Coding and Maintenance Strategies for Cloud Storage: Correlated Failures, Mobility and Architecture Awareness
AdvisorKoyluoglu, Onur Ozan
MetadataShow full item record
PublisherThe University of Arizona.
RightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
AbstractAs a result of evergrowing data and recent interest in storing and analyzing it, distributed storage systems (DSS), which is also known as cloud storage, have become one of the most important research areas in the literature. Not only such networks are being used as backbone systems for companies like Google, Microsoft and Facebook but also they have accelerated the growth of cloud computing, which is an essential business line for institutions such as IBM, Amazon and Salesforce. In this dissertation, the focus is on the storage side of cloud in order to address the important questions in designing such systems. First, coding theoretic approach is taken to handle correlated failures of multiple storage nodes. In particular, this dissertation studies distributed storage systems that can provide resilience against correlated failure patterns that affect the availability of multiple storage nodes, i.e., power loss that may affect multiple disks. Maximum file size that can be stored in such DSS is studied and then optimal code constructions are provided. This dissertation also studies cloud storage systems that prevent data loss from mixed failure patterns of disks and sectors in disk drives. Specifically, a general code construction is proposed to overcome such failures for any given parameter set. Due to its large field size requirement of proposed construction, a relaxation on the efficiency of storage system is considered to provide codes with smaller field sizes. Maintenance of cloud storage systems is also studied. To that end, this dissertation first studies the maintenance of DSS that include a backup node, which is called hierarchical DSS. Hierarchical DSS can model cellular networks such as femtocell as well as caching in wireless networks. In particular, we present an upper bound on the file size that can be stored over hierarchical DSS and propose optimal code constructions. Then, maintenance cost and data access cost for users of such DSS are studied. Lastly, mobility effects of cloud storage over wireless devices are studied. Specifically, an analysis on the mobile cloud storage system that initiates the maintenance process after certain number of devices remains in the network is performed and different maintenance strategies are proposed that are optimal with respect to average cost in certain mobility regimes.
Degree ProgramGraduate College
Electrical & Computer Engineering