Scheduling and Congestion Control for Wireless and Processing Networks (Record no. 85565)

000 -LEADER
fixed length control field 03910nam a22005535i 4500
001 - CONTROL NUMBER
control field 978-3-031-79992-1
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730164321.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220601s2010 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031799921
-- 978-3-031-79992-1
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Jiang, Libin.
245 10 - TITLE STATEMENT
Title Scheduling and Congestion Control for Wireless and Processing Networks
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2010.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XI, 144 p.
490 1# - SERIES STATEMENT
Series statement Synthesis Lectures on Learning, Networks, and Algorithms,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- Overview -- Scheduling in Wireless Networks -- Utility Maximization in Wireless Networks -- Distributed CSMA Scheduling with Collisions -- Stochastic Processing networks.
520 ## - SUMMARY, ETC.
Summary, etc In this book, we consider the problem of achieving the maximum throughput and utility in a class of networks with resource-sharing constraints. This is a classical problem of great importance. In the context of wireless networks, we first propose a fully distributed scheduling algorithm that achieves the maximum throughput. Inspired by CSMA (Carrier Sense Multiple Access), which is widely deployed in today's wireless networks, our algorithm is simple, asynchronous, and easy to implement. Second, using a novel maximal-entropy technique, we combine the CSMA scheduling algorithm with congestion control to approach the maximum utility. Also, we further show that CSMA scheduling is a modular MAC-layer algorithm that can work with other protocols in the transport layer and network layer. Third, for wireless networks where packet collisions are unavoidable, we establish a general analytical model and extend the above algorithms to that case. Stochastic Processing Networks (SPNs) model manufacturing, communication, and service systems. In manufacturing networks, for example, tasks require parts and resources to produce other parts. SPNs are more general than queueing networks and pose novel challenges to throughput-optimum scheduling. We proposes a "deficit maximum weight" (DMW) algorithm to achieve throughput optimality and maximize the net utility of the production in SPNs. Table of Contents: Introduction / Overview / Scheduling in Wireless Networks / Utility Maximization in Wireless Networks / Distributed CSMA Scheduling with Collisions / Stochastic Processing networks.
700 1# - AUTHOR 2
Author 2 Walrand, Jean.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-79992-1
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2010.
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-- txt
-- rdacontent
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-- computer
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-- rdamedia
338 ## -
-- online resource
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-- text file
-- PDF
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650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Cooperating objects (Computer systems).
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Programming languages (Electronic computers).
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Telecommunication.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Cyber-Physical Systems.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Programming Language.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Communications Engineering, Networks.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2690-4314
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-- ZDB-2-SXSC

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