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Institution

NTT DoCoMo

About: NTT DoCoMo is a based out in . It is known for research contribution in the topics: Base station & Mobile station. The organization has 4032 authors who have published 8655 publications receiving 160533 citations.


Papers
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Patent
27 Apr 2005
TL;DR: In this article, a wireless base station apparatus (100) used in a wireless communications system includes a statistical processing unit (140) that performs statistical processing on downlink radio quality information reported from a wireless communication terminal device; a radio QI offsetting unit (160) that adjusts the statistically processed downlink QI based on a downlink transmission confirmation (ACK/NACK/DTX) message transmitted from the wireless communications terminal device and a required downlink quality.
Abstract: A wireless base station apparatus (100) used in a wireless communications system includes a statistical processing unit (140) that performs statistical processing on downlink radio quality information reported from a wireless communications terminal device; a radio quality information offsetting unit (160) that adjusts the statistically processed downlink radio quality information based on a downlink transmission confirmation (ACK/NACK/DTX) message transmitted from the wireless communications terminal device and a required downlink quality; a transport format determination unit (170) that determines a downlink transport format based on the statistically processed radio quality information or the offset-adjusted radio quality information; and a transmitting unit (111) that transmits a downlink channel with the determined downlink transport format.

93 citations

Proceedings ArticleDOI
01 Apr 2014
TL;DR: TOFEC as discussed by the authors uses erasure coding, parallel connections to storage cloud and limited chunking together to significantly improve the delay performance of uploading and downloading data in and out of cloud storage.
Abstract: Our paper presents solutions using erasure coding, parallel connections to storage cloud and limited chunking (i.e., dividing the object into a few smaller segments) together to significantly improve the delay performance of uploading and downloading data in and out of cloud storage. TOFEC is a strategy that helps front-end proxy adapt to level of workload by treating scalable cloud storage (e.g. Amazon S3) as a shared resource requiring admission control. Under light workloads, TOFEC creates more smaller chunks and uses more parallel connections per file, minimizing service delay. Under heavy workloads, TOFEC automatically reduces the level of chunking (fewer chunks with increased size) and uses fewer parallel connections to reduce overhead, resulting in higher throughput and preventing queueing delay. Our trace-driven simulation results show that TOFEC's adaptation mechanism converges to an appropriate code that provides the optimal delay-throughput trade-off without reducing system capacity. Compared to a non-adaptive strategy optimized for throughput, TOFEC delivers 2.5× lower latency under light workloads; compared to a non-adaptive strategy optimized for latency, TOFEC can scale to support over 3× as many requests. Index Terms—FEC, Cloud storage, Queueing, Delay

93 citations

Journal ArticleDOI
TL;DR: This paper presents solutions that can significantly improve the delay performance of putting and retrieving data in and out of cloud storage, and develops load-adaptive algorithms that can pick the best code rate on a per-request basis by using offline computed queue backlog thresholds.
Abstract: Our paper presents solutions that can significantly improve the delay performance of putting and retrieving data in and out of cloud storage. We first focus on measuring the delay performance of a very popular cloud storage service Amazon S3. We establish that there is significant randomness in service times for reading and writing small and medium size objects when assigned distinct keys. We further demonstrate that using erasure coding, parallel connections to storage cloud and limited chunking (i.e., dividing the object into a few smaller objects) together pushes the envelope on service time distributions significantly (e.g., 76%, 80%, and 85% reductions in mean, 90th, and 99th percentiles for 2-MB files) at the expense of additional storage (e.g., 1.75x). However, chunking and erasure coding increase the load and hence the queuing delays while reducing the supportable rate region in number of requests per second per node. Thus, in the second part of our paper, we focus on analyzing the delay performance when chunking, forward error correction (FEC), and parallel connections are used together. Based on this analysis, we develop load-adaptive algorithms that can pick the best code rate on a per-request basis by using offline computed queue backlog thresholds. The solutions work with homogeneous services with fixed object sizes, chunk sizes, operation type (e.g., read or write) as well as heterogeneous services with mixture of object sizes, chunk sizes, and operation types. We also present a simple greedy solution that opportunistically uses idle connections and picks the erasure coding rate accordingly on the fly. Both backlog-based and greedy solutions support the full rate region and provide best mean delay performance when compared to the best fixed coding rate policy. Our evaluations show that backlog-based solutions achieve better delay performance at higher percentile values than the greedy solution.

93 citations

Patent
02 Mar 2004
TL;DR: In this article, a region of confidence (RoC) is formed according to certain algorithms and the location estimate candidates are put in a number of time-indexed bins to further improve the accuracy of the location estimation.
Abstract: A method for location estimation employs filtering in both the radio signal domain and the space domain separately. The method filters raw values of the run-time radio signal measurements to reject distorted inputs. A region of confidence (RoC) is formed according to certain algorithms. Only location estimates falling within the RoC are considered for further processing. The location estimate candidates filtered by the RoC are put in a number of time-indexed bins. Each of the bins contains location estimate candidates obtained at similar times. A shortest route connecting a candidate from each bin is calculated to further improve the accuracy of the location estimation.

93 citations

Proceedings ArticleDOI
19 Mar 2007
TL;DR: A generic framework that combines semantic Web service technology and physical mobile interaction is presented that uses mobile devices to extract information from augmented physical objects and use it for a more intuitive and convenient invocation of associated services.
Abstract: Although mobile services can be used ubiquitously, their employment and the interaction with them are still restricted by the constraints of mobile devices In order to facilitate and leverage mobile interaction with services, we present a generic framework that combines semantic Web service technology and physical mobile interaction This interaction paradigm uses mobile devices to extract information from augmented physical objects and use it for a more intuitive and convenient invocation of associated services For that purpose, the presented framework exploits Web service descriptions for the automatic and dynamic generation of customizable user interfaces that support and facilitate physical mobile interaction This generic approach to mobile interaction with services through the interaction with physical objects promises to meet the complementary development of the Internet of things A user study with a prototype application for mobile ticketing confirms our concept and shows its limits

93 citations


Authors

Showing all 4032 results

NameH-indexPapersCitations
Amit P. Sheth10175342655
Harald Haas8575034927
Giuseppe Caire8282540344
Craig Gentry7522239327
Raj Jain6442430018
Karl Aberer6355417392
Fumiyuki Adachi54101015344
Ismail Guvenc5245113893
Frank Piessens5239110381
Wolfgang Kellerer495029383
Yoshihisa Kishiyama4837911831
Ravi Jain481607467
Josef A. Nossek4862310377
Tadao Nagatsuma4743011117
Christian Bettstetter4620411051
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202164
2020143
2019240
2018269
2017193
2016173