MWM: a map-based world model for wireless sensor networks

ABSTRACT

A prominent functionality of a Wireless Sensor Network (WSN) is environmental monitoring. For this purpose the WSN creates a model for the real world by using abstractions to parse the collected data. Being cross-layer and application-oriented, most of WSN research does not allow for a widely accepted abstraction. A few approaches such as database-oriented and publish/subscribe provide acceptable abstractions by reducing application dependency and hiding communication details. Unfortunately, these approaches ignore the spatial correlation of sensor readings and still address single sensor nodes. In this work we present a novel approach based on a "world model" that exploits the spatial correlation of sensor readings and represents them as a collection of regions called maps. Maps are a natural way for the presentation of the physical world and its physical phenomena over space and time. Our Map-based World Model (MWM) abstracts from low-level communication issues and supports general applications by allowing for efficient event detection, prediction and queries. In addition our MWM unifies the monitoring of physical phenomena with network monitoring which maximizes its generality. Using two case studies we highlight the simplicity and also the versatility of the proposed architecture. From our approach we deduce a general modeling and design methodology for WSNs.

REFERENCES

• 1: K. Römer and F. Mattern. Event-Based Systems for Detecting Real-World States with Sensor Networks: A Critical Analysis. In DEST at ISSNIP, 2004.
• 2: Jeremy Elson , Deborah Estrin, Sensor networks: a bridge to the physical world, Wireless sensor networks, Kluwer Academic Publishers, Norwell, MA, 2004
• 3: D. Estrin et al. Instrumenting the World with Wireless Sensor Networks. In ICASSP, 2001.
• 4: Samuel R. Madden , Michael J. Franklin , Joseph M. Hellerstein , Wei Hong, TinyDB: an acquisitional query processing system for sensor networks, ACM Transactions on Database Systems (TODS), v.30 n.1, p.122-173, March 2005 [doi>10.1145/1061318.1061322]
• 5: Philippe Bonnet , Johannes Gehrke , Praveen Seshadri, Towards Sensor Database Systems, Proceedings of the Second International Conference on Mobile Data Management, p.3-14, January 08-10, 2001
• 6: Y. Yao and J. Gehrke. Query Processing for Sensor Networks. In CIDR, 2003.
• 7: Samuel Madden , Michael J. Franklin , Joseph M. Hellerstein , Wei Hong, The design of an acquisitional query processor for sensor networks, Proceedings of the 2003 ACM SIGMOD international conference on Management of data, June 09-12, 2003, San Diego, California [doi>10.1145/872757.872817]
• 8: Hejun Wu , Qiong Luo , Wenwei Xue, Distributed Cross-Layer Scheduling for In-Network Sensor Query Processing, Proceedings of the Fourth Annual IEEE International Conference on Pervasive Computing and Communications, p.180-189, March 13-17, 2006 [doi>10.1109/PERCOM.2006.22]
• 9: Mehdi Sharifzadeh , Cyrus Shahabi, Supporting spatial aggregation in sensor network databases, Proceedings of the 12th annual ACM international workshop on Geographic information systems, November 12-13, 2004, Washington DC, USA [doi>10.1145/1032222.1032248]
• 10: David Chu , Lucian Popa , Arsalan Tavakoli , Joseph M. Hellerstein , Philip Levis , Scott Shenker , Ion Stoica, The design and implementation of a declarative sensor network system, Proceedings of the 5th international conference on Embedded networked sensor systems, November 06-09, 2007, Sydney, Australia [doi>10.1145/1322263.1322281]
• 11: P. R. Pietzuch et al. Composite Event Detection as a Generic Middleware Extension. IEEE Network, 18(1), 2004.
• 12: P. Costa et al. Publish-subscribe on Sensor Networks: A Semi-probabilistic Approach. In MASS, 2005.
• 13: Jan Steffan , Ludger Fiege , Mariano Cilia , Alejandro Buchmann, Towards Multi-Purpose Wireless Sensor Networks, Proceedings of the 2005 Systems Communications, p.336-341, August 14-17, 2005 [doi>10.1109/ICW.2005.77]
• 14: Eduardo Souto , Germano Guimarães , Glauco Vasconcelos , Mardoqueu Vieira , Nelson Rosa , Carlos Ferraz , Judith Kelner, Mires: a publish/subscribe middleware for sensor networks, Personal and Ubiquitous Computing, v.10 n.1, p.37-44, December 2005 [doi>10.1007/s00779-005-0038-3]
• 15: M. Sharifi et al. A Publish-Subscribe Middleware for Real-Time Wireless Sensor Networks. In International Conference on Computational Science, 2006.
• 16: J. H. Hauer et al. A Component Framework for Content-based Publish/Subscribe in Sensor Networks. In EWSN, 2008.
• 17: V. Srivastava and M. Motani. Cross-layer Design: A Survey and the Road Ahead. IEEE Communications Magazine, 43(12), Dec. 2005.
• 18: D. Gracanin et al. On Modeling Wireless Sensor Networks. In IPDPS, 2004.
• 19: Matt Welsh , Geoff Mainland, Programming sensor networks using abstract regions, Proceedings of the 1st conference on Symposium on Networked Systems Design and Implementation, p.3-3, March 29-31, 2004, San Francisco, California
• 20: Y. Zhao et al. Residual energy scan for monitoring sensor networks. In IEEE WCNC, 2002.
• 21: Wenwei Xue , Qiong Luo , Lei Chen , Yunhao Liu, Contour map matching for event detection in sensor networks, Proceedings of the 2006 ACM SIGMOD international conference on Management of data, June 27-29, 2006, Chicago, IL, USA [doi>10.1145/1142473.1142491]
• 22: Mo Li , Yunhao Liu , Lei Chen, Non-Threshold based Event Detection for 3D Environment Monitoring in Sensor Networks, Proceedings of the 27th International Conference on Distributed Computing Systems, p.9, June 25-27, 2007 [doi>10.1109/ICDCS.2007.123]
• 23: M. V. Machado et al. Data Dissemination in Autonomic Wireless Sensor Networks. IEEE Journal on Selected Areas in Comm., 23(12), 2005.
• 24: O. Goussevskaia et al. Data Dissemination Based on the Energy Map. IEEE Comm. Magazine, 43(7), July 2005.
• 25: K. Ren et al. Secure and Fault-Tolerant Event Boundary Detection in Wireless Sensor Networks. IEEE Trans. on Wireless Comm., 7(1), Jan. 2008.
• 26: X. Zhu et al. Light-weight Contour Tracking in Wireless Sensor Networks. In INFOCOM, 2008.
• 27: Yunhao Liu , Mo Li, Iso-Map: Energy-Efficient Contour Mapping in Wireless Sensor Networks, Proceedings of the 27th International Conference on Distributed Computing Systems, p.36, June 25-27, 2007 [doi>10.1109/ICDCS.2007.115]
• 28: B. Sundararaman et al. Clock Synchronization for Wireless Sensor Networks: A Survey. Ad-Hoc Networks, 3(3), May 2005.
• 29: J. M. Hellerstein et al. Beyond Average: Toward Sophisticated Sensing with Queries. In IPSN, 2003.
• 30: Wenwei Xue , Qiong Luo , Lei Chen , Yunhao Liu, Contour map matching for event detection in sensor networks, Proceedings of the 2006 ACM SIGMOD international conference on Management of data, June 27-29, 2006, Chicago, IL, USA [doi>10.1145/1142473.1142491]
• 31: Ignacio Solis , Katia Obraczka, Isolines: Energy-Efficient Mapping in Sensor Networks, Proceedings of the 10th IEEE Symposium on Computers and Communications, p.379-385, June 27-30, 2005 [doi>10.1109/ISCC.2005.88]
• 32: Xiaoqiao Meng , Thyaga Nandagopal , Li Li , Songwu Lu, Contour maps: monitoring and diagnosis in sensor networks, Computer Networks: The International Journal of Computer and Telecommunications Networking, v.50 n.15, p.2820-2838, 18 October 2006 [doi>10.1016/j.comnet.2005.09.038]
• 33: Matt Welsh, Exposing resource tradeoffs in region-based communication abstractions for sensor networks, ACM SIGCOMM Computer Communication Review, v.34 n.1, January 2004 [doi>10.1145/972374.972395]
• 34: P. Bonnet et al. Querying the Physical World. IEEE Personal Comm., 7(10), 2000.
• 35: Daniel J. Abadi , Samuel Madden , Wolfgang Lindner, REED: robust, efficient filtering and event detection in sensor networks, Proceedings of the 31st international conference on Very large data bases, August 30-September 02, 2005, Trondheim, Norway
• 36: C. T. Vu et al. Composite Event Detection in Wireless Sensor Networks. In IPCCC, 2007.
• 37: A. V. U. P. Kumar et al. Distributed Collaboration for Event Detection in Wireless Sensor Networks. In MPAC, 2005.
• 38: J. Heidemann et al. Diffusion Filters as a Flexible Architecture for Event Notification in Wireless Sensor Networks. In USC/Information Sciences Institute (ISI-TR-556), 2002.
• 39: Bhaskar Krishnamachari , Sitharama Iyengar, Distributed Bayesian Algorithms for Fault-Tolerant Event Region Detection in Wireless Sensor Networks, IEEE Transactions on Computers, v.53 n.3, p.241-250, March 2004 [doi>10.1109/TC.2004.1261832]
• 40: A. Dogandzic and B. Zhang. Distributed Estimation and Detection for Sensor Networks Using Hidden Markov Random Field Models. IEEE Trans. on Signal Processing, 54(8), 2006.
• 41: Jun Fang , Hongbin Li, Distributed event-region detection in wireless sensor networks, EURASIP Journal on Advances in Signal Processing, v.2008 n.1, p.1-10, January 2008
• 42: Kuei-Ping Shih , Sheng-Shih Wang , Pao-Hwa Yang , Chau-Chieh Chang, CollECT: Collaborative Event deteCtion and Tracking in Wireless Heterogeneous Sensor Networks, Proceedings of the 11th IEEE Symposium on Computers and Communications, p.935-940, June 26-29, 2006 [doi>10.1109/ISCC.2006.50]
• 43: R. Sarkar et al. Iso-Contour Queries and Gradient Routing with Guaranteed Delivery in Sensor Networks. In INFOCOM, 2008.
• 44: E. Yoneki and J. Bacon. Unified Semantics for Event Correlation over Time and Space in Hybrid Network Environments. In CoopIS, 2005.
• 45: I. Lazaridis and S. Mehrotra. Capturing Sensor-generated Time Series with Quality Guarantee. In ICDE, 2003.
• 46: D. Tulone and S. Madden. PAQ: Time Series Forecasting for Approximate Query Answering in Sensor Networks. In EWSN, 2006.
• 47: S. Santini and K. Römer. An Adaptive Strategy for Quality-based Data Reduction in Wireless Sensor Networks. In INSS, 2006.
• 48: Yann-Aël Le Borgne , Silvia Santini , Gianluca Bontempi, Adaptive model selection for time series prediction in wireless sensor networks, Signal Processing, v.87 n.12, p.3010-3020, December, 2007 [doi>10.1016/j.sigpro.2007.05.015]
• 49: C. K. Tham. Sensor-Grid Computing and SensorGrid architecture for Event Detection, Classification and Decision-Making. book chapter in Sensor Network and Configuration: Fundamentals, Techniques, Platforms, and Experiments, 2006.
• 50: S. Chien et al. Lights Out Autonomous Operation of an Earth Observing SensorWEB. In RCSGSO, 2007.
• 51: M. Hefeeda and M. Bagheri. Wireless Sensor Networks for Early Detection of Forest Fires. In MASS, 2007.
• 52: D. M. Doolin and N. Sitar. Wireless Sensors for Wildfire Monitoring. In Proc. of SPIE Symposium on Smart Structures and Materials, 2005.
• 53: Chalermek Intanagonwiwat , Ramesh Govindan , Deborah Estrin, Directed diffusion: a scalable and robust communication paradigm for sensor networks, Proceedings of the 6th annual international conference on Mobile computing and networking, p.56-67, August 06-11, 2000, Boston, Massachusetts, United States [doi>10.1145/345910.345920]
• 54: Nisheeth Shrivastava , Subhash Suri , Csaba D. Tóth, Detecting cuts in sensor networks, Proceedings of the 4th international symposium on Information processing in sensor networks, April 24-27, 2005, Los Angeles, California
• 55: K. P. Shih et al. PALM: A Partition Avoidance Lazy Movement Protocol for Mobile Sensor Networks. In WCNC, 2007.
• 56: vast. Space Time Toolkit. http://vast.uah.edu/.
• 57: G. Reitmayr and S. Dieter. Semantic World Models for Ubiquitous Augmented Reality. In SVE, 2005.
• 58: D. Nicklas and B. Mitschang. The NEXUS Augmented World Model: An Extensible Approach for Mobile, Spatially Aware Applications. In OOIS, 2001.
• 59: D. Dudkowski et al. Efficient Algorithms for Probabilistic Spatial Queries in Mobile Ad Hoc Networks. In COMSWARE, 2006.
• 60: F. Kawsar. Prithibi: An Open Platform for Digitizing Real World through Sentient Artefact Model. In Joint Workshop on Next-Generation Computing Infrastructure, 2007.
• 61: M. P. Bauer. Observing Physical World Events through a Distributed World Model. University of Stuttgart, Germany, http://elib.uni-stuttgart.de/opus/volltexte/2007/3043/,2007.
• 62: C. Town and Z. Zhu. Sensor Fusion and Environmental Modelling for Multimodal Sentient Computing. In IEEE CVPR, 2007.
• 63: Mike Addlesee , Rupert Curwen , Steve Hodges , Joe Newman , Pete Steggles , Andy Ward , Andy Hopper, Implementing a Sentient Computing System, Computer, v.34 n.8, p.50-56, August 2001 [doi>10.1109/2.940013]

INDEX TERMS

Primary Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.1 Network Architecture and Design
          Subjects: Network communications

Additional Classification:
  C. Computer Systems Organization
  C.2 COMPUTER-COMMUNICATION NETWORKS
      C.2.1 Network Architecture and Design
          Subjects: Wireless communication
      C.2.2 Network Protocols

  I. Computing Methodologies
  I.6 SIMULATION AND MODELING
      I.6.5 Model Development
          Subjects: Modeling methodologies

Keywords:
design paradigm, event detection, global and local view, monitoring, wireless sensor networks, world model