A SpaceTime Oriented Macroprogramming Paradigm for Push-Pull Hybrid Sensor Networking

This paper proposes a spatio-temporal macroprogramming paradigm for push-pull hybrid wireless sensor networks (WSNs). The proposed paradigm, called SpaceTime Oriented Programming (STOP), is designed to reduce the complexity of WSN programming by specifying data collection and processing from a global viewpoint as a whole rather than a viewpoint of sensor nodes as individuals. STOP treats space and time as first-class citizens and combines them as spacetime continuum. A spacetime is a three dimensional object that consists of a two spatial dimensions and a time playing the role of the third dimension. STOP allows application developers to program data collection and processing to spacetime, and abstracts away the details in WSNs, such as how many nodes are deployed in a WSN, how nodes are connected with each other and how to route data queries in a WSN. Using the notion of spacetime, data collection/processing is consistently specified for both the past and future in arbitrary spatio-temporal resolutions. This paper describes the design of the STOP language and the implementation of the STOP runtime environment.

[1]  Philip Levis,et al.  Maté: a tiny virtual machine for sensor networks , 2002, ASPLOS X.

[2]  Wei Hong,et al.  TinyDB: an acquisitional query processing system for sensor networks , 2005, TODS.

[3]  Matt Welsh,et al.  Programming Sensor Networks Using Abstract Regions , 2004, NSDI.

[4]  Bhaskar Krishnamachari,et al.  Comparative Analysis of Push-Pull Query Strategies for Wireless Sensor Networks , 2006, DCOSS.

[5]  Gerald W. Both,et al.  Object-oriented analysis and design with applications , 1994 .

[6]  Grady Booch,et al.  Object-oriented analysis and design with applications (2nd ed.) , 1993 .

[7]  M Mernik,et al.  When and how to develop domain-specific languages , 2005, CSUR.

[8]  Jianliang Xu,et al.  Monitoring Top-k Query inWireless Sensor Networks , 2006, 22nd International Conference on Data Engineering (ICDE'06).

[9]  Deepak Ganesan,et al.  PRESTO: feedback-driven data management in sensor networks , 2009, TNET.

[10]  Yuguang Fang,et al.  Managing wireless sensor networks with supply chain strategy , 2004, First International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks.

[11]  M. Welsh,et al.  The Regiment Macroprogramming System , 2007, 2007 6th International Symposium on Information Processing in Sensor Networks.

[12]  David Chu,et al.  Entirely declarative sensor network systems , 2006, VLDB.

[13]  Erik Meijer.  Dynamic typing when needed: The end of the cold war between programming languages , 2004 .

[14]  Stephen H. Lieberman,et al.  Multispectral fluorometric sensor for real time in-situ detection of marine petroleum spills , 1970 .

[15]  Ramesh Govindan,et al.  Macro-programming Wireless Sensor Networks Using Kairos , 2005, DCOSS.