ProgME: Programmable Measurement Architecture
Traffic measurement is central to network operation, management, and security. Yet, support for measurement was not an integral part of the original Internet architecture. This project envisages and advocates a versatile measurement architecture as an integral part of any future network substrate, with not only built-in hardware and software primitives incorporated into network elements, but also network-wide architectural support for network measurement. The measurement architecture should be flexible enough to support current and future measurement needs, adaptable to dynamic network conditions, modular/lightweight, and scalable to high link speeds.
In particular, we explore a Programmable MEasurement (ProgME) architecture based on a novel concept of flowset arbitrary set of flows defined according to application requirements and/or traffic conditions. Through a simple flowset composition language, ProgME can incorporate application requirements, adapt itself to circumvent the challenges on scalability posed by the large number of flows, and achieve a better application-perceived accuracy. ProgME can analyze and adapt to traffic statistics in real-time. Using sequential hypothesis test, ProgME can achieve fast and scalable heavy hitter identification.
The team also strives to identify a core set of data streaming and sampling primitives that can be composed together to satisfy most of the queries. Efficient hardware implementation for these core set of primitives will constitute the basic measurement modules that can be easily reconfigured to measure traffic at different desired granularities. Measurement application case studies will be carried out to evaluate and showcase the capabilities of the proposed approach.
- Chen-Nee Chuah, UC Davis
External NSF Co-PIs
- Soheil Ghiasi, ECE, UC Davis
- Maya Gokhale, Lawrence Livermore National Laboratory
- Srini Seetharaman, Deutsche Telekom R&D Lab
- Puneet Sharma, Hewlett-Packard Laboratories
Graduate Students and Alumni
- Han Liu, ECE
- Mehdi Malboubi, ECE
- Liyuan Wang, ECE
- Arun Raghuramu, CS
- Faisal Khan, ECE (PhD, 2012, co-advised w/ Prof. Ghiasi)
- Guanyao Huang, ECE (PhD, 2012)
- Saqib Raza, CS (PhD, 2010)
- Lihua Yuan, ECE (PhD, 2008)
M. Malboubi, C. Vu, C-.N. Chuah, and P. Sharma, "Compressive Sensing Network Inference with Multiple-Description Fusion Estimation," to appear in IEEE Globecom, December 2013. [pdf]
F. Khan, N. Hosein, S. Ghiasi, C-N. Chuah, and P. Sharma, "Streaming Solutions for Fine-Grained Network Traffic Measurements and Analysis," to appear in IEEE/ACM Transactions on Networking.
F. Khan, C-N. Chuah, and S. Ghiasi, "A Dynamically Reconfigurable System For Close-Loop Measurements of Network Traffic," to appear in IEEE Transactions on Computers.
M. Malboubi, C. Vu, C-N. Chuah, and P. Sharma, "Decentralizing Network Inference Problems with Multiple-Description Fusion Estimation (MDFE)," IEEE INFOCOM, April 2013. [pdf]
C. Chang, G. Huang, H. Liu, B. Lin, and C-N. Chuah, "Distributed Measurement-Aware Routing: Striking A Balance Between Measurement And Traffic Engineering," IEEE INFOCOM MiniConference, March 2012. [pdf]
S. Raza, G. Huang, C-N. Chuah, S. Seetharamanh, and J. Pal Singh, "Measurouting: A Framework For Routing Assisted Traffic Monitoring," ACM/IEEE Transactions on Networking, vol. 20, no. 1, pp.45-56, February 2012. [pdf]
G. Huang, C. Chang, C-N. Chuah, and B. Lin, "Measurement-Aware Monitor Placement and Routing: A Joint Optimization Approach for Network-Wide Measurements in Dynamic Environments," IEEE Transactions on Network and Service Management, issue 99, pp. 1-12, January, 2012. [pdf]
F. Khan, N. Hosein, C-N. Chuah, and S. Ghiasi, "Streaming Solutions For Fine-Grained Network Traffic Measurements And Analysis," ACM/IEEE Symposium on Architectures for Networking and Communication Systems (ANCS), October 2011. [pdf]
C. Chang, G. Huang, B. Lin, and C-N. Chuah, "LEISURE: A Framework For Load-Balanced Network-Wide Traffic Measurements," ACM/IEEE Symposium on Architectures for Networking and Communication Systems (ANCS), October 2011. [pdf]
G. Huang, S. Raza, S. Seetharamanh, and C-N. Chuah, "Dynamic measurement-aware routing in practice," IEEE Networks Special Issue on Network Traffic Monitoring and Analysis, vol. 25, no. 3, pp. 29-34, May/June 2011. [pdf]
G. Huang, A. Lall, C-N. Chuah, and J. Xu, "Uncovering Global Icebergs in Distributed Streams: Results and Implications," Journal of Network and Systems Management, vol. 19, no. 1, pp. 84-110, March 2011 [pdf]
L. Yuan, C-N. Chuah, and P. Mohapatra, "ProgMe: Towards Programmable Network Measurement," ACM/IEEE Transactions on Networking, vol. 19, no. 1, pp. 115-128, February 2011. [pdf]
F. Khan, M. Gokhale, and C-N. Chuah, "FPGA-based Network Traffic Analysis using Traffic Dispersion Patterns," International Conference on Field Programmable Logic and Applications (FPL), August 2010. [pdf]
J. Mai, A. Sridharan, H. Zang, and C-N. Chuah, "Fast Filtered Sampling: Catching Mice and Elephants with One Net," Elsevier Computer Networks, vol. 54, no. 11, pp. 1885-1898, August 2010. [pdf]
R. Keralapura, A. Nucci, and C-N. Chuah, "A Novel Self-Learning Architecture for P2P Traffic Classification in High Speed Networks," Elsevier Computer Networks, vol. 54, no. 7, pp. 1055-68, May 2010. [pdf]
S. Raza, G. Y. Huang, C-N. Chuah, S. Seetharaman, and J. P. Singh, "MeasuRouting: A Framework for Routing-Assisted Traffic Monitoring," IEEE INFOCOM, March 2010. [pdf]
R. Keralapura, A. Nucci, and C-N. Chuah, "Self-Learning Peer-to-Peer Traffic Classifier," IEEE Conference on Computer Communications and Networks (ICCCN), August 2009. [pdf]
G. Huang, A. Lall, C-N. Chuah, and J. Xu, "Uncovering Global Icebergs in Distributed Monitors," IEEE IWQoS, July 2009. [pdf]
F. Khan, L. Yuan, C-N. Chuah, and S. Ghiasi, "Programmable and Real-time Network Traffic Measurements," ACM/IEEE Symposium on Architectures for Networking and Communications Systems, November 2008. [pdf]
This project is supported by National Science Foundation (NSF) NeTS CNS-0905273 grant , CITRIS Seed Funding, and HP Labs 2011, 2012, and 2013 Innovation Research Award