Jobcast — Parallel and distributed processing framework Data processing on a cloud style KVS database

Abstract

In this paper, we propose a new architecture for parallel and distributed processing framework, “Jobcast, ” which enables data processing on a cloud style KVS database. Nowadays, many KVS (as known as Key Value Store) systems exist which achieve high scalability for data spaces among a huge number of computers. The Jobcast architecture is an extension which has the capability to execute “job” on KVS data nodes so that it can also achieve scalability of processing space. In this paper, we introduce the Jobcast architecture and describe how Jobcast improves performance of some KVS applications especially by reducing data transmission cost. We evaluate and discuss performance improvement for some example applications as well.