1. Unistore: Project Updates
Presenter: Wei Xie
Project Members: Jiang Zhou, Mark Reyes, Jason Noble, David Cauthron and Yong Chen
Data-Intensive Scalable Computing Laboratory(DISCL)
Computer Science Department
Texas Tech University
We are grateful to the Nimboxx and the Cloud and Autonomic Computing site at Texas Tech University for the valuable support for this project

2. Unistore Overview
To build a unified storage architecture (Unistore) for Cloud storage systems with the co-existence and efficient integration of heterogeneous HDDs and SCM (Storage Class Memory) devices
Prototype development based on Sheepdog and/or Ceph
Data distribution management and workload characterization
Data Placement Component
Characterization Component
I/O Pattern
Random/Sequential
Read/write
Hot/cold
Workloads
Access patterns
guide
----- Meeting Notes (4/8/15 14:37) -----
Objective slide.
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unitore: design, idea
implement on sheepdog
title change to unistore objective and design
Prototype developement based on sheepdog distributed store for vm.
Component reflect objective.
Placement Algorithm
Modified Consistent Hash
Devices Characteristics
Bandwidth Throughput
Replication Algorithm
Pattern-directed Replication

3. Project Updates 2 new papers completed and submitted:
Pattern-directed Replication Scheme to ICPP2016
SUORA to SC16
2 new papers under preparation:
Version consistent hash
Tiered-CRUSH: in preparation for SoCC16
Simulation code and prototype developed to evaluate the proposed schemes
Proposed schemes improve the performance of heterogeneous storage systems and maintain the balanced storage utilization

4. Tiered-CRUSH
CRUSH (algorithm used in Ceph) ensures data placed across multiple independent locations to improve data availability
Tiered-CRUSH integrates storage tiering into the CRUSH data placement
Access frequency of object recorded per volume, hotter data more likely to be placed on faster tiers
Implemented in a benchmarks tool compiled with the CRUSH library functions
Simulation showed that data distribution uniformity can be maintained
Simulation shows 1.5 to 2X improvement in overall bandwidth in our experimental settings

5. Version Consistent Hashing Scheme
Build versions into the virtual nodes
Avoid data migration when adding nodes or node fails
Maintain efficient data lookup
Data lookup algorithm
Performance improvement:
v1: 1,2
v2: 4,1
v3: 4,6
v4: 4,6
Lookup locations: {4, 6, 1, 2}

6. Pattern-directed Replication
Trace object I/O requests when executing applications
Trace analysis, correlation finding and object grouping
Reorganize objects for replication in the background for better performance

7. Conclusions
Tiered-CRUSH algorithm achieves better IO performance and higher data availability at the same time for heterogeneous storage system
Version consistent hashing scheme for improving manageability of data center
PRS for high performance data replication by reorganizing the placement of data replications

8. On-going/Future Work
Implement/evaluate the proposed schemes in Sheepdog (currently simulation-based)
Instrument Sheepdog with Lttng framework for more flexible tracing capability

9. http://cac.ttu.edu/, http://discl.cs.ttu.edu/
Thank You
Please visit:
Acknowledgement: The is funded by the National Science Foundation under grants IIP and IIP

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Select “Cloud and Autonomic Computing Center”
then select “IAB” role.
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