Capacity of clustered distributed storage

Jy Yong Sohn, Beongjun Choi, Sung Whan Yoon, Jaekyun Moon

Research output: Chapter in Book/Report/Conference proceedingConference contribution


A new system model reflecting the clustered structure of distributed storage is suggested to investigate bandwidth requirements for repairing failed storage nodes. Large data centers with multiple racks/disks or local networks of storage devices (e.g. sensor network) are good applications of the suggested cluster-based model. In realistic scenarios involving clustered storage structures, repairing storage nodes using intact nodes residing in other clusters is more bandwidth-consuming than restoring nodes based on information from intra-cluster nodes. Therefore, it is important to differentiate between intra-cluster repair bandwidth and cross-cluster repair bandwidth in modeling distributed storage. Capacity of the suggested model is obtained as a function of fundamental resources of distributed storage systems, namely, storage capacity, intra-cluster repair bandwidth and cross-cluster repair bandwidth. Based on the capacity expression, feasible sets of required resources which enable reliable storage are analyzed. It is shown that the cross-cluster traffic can be minimized to zero (i.e., local repair within a cluster becomes possible) by allowing extra resources on storage capacity and intra-cluster repair bandwidth, according to a law specified in a closed-form. Moreover, trade-off between cross-cluster traffic and intra-cluster traffic is observed for sufficiently large storage capacity.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Communications, ICC 2017
EditorsMerouane Debbah, David Gesbert, Abdelhamid Mellouk
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467389990
Publication statusPublished - 2017 Jul 28
Event2017 IEEE International Conference on Communications, ICC 2017 - Paris, France
Duration: 2017 May 212017 May 25

Publication series

NameIEEE International Conference on Communications
ISSN (Print)1550-3607


Other2017 IEEE International Conference on Communications, ICC 2017

Bibliographical note

Funding Information:
This work is in part supported by the National Research Foundation of Korea under Grant No. 2016R1A2B4011298, and in part supported by the ICT R&D program of MSIP/IITP [2016-0-00563, Research on Adaptive Machine Learning Technology Development for Intelligent Autonomous Digital Companion].

Publisher Copyright:
© 2017 IEEE.

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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