Sweeps over wireless sensor networks

We present a robust approach to data collection, aggregation, and dissemination problems in sensor networks. Our method is based on the idea of a sweep over the network: a wavefront that traverses the network, passes over each node exactly once, and performs the desired operation(s). We do not require global information about the sensor field such as node locations. Instead, in a preprocessing phase, we compute a potential function over the network whose gradients guide the sweep process. The sweep itself operates asynchronously, using only local operations to advance the wave-front. The gradient information provides a local ordering of the nodes that helps reduce the number of MAC-layer collisions as the wavefront advances, while also globally shaping the wavefront so as to conform to the sensor field layout. The approach is robust to both link volatility and node failures that may be present in real network conditions. The potential is computed by a stable diffusion process in which each node repeatedly set its potential to the average of the potentials of its neighbors. Aggregation paths are decided on-line as the sweep proceeds and no fixed tree structure is needed over the course of the computation. We present simulation results illustrating the correctness of the algorithm and comparing the performance of the sweep to aggregation trees under various network conditions

[1]  Wei Hong,et al.  Proceedings of the 5th Symposium on Operating Systems Design and Implementation Tag: a Tiny Aggregation Service for Ad-hoc Sensor Networks , 2022 .

[2]  Rajmohan Rajaraman,et al.  WaveScheduling: energy-efficient data dissemination for sensor networks , 2004, DMSN '04.

[3]  Jeffrey Considine,et al.  Informed content delivery across adaptive overlay networks , 2002, IEEE/ACM Transactions on Networking.

[4]  Scott Shenker,et al.  Geographic routing without location information , 2003, MobiCom '03.

[5]  Robert Szewczyk,et al.  System architecture directions for networked sensors , 2000, ASPLOS IX.

[6]  Srinivasan Seshan,et al.  Synopsis diffusion for robust aggregation in sensor networks , 2004, SenSys '04.

[7]  David E. Culler,et al.  TOSSIM: accurate and scalable simulation of entire TinyOS applications , 2003, SenSys '03.

[8]  Deborah Estrin,et al.  Computing aggregates for monitoring wireless sensor networks , 2003, Proceedings of the First IEEE International Workshop on Sensor Network Protocols and Applications, 2003..

[9]  Calvin Newport,et al.  The mistaken axioms of wireless-network research , 2003 .

[10]  Qun Li,et al.  Design and Analysis of Wave Sensing Scheduling Protocols for Object-Tracking Applications , 2005, DCOSS.

[11]  Scott Shenker,et al.  Epidemic algorithms for replicated database maintenance , 1988, OPSR.

[12]  David E. Culler,et al.  A unifying link abstraction for wireless sensor networks , 2005, SenSys '05.

[13]  Tamal K. Dey,et al.  Shape Segmentation and Matching with Flow Discretization , 2003, WADS.

[14]  Leonidas J. Guibas,et al.  GLIDER: gradient landmark-based distributed routing for sensor networks , 2005, Proceedings IEEE 24th Annual Joint Conference of the IEEE Computer and Communications Societies..

[15]  Martin Reimers,et al.  Meshless parameterization and surface reconstruction , 2001, Comput. Aided Geom. Des..

[16]  Sándor P. Fekete,et al.  Neighborhood-Based Topology Recognition in Sensor Networks , 2004, ALGOSENSORS.

[17]  Stefan Funke,et al.  Topological hole detection in wireless sensor networks and its applications , 2005, DIALM-POMC '05.

[18]  David E. Culler,et al.  The dynamic behavior of a data dissemination protocol for network programming at scale , 2004, SenSys '04.

[19]  D. Young Iterative methods for solving partial difference equations of elliptic type , 1954 .

[20]  Sándor P. Fekete,et al.  Deterministic boundary recognition and topology extraction for large sensor networks , 2005, SODA '06.

[21]  Imrich Chlamtac,et al.  The wave expansion approach to broadcasting in multihop radio networks , 1991, IEEE Trans. Commun..

[22]  Jeffrey Considine,et al.  Approximate aggregation techniques for sensor databases , 2004, Proceedings. 20th International Conference on Data Engineering.