Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
A Graphical Simulation System for Modeling and Analysis of Sensor Networks
ISM '05 Proceedings of the Seventh IEEE International Symposium on Multimedia
e-Petri Net Model for Programming Integrated Network of Wireless Sensor Networks and Grids
CIT '07 Proceedings of the 7th IEEE International Conference on Computer and Information Technology
Design and Verification of Enhanced Secure Localization Scheme in Wireless Sensor Networks
IEEE Transactions on Parallel and Distributed Systems
Petri Net Based Reconfigurable Wireless Sensor Networks for Intelligent Monitoring Systems
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 02
Energy Modeling of Wireless Sensor Nodes Based on Petri Nets
ICPP '10 Proceedings of the 2010 39th International Conference on Parallel Processing
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This paper proposes an event sequence reconstruction algorithm for a given sensor network based on asynchronous observations of its state changes. We assume that the sensor network is modeled as a Petri net and the asynchronous observations are in the form of state (token) changes at different places in the Petri net. More specifically, the observed sequences of state changes are provided by local sensors and are asynchronous, i.e., they only contain partial information about the ordering of the state changes that occur. We propose an approach that is able to partition the given net into several subnets and reconstruct the event sequence for each subnet. Then we develop an algorithm that is able to reconstruct the event sequences for the entire net that are consistent with: 1) the asynchronous observations of state changes; 2) the event sequences of each subnet; and 3) the structure of the given Petri net. We also discuss the algorithmic complexity and present an example to illustrate our approach.