{"paper":{"title":"On the energy efficiency of client-centric data consistency management under random read/write access to Big Data with Apache HBase","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.PF"],"primary_cat":"cs.DC","authors_text":"\\'Alvaro Garc\\'ia-Recuero","submitted_at":"2015-09-09T05:44:42Z","abstract_excerpt":"The total estimated energy bill for data centers in 2010 was \\$11.5 billion, and experts estimate that the energy cost of a typical data center doubles every five years. On the other hand, computational developments have started to lag behind storage advancements, therein becoming a future bottleneck for the ongoing data growth which already approaches Exascale levels. We investigate the relationship among data throughput and energy footprint on a large storage cluster, with the goal of formalizing it as a metric that reflects the trading among consistency and energy. Employing a client-centri"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1509.02640","kind":"arxiv","version":7},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}