{"id":196,"date":"2021-03-19T14:20:57","date_gmt":"2021-03-19T05:20:57","guid":{"rendered":"https:\/\/orsj.org\/queue\/?page_id=196"},"modified":"2021-03-19T14:20:57","modified_gmt":"2021-03-19T05:20:57","slug":"quesym1995","status":"publish","type":"page","link":"https:\/\/orsj.org\/queue\/symposium\/quesym_history\/quesym1995\/","title":{"rendered":"1995\u5e74\u5ea6(\u7b2c14\u56de)\u5f85\u3061\u884c\u5217\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0"},"content":{"rendered":"<p>    <center><\/p>\n<h2>1995\u5e74\u5ea6\uff08\u7b2c14\u56de\uff09\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0<br \/>\n      &#8220;\u60c5\u5831\u901a\u4fe1\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306b\u95a2\u3059\u308b\u6027\u80fd\u8a55\u4fa1\u30e2\u30c7\u30eb\u306e\u7dcf\u5408\u7684\u7814\u7a76&#8221;<\/h2>\n<p>      \u65e5\u6642: 1996\u5e741\u670822-24\u65e5<br \/>\n      \u5834\u6240: \u4eac\u90fd\u30fb\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5d6f\u5ce8\u91ce\uff08\u4eac\u90fd\u5e9c\u52e4\u52b4\u8005\u7814\u4fee\u30bb\u30f3\u30bf\u30fc\uff09<br \/>\n      \u5370\u5237\u8cbb\u88dc\u52a9\uff1a\u79d1\u5b66\u7814\u7a76\u8cbb\u88dc\u52a9\u91d1 \u7dcf\u5408\u7814\u7a76 (A), \u8ab2\u984c\u756a\u53f7 07308029<br \/>\n      \u7814\u7a76\u4ee3\u8868\u8005: \u68ee \u96c5\u592b\uff08\u6771\u4eac\u5de5\u696d\u5927\u5b66\uff09<br \/>\n    <\/center><\/p>\n<hr>\n<ul>\n<li>MPEG \u7b26\u53f7\u5316\u3055\u308c\u305f\u52d5\u753b\u50cf\u30c8\u30e9\u30d2\u30c3\u30af\u306e\u30e2\u30c7\u30eb\u5316\u3068\u305d\u306e\u89e3\u6790<br \/>\n\t<br \/>\u6c38\u91ce \u9686\u6587\uff0c\u9ad8\u6a4b \u8c4a\uff0c\u9577\u8c37\u5ddd \u5229\u6cbb\uff08\u4eac\u90fd\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Performance Analysis of CSMA\/CA in Wireless Communication<br \/>\n\t<br \/>\u4e94\u5473 \u79c0\u4ec1\uff0c\u9ad8\u6a4b \u8c4a\uff0c\u9577\u8c37\u5ddd \u5229\u6cbb\uff08\u4eac\u90fd\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Performance Analysis of Fast Reservation Protocol with Generalize<br \/>\nBandwidth Reservation Method<br \/>\n\t<br \/>\u4e0b\u897f \u82f1\u4e4b\uff0c\u6edd\u6839 \u54f2\u54c9\uff0c\u6751\u7530 \u6b63\u5e78\uff0c\u5bae\u539f \u79c0\u592b\uff08\u5927\u962a\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Modeling of Heterogeneous Two-State Markov Process Based Traffic Sources<br \/>\n\t<br \/>\u6cb3\u6771 \u6674\u5b50\uff08\u4e09\u83f1\u96fb\u6a5f (\u682a)\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>ATM \u5e83\u57df\u7db2\u4e0a\u3067\u306e TCP\uff0fIP \u901a\u4fe1\u6027\u80fd\u306e\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u8a55\u4fa1<br \/>\n\t<br \/>\u77f3\u585a \u7f8e\u52a0\uff0c\u5317\u722a \u79c0\u96c4\uff0c\u5c0f\u6c60 \u65b0\uff08NTT\u901a\u4fe1\u7db2\u7814\u7a76\u6240\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Self-contained \u306a\u30b7\u30b9\u30c6\u30e0\u6027\u80fd\u8a55\u4fa1\u306e\u53ef\u80fd\u6027\u306b\u3064\u3044\u3066<br \/>\n\t<br \/>\u4e0b\u5ddd \u4fe1\u7950\uff08ATR\u5149\u96fb\u6ce2\u901a\u4fe1\u7814\u7a76\u6240\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>\u547c\u4eba\u30ab\u306e\u30d5\u30e9\u30af\u30af\u30eb\u6027\u3092\u7528\u3044\u305f\u30c8\u30e9\u30d2\u30c3\u30af\u4e88\u6e2c\u3068\u54c1\u8cea\u5236\u5fa1\u3078\u306e\u5fdc\u7528<br \/>\n\t<br \/>\u6642\u6c38 \u7965\u4e09\uff0c\u4e2d\u5cf6 \u5065\uff08\u4e5d\u5dde\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Modeling the Window Flow Control with Priority by Generalized Stochastic Petri Nets<br \/>\n\t<br \/>\u674e \u9821\uff0c\u4e80\u7530 \u58fd\u592b\uff08\u7b51\u6ce2\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Structured Markov Chains as a Result from the Synergy of Generalized Stochastic Petri Nets and Markovian Process Algebras<br \/>\n\t<br \/>Marco Tilgner\uff0c\u9ad8\u6a4b \u5e78\u96c4\uff08\u6771\u4eac\u5de5\u696d\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Sample Path Analysis for Two-Stage Tandem Queue and Its Application<br \/>\n\t<br \/>\u5ddd\u5cf6 \u6b66\uff0c\u4f50\u3005\u6728 \u4e00\u90ce\uff08\u9632\u885b\u5927\u5b66\u6821\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>On a Discrete-time Storage Process with the General State Space<br \/>\n\t<br \/>\u5927\u6ca2 \u79c0\u96c4\uff08\u611b\u77e5\u5b66\u6cc9\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Loss Probability Approximation of a Statistical Multiplexer and its Application to Call Admission Control in High-Speed Networks<br \/>\n\t<br \/>\u77f3\u5d0e \u6587\u96c4\uff08\u5fb3\u5cf6\u5927\u5b66\uff09\uff0c\u6edd\u6839 \u54f2\u54c9\uff0c\u5bfa\u7530 \u6d69\u8a54\uff08\u5927\u962a\u5927\u5b66\uff09, \u9577\u8c37\u5ddd \u5229\u6cbb\uff08\u4eac\u90fd\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Queueing Analysis of Alternating Traffic with a Signal Control and Starting Delays<br \/>\n\t<br \/> \u9234\u6728 \u8aa0\u9053\uff08\u4e0a\u667a\u5927\u5b66\uff09\uff0c\u5c71\u4e0b \u82f1\u660e\uff08\u99d2\u6fa4\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Rate Conservation Law Approach to Queueing Systems: A Tutorial<br \/>\n\t<br \/> \u9ad8\u6a4b \u656c\u9686\uff08NTT\u901a\u4fe1\u7db2\u7814\u7a76\u6240\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Some Basic Properties of the Cross Aggregation Method for Approximately Analyzing Acyclic Queueing Networks<br \/>\n\t<br \/> \u5e73\u4e95 \u529b\uff0c\u9ad8\u6a4b \u5e78\u96c4\uff08\u6771\u4eac\u5de5\u696d\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>An Optimal Maintenance Policy for a Server with Decreasing Arrival Rate<br \/>\n\t<br \/> \u5c0f\u67f3 \u6df3\u4e8c\uff0c\u6cb3\u5408 \u4e00\uff08\u9ce5\u53d6\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Symbolic Higher-Order Moments of the Waiting Time in an M\/G\/1 Queue with Random Order of Service<br \/>\n\t<br \/> \u9ad8\u6728 \u82f1\u660e\uff0c\u5de5\u85e4 \u8aa0\u4e5f\uff08\u7b51\u6ce2\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>A New Approach for Analyzing Multiclass M\/G\/1 Queues\u2212Mixture of the 1-limited Disciplines and the Gated Disciplines\u2212<br \/>\n\t<br \/> \u5e73\u5c71 \u54f2\u6cbb\uff08\u7b51\u6ce2\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>A Batch-Arrival Bound for the GI\/G\/1 Queue<br \/>\n\t<br \/> Ronald W\uff0eWolff\uff08\u6771\u4eac\u90fd\u7acb\u5927\u5b66 &#038; The University of California at Berkeley\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>\u96fb\u5b50\u7684\u60c5\u5831\u30cd\u30c3\u30c8\u30ef\u30fc\u30ad\u30f3\u30b0\u306e\u5168\u4f53\u69cb\u6210\u70cf\u77b0\u3068\u60c5\u5831\u30b5\u30fc\u30d3\u30b9\u7523\u696d\u306e\u6a5f\u80fd\u6bd4\u8f03<br \/>\n\t<br \/> \u5cf6\u5d0e \u8aa0\u5f66\uff08\u6771\u6d77\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>\u30af\u30e9\u30a4\u30a2\u30f3\u30c8\/\u30b5\u30fc\u30d0\u306e\u30a4\u30f3\u30d1\u30af\u30c8\u3068\u305d\u306e\u6027\u80fd\u8a55\u4fa1\u6cd5<br \/>\n\t<br \/> \u5927\u524d \u7fa9\u6b21\uff08\u795e\u5948\u5ddd\u5de5\u79d1\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>\u9ad8\u901f\u901a\u4fe1\u7db2\u306b\u304a\u3051\u308b\u3075\u304f\u305d\u3046\u5236\u5fa1\u306e Fairness \u306e\u8a55\u4fa1<br \/>\n\t<br \/> \u592a\u7530 \u6b63\u5b5d\uff08(\u682a)\u65e5\u7acb\u88fd\u4f5c\u6240\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>\u7db2\u8cc7\u6e90\u6709\u52b9\u5229\u7528\u306e\u305f\u3081\u306e\u7db2\u72b6\u614b\u901a\u77e5\u306b\u57fa\u3065\u304f\u30c8\u30e9\u30d2\u30c3\u30af\u8ca0\u8377\u5236\u5fa1<br \/>\n\t<br \/> \u4e2d\u6751 \u5143\uff0c\u6a2a\u5c71 \u6d69\u4e4b\uff0c\u5c0f\u7530 \u7a14\u5468\uff08KDD\u7814\u7a76\u6240\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>\u4e00\u822c\u5316\u30bb\u30df\u30de\u30eb\u30b3\u30d5\u904e\u7a0b\u3092\u7528\u3044\u305f\u591a\u6bb5\u751f\u7523\u30b7\u30b9\u30c6\u30e0\u306e\u6027\u80fd\u6bd4\u8f03<br \/>\n\t<br \/> \u4e2d\u51fa \u5eb7\u4e00\uff0c\u5927\u91ce \u52dd\u4e45\uff08\u540d\u53e4\u5c4b\u5de5\u696d\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Performance Analysis of a JIT Production System<br \/>\n\t<br \/> \u5c0f\u5cf6 \u8ca2\u5229\uff0c\u5927\u91ce \u52dd\u4e45\uff08\u540d\u53e4\u5c4b\u5de5\u696d\u5927\u5b66\uff09\uff0c\u4e2d\u5cf6 \u5065\u4e00\uff08\u5927\u962a\u5de5\u696d\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>\u7d44\u307f\u7acb\u3066\u578b\u5f85\u3061\u884c\u5217\u30b7\u30b9\u30c6\u30e0\u306e\u8fd1\u4f3c\u89e3\u6790<br \/>\n\t<br \/>\u5b8b \u5b87\uff08\u798f\u5ca1\u5de5\u696d\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>FMS \u306b\u304a\u3051\u308b AGV \u306e\u6700\u9069\u53f0\u6570\u6c7a\u5b9a\u554f\u984c\uff08\u6700\u9069\u53f0\u6570\u306e\u4e0b\u9650\uff09<br \/>\n\t<br \/>\u6607\u9ad8 \u8302\u6a39\uff0c\u5c71\u5d0e \u6e90\u6cbb\uff08\u6771\u4eac\u90fd\u7acb\u79d1\u5b66\u6280\u8853\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Birth-and-Death-Based Diffusion Approximations for Queues<br \/>\n\t<br \/>\u6728\u6751 \u4fca\u4e00\uff08\u5317\u6d77\u9053\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Exponential Decay of the Tail Probabilities in the Joint Queue-Lengths Distribution of Two-Stage Tandem Queues<br \/>\n\t<br \/>\u9ad8\u6a4b \u5e78\u96c4\uff0c\u7267\u672c \u76f4\u6a39\uff0c\u85e4\u672c \u8861\uff08\u6771\u4eac\u5de5\u696d\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Eigenvalue Expression for a Batch Markovian Arrival Process<br \/>\n\t<br \/>\u897f\u6751 \u5f70\u4e00\uff0c\u4f50\u85e4 \u5143\uff08\u6771\u4eac\u7406\u79d1\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>A Unified Analysis of the Queue Length Distributions in M(k)<sup>X<\/sup>\/G\/1\/N and GI\/M(k)<sup>Y<\/sup>\/1\/N Queues<br \/>\n\t<br \/>\u99ac\u5834 \u88d5\uff08\u6a2a\u6d5c\u56fd\u7acb\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>\u5171\u7528\u578b\u51fa\u529b\u30d0\u30c3\u30d5\u30a1\u306e\u30d1\u30b1\u30c3\u30c8\u5ec3\u68c4\u7387\u8fd1\u4f3c\u89e3\u6790\u6cd5<br \/>\n\t<br \/>\u5c0f\u6ca2 \u5229\u4e45\uff0c\u671d\u9999 \u5353\u4e5f\uff08NTT\u901a\u4fe1\u7db2\u7814\u7a76\u6240\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>\u30bb\u30eb\u30e9\u30fc\u901a\u4fe1\u30b7\u30b9\u30c6\u30e0\u306e\u6027\u80fd\u8a55\u4fa1\u30e2\u30c7\u30eb<br \/>\n\t<br \/>\u5742\u5dfb \u8ce2\u4e00\uff0c\u9ad8\u6728 \u82f1\u660e\uff08\u7b51\u6ce2\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>N-ISDN \u306b\u304a\u3051\u308b D \u30c1\u30e4\u30cd\u30eb\u30a2\u30af\u30bb\u30b9\u7af6\u5408\u5236\u5fa1\u65b9\u5f0f\u306e\u6027\u80fd\u8a55\u4fa1<br \/>\n\t<br \/>\u67f3\u751f \u5fc3\u5e73\uff0c\u9ad8\u6728 \u82f1\u660e\uff08\u7b51\u6ce2\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Data Analysis and Modeling of ATM Coded Video Traffic with Scene Changes<br \/>\n\t<br \/>\u8535\u6749 \u4fca\u5eb7\uff08\u6771\u4eac\u5de5\u696d\u5927\u5b66\uff09\uff0c\u5c0f\u6797 \u548c\u671d\uff08NEC C&#038;C \u7814\u7a76\u6240\uff09\uff0c\u9ad8\u6a4b \u5e78\u96c4\uff08\u6771\u4eac\u5de5\u696d\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>\u3042\u308b\u4fe1\u983c\u6027\u30b7\u30b9\u30c6\u30e0\u306b\u5bfe\u3059\u308b\u4fee\u7406\u9650\u754c\u53d6\u66ff\u3048\u653f\u7b56\u306e\u6700\u9069\u6027<br \/>\n\t<br \/>\u702c\u5ddd \u826f\u4e4b\uff08\u4eac\u90fd\u5b66\u5712\u5927\u5b66\uff09\uff0c\u5927\u897f \u5321\u5149\uff08\u6771\u5317\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Stack Distance Distribution in LRU<br \/>\n\t<br \/>\u7d00 \u4e00\u8aa0\uff0c\u7530\u4e2d \u6df3\u88d5\uff08NEC C&#038;C \u7814\u7a76\u6240\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>\u30de\u30eb\u30b3\u30d5\u904e\u7a0b\u3068\u5438\u53ce\u904e\u7a0b<br \/>\n\t<br \/>\u4e2d\u585a \u5229\u76f4\uff08\u6771\u4eac\u90fd\u7acb\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>GSMP \u306e\u69cb\u9020\u7684\u53ef\u9006\u6027<br \/>\n\t<br \/>\u8c37 \u6cf0\u5e83\uff0c\u4e38\u5c71 \u731b\uff0c\u5bae\u6ca2 \u653f\u6e05\uff08\u6771\u4eac\u7406\u79d1\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>\u30a4\u30f3\u30dd\u30fc\u30bf\u30f3\u30b9\u30b5\u30f3\u30d7\u30ea\u30f3\u30b0\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u6cd5\u306b\u304a\u3051\u308b\u6700\u9069\u30b7\u30df\u30e5\u30ec\u30fc\u30b7\u30e7\u30f3\u5206\u5e03\u306e\u5c0e\u51fa<br \/>\n\t<br \/>\u5c0f\u5ddd \u8015\u53f8, \u4e2d\u5ddd \u5065\u6cbb\uff08\u9577\u5ca1\u6280\u8853\u79d1\u5b66\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Perturbation Analysis for a Discrete-Time Stationary Queue<br \/>\n\t<br \/>\u5800\u90e8 \u5927\u53f8, \u4e09\u597d \u76f4\u4eba\uff08\u4eac\u90fd\u5927\u5b66\uff09\n\t<\/ul>\n<\/p>\n<ul>\n<li>Sensitivity Estimation of the Loss Rate in a Stationary Gradual Input Queue for ATM Networks<br \/>\n\t<br \/>\u5c71\u7530 \u4f73\u5ee3, \u4e09\u597d \u76f4\u4eba\uff08\u4eac\u90fd\u5927\u5b66\uff09\n\t<\/ul><\/p>\n","protected":false},"excerpt":{"rendered":"<p>1995\u5e74\u5ea6\uff08\u7b2c14\u56de\uff09\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0 &#8220;\u60c5\u5831\u901a\u4fe1\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306b\u95a2\u3059\u308b\u6027\u80fd\u8a55\u4fa1\u30e2\u30c7\u30eb\u306e\u7dcf\u5408\u7684\u7814\u7a76&#8221; \u65e5\u6642: 1996\u5e741\u670822-24\u65e5 \u5834\u6240: \u4eac\u90fd\u30fb\u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u5d6f\u5ce8\u91ce\uff08\u4eac\u90fd\u5e9c\u52e4\u52b4\u8005\u7814\u4fee\u30bb\u30f3\u30bf\u30fc\uff09  [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":24,"menu_order":43,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_mc_calendar":[]},"_links":{"self":[{"href":"https:\/\/orsj.org\/queue\/wp-json\/wp\/v2\/pages\/196"}],"collection":[{"href":"https:\/\/orsj.org\/queue\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/orsj.org\/queue\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/orsj.org\/queue\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/orsj.org\/queue\/wp-json\/wp\/v2\/comments?post=196"}],"version-history":[{"count":3,"href":"https:\/\/orsj.org\/queue\/wp-json\/wp\/v2\/pages\/196\/revisions"}],"predecessor-version":[{"id":235,"href":"https:\/\/orsj.org\/queue\/wp-json\/wp\/v2\/pages\/196\/revisions\/235"}],"up":[{"embeddable":true,"href":"https:\/\/orsj.org\/queue\/wp-json\/wp\/v2\/pages\/24"}],"wp:attachment":[{"href":"https:\/\/orsj.org\/queue\/wp-json\/wp\/v2\/media?parent=196"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}