Serverless Network File Systems
Serverless Network File Systems, T. Anderson, M. Dahlin, J. Neefe, D. Patterson, D. Roselli, and R. Wang, Proc. of the 15th ACM Symposium on Operating Systems Principles, December 1995, pp. 109-126.
The authors believe that the traditional central network file system still has a bottle neck, such that all the miss read/write goes through the central server. It is also expensive, such that it requires man to control or operate the server to be able to balance the server loads. Therefore, they have introduced a server less file systems distribute file system server which responsibilities across large numbers of cooperating machines. Ideally, the authors have implemented a prototype serverless network file system called xFS to provide better performance and scalability than traditional file systems.
There are three factors which motivate their work on the implementation of the serverless network file systems: the first one is the opportunity to provided by fast switched LANs, the second one is the expanding demands of users and the last one is the fundamental limitations of central server systems.Taking about their contributions, the authors make two sets of contributions. Firstly, xFs synthesizes a number of recent innovations which provide a basis for serverless file system design. Secondly, they have transformed DASH’s scalable cache consistency approach into a more general, distributed control system that is also fault tolerant. Moreover, they have improved the Zebra to eliminate bottlenecks.
The paper’s single most noticeable deficiency is the limitation of the measurements, such that the workloads are not real workloads, and they are micro benchmarks that provide a better performance in term of parallelism than real workloads. Another limitation of the measurements is that they compare against NFS, hence scalability is limited.
This paper seems very solid and interesting to me, I like many ideas, for example, the idea of taking advantage of the cooperative caching to server client memory. However, I still have a question regarding to the future work and its limitation such that, what would be a real workloads the author most likely to measure on and how much expectation would the author prefer to see according to such workloads.
I would rate this paper 5/5(breakthrough) due to the challenging idea and how the authors implements and their measurements. It improves the old fashion server in term of performance, scalability, and availability. It could also help reduce the cost of hardware.