leandros Tassiulas,et al.  Maximum lifetime routing in wireless sensor networks , 2004, IEEE/ACM Transactions on Networking.

[2]  Balázs Kotnyek,et al.  An annotated overview of dynamic network flows , 2003 .

[3]  Lili Qiu,et al.  Impact of Interference on Multi-Hop Wireless Network Performance , 2003, MobiCom '03.

[4]  Viktor K. Prasanna,et al.  Energy-latency tradeoffs for data gathering in wireless sensor networks , 2004, IEEE INFOCOM 2004.

[5]  Anantha Chandrakasan,et al.  Bounding the lifetime of sensor networks via optimal role assignments , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[6]  Dario Pompili,et al.  Underwater acoustic sensor networks: research challenges , 2005, Ad Hoc Networks.

[7]  Murali S. Kodialam,et al.  Characterizing achievable rates in multi-hop wireless networks: the joint routing and scheduling problem , 2003, MobiCom '03.

[8]  Robert J. Urick,et al.  Principles of underwater sound , 1975 .

[9]  Kevin Fall,et al.  A linear programming formulation of flows over time with piecewise constant capacity and transit times , 2003 .

[10]  Panganamala Ramana Kumar,et al.  RHEINISCH-WESTFÄLISCHE TECHNISCHE HOCHSCHULE AACHEN , 2001 .

[11]  M. Stojanovic,et al.  Underwater acoustic networks , 2000, IEEE Journal of Oceanic Engineering.

[12]  Paul A. Baxley,et al.  Networked Acoustic Modems for Real-Time Data Delivery from Distributed Subsurface Instruments in the Coastal Ocean: Initial System Development and Performance , 2004 .

[13]  Krishna M. Sivalingam,et al.  Data Gathering Algorithms in Sensor Networks Using Energy Metrics , 2002, IEEE Trans. Parallel Distributed Syst..

[14]  Murali S. Kodialam,et al.  Characterizing the capacity region in multi-radio multi-channel wireless mesh networks , 2005, MobiCom '05.

[15]  Li Li,et al.  Distributed topology control for power efficient operation in multihop wireless ad hoc networks , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[16]  Aravind Srinivasan,et al.  Algorithmic aspects of capacity in wireless networks , 2005, SIGMETRICS '05.

[17]  Ritesh Madan,et al.  Distributed algorithms for maximum lifetime routing in wireless sensor networks , 2004, IEEE Transactions on Wireless Communications.