Current Research Projects

Please check the group website for the latest projects.


Previous Research Projects

 

Scalable Logical Coordinates for Routing in Wireless Sensor Networks

In this project, we present logical coordinates based routing (LCR), a novel framework for scalable and location-independent routing in wireless sensor networks. LCR assigns each node a logical coordinate vector, and routes packets following these vectors. We demonstrate that LCR (i) guarantees packet delivery with a high probability, (ii) finds good paths, and (iii) exhibits robust performance in the presence of network voids and node failures. We systematically evaluate the performance of LCR through simulations and compare it with other state-of-the-art protocols. We also propose two extensions of LCR, one for three-dimensional node deployments and the other for unreliable wireless links.

Publications:

Q. Cao and T. Abdelzaher. A Scalable Logical Coordinates Framework for Routing in Wireless Sensor Networks. In Proceedings of the 25th IEEE Real-time Systems Symposium (IEEE RTSS), December 2004.

Q. Cao and T. Abdelzaher. A Scalable Logical Coordinates Framework for Routing in Wireless Sensor Networks. In ACM Transactions on Sensor Networks (TOSN) November 2006.


Analysis of Duty Scheduling Protocols in Wireless Sensor Networks

Lifetime maximization is one key element in the design of sensor-network-based surveillance applications. In this project, we investigated the problem of duty scheduling, where we derived the first closed-form analysis results on the quantitative relationship between energy consumption and surveillance performance. These results were integrated into ANDES, an AADL-based design time tool developed indepdently by researchers at the University of Virginia. We further developed a locally optimal algorithm to reduce the detection delay for intruding targets. We used these results to explain and optimize the performance of large-scale surveillance networks such as VigilNet, where the experimental results verified our conclusions.

Publications:

Q. Cao, T. F. Abdelzaher, T. He and J. A. Stankovic. Towards Optimal Sleep Scheduling in Sensor Networks for Rare Event Detection. In Proceedings of the Fourth International Conference on Information Processing in Sensor Networks (ACM/IEEE IPSN), April 2005.

Q. Cao, T. Yan, J. A. Stankovic, and T. F. Abdelzaher. Analysis of Target Detection Performance for Wireless Sensor Networks. In Proceedings of the First International Conference on Distributed Computing in Sensor Networks (ACM/IEEE DCOSS), June 2005.

P. Vicaire, T. He, Q. Cao, T. Yan, G. Zhou, L. Gu, L. Luo, R. Stoleru, J. A. Stankovic, and T. F. Abdelzaher. Achieving Long-Term Surveillance in VigilNet. In ACM Transactions on Sensor Networks (TOSN), Vol 5, No. 1, Feb 2009.


VigilNet/SOWN (Link)

VigilNet is a large-scale (targeted for 1,000 nodes), self-organized, wireless sensor networks system for long-term (6 months) surveillance, involving detection, tracking, classification, and identification of various targets. VigilNet represents one of the major efforts in the sensor network community to build an integrated sensor network system for surveillance missions. The focus of this effort is to acquire and verify information about enemy capabilities and positions of hostile targets. Such missions often involve a high element of risk for human personnel and require a high degree of stealthiness. Hence, the ability to deploy unmanned surveillance missions, by using wireless sensor networks, is of great practical importance for the military. In this project, we designed and implemented a complete running system (called VigilNet) for energy-efficient surveillance. VigilNet allows a group of cooperating sensor devices to detect and track the positions of moving vehicles in an energy-efficient and stealthy manner. The system consists of 40,000 lines of code, supporting XSM, Mica2 and Mica2dot platforms. The work is currently undergoing a technology transition to DIA.  The figure below shows the high level deployment architecture for VigilNet/SOWN.

 

 

 

 

 

 

 

 

 

 

 

Publications:

P. Vicaire, T. He, Q. Cao, T. Yan, G. Zhou, L. Gu, L. Luo, R. Stoleru, J. A. Stankovic, and T. F. Abdelzaher. Achieving Long-Term Surveillance in VigilNet. In ACM Transactions on Sensor Networks (TOSN), Vol 5, No. 1, Feb 2009.

T. He, P. Vicaire, T. Yan, Q. Cao, G. Zhou, L. Gu, L. Luo, R. Stoleru, J. A. Stankovic and T. Abdelzaher. Achieving Long-Term Surveillance in VigilNet. In Proceedings of the 24th Annual IEEE Conference on Computer Communications (IEEE INFOCOM), 2006. Acceptance ratio: 18%

T. He, S. Krishnamurthy, L. Luo, T. Yan, B. Krogh, L. Gu, R. Stoleru, G. Zhou, Q. Cao, P. Vicaire, J. A. Stankovic, T. Abdelzaher, and J. Hui. VigilNet: An Integrated Sensor Network System for Energy-Efficient Surveillance. In ACM Transactions on Sensor Networks (TOSN), February 2006.


EnviroMic

EnviroMic is a distributed acoustic monitoring, storage and trace retrieval sensor network system geared for a prolonged interval of disconnected operation. Audio represents one of the least exploited modalities in sensor networks to date. The relatively high frequency and large size of audio traces motivate distributed algorithms for coordinating recording tasks, reducing redundancy of data stored by nearby sensors, filtering out silence, and balancing storage utilization in the network. Applications of acoustic monitoring with EnviroMic range from the study of mating rituals and social behavior of animals in the wild to audio surveillance of military targets. EnviroMic is designed for disconnected operation, where the luxury of having a basestation cannot be assumed. We implement the system on a MicaZ platform and systematically evaluate its performance through both indoor testbed experiments and a preliminary outdoor deployment in a nearby forest. Results demonstrate up to a 4-fold improvement in effective storage capacity of the network compared to uncoordinated recording. The figure below shows the deployment environment of EnviroMic.

 

 

 

 

 

 

 

Publications:

L. Luo, Q. Cao, C. Huang, T. Abdelzaher, J. A. Stankovic, and M. Ward. EnviroMic: Towards Cooperative Storage and Retrieval in Audio Sensor Networks. In Proceedings of the 27th International Conference on Distributed Computing Systems (IEEE ICDCS), 2007. Acceptance ratio: 13%

L. Luo, Q. Cao, C. Huang, T. Abdelzaher, J. A. Stankovic, and M. Ward. Design, Implementation and Evaluation of EnviroMic: A Storage-Centric Audio Sensor Network. In ACM Transactions on Sensor Networks (TOSN), 2009.


EnviroTrack

Distributed sensor networks are quickly gaining recognition as viable embedded computing platforms. Current techniques for programming sensor networks are cumbersome, inflexible, and low-level. This project introduces EnviroTrack, an object-based distributed middleware system that raises the level of programming abstraction by providing a convenient and powerful interface to the application developer geared towards tracking the physical environment. EnviroTrack is novel in its seamless integration of objects that live in physical time and space into the computational environment of the application. Performance results demonstrate the ability of the middleware to track realistic targets. 

 

 

 

 

 

 

 

 

 

 

Publications:

T. Abdelzaher, B. Blum, Q. Cao, Y. Chen, D. Evans, J. George, S. George, L. Gu, T. He, S. Krishnamurthy, L. Luo, S. Son, J. Stankovic, R. Stoleru, A. Wood: EnviroTrack: Towards an Environmental Computing Paradigm for Distributed Sensor Networks. IEEE ICDCS 2004