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However, efficient operation of such actors in multiple, geographically distant datacenters is challenging, due to the very high communication latency. Caching and replication are essential to hide latency and exploit locality; but it is not a priori clear how to combine these techniques with the actor programming model.<\/jats:p>\n          <jats:p>We present Geo, an open-source geo-distributed actor system that improves performance by caching actor states in one or more datacenters, yet guarantees the existence of a single latest version by virtue of a distributed cache coherence protocol. Geo's programming model supports both volatile and persistent actors, and supports updates with a choice of linearizable and eventual consistency. Our evaluation on several workloads shows substantial performance benefits, and confirms the advantage of supporting both replicated and single-instance coherence protocols as configuration choices. For example, replication can provide fast, always-available reads and updates globally, while batching of linearizable storage accesses at a single location can boost the throughput of an order processing workload by 7x.<\/jats:p>","DOI":"10.1145\/3133931","type":"journal-article","created":{"date-parts":[[2017,10,13]],"date-time":"2017-10-13T15:15:45Z","timestamp":1507907745000},"page":"1-26","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":13,"title":["Geo-distribution of actor-based services"],"prefix":"10.1145","volume":"1","author":[{"given":"Philip A.","family":"Bernstein","sequence":"first","affiliation":[{"name":"Microsoft Research, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sebastian","family":"Burckhardt","sequence":"additional","affiliation":[{"name":"Microsoft Research, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sergey","family":"Bykov","sequence":"additional","affiliation":[{"name":"Microsoft, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Natacha","family":"Crooks","sequence":"additional","affiliation":[{"name":"University of Texas at Austin, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jose M.","family":"Faleiro","sequence":"additional","affiliation":[{"name":"Yale University, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gabriel","family":"Kliot","sequence":"additional","affiliation":[{"name":"Google, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alok","family":"Kumbhare","sequence":"additional","affiliation":[{"name":"Microsoft Research, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muntasir Raihan","family":"Rahman","sequence":"additional","affiliation":[{"name":"Microsoft, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vivek","family":"Shah","sequence":"additional","affiliation":[{"name":"University of Copenhagen, Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adriana","family":"Szekeres","sequence":"additional","affiliation":[{"name":"University of Washington, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jorgen","family":"Thelin","sequence":"additional","affiliation":[{"name":"Microsoft Research, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2017,10,12]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Akka 2016. 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