1. Hong, Y., Thottethodi, M.: Understanding and mitigating the impact of load imbalance in the memory caching tier. In: Lohman, G.M. (ed.) ACM Symposium on Cloud Computing, SOCC 2013, Santa Clara, CA, USA, 1–3 October 2013, pp. 13:1–13:17. ACM (2013)
2. Cheng, Y., Gupta, A., Butt, A.R.: An in-memory object caching framework with adaptive load balancing. In: Réveillère, L., Harris, T., Herlihy, M. (eds.) Proceedings of the Tenth European Conference on Computer Systems, EuroSys 2015, Bordeaux, France, 21–24 April 2015, pp. 4:1–4:16. ACM (2015)
3. Karger, D.R., Lehman, E., Leighton, F.T., Panigrahy, R., Levine, M.S., Lewin, D.: Consistent hashing and random trees: distributed caching protocols for relieving hot spots on the world wide web. In: Leighton, F.T., Shor, P.W. (eds.) Proceedings of the Twenty-Ninth Annual ACM Symposium on the Theory of Computing, El Paso, Texas, USA, 4–6 May 1997, pp. 654–663. ACM (1997)
4. Fan, B., Lim, H., Andersen, D.G., Kaminsky, M.: Small cache, big effect: provable load balancing for randomly partitioned cluster services. In: Chase, J.S., Abbadi, A.E. (eds.) ACM Symposium on Cloud Computing in Conjunction with SOSP 2011, SOCC 2011, Cascais, Portugal, 26–28 October 2011, p. 23. ACM (2011)
5. https://redis.io/topics . “Redis cluster specification,” Technical report (2018)