Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-848d4c4894-4hhp2 Total loading time: 0 Render date: 2024-05-08T23:50:03.538Z Has data issue: false hasContentIssue false

6 - Distributed big data storage in optical wireless networks

from Part II - Big data over cyber networks

Published online by Cambridge University Press:  18 December 2015

By
Chen Gong ,
Zhengyuan Xu  and
Xiaodong Wang
Edited by
Shuguang Cui ,
Alfred O. Hero, III ,
Zhi-Quan Luo  and
José M. F. Moura
Chen Gong
Affiliation:
University of Science and Technology of China, China
Zhengyuan Xu
Affiliation:
University of Science and Technology of China, China
Xiaodong Wang
Affiliation:
Columbia University, USA
Shuguang Cui
Affiliation:
Texas A & M University
Alfred O. Hero, III
Affiliation:
University of Michigan, Ann Arbor
Zhi-Quan Luo
Affiliation:
University of Minnesota
José M. F. Moura
Affiliation:
Carnegie Mellon University, Pennsylvania
Get access

Summary

We consider a distributed storage system employing some existing regenerate codes where the storage nodes are scattered in an optical wireless network. The data collector (DC) connects to the storage nodes via orthogonal channels and downloads data symbols from these nodes. In the existing data reconstruction schemes for distributed storage systems, the data collector downloads all symbols from a subset of the storage nodes. Such a full downloading approach becomes inefficient in wireless networks since due to fading, the wireless channels may not offer sufficient bandwidths for full downloading. Moreover, full downloading is also less power efficient than partial downloading. Given a coding scheme employed by the wireless distributed storage system, we propose a partial downloading scheme that allows downloading a portion of the symbols from any storage node. We formulate a cross-layer wireless resource allocation problem for data reconstruction in distributed storage systems employing such partial downloading. To derive the fundamental properties of partial downloading as well as to reduce the complexity of wireless resource allocation, we derive necessary and sufficient conditions for data reconstructability for partial downloading, in terms of the numbers of downloaded symbols from the storage nodes.We also propose channel and power allocation schemes for partial downloading in wireless distributed storage systems.

Introduction

The purpose of distributed storage is to store a data file in a distributed manner where the individual storage nodes may be unreliable. This has attracted significant research interests in both communication and computer science fields. The original data file is firstly encoded into multiple coded symbols,which are stored into various storage nodes. Note that, encoded by advanced coding schemes, the original data can be reconstructed if the number of collected data symbols is no less than the number of original data symbols.

Recently, two data encoding schemes for distributed data storage have been proposed, based on rateless coding and network coding [1, 2]. A criterion for distributed data storage is the transmission bandwidth for the reconstruction of the original data file and the repair of a failed storage node. For data reconstruction, a data collector (DC) downloads the symbols in some storage nodes to reconstruct the data. For node regeneration, assuming that a storage node has failed, a new storage node downloads the symbols from some other storage nodes to regenerate the symbols in the failed node.

Type
Chapter
Information
Big Data over Networks , pp. 161 - 179
Publisher: Cambridge University Press
Print publication year: 2016

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1] A. G., Dimakis, P. B., Godfrey, Y., Wu, M. J., Wainwright, and K., Ramchandran, “Network coding for distributed storage systems,” IEEE Trans. Info. Theory, vol. 56, no. 9, pp. 4539–4551, September 2010.Google Scholar
[2] Y., Wu, “Existence and construction of capacity-achieving network codes for distributed storage,” IEEE J. Sel. Areas Commun., vol. 28, no. 2, pp. 277–288, February 2010.Google Scholar
[3] C., Gong and X., Wang, “On partial downloading for wireless distributed storage networks,” IEEE Trans. Signal Process., vol. 60, no. 6, pp. 3278–3288, June 2012.Google Scholar
[4] S., Hranilovic and F. R., Kschischang, “Capacity bounds for power-and band-limited optical intensity channels corrupted by Gaussian noise,” IEEE Trans. Info. Theory, vol. 50, no. 5, pp. 784–795, May 2004.Google Scholar
[5] J., Armstrong and A., Lowery, “Power efficient optical OFDM,” Electron. Lett., vol. 42, no. 6, pp. 370–372, 2006.Google Scholar
[6] S., Dissanayake, K., Panta, and J., Armstrong, “A novel technique to simultaneously transmit ACO-OFDM and DCO-OFDM in IM/DD systems,” in 2011 IEEE GLOBECOM OWC Workshops, IEEE, 2011, pp. 782–786.Google Scholar
[7] S. C. J., Lee, S., Randel, F., Breyer, and A. M., Koonen, “PAM-DMT for intensity-modulated and direct-detection optical communication systems,” IEEE Photonics Technol. Lett., vol. 21, no. 23, pp. 1749–1751, 2009.Google Scholar
[8] D., Tsonev, S., Sinanovic, and H., Haas, “Novel unipolar orthogonal frequency division multiplexing (U-OFDM) for optical wireless,” in 2012 IEEE 75th Vehicular Technology Conference (VTC Spring), IEEE, 2012, pp. 1–5.Google Scholar
[9] N.|Fernando, Y.|Hong, and E.|Viterbo, “Flip-OFDM for optical wireless communications,” in 2011 IEEE Information Theory Workshop (ITW), IEEE, 2011, pp. 5–9.
[10] A., Shokrollahi, “Raptor codes,” IEEE Trans. Inform. Theory, vol. 62, no. 6, pp. 2551–2567, June 2006.Google Scholar
[11] M., Luby, “LT codes,” in Proceedings 43rd Annual IEEE Symposium on Foundations of Computer Science, November 2002, pp. 271–282.
[12] Z., Kong, S. A., Aly, and E., Soljanin, “Decentralized coding algorithms for distributed storage in wireless sensor networks,” IEEE J. Sel. Areas Commun., vol. 28, no. 2, pp. 261–267, February 2010.Google Scholar
[13] C., Suh and K., Ramchandran, “Exact-repair MDS code construction using interference alignment,” IEEE Trans. Info. Theory, vol. 57, no. 3, pp. 1425–1442, March 2011.Google Scholar
[14] Y., Wu and A. G., Dimakis, “Reducing repair traffic for erasure coding-based storage via interference alignment,” in 2009 IEEE International Symposium Information Theory (ISIT), Seoul, Korea, June 28–July 3, 2009, pp. 2276–2280.Google Scholar
[15] C., Suh and K., Ramchandran, “Exact-repairMDScodes for distributed storage using interference alignment,” in 2010 IEEE International Symposium Information Theory (ISIT), Austin, Texas, June 2010, pp. 161–165.Google Scholar
[16] K. V., Rashmi, N. B., Shah, P. V., Kumar, and K., Ramchandran, “Explicit and optimal exactregenerating codes for the minimum-bandwidth point in distributed storage,” in 2010 IEEE International Symposium Information Theory (ISIT), Austin, Texas, June 2010, pp. 1938–1942.Google Scholar
[17] N. B., Shah, K. V., Rashmi, and P. V., Kumar, “Flexible class of regenerating codes for distributed storage,” in 2010 IEEE International Symposium Information Theory (ISIT), Austin, Texas, June 2010, pp. 1943–1947.Google Scholar
[18] V. R., Cadambe, S. A., Jafar, and H., Maleki, “Minimum repair bandwidth for exact regeneration in distributed storage,” in 2010 Wireless Network Coding Workshop (WiNC), Boston, Massachusetts, June 2010, pp. 1–6.Google Scholar
[19] K. V., Rashmi, N. B., Shah, P. V., Kumar, and K., Ramchandran, “Explicit construction of optimal exact regenerating codes for distributed storage,” in 2009 Allerton Communication, Control, and Computing (Allerton), October 2009, pp. 1243–1249.Google Scholar
[20] N. B., Shah, K. V., Rashmi, P. V., Kumar, and K., Ramchandran, “Explicit codes minimizing repair bandwidth for distributed storage,” arXiv:0908.2984v2 [cs.IT] 5, September 2009.
[21] K. V., Rashmi, N. B., Shah, and P. V., Kumar, “Optimal exact-regenerating codes for distributed storage at the msr and mbr points via a product-matrix construction,” arXiv:1005.4178v1 [cs.IT] 23, May. 2010.
[22] R., Koetter, M., Effros, and M., Medard, “On a theory of network equivalence,” in 2009 IEEE Information Theory Workshop (ITW), Volos, Greece, June 2009, pp. 326–330.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×