Shengpu Liu and Liang Cheng, A Context-Aware Reflective Middleware Framework for Distributed Real-time and Embedded Systems, Journal of Systems and Software, Vol. 84, No. 2, pp. 205-218, February 2011.

  To improve the reconfiguration efficiency for supporting distributed real-time and embedded systems, we have designed a new context-aware reflective middleware (CARM) framework - MARCHES, which offers an original structure of multiple component chains to reduce local behavior change time and a novel synchronization protocol using active messages to reduce distributed behavior synchronization time. To the best of knowledge, we have established the first generic analytical model for fair comparisons of the reconfiguration efficiency of various CARM frameworks and compared MARCHES with peer CARM frameworks based on it. Quantitative empirical results also verified the effectiveness of the MARCHES framework. Evaluations demonstrate that MARCHES is robust and scalable and generates small memory footprint as well, which makes it suitable for supporting DRE systems.

Shengpu Liu and Liang Cheng, A Context-Aware Reflective Middleware Framework for Adaptive Real-time Vehicle Applications, Technical Report LU-CSE-09-001, Department of Computer Science and Engineering, Lehigh University, accessible at http://www3.lehigh.edu/engineering/cse//research/technicalreports.asp.

 This paper introduces context-aware reflective middleware, which can measure real-time contexts and accordingly reconfigure the behavior of supported applications, to enhance the affordability, flexibility, and adaptability of the future vehicle safety systems. Then, it presents MARCHES, which improves the reconfiguration efficiency for engineering real-time vehicle applications in dynamic environments. Experimental results and Evaluations demonstrate that MARCHES is time efficient, robust, and scalable and generates small memory footprint, which makes it suitable for supporting the real-time vehicle applications.

Shengpu Liu,  Liang Cheng, Active Message Oriented Adaptation Middleware for Collaborative Applications in Heterogeneous Environments , to appear in Proceedings of the 2008 IEEE International Conference on Communications (ICC 2008) , Beijing, China, May 19-23, 2008

 This paper presents an active message based asynchronous synchronization algorithm to improve the reconfiguration efficiency of adaptive middleware, like MARCHES, for distributed collaborative applications. The experiments and evaluations show that the proposed algorithm has the following advantages like: short reconfiguration time, which is reduced from seconds to hundreds of microseconds; low overhead, which is only one integer index as active message header, and good robustness, which makes the reconfiguration not affected by network conditions.

Shengpu Liu,  Liang Cheng, Local Tree Based Geometric Routing , to appear in Proceedings of the 2007 IEEE International Conference on Communications (ICC 2007) , Glasgow, Scotland, June 24-28, 2007

 This paper presents a local tree based geometric routing algorithm (LTGR) to solve the implementation issues of existing geometric routing algorithms, which use planarization and right hand rule to bypass the "void areas" where the greedy algorithm does not work. LTGR is one of the routing protocols to build the MARCHES test-bed involving distributed applications in ad-hoc networks. It can support the communication and synchronization of MARCHES agents, which may be connected through multiple hops.

Qiang Wang, Liang Cheng. FEAT: Improving Accuracy in End-to-end Available Bandwidth Measurement, In Proceedings of the 2006 IEEE Global Telecommunications Conference (GLOBECOM 2006), San Francisco, CA, Nov. 27 -Dec.1, 2006.

 This paper presents an end-to-end available bandwidth measurement tool, called FEAT (Fish-Eye Available- bandwidth Tool), which can sample probing rates more frequently and increase the number of packets used at each rate in a focus region to improve the measurement accuracy. Experiments show that FEAT provides both accurate estimations of the available bandwidth and low overhead compared to the existing techniques. FEAT is one of the network awareness tools for the MARCHES awareness measurement layer.

Qiang Wang, Yaoyao Zhu, and Liang Cheng, Reprogramming Wireless Sensor Networks: Challenges and Approaches, IEEE Network, May 2006. (acceptance rate: 7/68 = 10.3%)

 This paper provides a comprehensive survey of the state-of-the-art reprogramming systems and outlines a framework to examine different functions in reprogramming, followed by an analysis of reprogramming challenges and different approaches to address these challenges. Sensor reprogramming is an important technique to deploy different monitoring functions to wireless sensor networks and measure the physical environment awareness in the MARCHES awareness measurement layer. Further, sensor reprogramming is the most explored method for sensor application adaptation, although there are still many implementation issues for this method, like high overhead and power consumption and less flexibility. The sensor network extension of MARCHES will address these issues based on the designed component-based architecture and active message-based synchronization protocol.

Shengpu Liu and Liang Cheng, Efficient Data Compression in Wireless Sensor Networks for Civil Infrastructure Health Monitoring, in Proceedings of 2006 International Workshop on Wireless Ad-hoc and Sensor Networks, New York City, June 2006.

 This paper presents a distributed data compression scheme for bridge monitoring data collection via wireless sensor networks. The research serves two roles in this project: one as a data compression service for environment awareness data collection, the other as an application to test the adaptation middleware in wireless sensor networks.

Qiang Wang, Qing Ye, Liang Cheng. A QoS Proxy in Heterogeneous Networks using Inter-application and Inter-client Priorities. In Proceedings of the tenth IEEE Symposium on Computers and Communications (ISCC'05). Cartagena, SPAIN. June 27-30, 2005.

 This paper presents a system architecture study related to how to use MARCHES to support adaptive robust collaborations across heterogeneous environments and systems. The proposed proxy-based architecture does not require application source-code modifications to work with MARCHES but instead it integrates QoS awareness information and inter-application and inter-client priority policies to support application-transparent adaptation using priority fair queues at the proxy.

Qiang Wang, Liang Cheng. A Flexible Awareness Measurement and Management Architecture for Adaptive Applications. In Proceedings of the 2004 IEEE Global Telecommunications Conference (Globecom 2004), Dallas, Texas, Nov 29 - Dec 3, 2004.

 This paper presents the MARCHES design considerations about flexible awareness measurement and management for adaptive applications in a pervasive computing environment.

Qiang Wang, Liang Cheng. AwareWare: An Adaptation Middleware for Heterogeneous Environments. In Proceedings of the 2004 IEEE International Conference on Communications (ICC 2004),Paris, France, June 20-24, 2004. pp.1406-1410.

 This paper presents the AwareWare design considerations.