Passive Overall Packet Loss Estimation at the Border of an ISP

In this paper, a heuristic method that leverages packet traces captured at the entire boarder of an ISP to distinguish and estimate the overall packet loss within an ISP’s management domain (Intra_Path_Loss) and that in the outside Internet (Inter_Path_Loss) is proposed. Our method is inspired by that packet losses happened at different locations will cause different TCP sequence number patterns at the border of an ISP. Thereby, we leverage these TCP sequence number patterns to build a series of heuristic rules to estimate Intra_Path_Loss and Inter_Path_Loss, respectively. We do this work with an eye towards showing that the overall packet losses defined and estimated in this paper can provide the operators with some valuable information to help them precisely grasp the overall performance of network paths and narrow down the range of network anomalies. The proposed method is rigorously validated with simulations, and finally the results from a regional academic network JSERNET verify its effectiveness and practicability. 1 JSERNET (Jiangsu Education and Research Network) is a regional academic network of CERNET. It covers more than 100 research units and universities, and its backbone bandwidth increased from OC-48 to OC-192 in January 2006. http://doi.org/10.3837/tiis.2018.07.010 ISSN : 1976-7277 KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS VOL. 12, NO. 7, July 2018 3151

[1]  Liang Zhou,et al.  On Data-Driven Delay Estimation for Media Cloud , 2016, IEEE Transactions on Multimedia.

[2]  kc claffy,et al.  Estimating internet address space usage through passive measurements , 2013, CCRV.

[3]  Liang Zhou,et al.  QoE-Driven Delay Announcement for Cloud Mobile Media , 2017, IEEE Transactions on Circuits and Systems for Video Technology.

[4]  V. Paxson End-to-end Internet packet dynamics , 1997, SIGCOMM '97.

[5]  K. Murugan,et al.  Improving TCP Performance in Wireless Networks by Detection and Avoidance of Spurious Retransmission Timeouts , 2015, J. Inf. Sci. Eng..

[6]  Jian Gong,et al.  A real-time method for detecting internet-wide SYN flooding attacks , 2015, The 21st IEEE International Workshop on Local and Metropolitan Area Networks.

[7]  Xenofontas A. Dimitropoulos,et al.  Classifying internet one-way traffic , 2012, Internet Measurement Conference.

[8]  Simone Basso,et al.  Strengthening measurements from the edges: application-level packet loss rate estimation , 2013, CCRV.

[9]  Simone Basso,et al.  Estimating packet loss rate in the access through application-level measurements , 2012, W-MUST '12.

[10]  Hongke Zhang,et al.  Cache-Filter: A Cache Permission Policy for Information-Centric Networking , 2015, KSII Trans. Internet Inf. Syst..

[11]  Matthew Roughan,et al.  Rigorous Statistical Analysis of Internet Loss Measurements , 2013, IEEE/ACM Transactions on Networking.

[12]  Fernando Silveira,et al.  Predicting packet loss statistics with hidden Markov models for FEC control , 2012, Comput. Networks.

[13]  Evangelos P. Markatos,et al.  Realistic Passive Packet Loss Measurement for High-Speed Networks , 2009, TMA.

[14]  Kazunori Yamamoto,et al.  Forward RTO-Recovery ( F-RTO ) : An Algorithm for Detecting Spurious Retransmission Timeouts with TCP , 2005 .

[15]  Zhiguo Hu,et al.  A new approach for packet loss measurement of video streaming and its application , 2016, Multimedia Tools and Applications.

[16]  Randy H. Katz,et al.  The Eifel algorithm: making TCP robust against spurious retransmissions , 2000, CCRV.

[17]  Arun Venkataramani,et al.  iPlane: an information plane for distributed services , 2006, OSDI '06.