Article records
https://feeds.library.caltech.edu/people/Jiang-Anxiao-Andrew/article.rss
A Caltech Library Repository Feedhttp://www.rssboard.org/rss-specificationpython-feedgenenTue, 16 Apr 2024 13:45:45 +0000Multicluster interleaving on paths and cycles
https://resolver.caltech.edu/CaltechAUTHORS:JIAieeetit05
Authors: {'items': [{'id': 'Jiang-Anxiao-Andrew', 'name': {'family': 'Jiang', 'given': 'Anxiao (Andrew)'}}, {'id': 'Bruck-J', 'name': {'family': 'Bruck', 'given': 'Jehoshua'}, 'orcid': '0000-0001-8474-0812'}]}
Year: 2005
DOI: 10.1109/TIT.2004.840893
Interleaving codewords is an important method not only for combatting burst errors, but also for distributed data retrieval. This paper introduces the concept of multicluster interleaving (MCI), a generalization of traditional interleaving problems. MCI problems for paths and cycles are studied. The following problem is solved: how to interleave integers on a path or cycle such that any m (m/spl ges/2) nonoverlapping clusters of order 2 in the path or cycle have at least three distinct integers. We then present a scheme using a "hierarchical-chain structure" to solve the following more general problem for paths: how to interleave integers on a path such that any m (m/spl ges/2) nonoverlapping clusters of order L (L/spl ges/2) in the path have at least L+1 distinct integers. It is shown that the scheme solves the second interleaving problem for paths that are asymptotically as long as the longest path on which an MCI exists, and clearly, for shorter paths as well.https://authors.library.caltech.edu/records/7b4k9-c3k29MAP: Medial axis based geometric routing in sensor networks
https://resolver.caltech.edu/CaltechAUTHORS:20100505-134021747
Authors: {'items': [{'id': 'Bruck-J', 'name': {'family': 'Bruck', 'given': 'Jehoshua'}, 'orcid': '0000-0001-8474-0812'}, {'id': 'Gao-Jie', 'name': {'family': 'Gao', 'given': 'Jie'}}, {'id': 'Jiang-Anxiao-Andrew', 'name': {'family': 'Jiang', 'given': 'Anxiao (Andrew)'}}]}
Year: 2007
DOI: 10.1007/s11276-006-9857-z
One of the challenging tasks in the deployment of dense wireless networks (like sensor networks) is in devising a routing scheme for node to node communication. Important consideration includes scalability, routing complexity, quality of communication paths and the load sharing of the routes. In this paper, we show that a compact and expressive abstraction of network connectivity by the medial axis enables efficient and localized routing. We propose MAP, a Medial Axis based naming and routing Protocol that does not require geographical locations, makes routing decisions locally, and achieves good load balancing. In its preprocessing phase, MAP constructs the medial axis of the sensor field, defined as the set of nodes with at least two closest boundary nodes. The medial axis of the network captures both the complex geometry and non-trivial topology of the sensor field. It can be represented succinctly by a graph whose size is in the order of the complexity of the geometric features (e.g., the number of holes). Each node is then given a name related to its position with respect to the medial axis. The routing scheme is derived through local decisions based on the names of the source and destination nodes and guarantees delivery with reasonable and natural routes. We show by both theoretical analysis and simulations that our medial axis based geometric routing scheme is scalable, produces short routes, achieves excellent load balancing, and is very robust to variations in the network model.https://authors.library.caltech.edu/records/762qx-x3s09Storage Coding for Wear Leveling in Flash Memories
https://resolver.caltech.edu/CaltechAUTHORS:20170309-140500073
Authors: {'items': [{'id': 'Jiang-Anxiao-Andrew', 'name': {'family': 'Jiang', 'given': 'Anxiao (Andrew)'}}, {'id': 'Mateescu-R', 'name': {'family': 'Mateescu', 'given': 'Robert'}}, {'id': 'Yaakobi-E', 'name': {'family': 'Yaakobi', 'given': 'Eitan'}, 'orcid': '0000-0002-9851-5234'}, {'id': 'Bruck-J', 'name': {'family': 'Bruck', 'given': 'Jehoshua'}, 'orcid': '0000-0001-8474-0812'}, {'id': 'Siegel-P-H', 'name': {'family': 'Siegel', 'given': 'Paul H.'}, 'orcid': '0000-0002-2539-4646'}, {'id': 'Vardy-A', 'name': {'family': 'Vardy', 'given': 'Alexander'}}, {'id': 'Wolf-J-K', 'name': {'family': 'Wolf', 'given': 'Jack K.'}}]}
Year: 2010
DOI: 10.1109/TIT.2010.2059833
Flash memory is a nonvolatile computer memory comprised of blocks of cells, wherein each cell is implemented as either NAND or NOR floating gate. NAND flash is currently the most widely used type of flash memory. In a NAND flash memory, every block of cells consists of numerous pages; rewriting even a single page requires the whole block to be erased and reprogrammed. Block erasures determine both the longevity and the efficiency of a flash memory. Therefore, when data in a NAND flash memory are reorganized, minimizing the total number of block erasures required to achieve the desired data movement is an important goal. This leads to the flash data movement problem studied in this paper. We show that coding can significantly reduce the number of block erasures required for data movement, and present several optimal or nearly optimal data-movement algorithms based upon ideas from coding theory and combinatorics. In particular, we show that the sorting-based (noncoding) schemes require O(n log n) erasures to move data among n blocks, whereas coding-based schemes require only O(n) erasures. Furthermore, coding-based schemes use only one auxiliary block, which is the best possible and achieve a good balance between the number of erasures in each of the n+1 blocks.https://authors.library.caltech.edu/records/cfs8k-bx907On the Capacity and Programming of Flash Memories
https://resolver.caltech.edu/CaltechAUTHORS:20120326-082904019
Authors: {'items': [{'id': 'Jiang-Anxiao-Andrew', 'name': {'family': 'Jiang', 'given': 'Anxiao (Andrew)'}}, {'id': 'Li-Hao', 'name': {'family': 'Li', 'given': 'Hao'}}, {'id': 'Bruck-J', 'name': {'family': 'Bruck', 'given': 'Jehoshua'}, 'orcid': '0000-0001-8474-0812'}]}
Year: 2012
DOI: 10.1109/TIT.2011.2177755
Flash memories are currently the most widely used type of nonvolatile memories. A flash memory consists of floating-gate cells as its storage elements, where the charge level stored in a cell is used to represent data. Compared to magnetic recording and optical recording, flash memories have the unique property that the cells are programmed using an iterative procedure that monotonically shifts each cell's charge level upward toward its target value. In this paper, we model the cell as a monotonic storage channel, and explore its capacity and optimal programming. We present two optimal programming algorithms based on a few different noise models and optimization objectives.https://authors.library.caltech.edu/records/m53em-ky777