Chen, Xuan and Heidemann, John
USC/Information Sciences Institute
Xuan Chen and John Heidemann 2005. Flash Crowd Mitigation via Adaptive Admission Control Based on Application-Level Observation. ACM Transactions on Internet Technology. 5, 3 (Aug. 2005), 532–562. [DOI] [PDF]
We design an adaptive admission control mechanism, network early warning system (NEWS), to protect servers and networks from flash crowds and maintain high performance for end-users. NEWS detects flash crowds from performance degradation in responses and mitigates flash crowds by admitting incoming requests adaptively. We evaluate NEWS performance with both simulations and testbed experiments. We first investigate a network-limited scenarion in simulations. We find that NEWS detects flash crowds within 20 seconds. By discarding 32% of incoming requests, NEWS protects the target server and networks from overloading, reducing the response packet drop rate from 25% to 2%. For admitted requests, NEWS increases their response rate by two times. This performance is similar to the best static rate limiter deployed in the same scenario. We also investigate the impact of detection intervals on NEWS performance, showing it affects both detection delay and false alarm rate. We further consider a server memory-limited scenario in testbed experiments, confirming that NEWS is also effective in this case. We also examine the runtime cost of NEWS traffic monitoring in practice and find that it consumes little CPU time and relatively small memory. Finally, we show NEWS effectively protects bystander traffic from flash crowds.
@article{Chen05a, author = {Chen, Xuan and Heidemann, John}, title = {Flash Crowd Mitigation via Adaptive Admission Control Based on Application-Level Observation}, journal = {ACM Transactions on Internet Technology}, year = {2005}, sortdate = {2005-08-01}, project = {ant, saman, conser}, jsubject = {www}, volume = {5}, number = {3}, month = aug, pages = {532--562}, jlocation = {johnh: pafile}, keywords = {NEWS, admission control, congestion control}, url = {https://ant.isi.edu/%7ejohnh/PAPERS/Chen05a.html}, pdfurl = {https://ant.isi.edu/%7ejohnh/PAPERS/Chen05a.pdf}, copyrightholder = {ACM}, copyrightterms = { Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. }, myorganization = {USC/Information Sciences Institute}, doi = {http://doi.acm.org/10.1145/1084772.1084776}, otherurl = {http://portal.acm.org/ft_gateway.cfm?id=1084776&type=pdf&coll=portal&dl=ACM&CFID=58869837&CFTOKEN=77379250} }
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.