E. Schurman and J. Brutlag, Performance related changes and their user impact, Velocity: web performance and operations conference, 2009.

J. Brutlag, Speed matters for google web search, 2009.

J. Dean and L. A. Barroso, The tail at scale, Communications of the ACM, 2013.
DOI : 10.1145/2408776.2408794

K. Ousterhout, P. Wendell, M. Zaharia, and I. Stoica, Sparrow: Distributed, low latency scheduling, SOSP, 2013.

T. Zhu, A. Tumanov, M. A. Kozuch, M. Harchol-balter, and G. R. Ganger, Prioritymeister: Tail latency qos for shared networked storage, 2014.

C. Stewart, A. Chakrabarti, and R. Griffith, Zoolander: Efficiently meeting very strict, low-latency SLOs, ICAC, 2013.

A. D. Ferguson, P. Bodik, S. Kandula, E. Boutin, and R. Fonseca, Jockey: Guaranteed job latency in data parallel clusters, 2012.

V. Jalaparti, P. Bodik, S. Kandula, I. Menache, M. Rybalkin et al., Speeding up distributed request-response workflows, SIGCOMM, 2013.

M. E. Haque, Y. H. Eom, Y. He, S. Elnikety, R. Bianchini et al., Few-to-many: Incremental parallelism for reducing tail latency in interactive services, ASPLOS, 2015.

M. Jeon, S. Kim, S. Hwang, Y. He, S. Elnikety et al., Predictive parallelization: Taming tail latencies in web search, SIGIR, 2014.

P. Delgado, F. Dinu, A. Kermarrec, and W. Zwaenepoel, Hawk: Hybrid datacenter scheduling, USENIX ATC, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01183857

A. Lakshman and P. Malik, Cassandra: A decentralized structured storage system, SIGOPS Oper. Syst. Rev, 2010.

L. Suresh, M. Canini, S. Schmid, and A. Feldmann, C3: Cutting tail latency in cloud data stores via adaptive replica selection, NSDI, 2015.

B. Atikoglu, Y. Xu, E. Frachtenberg, S. Jiang, and M. Paleczny, Workload analysis of a large-scale key-value store, SIGMETRICS, 2012.

D. Balouek, A. Carpen-amarie, G. Charrier, F. Desprez, E. Jeannot et al., Adding virtualization capabilities to the Grid'5000 testbed, Cloud Computing and Services Science, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00946971

M. J. Huiskes and M. S. Lew, The MIR Flickr retrieval evaluation, 2008.

, Wikimedia downloads

B. F. Cooper, A. Silberstein, E. Tam, R. Ramakrishnan, and R. Sears, Benchmarking cloud serving systems with YCSB, 2010.

, Mongodb

, Openstack swift

, Apache accumulo

, Riak Load Balancing and Proxy Configuration

R. Nishtala, H. Fugal, S. Grimm, M. Kwiatkowski, H. Lee et al., Scaling Memcache at Facebook, NSDI, 2013.

P. Delgado, D. Didona, F. Dinu, and W. Zwaenepoel, Job-aware scheduling in Eagle: Divide and stick to your probes, 2016.

J. Lenstra, A. R. Kan, and P. Brucker, Complexity of machine scheduling problems, Studies in Integer Programming, 1977.

B. H. Bloom, Space/time trade-offs in hash coding with allowable errors, Communications of the ACM, 1970.
DOI : 10.1145/362686.362692

F. Bonomi, M. Mitzenmacher, R. Panigrahy, S. Singh, and G. Varghese, An improved construction for counting bloom filters, European Symposium on Algorithms, 2009.
DOI : 10.1007/11841036_61

P. Pandey, M. A. Bender, R. Johnson, and R. Patro, A general-purpose counting filter: Making every bit count, SIGMOD, 2017.
DOI : 10.1145/3035918.3035963

F. Hao, M. Kodialam, and T. V. Lakshman, Incremental bloom filters, INFOCOM, 2008.
DOI : 10.1109/infocom.2008.161

W. Reda, M. Canini, L. Suresh, D. Kosti´ckosti´c, and S. Braithwaite, Rein: Taming tail latency in key-value stores via multiget scheduling, 2017.

Z. Wu, C. Yu, and H. V. Madhyastha, Costlo: Cost-effective redundancy for lower latency variance on cloud storage services, NSDI, 2015.

C. R. Lumb, R. Golding, and G. R. Ganger, D-SPTF: Decentralized request distribution in brick-based storage systems, ASPLOS, 2004.

J. Li, N. K. Sharma, D. R. Ports, and S. D. Gribble, Tales of the tail: Hardware, OS, and application-level sources of tail latency, 2014.

F. R. Dogar, T. Karagiannis, H. Ballani, and A. Rowstron, Decentralized task-aware scheduling for data center networks, SIGCOMM, 2014.
DOI : 10.1145/2619239.2626322
URL : http://www.cs.uccs.edu/~xzhou/teaching/CS522/Projects/SIGCOMM14-Baraat.pdf

M. Jeon, Y. He, H. Kim, S. Elnikety, S. Rixner et al., TPC: Target-driven parallelism combining prediction and correction to reduce tail latency in interactive services, ASPLOS, 2016.