6 research outputs found
Small-Sample Inferred Adaptive Recoding for Batched Network Coding
Batched network coding is a low-complexity network coding solution to
feedbackless multi-hop wireless packet network transmission with packet loss.
The data to be transmitted is encoded into batches where each of which consists
of a few coded packets. Unlike the traditional forwarding strategy, the
intermediate network nodes have to perform recoding, which generates recoded
packets by network coding operations restricted within the same batch. Adaptive
recoding is a technique to adapt the fluctuation of packet loss by optimizing
the number of recoded packets per batch to enhance the throughput. The input
rank distribution, which is a piece of information regarding the batches
arriving at the node, is required to apply adaptive recoding. However, this
distribution is not known in advance in practice as the incoming link's channel
condition may change from time to time. On the other hand, to fully utilize the
potential of adaptive recoding, we need to have a good estimation of this
distribution. In other words, we need to guess this distribution from a few
samples so that we can apply adaptive recoding as soon as possible. In this
paper, we propose a distributionally robust optimization for adaptive recoding
with a small-sample inferred prediction of the input rank distribution. We
develop an algorithm to efficiently solve this optimization with the support of
theoretical guarantees that our optimization's performance would constitute as
a confidence lower bound of the optimal throughput with high probability.Comment: 7 pages, 2 figures, accepted in ISIT-21, appendix adde
BAR: Blockwise Adaptive Recoding for Batched Network Coding
Multi-hop networks become popular network topologies in various emerging
Internet of things applications. Batched network coding (BNC) is a solution to
reliable communications in such networks with packet loss. By grouping packets
into small batches and restricting recoding to the packets belonging to the
same batch, BNC has a much smaller computational and storage requirements at
the intermediate nodes compared with a direct application of random linear
network coding. In this paper, we propose a practical recoding scheme called
blockwise adaptive recoding (BAR) which learns the latest channel knowledge
from short observations so that BAR can adapt to the fluctuation of channel
conditions. We focus on investigating practical concerns such as the design of
efficient BAR algorithms. We also design and investigate feedback schemes for
BAR under imperfect feedback systems. Our numerical evaluations show that BAR
has significant throughput gain for small batch size compared with the existing
baseline recoding scheme. More importantly, this gain is insensitive to
inaccurate channel knowledge. This encouraging result suggests that BAR is
suitable to be realized in practice as the exact channel model and its
parameters could be unknown and subject to change from time to time.Comment: submitted for journal publicatio
On the Design of Future Communication Systems with Coded Transport, Storage, and Computing
Communication systems are experiencing a fundamental change. There are novel applications that require an increased performance not only of throughput but also latency, reliability, security, and heterogeneity support from these systems. To fulfil the requirements, future systems understand communication not only as the transport of bits but also as their storage, processing, and relation. In these systems, every network node has transport storage and computing resources that the network operator and its users can exploit through virtualisation and softwarisation of the resources. It is within this context that this work presents its results. We proposed distributed coded approaches to improve communication systems. Our results improve the reliability and latency performance of the transport of information. They also increase the reliability, flexibility, and throughput of storage applications. Furthermore, based on the lessons that coded approaches improve the transport and storage performance of communication systems, we propose a distributed coded approach for the computing of novel in-network applications such as the steering and control of cyber-physical systems. Our proposed approach can increase the reliability and latency performance of distributed in-network computing in the presence of errors, erasures, and attackers
IUS/TUG orbital operations and mission support study. Volume 2: Interim upper stage operations
Background data and study results are presented for the interim upper stage (IUS) operations phase of the IUS/tug orbital operations study. The study was conducted to develop IUS operational concepts and an IUS baseline operations plan, and to provide cost estimates for IUS operations. The approach used was to compile and evaluate baseline concepts, definitions, and system, and to use that data as a basis for the IUS operations phase definition, analysis, and costing analysis. Both expendable and reusable IUS configurations were analyzed and two autonomy levels were specified for each configuration. Topics discussed include on-orbit operations and interfaces with the orbiter, the tracking and data relay satellites and ground station support capability analysis, and flight control center sizing to support the IUS operations
Fourth Annual Workshop on Space Operations Applications and Research (SOAR 90)
The proceedings of the SOAR workshop are presented. The technical areas included are as follows: Automation and Robotics; Environmental Interactions; Human Factors; Intelligent Systems; and Life Sciences. NASA and Air Force programmatic overviews and panel sessions were also held in each technical area
NASA patent abstracts bibliography: A continuing bibliography. Section 2: Indexes (supplement 10)
Abstracts for 3089 patents and applications for patent entered in the NASA scientific and information system for the period covering May 1969 through December 1976 are indexed by subject, inventor, source, NASA case or U.S. patent number, and accession number in the NASA system