DOWNLOAD MY Ph.D Thesis - UNAM

More documents

Recommendations

Info

Chapter 6Optimisation of CRA using adaptive CSAs pHowever, for different traffic types (e.g. Internet at 32 kbps per station and mixed at41.7 kbps traffic as summarised in Table 6.1), for the exponential backoff algorithm, theoptimal system performance, was found with at least 4 and 5 CSs per signalling framefor Internet and mixed traffic, respectively. For the splitting tree algorithm this value(1CSs) was unchanged. In the following section we introduce two enhanced CSAs,which will optimise further the maximum system performance.Table 6.1 - Maximum system performance for Internet and mixed traffic scenarios.CRAExponentialBackoffAlgorithmTrafficTypeInternetInternetInternetInternetMixedMixedMixedMixedMin.CSs perSign. FrameMaximumThroughput (%)Mean AccessDelay (ms)CSs perRequestOfferedLoad (%)ActiveStations2 47.9 236 3.6 48.4 483 47.9 602 3.62 49.4 484 49.3 57 3.31 49.4 485 48.4 178 3.51 48.8 482 43.5 1435 3.26 45.7 343 43.8 926 3.18 45.7 344 44.5 764 3.05 46.1 345 45.23 179 2.88 45.5 34SplittingTreeAlgorithmInternet 1 61.01 155 1.09 61.1 60Internet 2 58.06 189 1.54 58.5 57Internet 3 55.07 153 2.08 55.1 54Internet 4 51.6 257 2.8 52.2 51Mixed1 57.27 282 0.93 57.9 43Mixed2 55.3 98 1.27 55.5 41Mixed3 52.4 331 1.63 53 39Mixed 4 48.99 191 2.15 49.4 37Shaded rows represent the configuration for optimum system performance.6.2.3 Enhanced - CSAsIn this section two enhanced CSAs are introduced. We have called these enhancedmechanisms ‘Forced-CSA’ and ‘Variable-CSA’. Such mechanisms adjust dynamicallythe number of CSs per signalling frame according to the current traffic load, meanpacket size, mean requested slots and possible collisions. These mechanisms willimprove the maximum system performance for the exponential backoff algorithm bysending more CSs when they are needed (and not when they are available) and byreducing the average number of contention slots needed per request, from 3.08 CSs(Figure 6.3) to a value very close to the optimum ‘e(=2.718)’6-9
Chapter 6Optimisation of CRA using adaptive CSAs pFor the splitting tree algorithm a more efficient CSA is not necessary, since the systemperformance has already been maximised by fixing the Min. o. of CSs per signallingframe to 1 CSs, regardless of the traffic type and when a medium size network has beenconsidered (under 70 stations).6.2.3.1 Forced-CSA used with the exponential backoff algorithmThis mechanism is based on the dynamics of the splitting tree algorithm. When acollision occurs, the splittting tree algorithm automatically allocates a CS in the nextsignalling frame, which is then split into 3MSs and used only between the stationsinvolved in the collision. The Forced-CSA, on the other hand, allocates a flexiblenumber of CSs in the next signalling frame. We refer to these additional slots as forcedcontention slots (FSs). With this new functionally, stations competing for contentionaccess have more chance to transmit successfully, since more contention slots areallocated when they are needed, reducing considerably packet access delays.The idea of allocating more contention slots, in additional to the unreserved slots thatare also allocated to the contention-based access region, was first reported in [96] and[98]. Here the authors introduced a new contention slots allocator, referred to as‘Forced Mini-Slots CSA’ for the IEEE 802.14 protocol. The main difference betweenour Forced-CSA and the Forced Mini-Slots CSA, is that the latter allocates more CSsaccording to the maximum throughput of the Slotted Aloha System, defined inEquation 6.1. a −1ηmax= a⋅ p ⋅ (1 − p)(6.1)where p is the retransmission probability and a is an estimation of the number ofstations competing for a contention slot.On high traffic loads, the Forced Mini-Slots CSA allocates e(=1/η max ) CSs for each datamessage to be transmitted. Conversely on low traffic loads, it allocates less thane(=1/η max ) CSs. However, our mechanism (Forced-CSA) allocates more CSs when acollision occurs and on high traffic loads, the average number of CSs required perrequested data message approaches very close to e(=1/η max ).6-10
Page 6 and 7:
I would like to thank all the peopl
Page 10:
CHAPTER 6: OPTIMISATIO OF CRA ALGOR
Page 13 and 14:
FIGURE 5.17 - SYSTEM THROUGHPUT VS.
Page 15 and 16:
LIST OF TABLESTABLE 2.1 - NEXT GENE
Page 17 and 18:
Chapter 1Introduction pBecause of h
Page 19 and 20:
Chapter 1Introduction pA first step
Page 21 and 22:
Chapter 1Introduction passumption i
Page 23 and 24:
Chapter 1Introduction ppolynomial b
Page 25 and 26:
Chapter 1Introduction pIn general,
Page 27 and 28:
Chapter 1Introduction pminislots to
Page 29 and 30:
Chapter 1Introduction pThe authors
Page 31 and 32:
Chapter 1Introduction prate access
Page 33 and 34:
Chapter 1Introduction p1.4 Overview
Page 35 and 36:
Chapter 2OVERVIEW OF CURRENT CATVNE
Page 37 and 38:
Chapter 2Overview of current CATV n
Page 39 and 40:
Page 41 and 42:
Page 43 and 44:
Page 45 and 46:
Page 47 and 48:
Page 49 and 50:
Page 51 and 52:
Page 53 and 54:
Page 55 and 56:
Chapter 3THE DVB/DAVIC PROTOCOL3.1
Page 57 and 58:
Chapter 3The DVB/DAVIC protocol pEu
Page 59 and 60:
Chapter 3The DVB/DAVIC protocol pMA
Page 61 and 62:
Chapter 3The DVB/DAVIC protocol pTh
Page 63 and 64:
Page 65 and 66:
Page 67 and 68:
Chapter 3The DVB/DAVIC protocol p3.
Page 69 and 70:
Chapter 4Simulation and analytical
Page 71 and 72:
Page 73 and 74:
Page 75 and 76:
Page 77 and 78:
Page 79 and 80:
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
Page 87 and 88:
Page 89 and 90:
Page 91 and 92:
Page 93 and 94:
Page 95 and 96:
Page 97 and 98:
Page 99 and 100: Chapter 4Simulation and analytical
Page 105 and 106: Chapter 5Upstream channel capacity
Page 143 and 144: Chapter 6Optimisation of CRA using
Page 149: Chapter 6Optimisation of CRA using
Page 171 and 172: Chapter 7PERFORMANCE OPTIMISATION F
Page 173 and 174: Chapter 7Performance optimisation f
Page 201 and 202:
aChapter 7Performance optimisation
Page 203 and 204:
Chapter 7Performance optimisation f
Page 205 and 206:
Page 207 and 208:
Page 209 and 210:
Chapter 8Final conclusions p8.2 Gen
Page 211 and 212:
Chapter 8Final conclusions pWe have
Page 213 and 214:
Chapter 8Final conclusions pperform
Page 215 and 216:
Chapter 8Final conclusions pslots i
Page 217 and 218:
Chapter 8Final conclusions pfocused
Page 219 and 220:
Chapter 8Final conclusions preserva
Page 221 and 222:
Chapter 8Final conclusions pbandwid
Page 223 and 224:
Chapter 8Final conclusions pThe opt
Page 225 and 226:
Chapter 8Final conclusions p8.4 Fut
Page 227 and 228:
Chapter 8Final conclusions pApplica
Page 229 and 230:
Chapter 8Final conclusions pTCIS st
Page 231 and 232:
Referencesp[17] I. Cidon, and M. Si
Page 233 and 234:
Referencesp[50] N. F. Huang, C. A.
Page 235 and 236:
Referencesp[85] V. Rangel, R. Edwar
Page 237 and 238:
Referencesp[112] K. Sriram, “Meth
Page 239 and 240:
APPEDIX A: GLOSSARYAALABRADSLATMBCB
Page 241 and 242:
Appendix AGlossary pkbpsLANLLCMACMA
Page 243 and 244:
Appendix AGlossary pUSBUWVDSLVoDVoI
Page 245 and 246:
Appendix BProtocol stack and packet
Page 247 and 248:
Appendix BProtocol stack and packet
Page 249 and 250:
APPENDIX C: D VERIFICATION TEST FOR
Page 251 and 252:
Appendix D Verification test p209 2
Page 253 and 254:
Appendix EResults for a 6 Mbps upst
Page 255:
Appendix FGuide to CD-ROM p IEEE802
show all

DOWNLOAD MY Ph.D Thesis - UNAM

Create successful ePaper yourself

Delete template?

Save as template?