Wireless Network Design: Optimization Models and Solution ...

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9 Routing in Mobile Ad Hoc Networks 213 are known, allowing for multiple choices with respect to some bandwidth requirements), though the use of some QoS-aware routing protocol is encouraged. 9.5.2 CEDAR (Core-Extraction Distributed Ad hoc Routing) CEDAR [18] is a reactive protocol which optimizes routing requests by using core nodes, i.e., nodes that belong to the dominating set of the network. Each node periodically broadcasts BEACON messages which are used for one-hop neighborhood discovery. In a first phase of the protocol, each node must elect its core node. The set of nodes that are the core node of a neighbor is called the core of the network. Then, local topology information is disseminated by means of piggybacking link information to BEACON messages to the three-hop neighborhood of the nodes, allowing each core node to maintain virtual links to its neighboring core nodes. Thus, core nodes maintain information about the local core graph. When a node s needs a route to d, it requests a route calculation to its core node, dom(s). By means of some chosen reactive routing protocols, dom(s) finds a core path to dom(d). After having determined the route to dom(d), s sends packets to d by means of source-routing. Now if QoS constraints are to be honored for a given route calculation, each core node must find a virtual link to the next core node towards dom(d) that satisfies the constraints. The use of core nodes for route calculation assumes that the core path is a good hint towards the optimal route. But it does not ensure that the best route can be found. 9.5.3 TBP (Ticket-based Probing) TBP [7] attempts to achieve near optimal performance while avoiding flooding, and accounting for link information imprecision. QoS-satisfying routes are found by sending probes carrying some limited total amount of tickets towards the destination using distance vector information. At each intermediate node, a probe may be split up with the tickets distributed between the probes resulting from the split. The total number of tickets must remain the same along the propagation. The goal is to maintain a compromise between the odds of finding an optimal route (more tickets sent) and reduced control overhead (fewer tickets sent). If only one ticket is sent, then the plain, old shortest path is searched. TBP relies on the assumption that stable links tend to remain stable, as opposed to so called transient links. Each node i collects statistical information about delay Di(t), bandwidth Bi(t) and cost Ci(t) to each other node t in the network. It is thus not meant to be scalable, but is rather designed for moderate scale networks. Along with Di(t) and Bi(t), each node maintains the association variation ∆Di(t) and ∆Bi(t) by which the next reported value will differ with the current one.
214 Khaldoun Al Agha and Steven Martin The protocol makes a distinction between delay and bandwidth constrained paths. Thus, it either searches a route for least-cost delay-constrained connections, or least-cost bandwidth-constrained connections. For each purpose, it defines two kinds of tickets—yellow ones and green ones—that make the probes either look for feasible paths or least-cost paths. The relative quantity of each kind governs which kind of path is going to be searched. 9.5.4 INSIGNIA INSIGNIA [12] is meant to provide a complete framework for QoS support in MANET. It is based on the assumption that applications requiring QoS support also provide a way to modulate this requirement and can sustain service degradation by the use of adaptive services. The model thus defines three operating modes for a flow: best effort (BE), base QoS (BQ) constraints with minimum bandwidth, and enhanced QoS (EQ) with maximum bandwidth. It also assumes, quite rightfully, that the destination node is the best place to measure the QoS of a flow and make decisions about service degradation. The framework provides a form of in-band signaling between source and destination by the addition of an option in the IP header of packets, the purpose of which is to attach QoS requirements to a flow as well as a means to alert the destination in case the requirements are not fulfilled at a bottleneck node. It is not specifically designed to operate with a given routing protocol and is rather meant to support any MANET routing protocol. Thus, it does not take any advantage of QoS-aware routing but rather relies on service adaptation on the application’s side. Moreover, the framework remains independent of any MAC layer specificities which should ensure easy implementation with existing networking equipment. The destination is required to report the QoS level to the source in the feedback in order to modulate the flow to suit QoS conditions. Rerouting is provided by the routing protocol and quality is subject to degradation in case of failure to reserve resources along the new path. Old reservations disappear if they are not regularly refreshed. 9.5.5 SWAN (Stateless Wireless Ad hoc Network) SWAN [3] provides QoS support through service differentiation. It is another framework independent of the routing protocol and the MAC layer, though it relies on the latter for bandwidth and delay measurement. The novelty is that routing nodes do not maintain any state information about the flows they forward, hence the term “stateless”. Each node differentiates two kinds of traffic through DSCP flags in the IP header: real time (RT) and best effort (BE). RT flows are forwarded normally, whereas BE are fed to a traffic conditioner. The node actively monitors RT band-
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International Series in Operations
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Editors Jeff Kennington Eli Olinick
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vi Preface assistance. The work of
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viii Contents 3.4.1 Experiments to
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x Contents 8.3.2 The Solution Proce
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xii Contents References . . . . . .
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List of Contributors Khaldoun Al Ag
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List of Contributors xvii Nitin Sal
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Chapter 1 Introduction to Optimizat
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1 Introduction to Optimization in W
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1 Introduction to Optimization in W
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Part I Background
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10 Dinesh Rajan The goal of this ch
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12 Dinesh Rajan The source encoder
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14 Dinesh Rajan ping (FH) CDMA, and
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16 Dinesh Rajan of SNR is given in
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18 Dinesh Rajan 2.3 Information The
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20 Dinesh Rajan Perror ≤ e −nE
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22 Dinesh Rajan For instance, for t
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24 Dinesh Rajan 2.4.1 Block Codes I
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26 Dinesh Rajan B(z) = 1 � (1 + z
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28 Dinesh Rajan layers. Two of the
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30 Dinesh Rajan nel can support a p
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32 Dinesh Rajan 2.5.2 Physical laye
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34 Dinesh Rajan matched filter for
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36 Dinesh Rajan codes) leads to bet
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38 Dinesh Rajan a length N Inverse
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40 Dinesh Rajan the transmission of
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42 Dinesh Rajan setting, a node may
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44 Dinesh Rajan weighting of the si
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46 Dinesh Rajan 29. Oestges, C., Cl
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48 K. V. S. Hari terrain of operati
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50 K. V. S. Hari fading is calculat
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52 K. V. S. Hari terms have been pr
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54 K. V. S. Hari Fig. 3.1 Normalize
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56 K. V. S. Hari Table 3.3 Impulse
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58 K. V. S. Hari where m antennas a
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60 K. V. S. Hari 3.5.2.4 Dominant R
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62 K. V. S. Hari March, 1984-13 Sep
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64 K. V. S. Hari 47. Van Rees, J.:
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66 J. Cole Smith and Sibel B. Sonuc
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Part II Optimization Problems for N
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102 Eli Olinick carrying capacity.
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104 Eli Olinick 93 85 160 16 38 21
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106 Eli Olinick Amaldi et al. [7] p
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108 Eli Olinick levels (possibly le
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110 Eli Olinick gmℓ ∑ ∑ m∈M
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112 Eli Olinick Using bk to denote
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114 Eli Olinick 5.3.5 Additional De
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116 Eli Olinick capacity, provide n
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118 Eli Olinick ficult optimization
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120 Eli Olinick and-bound so that t
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122 Eli Olinick solution times. Cai
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124 Eli Olinick 27. Glover, F.: Tab
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Chapter 6 Optimization Based WLAN M
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6 Optimization Based WLAN Modeling
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Chapter 7 Spectrum Auctions Karla H
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7 Spectrum Auctions 149 full value.
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7 Spectrum Auctions 151 also decide
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7 Spectrum Auctions 153 disclosed t
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7 Spectrum Auctions 155 focused on
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7 Spectrum Auctions 157 bidders to
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7 Spectrum Auctions 159 in the regi
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7 Spectrum Auctions 161 we suggest
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11 Improving Network Connectivity i
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Chapter 12 Simulation-Based Methods
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12 Simulation-Based Methods for Net
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296 Hang Jin and Li Guo formance in
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298 Hang Jin and Li Guo (ISI) as lo
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300 Hang Jin and Li Guo ARQ (HARQ)
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302 Hang Jin and Li Guo 13.3 Radio
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304 Hang Jin and Li Guo Table 13.2
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306 Hang Jin and Li Guo is transmit
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308 Hang Jin and Li Guo uplink powe
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310 Hang Jin and Li Guo The link ad
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312 Hang Jin and Li Guo where ρ mi
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314 Hang Jin and Li Guo 13.4.4.3 Ex
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316 Hang Jin and Li Guo Fig. 13.9 P
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318 Hang Jin and Li Guo 1. Guarante
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Chapter 14 Cross Layer Scheduling i
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14 Cross Layer Scheduling in Wirele
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Chapter 15 Major Trends in Cellular
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15 Major Trends in Cellular Network
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