Rack-Aware Regenerating Codes for Data Centers

نویسندگان

  • Hanxu Hou
  • Patrick P. C. Lee
  • Kenneth W. Shum
  • Yuchong Hu
چکیده

Erasure coding is widely used for massive storage in data centers to achieve high fault tolerance and low storage redundancy. Since the cross-rack communication cost is often high, it is critical to design erasure codes that minimize the cross-rack repair bandwidth during failure repair. In this paper, we analyze the optimal trade-off between storage redundancy and cross-rack repair bandwidth specifically for data centers, subject to the condition that the original data can be reconstructed from a sufficient number of any non-failed nodes. We characterize the optimal trade-off curve under functional repair, and propose a general family of erasure codes called rack-aware regenerating codes (RRC), which achieve the optimal trade-off. We further propose exact repair constructions of RRC that have minimum storage redundancy and minimum cross-rack repair bandwidth, respectively. We show that (i) the minimum storage redundancy constructions support a wide range of parameters and have cross-rack repair bandwidth that is strictly less than that of the classical minimum storage regenerating codes in most cases, and (ii) the minimum cross-rack repair bandwidth constructions support all the parameters and have less cross-rack repair bandwidth than that of the minimum bandwidth regenerating codes for almost all of the parameters.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Hybrid Regenerating Codes for Distributed Storage Systems

Distributed storage systems are mainly justified due to their ability to store data reliably over some unreliable nodes such that the system can have long term durability. Recently, regenerating codes are proposed to make a balance between the repair bandwidth and the storage capacity per node. This is achieved through using the notion of network coding approach. In this paper, a new variation ...

متن کامل

UPS-Aware Workload Placement in Enterprise Data Centers

Energy efficiency has become a very important concern for enterprise data centers due to the significant cost on electricity. To improve the energy efficiency of data centers, researchers and practitioners have proposed enormous work to reduce the energy consumption of data centers. Most of previous work focus on reducing the energy consumption of IT equipment; however, the power losses caused ...

متن کامل

Architecture-aware Coding for Distributed Storage: Repairable Block Failure Resilient Codes

In large scale distributed storage systems (DSS) deployed in cloud computing, correlated failures resulting in simultaneous failure (or, unavailability) of blocks of nodes are common. In such scenarios, the stored data or a content of a failed node can only be reconstructed from the available live nodes belonging to the available blocks. To analyze the resilience of the system against such bloc...

متن کامل

Retrieval–travel-time model for free-fall-flow-rack automated storage and retrieval system

Automated storage and retrieval systems (AS/RSs) are material handling systems that are frequently used in manufacturing and distribution centers. The modelling of the retrieval–travel time of an AS/RS (expected product delivery time) is practically important, because it allows us to evaluate and improve the system throughput. The free-fall-flow-rack AS/RS has emerged as a new technology for dr...

متن کامل

Adaptive Dynamic Data Placement Algorithm for Hadoop in Heterogeneous Environments

Hadoop MapReduce framework is an important distributed processing model for large-scale data intensive applications. The current Hadoop and the existing Hadoop distributed file system’s rack-aware data placement strategy in MapReduce in the homogeneous Hadoop cluster assume that each node in a cluster has the same computing capacity and a same workload is assigned to each node. Default Hadoop d...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • CoRR

دوره abs/1802.04031  شماره 

صفحات  -

تاریخ انتشار 2018