MCP: An Energy-Efficient Code Distribution Protocol for Multi-Application WSNs

In this paper, we study the code distribution problem in multi-application wireless sensor networks (MA-WSNs), i.e., sensor networks that can support multiple applications. While MA-WSNs have many advantages over traditional WSNs, they tend to require frequent code movements in the network, and thus here new challenges for designing energy efficient code dissemination protocols. We propose MCP, a stateful Multicast based Code redistribution Protocol for achieving energy efficiency. Each node in MCP maintains a small table to record the interesting information of known applications. The table enables sending out multicast-based code dissemination requests such that only a subset of neighboring sensors contribute to code dissemination. Compared to broadcasting based schemes, MCP greatly reduces signal collision and saves both the dissemination time and reduces the number of dissemination messages. Our experiments results show that MCP can reduce dissemination time by 25% and message overhead by 20% under various network settings.

[1]  Weijia Li,et al.  UCC: update-conscious compilation for energy efficiency in wireless sensor networks , 2007, PLDI '07.

[2]  David E. Culler,et al.  Incremental network programming for wireless sensors , 2004, 2004 First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, 2004. IEEE SECON 2004..

[3]  Issa M. Khalil,et al.  Stream: Low Overhead Wireless Reprogramming for Sensor Networks , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[4]  Sandeep S. Kulkarni,et al.  Infuse: A TDMA Based Data Dissemination Protocol for Sensor Networks , 2006, Int. J. Distributed Sens. Networks.

[5]  Jonathan W. Hui,et al.  Securing the Deluge network programming system , 2006, 2006 5th International Conference on Information Processing in Sensor Networks.

[6]  Alejandro P. Buchmann,et al.  Towards multi-purpose wireless sensor networks , 2005, 2005 Systems Communications (ICW'05, ICHSN'05, ICMCS'05, SENET'05).

[7]  Koen Langendoen,et al.  Efficient code distribution in wireless sensor networks , 2003, WSNA '03.

[8]  Rajeev Gandhi,et al.  Sluice: Secure Dissemination of Code Updates in Sensor Networks , 2005, 26th IEEE International Conference on Distributed Computing Systems (ICDCS'06).

[9]  Limin Wang,et al.  MNP: Multihop Network Reprogramming Service for Sensor Networks , 2004, 25th IEEE International Conference on Distributed Computing Systems (ICDCS'05).

[10]  David E. Culler,et al.  Telos: enabling ultra-low power wireless research , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[11]  Feng Zhao,et al.  Scalable Information-Driven Sensor Querying and Routing for Ad Hoc Heterogeneous Sensor Networks , 2002, Int. J. High Perform. Comput. Appl..

[12]  David E. Culler,et al.  The dynamic behavior of a data dissemination protocol for network programming at scale , 2004, SenSys '04.

[13]  David E. Culler,et al.  TOSSIM: accurate and scalable simulation of entire TinyOS applications , 2003, SenSys '03.

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

[15]  Behçet Sarikaya,et al.  Code Dissemination in Sensor Networks with MDeluge , 2006, 2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks.

[16]  Yang Yu,et al.  Supporting concurrent applications in wireless sensor networks , 2006, SenSys '06.

[17]  Adam Dunkels,et al.  Run-time dynamic linking for reprogramming wireless sensor networks , 2006, SenSys '06.

[18]  Margaret Martonosi,et al.  Implementing software on resource-constrained mobile sensors: experiences with Impala and ZebraNet , 2004, MobiSys '04.

[19]  Umamaheswaran Arumugam Infuse: a TDMA based reprogramming service for sensor networks , 2004, SenSys '04.