• PUB Student: Mihaela Badiu
• PUB Advisor: Catalin Leordeanu

This project addresses the issue of garbage collection in the BlobSeer data management system. For the moment this distributed service offers efficient methods of storing and accessing very large binary data objects (blobs). It contains a versioning scheme and an original metadata scheme which allow a large number of clients to concurrently read, write and append data to huge blobs that are fragmented and distributed at a very large scale. However, malicious users can add false data or use inefficiently the available storage space. Taking this into consideration and the fact that data is always created and never overwritten in the system, the issue of being able to delete unwanted data becomes crucial. As a result, this thesis proposes a BlobSeer data deletion algorithm which can be used to eliminate false data that would otherwise pollute the system.

More details: thesis_mihaela_badiu.pdf