Sandooq: improving the communication cost and service latency for a multi-user erasure-coded geo-distributed cloud environment

Modern data centers have to accommodate the storage of an increasing amount of data with multiple users accessing that data from all over the world. Most of these data centers are geo-distributed to improve availability and protect against the loss of data in the case of outages and disasters. They are also increasingly using erasure codes to improve the reliability at a much lower storage cost. In addition to reliability, the clients and applications also demand storage solutions with better performance and cost-effectiveness. For a geo-distributed data center, a major part of the cost is associated with sending the data between the data centers. This paper builds on previous work to minimize the latency and cost in a data center and applies it to a multi-user geo-distributed environment. We develop a mathematical model for service latency and communication cost for a multi-user geo-distributed cloud environment. We also provide an algorithm to jointly optimize the service latency and communication cost by controlling the placement of the erasure-coded file chunks and scheduling the requests for these chunks. Through simulations, we show that our algorithm converges quickly and outperforms other heuristics in optimizing service latency and communication cost