Evaluation of the performance of the SLoPS: Available Bandwidth Estimation Technique in IEEE 802.11b Wireless Networks

  • AMAMRA Abdelaziz
  • HOU Kun Mean
  • CHANET Jean-Pierre

Abstract

Over the past few years, to actively measure the end-to-end available bandwidth of a network path several algorithms have been created (TOPP, SLoPS, Spurce, VPS ldots). These algorithms are dedicated to wired Ethernet network; however the bandwidth estimation in wireless network field remains a challenge. In the present work we evaluate the performance of Self-Loading Periodic Stream (SLoPS) method to estimate the available bandwidth in the IEEE 802.11b wireless network. By using different probe packet sizes and different Cross-Traffics, we show that the available bandwidth measurements are affected by the varying Cross-Traffic in both Ethernet and wireless IEEE 802.11b network. The variation of probe packet size affects only the available bandwidth measurements in the wireless network and not in Ethernet network case. Also SLoPS technique provides less accurate measurements in the IEEE 802.11b wireless network. The simulation is built in NS-2. The results are analyzed by MatLab software

Keywords

IEEE 802.11b SLoPS Available Bandwidth Cross-Traffic Quality of Service 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Amamra A, Hou KM, Chanet JP (2006) Wireless Available Bandwidth Estimation: TOPP. 5th edn, international I2TS, Cuiabá, MT-BrazilGoogle Scholar
  2. 2.
    Bolot JC (1993) Characterizing End-to-End Packet Delay and Loss in the Internet. ACM SIGCOMM, pp 289–298Google Scholar
  3. 3.
    Carter, Crovella ME (1996) Measuring bottleneck link speed in packet-switched networks. Technical Report TR-96-006, Boston University Computer Science Department, Boston, MA, USAGoogle Scholar
  4. 4.
    Dovrolis C, Ramanathanm P, Moore D (2001) What Do Packet Dispersion Techniques Measure?. In: IEEE INFOCOM’01, Anchorage, AK, USA, vol 2, pp 905–914Google Scholar
  5. 5.
    Hou KM et al (2006) LiveNode: LIMOS versatile embedded wireless sensor node. Technical Report, LIMOS, France, pp 1–6Google Scholar
  6. 6.
    Http://www.erg.abdn.ac.uk/users/gorry/course/lan-pages/enet-calc.htmlGoogle Scholar
  7. 7.
    Jacobson V (1988) Congestion Avoidance and Control. ACM SIGCOMM, pp 314–329Google Scholar
  8. 8.
    Johnsson A, Melander B, Björkman M (2005) Bandwidth Measurement in Wireless Networks. Mediterranean Ad Hoc Networking Workshop, Porquerolles, FranceGoogle Scholar
  9. 9.
    Keshav S (1991) A Control-Theoretic Approach to Flow Control. ACM SIGCOMM, pp 3–15Google Scholar
  10. 10.
    Manish J, Dovrolis C (2002) End-to-end available bandwidth: Measurement methodology, dynamics, and relation with TCP throughput. ACM SIGCOMM, Pittsburg, PA, USA, pp 295–308Google Scholar
  11. 11.
    Manish J, Dovrolis C (2002) Pathload: A Measurement Tool for End-to-End Available Bandwidth. Passive and Active Measurements, Fort Collins, Colorado, USA, pp 14–25Google Scholar
  12. 12.
    McGraw Hill Osborne (2003) CWNA Certified Wireless Network Administrator: Official Study Guide (Exam PW0-100). Snd Edn. ed Planet3 WirelessGoogle Scholar
  13. 13.
    Melander B, Bjorkman M, Gunningberg P (2000) A New End-to-End Probing and Analysis Method for Estimating Bandwidth Bottlenecks. Global Internet SymposiumGoogle Scholar
  14. 14.
    Prasad RS, Murray M, Dovrolis C, Claffy K (2003) Bandwidth estimation: Metrics, measurement techniques and tools. IEEE Network vol 17, 6:27–35CrossRefGoogle Scholar
  15. 15.
    Ribeiro VJ, Riedi RH, Baraniuk RG, Navratil J, Cottrell L (2003) PathChirp: Efficient Available Bandwidth Estimation for Network Paths. Passive and Active Measurement Workshop, San DiegoGoogle Scholar
  16. 16.
    Strauss J, Katabi D, Kaashoek F (2003) A Measurement Study of Available Bandwidth Estimation Tools. 3rd edn, ACM SIGCOMM Internet Measurement Workshop, Miami Breach, FL, USA, pp 39–44Google Scholar

Copyright information

© Springer 2007

Authors and Affiliations

  • AMAMRA Abdelaziz
    • 1
  • HOU Kun Mean
    • 1
  • CHANET Jean-Pierre
    • 1
  1. 1.LIMOS Laboratory, UMR 6158 CNRSUniversity of Blaise Pascal BP 1025 24 av des Landais 63173AubiéreFrance

Personalised recommendations