“��€‚‹…�ˆ… �Ž‹œ˜ˆŒˆ ‘ˆ‘’…Œ€Œˆ
íà ãëàâíóþ íàïèñàòü ïèñüìî êàðòà ñàéòà


Àâòîð:  Ìîèñååâà Ñ.Ï., Ïàíêðàòîâà Å.Â.
Íàçâàíèå:  Àñèìïòîòè÷åñêèé àíàëèç ìíîãîïîòî÷íîé ãåòåðîãåííîé ÑÌÎ â óñëîâèè ïðåäåëüíî ðåäêèõ èçìåíåíèé ñîñòîÿíèé óïðàâëÿþùåé âõîäÿùèìè ïîòîêàìè öåïè Ìàðêîâà
Âûïóñê:  112
Ðóáðèêà:  Ñèñòåìíûé àíàëèç
Ãîä:  2024
Áèáëèîãðàôèÿ:  Ìîèñååâà Ñ.Ï., Ïàíêðàòîâà Å.Â. Àñèìïòîòè÷åñêèé àíàëèç ìíîãîïîòî÷íîé ãåòåðîãåííîé ÑÌÎ â óñëîâèè ïðåäåëüíî ðåäêèõ èçìåíåíèé ñîñòîÿíèé óïðàâëÿþùåé âõîäÿùèìè ïîòîêàìè öåïè Ìàðêîâà // Óïðàâëåíèå áîëüøèìè ñèñòåìàìè. - 2024. - Âûï. 112. - Ñ.30-44.
Êëþ÷åâûå ñëîâà:  ìàðêîâñêè ìîäóëèðîâàííûå ïóàññîíîâñêèå ïîòîêè, àñèìïòîòè÷åñêèé àíàëèç, ïðåäåëüíî ðåäêèå èçìåíåíèÿ ñîñòîÿíèé öåïè Ìàðêîâà
Êëþ÷åâûå ñëîâà (àíãë.):  Markov modulated Poisson flows, asymptotic analysis, extremely rare changes in the states of a Markov chain
Àííîòàöèÿ:  Â íàñòîÿùåå âðåìÿ ìíîãîìîäàëüíûå ñèñòåìû íàáèðàþò ïîïóëÿðíîñòü ñ ðàçâèòèåì ìíîãîìîäàëüíûõ èíòåðôåéñîâ. Ìíîãîìîäàëüíûå ïîòîêè ïðåäñòàâëÿþò ñîáîé èíòåãðèðîâàííûå ðàçíîòèïíûå ïîòîêè, âêëþ÷àþùèå ïåðåäà÷ó ãîëîñà, òåêñòîâûõ äàííûõ è âèäåî, ïîýòîìó äëÿ èõ îïèñàíèÿ ëîãè÷íî ïðèìåíÿòü íåïóàññîíîâñêèå ìîäåëè.  êà÷åñòâå ìàòåìàòè÷åñêîé ìîäåëè ìíîãîìîäàëüíîé îáñëóæèâàþùåé ñèñòåìû ðàññìàòðèâàåòñÿ ìíîãîïîòî÷íàÿ ñèñòåìà ìàññîâîãî îáñëóæèâàíèÿ ñ ïîòîêàìè, ìåíÿþùèìè ñâîþ èíòåíñèâíîñòü â çàâèñèìîñòè îò ñîñòîÿíèé ìàðêîâñêîé ñëó÷àéíîé ñðåäû. Ïîñòóïàþùèå òðåáîâàíèÿ ðàçëè÷íûõ ïîòîêîâ îáñëóæèâàþòñÿ â òå÷åíèè ýêñïîíåíöèàëüíî ðàñïðåäåëåííîãî ñëó÷àéíîãî âðåìåíè ñ ïàðàìåòðàìè, îïðåäåëÿåìûìè òèïîì ïîòîêà. Ñòàâèòñÿ çàäà÷à èññëåäîâàíèÿ ìíîãîìåðíîãî ìàðêîâñêîãî ïðîöåññà ÷èñëà çàíÿòûõ ïðèáîðîâ â ñèñòåìå â ñòàöèîíàðíîì ðåæèìå. Èñïîëüçóÿ ñâîéñòâà õàðàêòåðèñòè÷åñêèõ ôóíêöèé, ïîëó÷åíû âûðàæåíèÿ äëÿ íàõîæäåíèÿ äîïðåäåëüíûõ çíà÷åíèé îñíîâíûõ âåðîÿòíîñòíûõ õàðàêòåðèñòèê ÷èñëà çàíÿòûõ ïðèáîðîâ êàæäîãî òèïà. Àñèìïòîòè÷åñêîå èññëåäîâàíèå ïðîâîäèòñÿ â óñëîâèè ïðåäåëüíî ðåäêèõ èçìåíåíèé ñîñòîÿíèé ñðåäû. Ïîëó÷åí âèä ìíîãîìåðíîé àñèìïòîòè÷åñêîé õàðàêòåðèñòè÷åñêîé ôóíêöèè. Ïîëó÷åííîå àñèìïòîòè÷åñêîå ðàñïðåäåëåíèå ÿâëÿåòñÿ ìíîãîìîäàëüíûì, òàê êàê èìååò íåñêîëüêî ëîêàëüíûõ ìàêñèìóìîâ, ÷òî èìååò ïðèíöèïèàëüíîå çíà÷åíèå äëÿ ïðèìåíåíèÿ ðåçóëüòàòîâ íà ïðàêòèêå. Äîêàçàíî, ÷òî îäíîìåðíûå (ìàðãèíàëüíûå) ñòàöèîíàðíûå ðàñïðåäåëåíèÿ âåðîÿòíîñòåé ÷èñëà çàíÿòûõ ïðèáîðîâ êàæäîãî òèïà ÿâëÿþòñÿ âçâåøåííûìè ñóììàìè ïóàññîíîâñêèõ ðàñïðåäåëåíèé. Ïðîâåäåí ÷èñëåííûé àíàëèç îáëàñòè ïðèìåíèìîñòè ïîëó÷åííîé àïïðîêñèìàöèè.
Àííîòàöèÿ (àíãë.):  Currently, multimodal systems are gaining popularity with the development of multimodal interfaces. Multimodal streams are integrated streams of different types, including the transmission of voice, text data and video, so it is logical to use non-Poisson models to describe them. As a mathematical model of a multimodal servicing system, a multi-threaded heterogeneous queuing system with flows changing their intensity depending on the states of the Markov random environment is considered. Incoming requests from various flows are serviced during an exponentially distributed random time with parameters determined by the type of flow. Expressions are obtained for finding the maximum values of the main probabilistic characteristics of the number of occupied devices of each type. Asymptotic research is carried out under the condition of extremely rare changes in the states of the environment. The form of the multidimensional asymptotic characteristic function is obtained. It is proven that one-dimensional (marginal) stationary probability distributions of the number of occupied devices of each type are weighted sums of Poisson distributions. A numerical analysis of the range of applicability of the obtained approximation was carried out.

â ôîðìàòå PDF

Ïðîñìîòðîâ: 732, çàãðóçîê: 447, çà ìåñÿö: 7.

Íàçàä

ÈÏÓ ÐÀÍ © 2007. Âñå ïðàâà çàùèùåíû