As a new generation of high-performance distributed storage system, object-based storage system is being
developed to support high-performance computing environments. In the petabyte-scale object-based storage
system, reasonable data distribution and parameters configuration can improve system performance and
availability. To make the system performance evaluation work easier, we propose an approximate parameters
analysis method to build performance model. We firstly model the whole storage system's architecture based
on closed Fork-Join queue model; using our system architecture model, we then deduce an approximately
analytical expression with erasure codes and replicas to predict the storage system's mean response time
under various workloads simulating the real-world condition. Finally, a large number of comparison
experiments validate our approximately analytical expression of system performance, and proved that our
analytic method is appropriate to build performance model for object-based storage system.
KEYWORDS: Data storage, Data backup, System integration, Reliability, Data storage servers, Distributed computing, Data processing, Lithium, Optoelectronics, Logic
Recent advances in large-capacity, low-cost storage devices have led to active research in design of large-scale storage
system built from commodity devices. These storage systems are composed of thousands of storage device and require
an efficient file system to provide high system bandwidth and petabyte-scale data storage. Object-based file system
integrates advantage of both NAS and SAN, can be applied in above environment. Continuous data protection
(CDP) is a methodology that continuously captures or tracks data modifications and stores changes independent of the
primary data, enabling recovery points from any point in the past. All changes to files and file metadata are stored and
managed. A CDP method in Object-based file system is presented in this thesis to improve the system reliability. Firstly,
we can get detail at byte level of every write request because data protection operates at the file system level. It can
consume less storage space. Secondly, every object storage server can compute the recovery strip data object
independently to decrease the recovery time. Thirdly a journal-like metadata management way is introduced to provide
metadata optimization for CDP.
KEYWORDS: Sensors, Data storage, Computer security, Detection and tracking algorithms, Databases, Target detection, Information security, Artificial intelligence, Network security, Rule based systems
The paper proposed a novel authentication method for networked storage using artificial immune technique, addressing
the storage security issue. Most authentication sub-systems adopt the positive identification to judge the user identity,
however if an intruder obtains some account information, he may crack the authentication sub-system using Rule-based
Attack and do harm to the storage system. Aiming at this problem, we designed a negative authentication to improve
entrance security of storage system, where the identification data are stored in Non-self space so as to prevent the
intruder from discovering any account information. Additionally, the negative authentication sub-system can filter out
the unauthorized users. The experimental results showed that the proposed authentication method could be efficient in
detecting unauthorized user, so the negative authentication sub-system may improve the storage security.
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