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| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 | 1x | /** * The copyright in this software is being made available under the BSD License, * included below. This software may be subject to other third party and contributor * rights, including patent rights, and no such rights are granted under this license. * * Copyright (c) 2013, Dash Industry Forum. * All rights reserved. * * Redistribution and use in source and binary forms, with or without modification, * are permitted provided that the following conditions are met: * * Redistributions of source code must retain the above copyright notice, this * list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright notice, * this list of conditions and the following disclaimer in the documentation and/or * other materials provided with the distribution. * * Neither the name of Dash Industry Forum nor the names of its * contributors may be used to endorse or promote products derived from this software * without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS AS IS AND ANY * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. * IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, * INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT * NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, * WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE * POSSIBILITY OF SUCH DAMAGE. */ /** * Authors: * Abdelhak Bentaleb | National University of Singapore | bentaleb@comp.nus.edu.sg * Mehmet N. Akcay | Ozyegin University | necmettin.akcay@ozu.edu.tr * May Lim | National University of Singapore | maylim@comp.nus.edu.sg */ import FactoryMaker from '../../../../core/FactoryMaker.js'; function LoLpWeightSelector(config) { let targetLatency = config.targetLatency; let bufferMin = config.bufferMin; let segmentDuration = config.segmentDuration; let qoeEvaluator = config.qoeEvaluator; let instance, valueList, weightTypeCount, weightOptions, previousLatency; /** * * @private */ function _setup() { _resetInitialSettings(); } /** * * @private */ function _resetInitialSettings() { valueList = [0.2, 0.4, 0.6, 0.8, 1]; weightTypeCount = 4; weightOptions = _getPermutations(valueList, weightTypeCount); previousLatency = 0; } /** * Next, at each segment boundary, ABR to input current neurons and target state (only used in Method II) to find the desired weight vector * @param {array} neurons * @param {number} currentLatency * @param {number} currentBuffer * @param {number} currentRebuffer * @param {number} currentThroughput * @param {number} playbackRate * @return {number|null} * @private */ function findWeightVector(neurons, currentLatency, currentBuffer, currentRebuffer, currentThroughput, playbackRate) { let maxQoE = null; let winnerWeights = null; let winnerBitrate = null; let deltaLatency = Math.abs(currentLatency - previousLatency); // For each neuron, m neurons.forEach((neuron) => { // For each possible weight vector, z // E.g. For [ throughput, latency, buffer, playbackRate, QoE ] // Possible weightVector = [ 0.2, 0.4, 0.2, 0, 0.2 ] weightOptions.forEach((weightVector) => { // Apply weightVector to neuron, compute utility and determine winnerWeights // Method I: Utility based on QoE given current state let weightsObj = { throughput: weightVector[0], latency: weightVector[1], buffer: weightVector[2], switch: weightVector[3] }; let downloadTime = (neuron.representation.bandwidth * segmentDuration) / currentThroughput; let nextBuffer = getNextBuffer(currentBuffer, downloadTime); let rebuffer = Math.max(0.00001, (downloadTime - nextBuffer)); let wt; if (weightsObj.buffer === 0) { wt = 10; } else { wt = (1 / weightsObj.buffer); } let weightedRebuffer = wt * rebuffer; if (weightsObj.latency === 0) { wt = 10; } else { wt = (1 / weightsObj.latency); // inverse the weight because wt and latency should have positive relationship, i.e., higher latency = higher wt } let weightedLatency = wt * neuron.state.latency; let totalQoE = qoeEvaluator.calculateSingleUseQoe(neuron.representation.bandwidth, weightedRebuffer, weightedLatency, playbackRate); if ((maxQoE === null || totalQoE > maxQoE) && _checkConstraints(currentLatency, nextBuffer, deltaLatency)) { maxQoE = totalQoE; winnerWeights = weightVector; winnerBitrate = neuron.representation.bandwidth; } }); }); // winnerWeights was found, check if constraints are satisfied if (winnerWeights === null && winnerBitrate === null) { winnerWeights = -1; } previousLatency = currentLatency; return winnerWeights; } /** * * @param {number} nextLatency * @param {number} nextBuffer * @param {number} deltaLatency * @return {boolean} * @private */ function _checkConstraints(nextLatency, nextBuffer, deltaLatency) { // A1 // disabled till we find a better way of estimating latency // fails for all with current value if (nextLatency > targetLatency + deltaLatency) { return false; } return nextBuffer >= bufferMin; } /** * * @param {array} list * @param {number} length * @return {*} * @private */ function _getPermutations(list, length) { // Copy initial values as arrays let perm = list.map(function (val) { return [val]; }); // Our permutation generator let generate = function (perm, length, currLen) { // Reached desired length if (currLen === length) { return perm; } // For each existing permutation let len = perm.length; for (let i = 0; i < len; i++) { let currPerm = perm.shift(); // Create new permutation for (let k = 0; k < list.length; k++) { perm.push(currPerm.concat(list[k])); } } // Recurse return generate(perm, length, currLen + 1); }; // Start with size 1 because of initial values return generate(perm, length, 1); } /** * * @return {number} */ function getMinBuffer() { return bufferMin; } /** * * @return {number} */ function getSegmentDuration() { return segmentDuration; } /** * * @param {number} bitrateToDownload * @param {number} currentBuffer * @param {number} currentThroughput * @return {number} */ function getNextBufferWithBitrate(bitrateToDownload, currentBuffer, currentThroughput) { let downloadTime = (bitrateToDownload * segmentDuration) / currentThroughput; return getNextBuffer(currentBuffer, downloadTime); } /** * * @param {number} currentBuffer * @param {number} downloadTime * @return {number} */ function getNextBuffer(currentBuffer, downloadTime) { const segmentDuration = getSegmentDuration(); let nextBuffer; if (downloadTime > segmentDuration) { nextBuffer = currentBuffer - segmentDuration; } else { nextBuffer = currentBuffer + segmentDuration - downloadTime; } return nextBuffer; } instance = { getMinBuffer, getSegmentDuration, getNextBufferWithBitrate, getNextBuffer, findWeightVector }; _setup(); return instance; } LoLpWeightSelector.__dashjs_factory_name = 'LoLpWeightSelector'; export default FactoryMaker.getClassFactory(LoLpWeightSelector); |