Implicit situation awareness of a wireless sensor network utilising channel quality estimations
By Stephan Sigg
December 2010 - November 2011
Scope
Networks of sensor nodes are utilised to sense, process and publish environmental information. In context aware, Ubiquitous environments, this is required to classify a given situation. Additionally to the communication load for non-context aware functions of a sensor network, communication, processing and maintenance costs for context awareness arises. This reduces the overall lifetime of a sensor network. We investigate the implicit use of context information that is available as a by-product of indispensable operations in a wireless sensor network. For each communication link, the instantaneous channel quality is known at the receiver node. With changing environmental situations this channel quality may vary. We propose the implicit use of channel characteristics for context computation in a wireless sensor network. By this approach the count of classical sensors required in a wireless sensor network can be reduced. This enables the design of simpler, cheaper and less resource demanding nodes.
Objective
The objective of this research proposal is to provide a concise investigation on the feasibility of generating implicit context classifications from channel characteristics in a sensor network. Our approach is holistic in the sense that it
provides the theoretic foundation, algorithms and computational complexity to optimally utilise channel quality measurements in a distributed network of nodes,
quantifies the impact of a possibly decreased classification accuracy on subsequent context processing operations (using the example of context prediction) and
validates the theoretical findings in an experimental setting.
December 2011 - November 2012
Scope
In networks of tightly integrated nodes that compute some distributed processing task we expect a high amount of inter-node communication. In this situation, it is important that the communication is efficient and coordinated with the computation and relative location of nodes. Furthermore, communication should be sufficiently secure to prevent an adversary from overhearing relevant information and from manipulating the network operation by inserting malicious data. We identify and study the following two issues in this project proposal
How can the communication load be organised most effectively with respect to the computation among the distributed nodes
How can the network be efficiently and unobtrusively guarded from adversary nodes witnessing the information transmitted or from inserting malicious data.
In this project proposal we will consider both issues and study algorithmic solutions in order to optimise the network operation by optimally organising the communication among nodes. Additionally, we will propose a solution for an unobtrusive and ad-hoc mechanism to establish a secure communication channel among nodes in a network.
Objective
At the end of the first project year, we will have studied a method for implicit situation awareness in wireless networks. In this approach, the computation for a context classification and context prediction are distributed among nodes in a network in such a way that the communication and computational costs are minimised among all nodes.For the duration of the second project phase we will consider extensions of this approach regarding the following two aspects:
Further reduction of communication and computational cost
Establishing of an unobtrusive secure channel among nodes in an ad-hoc manner
Stephan Sigg, Markus Scholz, Shuyu Si, Yusheng Ji and Michael Beigl: RF-sensing of activities from non-cooperative subjects in device-free recognition systems using ambient and local signals, accepted for publication in IEEE Transactions on Mobile Computing (TMC) (DOI)
Stephan Sigg and Dominik Schuermann: Secure communication based on ambient audio, in IEEE Transactions on Mobile Computing (TMC), Feb. 2013, vol. 12 no. 2 (DOI)
Markus Scholz, Dawud Gordon, Leonardo Ramirez, Stephan Sigg, Tobias Dyrks and Michael Beigl: A Concept for Support of Firefighter Frontline Communication, in Future Internet, vol.5, no. 2, pp. 113-127 (PDF)
Shuyu Shi, Stephan Sigg and Yusheng Ji: A comparison of two approaches to activity recognition of individuals in an indoor environment, in 2013 IEICE General Conference
2012
Shuyu Shi, Stephan Sigg and Yusheng Ji: Passive detection of situations from ambient FM-radio signals, in Proceedings of the International Workshop on Situation, Activity and Goal Awareness (SAGAware2012) in conjunction with UbiComp2012, September 28th 2012 (DOI)
Shuyu Shi, Stephan Sigg and Yusheng Ji: Activity recognition from Radio Frequency data: Two-stage recognition and features, in Proceedings of the 2012 IEICE Society Conference
Stephan Sigg, Predrag Jakimovski and Michael Beigl: Calculation of functions on the RF-channel for IoT, in Proceedings of the 3rd international conference on the Internet of Things (IoT2012), October 2012 (DOI)
Shuyu Shi, Stephan Sigg and Yusheng Ji: Activity recognition from Radio Frequency data: Multi-stage recognition and features, in Proceedings of the 5th IEEE conference on Context Awareness for Proactive Systems (CAPS 2012), September 2012 (DOI)
Stephan Sigg, Lei Zhong, Yusheng Ji: Activity recognition with implicit context classification, in Proceedings of the 5th IEEE conference on Context Awareness for Proactive Systems (CAPS 2012), September 2012 (DOI)
Stephan Sigg, Ngu Nguyen, An Huynh and Yusheng Ji: AdhocPairing: Spontaneous audio based secure device pairing for Android mobile devices, in Proceedings of the 4th International Workshop on Security and Privacy in Spontaneous Interaction and Mobile Phone Use, in conjunction with Pervasive 2012, 2012
Stephan Sigg and Dominik Schuermann: Secure communication based on ambient audio, in IEEE Transactions on Mobile Computing (TMC), 2012 (Accepted for publication)
Stephan Sigg, Dawud Gordon, Georg von Zengen, Michael Beigl, Sandra Haseloff and Klaus David: Investigation of context prediction accuracy for different context abstraction levels, in IEEE Transactions on Mobile Computing (TMC), 2012 (DOI)
Ngu Nguyen, Stephan Sigg, An Huynh and Yusheng Ji: Pattern-based Alignment of Audio Data for Ad-hoc Secure Device Pairing, in Proceedings of the 16th annual International Symposium on Wearable Computers (ISWC), 2012
Ngu Nguyen, Stephan Sigg, An Huynh and Yusheng Ji: Using ambient audio in secure mobile phone communication, in Proceedings of the 10th IEEE International Conference on Pervasive Computing and Communications (PerCom), WiP session, 2012
Predrag Jakimovski, Hedda R. Schmidtke, Stephan Sigg, Leonardo Weiss, Ferreira Chaves and Michael Beigl: Collective Communication for Dense Sensing Environments, in Journal of Ambient Intelligence and Smart Environments (JAISE), 2012
2011
Markus Scholz, Stephan Sigg, Hedda Schmidtke and Michael Beigl: Challenges for device-free radio-based activity recognition, in Proceedings of the 3rd Workshop on Context Systems Design Evaluation and Optimisation (CoSDEO), 2011
Markus Scholz, Stephan Sigg, Dimana Shihskova, Georg von Zengen, Gerrit Bagshik, Toni Guenther, Michael Beigl and Yusheng Ji: SenseWaves: Radiowaves for context recognition, in Video Proceedings of the 9th International Conference on Pervasive Computing (Pervasive 2011), 2011 (Video, PDF)
Stephan Sigg, Dominik Schuermann and Jusheng Ji: PINtext: A framework for secure communication based on context, in Proceedings of the 8th International ICST Conference on Mobile and Ubiquitous Systems (MobiQuitous 2011), 2011
Johannes Starosta, Markus Reschke, Sebastian Schwarzl, Stephan Sigg and Michael Beigl: Context awareness through the RF-channel, in 2nd workshop for Context Systems Design and Evaluation (CoSDEO) in conjunction with 5th Conference on Architecture for Computing Systems (ARCS), 2011
Stephan Sigg, Rayan Merched El Masri and Michael Beigl: Feedback based closed-loop carrier synchronisation: A sharp asymptotic bound, an asymptotically optimal approach, simulations and experiments, in IEEE Transactions on Mobile Computing (TMC), 2011 (DOI)
Stephan Sigg, Predrag Jakimovski, Florian Becker, Hedda Schmidtke, Martin Alexander Neumann, Yusheng Ji and Michael Beigl: Neuron-inspired collaborative transmission in wireless sensor networks, in Proceedings of the 8th International ICST Conference on Mobile and Ubiquitous Systems (MobiQuitous 2011), 2011
Stephan Sigg: Context-based security: State of the art, open research topics and a case study, in Proceedings of the 5th ACM International Workshop on Context-Awareness for Self-Managing Systems (CASEMANS 2011), 2011 (DOI)
Stephan Sigg, Matthias Budde, Yusheng Ji and Michael Beigl: Entropy of audio fingerprints for unobtrusive device authentication, in Poster Proceedings of the 7th International and Interdisciplinary Conference on Modeling and Using Context (Context2011), 2011 (Online)
Stephan Sigg, Michael Beigl and Behnam Banitalebi: Efficient adaptive communication from resource restricted transmitters, In Organic Computing - A Paradigm Shift for Complex Systems, Christian Mueller-Schloer and Hartmut Schmeck and and Theo Ungerer, Springer, 2011 (Online)
Stephan Sigg and Michael Beigl: An adaptive protocol for distributed beamforming, in 17. Fachtagung 'Kommunikation in Verteilten Systemen 2011' (KiVS11), 2011 (PDF)
Markus Reschke, Johannes Starosta, Sebastian Schwarzl and Stephan Sigg: Situation awareness based on channel measurements, in 4th conference on context awareness for proactive systems (CAPS), 2011 (DOI)
Predrag Jakimovski, Florian Becker, Stephan Sigg, Hedda R. Schmidtke and Michael Beigl: Collective Communication for Dense Sensing Environments, in 7th IEEE International Conference on Intelligent Environments (IE), 2011 (**Best paper**) (DOI)
Behnam Banitalebi, Dawud Gordon, Stephan Sigg, Takashi Miyaki and Michael Beigl: Collaborative Channel Equalization: Analysis and Performance Evaluation of Distributed Aggregation Algorithms in WSNs, in Proceedings of the 8th IEEE International Conference on Mobile Ad-hoc and Sensor Systems (IEEE MASS 2011), 2011 (DOI)
2010
Stephan Sigg and Michael Beigl: Distributed adaptive expectation aware in-network context processing, in Fourth ACM International Workshop on Context-Awareness for Self-Managing Systems, 2010
Contact
Stephan Sigg National Institute of Informatics (NII) 2-1-2 Hitotsubashi, Chiyoda-ku 101-8430 Tokyo Japan
