Flexible Data Access in a Cloud based on Freshness Requirements

Data clouds are newly emerging environments in which commercial providers manage large volumes of data with individual quality of service (QoS) guarantees per customer. These guarantees mainly include keeping several replicas of each data item in different distributed data centers for availability purposes. However, as the cost of maintaining several updateable replicas per data object is very high, cloud providers usually offer a limited number of synchronously updated replicas and several read-only replicas that are updated in a lazy way and thus might hold stale data. QoS agreements may also include the maintenance of dedicated archives, i.e., copies of data which are frozen at some point in time. In this paper we present Re:FRESHiT, our novel approach to freshness-aware cloud data management that allows providers to offer a variety of read operations with different semantics. These read operations can be supported by a read-only site using a stale replica, or by exploiting one of several locally managed archives. We discuss in detail how the replicas are organized based on their freshness and how refresh and defresh of individual replicas is provided in a completely distributed way. Finally, we present the results of a performance evaluation of Re:FRESHiT in a data cloud setting.