XMAS: An eXtraordinary Memory Allocation Scheme for Resource-Constrained Sensor Operating Systems

  • Sangho Yi
  • Hong Min
  • Junyoung Heo
  • Boncheol Gu
  • Yookun Cho
  • Jiman Hong
  • Hyukjun Oh
  • Byunghun Song
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4325)


The wireless sensor networks are sensing, computing and communication infrastructures that allow us to monitor, instrument, observe, and respond to phenomena in the harsh environment. Sensor operating systems that run on tiny sensor nodes are the key to the performance of the distributed computing environment for the wireless sensor networks. Therefore, sensor operating systems should be able to operate efficiently in terms of energy consumption and resource management. In this paper, we present XMAS to improve the time and space efficiency of memory management for the sensor operating systems. XMAS was implemented on Nano-Qplus which is a multi-threading sensor operating system. Our experimental results show that the XMAS performs efficiently in both time and space compared with existing memory allocation mechanisms.


Sensor Node Wireless Sensor Network Memory Space Memory Block Memory Allocation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Bhatti, S., Carlson, J., Dai, H., Deng, J., Rose, J., Sheth, A., Shucker, B., Gruenwald, C., Torgerson, A., Han, R.: Mantis os: An embedded multithreaded operating system for wireless micro sensor platforms. ACMKluwer Mobile Networks and Applications (MONET) Journal, Special Issue on Wireless Sensor Networks (2005)Google Scholar
  2. 2.
    Lee, K., Shin, Y., Choi, H., Park, S.: A design of sensor network system based on scalable and reconfigurable nano-os platform. In: IT-Soc International Conference (2004)Google Scholar
  3. 3.
    Akyildiz, I., Su, W., Sankarasubramaniam, Y., Cayirci, E.: A survey on sensor networks. IEEE Communications Magazine, 102–114 (2002)Google Scholar
  4. 4.
    Lundquist, J.D., Cayan, D.R., Dettinger, M.: Meteorology and hydrology in yosemite national park: A sensor network application. In: Zhao, F., Guibas, L.J. (eds.) IPSN 2003. LNCS, vol. 2634, pp. 518–528. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  5. 5.
    Hirafuji, M., Fukatsu, T., Hu, H., Kiura, T., Laurenson, M., He, D., Yamakawa, A., Imada, A., Ninomiya, S.: Advanced sensor-network with field monitoring servers and metbroker. In: CIGR International Conference (2004)Google Scholar
  6. 6.
    Levis, P., Madden, S., Gay, D., Polastre, J., Szewczyk, R., Woo, A., Brewer, E., Culler, D.: The emergence of networking abstractions and techniques in tinyos. In: First USENIX/ACM Symposium on Networked Systems Design and Implementation (NSDI 2004) (2004)Google Scholar
  7. 7.
    Levis, P., Culler, D.: Mate: a virtual machine for tiny networked sensors. In: International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 85–95 (2002)Google Scholar
  8. 8.
    Han, C.C., Kumar, R., Shea, R., Kohler, E., Srivastava, M.B.: A dynamic operating system for sensor nodes. In: MobiSys, pp. 163–176 (2005)Google Scholar
  9. 9.
    Knuth, D.E.: The art of computer programming. In: Fundamental algorithms, vol. 1. Addison-Wesley, Reading (1973)Google Scholar
  10. 10.
    McKusick, M.K., Karels, M.J.: Design of a general purpose memory allocator for the 4.3bsd unix kernel. In: Proceedings of the San Francisco USENIX Conference, pp. 295–303 (1988)Google Scholar
  11. 11.
    Lea, D.: A memory allocator. Unix/Mail, 6/96 (1996)Google Scholar
  12. 12.
    Knowlton, K.C.: A fast storage allocator. Communications of the ACM 8, 623–625 (1965)MATHCrossRefGoogle Scholar
  13. 13.
    Peterson, J.L., Norman, T.A.: Buddy systems. Communications of the ACM 20, 421–431 (1977)MATHCrossRefGoogle Scholar
  14. 14.
    Page, I.P., Hagins, J.: Improving the performance of buddy systems. IEEE Transactions on Computers C-35, 441–447 (1986)CrossRefGoogle Scholar
  15. 15.
    Masmano, M., Ripoll, I., Crespo, A., Real, J.: Tlsf: a new dynamic memory allocator for real-time systems. In: Euromicro Conference on Real-Time Systems (ECRTS 2004) (2004)Google Scholar
  16. 16.
    Vahalia, U.: Unix internals: The new frontiers. Prentice Hall, Englewood Cliffs (1996)MATHGoogle Scholar
  17. 17.
    Johnstone, M.S., Wilson, P.R.: The memory fragmentation problem: solved? ACM SIGPLAN Notices 34, 26–36 (1999)CrossRefGoogle Scholar
  18. 18.
    Crossbow (website),
  19. 19.
    Octacomm (website),

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Sangho Yi
    • 1
  • Hong Min
    • 1
  • Junyoung Heo
    • 1
  • Boncheol Gu
    • 1
  • Yookun Cho
    • 1
  • Jiman Hong
    • 2
  • Hyukjun Oh
    • 3
  • Byunghun Song
    • 4
  1. 1.System Software Research Laboratory, School of Computer Science and EngineeringSeoul National University 
  2. 2.School of Computer Science and EngineeringKwangwoon University 
  3. 3.School of Electronic EngineeringKwangwoon University 
  4. 4.Korea Electronics Technology InstituteIntelligent IT System Research Center 

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