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Buzen's algorithm

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additions. This dramatic improvement opened the door to applying the Gordon-Newell theorem to models of real world computer systems as well as flexible manufacturing systems and other cases where bottlenecks and queues can form within networks of inter-connected service facilities. The values of
2122:) is in principle a two dimensional matrix, it can be computed in a column by column fashion starting from the top of the leftmost column and running down each column to the bottom before proceeding to the next column on the right. The routine uses a single column vector 1561:
The Gordon-Newell theorem enables analysts to determine the stationary probability associated with each individual state of a closed queueing network.  These individual probabilities must then be added together to evaluate other important probabilities. For example
699: 1252:, a surprising result emerges: the modified terms in the first group are identical to the terms used to compute the normalizing constant for the same network with one customer removed. Thus, the sum of the terms in the first group can be written as “ 1885: 836: 2095: 401: 1969: 978: 280: 555: 2133:
The first loop in the algorithm below initializes the column vector C so that C = 1 and C(n) = 0 for n≄1.   Note that C remains equal to 1 throughout all subsequent iterations.  
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effectively disappears from all terms in this group (since it reduces in every case to a factor of 1). This leaves the total number of customers at the remaining
1982: 1518:-1).  Buzen’s algorithm is simply the iterative application of this fundamental recurrence relation, along with the following boundary conditions. 310: 2534: 2823: 1891: 2367: 1144:. Note that this set of terms can be partitioned into two groups. The first group comprises all terms for which the exponent of 2740: 1617:
Many of these marginal probabilities can be computed with minimal additional effort.  This is easy to see for the case of P(
2599: 3010: 913: 215: 694:{\displaystyle \mathbb {P} (n_{1},n_{2},\cdots ,n_{M})={\frac {1}{{\text{G}}(N)}}\prod _{i=1}^{M}\left(X_{i}\right)^{n_{i}}} 2811: 2527: 2431: 159:-1), which can be used to calculate other important quantities of interest, are computed as by-products of the algorithm. 59:
Performing a naĂŻve computation of the normalizing constant requires enumeration of all states. For a closed network with
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can be factored out from each of these probabilities, leaving a set of modified probabilities whose sum is given by G(
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as the algorithm proceeds down column m.  This is achieved by setting each successive value of C(n) equal to:
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have been computed by solving the relevant equations and are available as an input to our routine. Although g(
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In the second loop, each successive value of C(n) for n≄1 is set equal to the corresponding value of g(
2626: 1880:{\displaystyle \mathbb {P} (n_{i}=k)={\frac {X_{i}^{k}}{G(N)}}\quad {\text{ for }}k=0,1,\ldots ,N-1,} 2638: 2955: 2935: 2930: 2702: 48:
in his 1971 PhD dissertation and subsequently published in a refereed journal in 1973. Computing G(
831:{\displaystyle \mu _{j}X_{j}=\sum _{i=1}^{M}\mu _{i}X_{i}p_{ij}\quad {\text{ for }}j=1,\ldots ,M.} 2960: 2945: 2912: 2806: 2448: 2390: 21: 2577: 2507: 2950: 2849: 2760: 2750: 2690: 2801: 2745: 2631: 2484: 2440: 2426: 2382: 2363: 45: 2589: 980:
is equal to 1. Buzen's algorithm represents the first efficient procedure for computing G(
2818: 2685: 2543: 2398: 1265:-1)”. This insight provides the foundation for the development of the algorithm.   17: 2828: 2791: 2502: 1376:
Given this definition, the sum of the terms in the second group can now be written as g(
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circulating customers. Assume that the service time for a customer at service facility
2887: 1699: 2999: 2940: 2925: 2902: 2714: 1658:).   This observation yields the following simple and highly efficient result: 2897: 2724: 2090:{\displaystyle \mathbb {E} (n_{i})=\sum _{k=1}^{N}X_{i}^{k}{\frac {G(N-k)}{G(N)}}.} 396:{\displaystyle \mathbb {P} (n_{1},n_{2},\cdots ,n_{M})={\frac {1}{{\text{G}}(N)}}} 2394: 282:
be the steady state probability that the number of customers at service facility
2920: 2877: 2844: 2621: 2616: 2611: 2594: 2584: 2572: 2567: 2562: 2557: 2368:"Computational algorithms for closed queueing networks with exponential servers" 2643: 1289:. The second group includes all possible arrangements of these N customers. 2719: 2340: 1435:) is equal to the combined sum of the terms in the first and second groups, 1476:
This same recurrence relation clearly exists for any intermediate value of
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for every term in this group is zero.  As a result, service facility
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or higher in every state where the number of customers at service center
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raised to the power 1 can be factored out of each of these terms.  
1573:), the probability that the total number of customers at service center 2452: 1398:-1)”, the sum of the terms in the first group, can be re-written as “ 2489: 2099:
These characterizations of quantities of interest in terms of the G(
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Menasce: Convolution Approach to Queueing Algorithms (presentation)
2512: 1964:{\displaystyle \mathbb {P} (n_{i}=N)={\frac {X_{i}^{N}}{G(N)}}.} 2516: 992:
The individual terms that must be added together to compute G(
2473:"Rethinking Randomness: An interview with Jeff Buzen, Part I" 2429:(1967). "Closed Queuing Systems with Exponential Servers". 2342:
DTIC AD0731575: Queueing Network Models of Multiprogramming
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At completion, the final values of C correspond to column
1420:) in the Gordon-Newell theorem can now be re-written as g( 847:) is a normalizing constant chosen so that the sum of all 1179:
is greater than or equal to 1.  This implies that
973:{\displaystyle \mathbb {P} (n_{1},n_{2},\cdots ,n_{M})} 275:{\displaystyle \mathbb {P} (n_{1},n_{2},\cdots ,n_{M})} 192:
and that, after completing service at service facility
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Next consider the second group.  The exponent of
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The expected number of customers at service facility
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Marginal distributions, expected number of customers
2911: 2870: 2837: 2774: 2733: 2678: 2652: 2550: 196:, a customer will proceed next to service facility 2089: 1963: 1879: 1694:This relationship can then be used to compute the 1244: 1206: 1171: 1136: 1087: 1039: 972: 902: 830: 693: 540: 491: 443: 395: 274: 126: 2310:).  Thus they represent the desired values G 1327:) as the normalizing constant for a network with 550:This result is usually written more compactly as 2503:Jain: The Convolution Algorithm (class handout) 1292:To express this concept precisely, assume that 134:individual terms, with each term consisting of 1702:number of customers at each service facility. 1610:customers can be distributed across the other 2528: 893: 858: 117: 82: 8: 2358: 2356: 2354: 2352: 1307:have been obtained for a given network with 2535: 2521: 2513: 1137:{\displaystyle \left(X_{M}\right)^{n_{M}}} 1088:{\displaystyle \left(X_{2}\right)^{n_{2}}} 1040:{\displaystyle \left(X_{1}\right)^{n_{1}}} 541:{\displaystyle \left(X_{M}\right)^{n_{M}}} 492:{\displaystyle \left(X_{2}\right)^{n_{2}}} 444:{\displaystyle \left(X_{1}\right)^{n_{1}}} 2488: 2046: 2040: 2035: 2025: 2014: 1998: 1987: 1986: 1984: 1936: 1931: 1925: 1907: 1896: 1895: 1893: 1836: 1802: 1752: 1747: 1741: 1723: 1712: 1711: 1709: 1232: 1222: 1194: 1184: 1159: 1149: 1126: 1121: 1111: 1100: 1077: 1072: 1062: 1051: 1029: 1024: 1014: 1003: 961: 942: 929: 918: 917: 915: 892: 857: 854: 852: 799: 789: 779: 769: 759: 748: 735: 725: 719: 683: 678: 668: 653: 642: 621: 615: 603: 584: 571: 560: 559: 557: 530: 525: 515: 504: 481: 476: 466: 455: 433: 428: 418: 407: 376: 370: 358: 339: 326: 315: 314: 312: 263: 244: 231: 220: 219: 217: 116: 81: 78: 76: 1416:In addition, the normalizing constant G( 167:Consider a closed queueing network with 52:) is required to compute the stationary 2331: 2165:) is the previous value of C(n), and g( 1599:, over all possible ways the remaining 20:, a discipline within the mathematical 903:{\displaystyle {\tbinom {N+M-1}{M-1}}} 138:factors raised to powers whose sum is 127:{\displaystyle {\tbinom {N+M-1}{M-1}}} 32:) is an algorithm for calculating the 7: 2471:Denning, Peter J. (24 August 2016). 2466: 2464: 2462: 2420: 2418: 1614:-1 service centers in the network. 1581:, must be summed over all values of 1484:, and for any intermediate value of 44:. This method was first proposed by 2126:to represent the current column of 2169:) is the current value of C(n-1) 1387:It also follows immediately that “ 1245:{\displaystyle \left(X_{M}\right)} 1207:{\displaystyle \left(X_{M}\right)} 1172:{\displaystyle \left(X_{M}\right)} 862: 86: 14: 1358:members of the original sequence 996:) all have the following form: 2982: 2981: 142:. Buzen's algorithm computes G( 1835: 1631:must be raised to the power of 1285:-1 service facilities equal to 798: 183:random variable with parameter 2078: 2072: 2064: 2052: 2004: 1991: 1952: 1946: 1919: 1900: 1832: 1829: 1811: 1792: 1780: 1774: 1768: 1762: 1735: 1716: 967: 922: 632: 626: 609: 564: 387: 381: 364: 319: 269: 224: 56:of a closed queueing network. 1: 2812:Flow-equivalent server method 2893:Adversarial queueing network 2782:Continuous-time Markov chain 2111:It will be assumed that the 1639:is greater than or equal to 1592:and, for each such value of 1577:is greater than or equal to 1311:service facilities. For any 2855:Heavy traffic approximation 2600:Pollaczek–Khinchine formula 1354: that match the first 1335:service facilities (1,2, 
 3027: 2339:Buzen, J.P. (1971-08-01). 712:are determined by solving 63:circulating customers and 2979: 2860:Reflected Brownian motion 2665:Markovian arrival process 2375:Communications of the ACM 2103:) are also due to Buzen. 181:exponentially distributed 2883:Layered queueing network 2670:Rational arrival process 2171: 54:probability distribution 2971:Teletraffic engineering 2766:Shortest remaining time 1339:), and values of   171:service facilities and 3011:Statistical algorithms 2966:Scheduling (computing) 2605:Matrix analytic method 2091: 2030: 1965: 1881: 1696:marginal distributions 1624:≄ k).   Clearly, 1246: 1208: 1173: 1138: 1089: 1041: 974: 904: 832: 764: 695: 658: 542: 493: 445: 397: 276: 128: 67:service facilities, G( 34:normalization constant 2797:Product-form solution 2698:Gordon–Newell theorem 2660:Poisson point process 2551:Single queueing nodes 2445:10.1287/opre.15.2.254 2387:10.1145/362342.362345 2092: 2010: 1966: 1882: 1247: 1209: 1174: 1139: 1090: 1042: 988:Algorithm description 975: 905: 833: 744: 696: 638: 543: 494: 446: 398: 303:Gordon–Newell theorem 277: 129: 42:Gordon–Newell theorem 30:convolution algorithm 22:theory of probability 2824:Decomposition method 2483:(August): 1:1–1:17. 1983: 1892: 1708: 1221: 1217:After factoring out 1183: 1148: 1099: 1050: 1002: 914: 851: 718: 556: 503: 454: 406: 311: 301:It follows from the 216: 150:multiplications and 75: 2956:Pipeline (software) 2936:Flow control (data) 2931:Erlang distribution 2913:Information systems 2703:Mean value analysis 2432:Operations Research 2045: 1941: 1757: 1539:,1)  =  ( 2961:Quality of service 2946:Network congestion 2807:Quasireversibility 2787:Kendall's notation 2087: 2031: 1961: 1927: 1877: 1743: 1242: 1204: 1169: 1134: 1085: 1037: 970: 900: 898: 828: 691: 538: 489: 441: 393: 272: 124: 122: 2993: 2992: 2951:Network scheduler 2850:Mean-field theory 2761:Shortest job next 2751:Processor sharing 2708:Buzen's algorithm 2691:Traffic equations 2679:Queueing networks 2653:Arrival processes 2627:Kingman's formula 2082: 1956: 1839: 1772: 891: 802: 636: 624: 391: 379: 200:with probability 155:G(1), G(2) ... G( 115: 26:Buzen's algorithm 3018: 2985: 2984: 2802:Balance equation 2734:Service policies 2632:Lindley equation 2537: 2530: 2523: 2514: 2495: 2494: 2492: 2468: 2457: 2456: 2422: 2413: 2412: 2410: 2409: 2403: 2397:. Archived from 2372: 2360: 2347: 2346: 2336: 2306:in the matrix g( 2298: 2295: 2292: 2289: 2286: 2283: 2280: 2277: 2274: 2271: 2268: 2265: 2262: 2259: 2256: 2253: 2250: 2247: 2244: 2241: 2238: 2235: 2232: 2229: 2226: 2223: 2220: 2217: 2214: 2211: 2208: 2205: 2202: 2199: 2196: 2193: 2190: 2187: 2184: 2181: 2178: 2175: 2096: 2094: 2093: 2088: 2083: 2081: 2067: 2047: 2044: 2039: 2029: 2024: 2003: 2002: 1990: 1970: 1968: 1967: 1962: 1957: 1955: 1940: 1935: 1926: 1912: 1911: 1899: 1886: 1884: 1883: 1878: 1840: 1837: 1807: 1806: 1773: 1771: 1756: 1751: 1742: 1728: 1727: 1715: 1251: 1249: 1248: 1243: 1241: 1237: 1236: 1213: 1211: 1210: 1205: 1203: 1199: 1198: 1178: 1176: 1175: 1170: 1168: 1164: 1163: 1143: 1141: 1140: 1135: 1133: 1132: 1131: 1130: 1120: 1116: 1115: 1094: 1092: 1091: 1086: 1084: 1083: 1082: 1081: 1071: 1067: 1066: 1046: 1044: 1043: 1038: 1036: 1035: 1034: 1033: 1023: 1019: 1018: 979: 977: 976: 971: 966: 965: 947: 946: 934: 933: 921: 909: 907: 906: 901: 899: 897: 896: 890: 879: 861: 837: 835: 834: 829: 803: 800: 797: 796: 784: 783: 774: 773: 763: 758: 740: 739: 730: 729: 700: 698: 697: 692: 690: 689: 688: 687: 677: 673: 672: 657: 652: 637: 635: 625: 622: 616: 608: 607: 589: 588: 576: 575: 563: 547: 545: 544: 539: 537: 536: 535: 534: 524: 520: 519: 498: 496: 495: 490: 488: 487: 486: 485: 475: 471: 470: 450: 448: 447: 442: 440: 439: 438: 437: 427: 423: 422: 402: 400: 399: 394: 392: 390: 380: 377: 371: 363: 362: 344: 343: 331: 330: 318: 281: 279: 278: 273: 268: 267: 249: 248: 236: 235: 223: 133: 131: 130: 125: 123: 121: 120: 114: 103: 85: 71:) is the sum of 46:Jeffrey P. Buzen 3026: 3025: 3021: 3020: 3019: 3017: 3016: 3015: 3006:Queueing theory 2996: 2995: 2994: 2989: 2975: 2907: 2866: 2833: 2819:Arrival theorem 2770: 2729: 2686:Jackson network 2674: 2648: 2639:Fork–join queue 2578:Burke's theorem 2546: 2544:Queueing theory 2541: 2499: 2498: 2490:10.1145/2986329 2470: 2469: 2460: 2425:Gordon, W. J.; 2424: 2423: 2416: 2407: 2405: 2401: 2370: 2362: 2361: 2350: 2338: 2337: 2333: 2328: 2300: 2299: 2296: 2293: 2290: 2287: 2284: 2281: 2278: 2275: 2272: 2269: 2266: 2263: 2260: 2257: 2254: 2251: 2248: 2245: 2242: 2239: 2236: 2233: 2230: 2227: 2224: 2221: 2218: 2215: 2212: 2209: 2206: 2203: 2200: 2197: 2194: 2191: 2188: 2185: 2182: 2179: 2176: 2173: 2152: 2116: 2109: 2068: 2048: 1994: 1981: 1980: 1942: 1903: 1890: 1889: 1838: for  1798: 1758: 1719: 1706: 1705: 1677: 1666: 1648: 1629: 1622: 1608: 1597: 1586: 1567: 1559: 1545: 1504: 1495:This implies g( 1455: 1403: 1392: 1371: 1367: 1363: 1352: 1348: 1344: 1305: 1301: 1297: 1276: 1260: 1228: 1224: 1219: 1218: 1190: 1186: 1181: 1180: 1155: 1151: 1146: 1145: 1122: 1107: 1103: 1102: 1097: 1096: 1073: 1058: 1054: 1053: 1048: 1047: 1025: 1010: 1006: 1005: 1000: 999: 990: 957: 938: 925: 912: 911: 880: 863: 856: 849: 848: 801: for  785: 775: 765: 731: 721: 716: 715: 711: 679: 664: 660: 659: 620: 599: 580: 567: 554: 553: 526: 511: 507: 506: 501: 500: 477: 462: 458: 457: 452: 451: 429: 414: 410: 409: 404: 403: 375: 354: 335: 322: 309: 308: 291: 259: 240: 227: 214: 213: 208: 191: 179:is given by an 165: 104: 87: 80: 73: 72: 18:queueing theory 12: 11: 5: 3024: 3022: 3014: 3013: 3008: 2998: 2997: 2991: 2990: 2980: 2977: 2976: 2974: 2973: 2968: 2963: 2958: 2953: 2948: 2943: 2938: 2933: 2928: 2923: 2917: 2915: 2909: 2908: 2906: 2905: 2900: 2895: 2890: 2888:Polling system 2885: 2880: 2874: 2872: 2868: 2867: 2865: 2864: 2863: 2862: 2852: 2847: 2841: 2839: 2838:Limit theorems 2835: 2834: 2832: 2831: 2826: 2821: 2816: 2815: 2814: 2809: 2804: 2794: 2789: 2784: 2778: 2776: 2772: 2771: 2769: 2768: 2763: 2758: 2753: 2748: 2743: 2737: 2735: 2731: 2730: 2728: 2727: 2722: 2717: 2712: 2711: 2710: 2705: 2695: 2694: 2693: 2682: 2680: 2676: 2675: 2673: 2672: 2667: 2662: 2656: 2654: 2650: 2649: 2647: 2646: 2641: 2636: 2635: 2634: 2629: 2619: 2614: 2609: 2608: 2607: 2602: 2592: 2587: 2582: 2581: 2580: 2570: 2565: 2560: 2554: 2552: 2548: 2547: 2542: 2540: 2539: 2532: 2525: 2517: 2511: 2510: 2505: 2497: 2496: 2458: 2414: 2381:(9): 527–531. 2348: 2330: 2329: 2327: 2324: 2172: 2150: 2114: 2108: 2107:Implementation 2105: 2086: 2080: 2077: 2074: 2071: 2066: 2063: 2060: 2057: 2054: 2051: 2043: 2038: 2034: 2028: 2023: 2020: 2017: 2013: 2009: 2006: 2001: 1997: 1993: 1989: 1960: 1954: 1951: 1948: 1945: 1939: 1934: 1930: 1924: 1921: 1918: 1915: 1910: 1906: 1902: 1898: 1876: 1873: 1870: 1867: 1864: 1861: 1858: 1855: 1852: 1849: 1846: 1843: 1834: 1831: 1828: 1825: 1822: 1819: 1816: 1813: 1810: 1805: 1801: 1797: 1794: 1791: 1788: 1785: 1782: 1779: 1776: 1770: 1767: 1764: 1761: 1755: 1750: 1746: 1740: 1737: 1734: 1731: 1726: 1722: 1718: 1714: 1675: 1664: 1646: 1627: 1620: 1606: 1595: 1584: 1565: 1558: 1555: 1543: 1502: 1453: 1401: 1390: 1369: 1365: 1361: 1350: 1346: 1342: 1303: 1299: 1295: 1272: 1256: 1240: 1235: 1231: 1227: 1202: 1197: 1193: 1189: 1167: 1162: 1158: 1154: 1129: 1125: 1119: 1114: 1110: 1106: 1080: 1076: 1070: 1065: 1061: 1057: 1032: 1028: 1022: 1017: 1013: 1009: 989: 986: 969: 964: 960: 956: 953: 950: 945: 941: 937: 932: 928: 924: 920: 895: 889: 886: 883: 878: 875: 872: 869: 866: 860: 827: 824: 821: 818: 815: 812: 809: 806: 795: 792: 788: 782: 778: 772: 768: 762: 757: 754: 751: 747: 743: 738: 734: 728: 724: 707: 703:The values of 686: 682: 676: 671: 667: 663: 656: 651: 648: 645: 641: 634: 631: 628: 619: 614: 611: 606: 602: 598: 595: 592: 587: 583: 579: 574: 570: 566: 562: 533: 529: 523: 518: 514: 510: 484: 480: 474: 469: 465: 461: 436: 432: 426: 421: 417: 413: 389: 386: 383: 374: 369: 366: 361: 357: 353: 350: 347: 342: 338: 334: 329: 325: 321: 317: 297:= 1, 2, ... , 289: 271: 266: 262: 258: 255: 252: 247: 243: 239: 234: 230: 226: 222: 204: 187: 164: 161: 119: 113: 110: 107: 102: 99: 96: 93: 90: 84: 13: 10: 9: 6: 4: 3: 2: 3023: 3012: 3009: 3007: 3004: 3003: 3001: 2988: 2978: 2972: 2969: 2967: 2964: 2962: 2959: 2957: 2954: 2952: 2949: 2947: 2944: 2942: 2941:Message queue 2939: 2937: 2934: 2932: 2929: 2927: 2926:Erlang (unit) 2924: 2922: 2919: 2918: 2916: 2914: 2910: 2904: 2903:Retrial queue 2901: 2899: 2896: 2894: 2891: 2889: 2886: 2884: 2881: 2879: 2876: 2875: 2873: 2869: 2861: 2858: 2857: 2856: 2853: 2851: 2848: 2846: 2843: 2842: 2840: 2836: 2830: 2827: 2825: 2822: 2820: 2817: 2813: 2810: 2808: 2805: 2803: 2800: 2799: 2798: 2795: 2793: 2790: 2788: 2785: 2783: 2780: 2779: 2777: 2773: 2767: 2764: 2762: 2759: 2757: 2754: 2752: 2749: 2747: 2744: 2742: 2739: 2738: 2736: 2732: 2726: 2723: 2721: 2718: 2716: 2715:Kelly network 2713: 2709: 2706: 2704: 2701: 2700: 2699: 2696: 2692: 2689: 2688: 2687: 2684: 2683: 2681: 2677: 2671: 2668: 2666: 2663: 2661: 2658: 2657: 2655: 2651: 2645: 2642: 2640: 2637: 2633: 2630: 2628: 2625: 2624: 2623: 2620: 2618: 2615: 2613: 2610: 2606: 2603: 2601: 2598: 2597: 2596: 2593: 2591: 2588: 2586: 2583: 2579: 2576: 2575: 2574: 2571: 2569: 2566: 2564: 2561: 2559: 2556: 2555: 2553: 2549: 2545: 2538: 2533: 2531: 2526: 2524: 2519: 2518: 2515: 2509: 2506: 2504: 2501: 2500: 2491: 2486: 2482: 2478: 2474: 2467: 2465: 2463: 2459: 2454: 2450: 2446: 2442: 2438: 2434: 2433: 2428: 2427:Newell, G. F. 2421: 2419: 2415: 2404:on 2016-05-13 2400: 2396: 2392: 2388: 2384: 2380: 2376: 2369: 2365: 2359: 2357: 2355: 2353: 2349: 2344: 2343: 2335: 2332: 2325: 2323: 2321: 2317: 2313: 2309: 2305: 2170: 2168: 2164: 2159: 2157: 2153: 2146: 2141: 2139: 2134: 2131: 2129: 2125: 2121: 2117: 2106: 2104: 2102: 2097: 2084: 2075: 2069: 2061: 2058: 2055: 2049: 2041: 2036: 2032: 2026: 2021: 2018: 2015: 2011: 2007: 1999: 1995: 1978: 1976: 1971: 1958: 1949: 1943: 1937: 1932: 1928: 1922: 1916: 1913: 1908: 1904: 1887: 1874: 1871: 1868: 1865: 1862: 1859: 1856: 1853: 1850: 1847: 1844: 1841: 1826: 1823: 1820: 1817: 1814: 1808: 1803: 1799: 1795: 1789: 1786: 1783: 1777: 1765: 1759: 1753: 1748: 1744: 1738: 1732: 1729: 1724: 1720: 1703: 1701: 1697: 1692: 1690: 1686: 1682: 1678: 1671: 1667: 1659: 1657: 1653: 1649: 1642: 1638: 1634: 1630: 1623: 1615: 1613: 1609: 1602: 1598: 1591: 1587: 1580: 1576: 1572: 1568: 1556: 1554: 1553: 1549: 1542: 1538: 1533: 1532: 1528: 1524: 1519: 1517: 1513: 1509: 1505: 1498: 1493: 1491: 1487: 1483: 1479: 1474: 1472: 1468: 1464: 1460: 1456: 1449: 1445: 1441: 1436: 1434: 1429: 1427: 1423: 1419: 1414: 1412: 1408: 1404: 1397: 1393: 1385: 1383: 1379: 1374: 1372: 1357: 1353: 1338: 1334: 1330: 1326: 1322: 1318: 1314: 1310: 1306: 1290: 1288: 1284: 1280: 1275: 1271: 1266: 1264: 1259: 1255: 1238: 1233: 1229: 1225: 1215: 1200: 1195: 1191: 1187: 1165: 1160: 1156: 1152: 1127: 1123: 1117: 1112: 1108: 1104: 1078: 1074: 1068: 1063: 1059: 1055: 1030: 1026: 1020: 1015: 1011: 1007: 997: 995: 987: 985: 983: 962: 958: 954: 951: 948: 943: 939: 935: 930: 926: 887: 884: 881: 876: 873: 870: 867: 864: 846: 842: 838: 825: 822: 819: 816: 813: 810: 807: 804: 793: 790: 786: 780: 776: 770: 766: 760: 755: 752: 749: 745: 741: 736: 732: 726: 722: 713: 710: 706: 701: 684: 680: 674: 669: 665: 661: 654: 649: 646: 643: 639: 629: 617: 612: 604: 600: 596: 593: 590: 585: 581: 577: 572: 568: 551: 548: 531: 527: 521: 516: 512: 508: 482: 478: 472: 467: 463: 459: 434: 430: 424: 419: 415: 411: 384: 372: 367: 359: 355: 351: 348: 345: 340: 336: 332: 327: 323: 306: 304: 300: 296: 292: 285: 264: 260: 256: 253: 250: 245: 241: 237: 232: 228: 210: 207: 203: 199: 195: 190: 186: 182: 178: 174: 170: 163:Problem setup 162: 160: 158: 153: 149: 146:) using only 145: 141: 137: 111: 108: 105: 100: 97: 94: 91: 88: 70: 66: 62: 57: 55: 51: 47: 43: 39: 35: 31: 27: 23: 19: 2898:Loss network 2829:BeneĆĄ method 2792:Little's law 2775:Key concepts 2725:BCMP network 2707: 2480: 2476: 2436: 2430: 2406:. Retrieved 2399:the original 2378: 2374: 2364:Buzen, J. P. 2341: 2334: 2319: 2315: 2311: 2307: 2303: 2301: 2166: 2162: 2161:Note that g( 2160: 2155: 2148: 2144: 2142: 2137: 2135: 2132: 2127: 2123: 2119: 2112: 2110: 2100: 2098: 1979: 1977:is given by 1974: 1972: 1888: 1704: 1693: 1688: 1684: 1680: 1673: 1669: 1662: 1660: 1655: 1651: 1644: 1640: 1636: 1632: 1625: 1618: 1616: 1611: 1604: 1600: 1593: 1589: 1582: 1578: 1574: 1570: 1563: 1560: 1551: 1547: 1540: 1536: 1534: 1530: 1526: 1522: 1520: 1515: 1511: 1507: 1500: 1496: 1494: 1489: 1485: 1481: 1477: 1475: 1470: 1466: 1462: 1458: 1451: 1447: 1443: 1439: 1437: 1432: 1430: 1425: 1421: 1417: 1415: 1410: 1406: 1399: 1395: 1388: 1386: 1381: 1377: 1375: 1359: 1355: 1340: 1336: 1332: 1328: 1324: 1320: 1316: 1312: 1308: 1293: 1291: 1286: 1282: 1278: 1273: 1269: 1267: 1262: 1257: 1253: 1216: 998: 993: 991: 981: 844: 840: 839: 714: 708: 704: 702: 552: 549: 307: 298: 294: 287: 286:is equal to 283: 211: 205: 201: 197: 193: 188: 184: 176: 172: 168: 166: 156: 151: 147: 143: 139: 135: 68: 64: 60: 58: 49: 37: 29: 25: 15: 2921:Data buffer 2878:Fluid queue 2845:Fluid limit 2756:Round-robin 2622:G/G/1 queue 2617:G/M/1 queue 2612:M/G/k queue 2595:M/G/1 queue 2590:M/M/∞ queue 2585:M/M/c queue 2573:M/M/1 queue 2568:M/D/c queue 2563:M/D/1 queue 2558:D/M/1 queue 2158:).   1413:)”.   1331:customers, 3000:Categories 2871:Extensions 2644:Bulk queue 2439:(2): 254. 2408:2006-04-15 2326:References 2316:(1), ... , 1550:= 0, 1, 
 1525:) = 1 for 1488:from 1 to 1480:from 1 to 910:values of 2720:G-network 2059:− 2012:∑ 1869:− 1860:… 1824:− 1818:− 1796:− 1787:− 1529:= 1, 2, 
 1492:.   1323:define g( 952:⋯ 885:− 874:− 817:… 767:μ 746:∑ 723:μ 640:∏ 594:⋯ 349:⋯ 254:⋯ 109:− 98:− 40:) in the 2987:Category 2477:Ubiquity 2366:(1973). 2154:times g( 1700:expected 1431:Since G( 1405:times g( 1394:times G( 1319:and m ≀ 1261:times G( 2147:) plus 1643:. Thus 2453:168557 2451:  2393:  1654:-k)/G( 1546:) for 1514:) + g( 1465:) + g( 1442:) = g( 305:that 2449:JSTOR 2402:(PDF) 2395:10702 2391:S2CID 2371:(PDF) 2267:until 2240:until 2201:until 2167:n-1,m 2163:n,m-1 2156:n-1,m 2145:n,m-1 1672:) = ( 1428:). 1384:-1). 1368:, 
 X 1349:, 
 X 1302:, 
 X 1095:.... 499:.... 28:(or 2746:LIFO 2741:FIFO 2481:2016 2312:(0), 2261:step 2234:step 2195:step 2138:n,m) 1698:and 1687:)/G( 1679:) G( 1521:g(0, 1499:) = 1473:-1) 1450:) = 293:for 212:Let 2485:doi 2441:doi 2383:doi 2322:. 2320:(N) 2308:n,m 2249:for 2222:for 2183:for 2130:. 2120:n,m 1516:n,m 1510:-1, 1497:n,m 1461:-1, 1409:-1, 1373:. 1364:, X 1345:, X 1325:n,m 1298:, X 984:). 299:M . 16:In 3002:: 2479:. 2475:. 2461:^ 2447:. 2437:15 2435:. 2417:^ 2389:. 2379:16 2377:. 2373:. 2351:^ 2279::= 2273:do 2255::= 2246:do 2228::= 2213::= 2207:do 2189::= 2177::= 2143:g( 1691:) 1668:≄ 1661:P( 1603:– 1588:≄ 1569:≄ 1562:P( 1535:g( 1506:g( 1457:g( 1446:, 1438:G( 1380:, 1321:M, 1315:≀ 209:. 206:ij 152:NM 148:NM 36:G( 24:, 2536:e 2529:t 2522:v 2493:. 2487:: 2455:. 2443:: 2411:. 2385:: 2345:. 2318:G 2314:G 2304:M 2297:; 2294:C 2291:* 2288:X 2285:+ 2282:C 2276:C 2270:N 2264:1 2258:1 2252:n 2243:M 2237:1 2231:1 2225:m 2219:; 2216:0 2210:C 2204:N 2198:1 2192:1 2186:n 2180:1 2174:C 2151:m 2149:X 2128:g 2124:C 2115:m 2113:X 2101:n 2085:. 2079:) 2076:N 2073:( 2070:G 2065:) 2062:k 2056:N 2053:( 2050:G 2042:k 2037:i 2033:X 2027:N 2022:1 2019:= 2016:k 2008:= 2005:) 2000:i 1996:n 1992:( 1988:E 1975:i 1959:. 1953:) 1950:N 1947:( 1944:G 1938:N 1933:i 1929:X 1923:= 1920:) 1917:N 1914:= 1909:i 1905:n 1901:( 1897:P 1875:, 1872:1 1866:N 1863:, 1857:, 1854:1 1851:, 1848:0 1845:= 1842:k 1833:] 1830:) 1827:1 1821:k 1815:N 1812:( 1809:G 1804:i 1800:X 1793:) 1790:k 1784:N 1781:( 1778:G 1775:[ 1769:) 1766:N 1763:( 1760:G 1754:k 1749:i 1745:X 1739:= 1736:) 1733:k 1730:= 1725:i 1721:n 1717:( 1713:P 1689:N 1685:k 1683:- 1681:N 1676:i 1674:X 1670:k 1665:i 1663:n 1656:N 1652:N 1647:i 1645:X 1641:k 1637:i 1633:k 1628:i 1626:X 1621:i 1619:n 1612:M 1607:i 1605:n 1601:N 1596:i 1594:n 1590:k 1585:i 1583:n 1579:k 1575:i 1571:k 1566:i 1564:n 1552:N 1548:n 1544:i 1541:X 1537:n 1531:M 1527:m 1523:m 1512:m 1508:n 1503:m 1501:X 1490:M 1486:m 1482:N 1478:n 1471:M 1469:, 1467:N 1463:M 1459:N 1454:M 1452:X 1448:M 1444:N 1440:N 1433:N 1426:M 1424:, 1422:N 1418:N 1411:M 1407:N 1402:M 1400:X 1396:N 1391:M 1389:X 1382:M 1378:N 1370:M 1366:2 1362:1 1360:X 1356:m 1351:m 1347:2 1343:1 1341:X 1337:m 1333:m 1329:n 1317:N 1313:n 1309:M 1304:M 1300:2 1296:1 1294:X 1287:N 1283:M 1279:M 1274:M 1270:X 1263:N 1258:M 1254:X 1239:) 1234:M 1230:X 1226:( 1201:) 1196:M 1192:X 1188:( 1166:) 1161:M 1157:X 1153:( 1128:M 1124:n 1118:) 1113:M 1109:X 1105:( 1079:2 1075:n 1069:) 1064:2 1060:X 1056:( 1031:1 1027:n 1021:) 1016:1 1012:X 1008:( 994:N 982:N 968:) 963:M 959:n 955:, 949:, 944:2 940:n 936:, 931:1 927:n 923:( 919:P 894:) 888:1 882:M 877:1 871:M 868:+ 865:N 859:( 845:N 843:( 841:G 826:. 823:M 820:, 814:, 811:1 808:= 805:j 794:j 791:i 787:p 781:i 777:X 771:i 761:M 756:1 753:= 750:i 742:= 737:j 733:X 727:j 709:i 705:X 685:i 681:n 675:) 670:i 666:X 662:( 655:M 650:1 647:= 644:i 633:) 630:N 627:( 623:G 618:1 613:= 610:) 605:M 601:n 597:, 591:, 586:2 582:n 578:, 573:1 569:n 565:( 561:P 532:M 528:n 522:) 517:M 513:X 509:( 483:2 479:n 473:) 468:2 464:X 460:( 435:1 431:n 425:) 420:1 416:X 412:( 388:) 385:N 382:( 378:G 373:1 368:= 365:) 360:M 356:n 352:, 346:, 341:2 337:n 333:, 328:1 324:n 320:( 316:P 295:i 290:i 288:n 284:i 270:) 265:M 261:n 257:, 251:, 246:2 242:n 238:, 233:1 229:n 225:( 221:P 202:p 198:j 194:i 189:i 185:ÎŒ 177:i 173:N 169:M 157:N 144:N 140:N 136:M 118:) 112:1 106:M 101:1 95:M 92:+ 89:N 83:( 69:N 65:M 61:N 50:N 38:N

Index

queueing theory
theory of probability
normalization constant
Gordon–Newell theorem
Jeffrey P. Buzen
probability distribution
exponentially distributed
Gordon–Newell theorem
marginal distributions
expected
DTIC AD0731575: Queueing Network Models of Multiprogramming




Buzen, J. P.
"Computational algorithms for closed queueing networks with exponential servers"
doi
10.1145/362342.362345
S2CID
10702
the original


Newell, G. F.
Operations Research
doi
10.1287/opre.15.2.254
JSTOR
168557

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