Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/7571

Constructing enhanced file system and memory abstractions on public cloud

Authors Sheng, Zhonghua
Issue Date 2012
Summary With the development of cloud-based systems and applications, a number of major technical firms have started to provide public cloud services. A challenge behind the cloud computing is how to store, share and process the users’ data securely and efficiently. Therefore, we need to enhance the file system and memory abstractions for the cloud computing paradigm. On the traditional computing architecture, the user have full control over their data on their computer or in their private datacenter. However, when users store private data in shared datacenters, they lose control over how the data are stored and accessed. Multiple classes of personnel may access the physical storage media and potentially read the data. While strong cryptographic methods can protect user files from unauthorized accesses, they incur computational overhead, and make it difficult for the infrastructure provider to optimize the storage space with effective compression and deduplication. To provide strong protection on user data, we design a new file system called BIFS (Bit-Interleaving File System). Focusing on the privacy protection of the on-disk state, BIFS re-orders data in user files at the bit level, and stores bit slices at distributed locations in the storage system. While providing strong privacy protection, BIFS still retains part of the regularity in user data, and thus enables the infrastructure provider to perform a certain level of space optimization (e.g., compression). Storing the users’ data with strong privacy protection is not enough. Sharing and processing the user’s data efficiently on the cloud infrastructure remains a factor which prevents many users from stepping into the cloud computing era. Message passing introduces too much burden to the users for programming. Traditional Distributed Shard Memory (DSM) design fails in scalability and efficiency. Focusing on the efficiency and flexibility, while changes the user’s programming behavior as less as possible, we combine the advantages of transactional memory and distributed shared memory to design a scalable distributed transactional memory (SDTM). We implement BIFS and SDTM to examine their performance characteristics. The cloud storage service used for our implementation of BIFS is the Amazon Simple Storage Service (S3). The comparison with several existing network or Internet-based file systems shows that BIFS provides robust file system functions with satisfactory throughput on S3. The evaluation of SDTM also shows it is both scalable and efficient.
Note Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2012
Subjects
Language English
Format Thesis
Access
Files in this item:
File Description Size Format
th_redirect.html 343 B HTML