110 research outputs found

    Performance analysis of a polling model with BMAP and across-queue state-dependent service discipline

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    As various video services become popular, video streaming will dominate the mobile data traffic. The H.264 standard has been widely used for video compression. As the successor to H.264, H.265 can compress video streaming better, hence it is gradually gaining market share. However, in the short term H.264 will not be completely replaced, and will co-exist with H.265. Using H.264 and H.265 standards, three types of frames are generated, and among different types of frames exist dependencies. Since the radio resources are limited, using dependencies and quantities of frames in buffers, an appropriate time division transmission policy can be applied to transmit different types of frames sequentially, in order to avoid the occurrence of video carton or decoding failure. Polling models with batch Markovian arrival process (BMAP) and across-queue state-dependent service discipline are considered to be effective means in the design and optimization of appropriate time division transmission policies. However, the BMAP and across-queue state-dependent service discipline of the polling models lead to the large state space and several coupled state transition processes, which complicate the performance analysis. There have been very few researches in this regard. In this paper, a polling model of this type is analyzed. By constructing a supplementary embedded Markov chain and applying the matrix-analytic method based on the semi-regenerative process, the expressions of important performance measures including the joint queue length distribution, the customer blocking probability and the customer mean waiting time are obtained. The analysis will provide inspiration for analyzing the polling models with BMAP and across-queue state-dependent service discipline, to guide the design and optimization of time division transmission policies for transmitting the video compressed by H.264 and H.265

    Performance Analysis for Bandwidth Allocation in IEEE 802.16 Broadband Wireless Networks using BMAP Queueing

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    This paper presents a performance analysis for the bandwidth allocation in IEEE 802.16 broadband wireless access (BWA) networks considering the packet-level quality-of-service (QoS) constraints. Adaptive Modulation and Coding (AMC) rate based on IEEE 802.16 standard is used to adjust the transmission rate adaptively in each frame time according to channel quality in order to obtain multiuser diversity gain. To model the arrival process and the traffic source we use the Batch Markov Arrival Process (BMAP), which enables more realistic and more accurate traffic modelling. We determine analytically different performance parameters, such as average queue length, packet dropping probability, queue throughput and average packet delay. Finally, the analytical results are validated numerically.Comment: 16 page

    Traffic modeling in mobile internet protocol : version 6.

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    Thesis (M.Sc.Eng.)-University of KwaZulu-Natal, Durban, 2005.Mobile Internet Protocol Version 6 (lPv6) is the new version of the Internet Protocol (IP) born out of the great success of Internet Protocol version 4 (IPv4). The motivation behind the development of Mobile IPv6 standard stems from user's demand for mobile devices which can connect and move seamlessly across a growing number of connectivity options. It is both suitable for mobility between subnets across homogenous and inhomogeneous media. The protocol allows a mobile node to communicate with other hosts after changing its point of attachment from one subnet to another. The huge address space available meets the requirements for rapid development of internet as the number of mobile nodes increases tremendously with the rapid expansion of the internet. Mobility, security and quality of service (QoS) being integrated in Mobile TPv6 makes it the important foundation stone for building the mobile information society and the future internet. Convergence between current network technologies: the intern et and mobile telephony is taking place, but the internet's IP routing was designed to work with conventional static nodes. Mobile IPv6 is therefore considered to be one of the key technologies for realizing convergence which enables seamless communication between fixed and mobile access networks. For this reason, there is numerous works in location registrations and mobility management, traffic modeling, QoS, routing procedures etc. To meet the increased demand for mobile telecommunications, traffic modeling is an important step towards understanding and solving performance problems in the future wireless IP networks. Understanding the nature of this traffic, identifying its characteristics and developing appropriate traffic models coupled with appropriate mobility management architectures are of great importance to the traffic engineering and performance evaluation of these networks. It is imperative that the mobility management used keeps providing good performance to mobile users and maintain network load due to signaling and packet delivery as low as possible. To reduce this load, Intemet Engineering Task Force (IETF) proposed a regional mobility management. The load is reduced by allowing local migrations to be handled locally transparent from the Home Agent and the Correspondent Node as the mobile nodes roams freely around the network. This dissertation tackles two major aspects. Firstly, we propose the dynamic regional mobility management (DRMM) architecture with the aim to minimize network load while keeping an optimal number of access routers in the region. The mobility management is dynamic based on the movement and population of the mobile nodes around the network. Most traffic models in telecommunication networks have been based on the exponential Poisson processes. This model unfortunately has been proved to be unsuitable for modeling busty IP traffic. Several approaches to model IP traffic using Markovian processes have been developed using the Batch Markovian Alrival Process (BMAP) by characterizing arrivals as batches of sizes of different distributions. The BMAP is constructed by generalizing batch Poisson processes to allow for non-exponential times between arrivals of batches while maintaining an underlying Markovian structure. The second aspect of this dissertation covers the traffic characterization. We give the analysis of an access router as a single server queue with unlimited waiting space under a non pre-emptive priority queuing discipline. We model the arrival process as a superposition of BMAP processes. We characterize the superimposed arrival processes using the BMAP presentation. We derive the queue length and waiting time for this type of queuing system. Performance of this traffic model is evaluated by obtaining numerical results in terms of queue length and waiting time and its distribution for the high and low priority traffic. We finally present a call admission control scheme that supports QoS

    ATM virtual connection performance modeling

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    Markovian arrivals in stochastic modelling: a survey and some new results

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    This paper aims to provide a comprehensive review on Markovian arrival processes (MAPs), which constitute a rich class of point processes used extensively in stochastic modelling. Our starting point is the versatile process introduced by Neuts (1979) which, under some simplified notation, was coined as the batch Markovian arrival process (BMAP). On the one hand, a general point process can be approximated by appropriate MAPs and, on the other hand, the MAPs provide a versatile, yet tractable option for modelling a bursty flow by preserving the Markovian formalism. While a number of well-known arrival processes are subsumed under a BMAP as special cases, the literature also shows generalizations to model arrival streams with marks, nonhomogeneous settings or even spatial arrivals. We survey on the main aspects of the BMAP, discuss on some of its variants and generalizations, and give a few new results in the context of a recent state-dependent extension.Peer Reviewe

    Forgalom modellezési módszerek fejlesztése = Advanced traffic modeling techniques

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    A projekt alapvetően sikeresen járult hozzá a vizsgált szakterület eredményeinek bővítéséhez és a résztvevő kutatócsoport fejlődéséhez. A projekt eredményihez kapcsolódó dolgozatok alapján PHD fokozatot szerzett Bodrog Levente és Saffer Zsolt. A projekt eredményeit összegző publikációk együttes impakt faktora ~22. A szakmai eredmenyek közül Markov érkezési folyamatok alapvető tulajdonságait összegző cikk (A minimal representation of Markov arrival processes and a moments matching method) emelhető ki, amelyik időközben az ezen folyamatok illesztési korlátait vizsgálló munkák alapjává vált. | The project successfully enhanced the field of traffic modeling of computer and communication systems and helped to improve the carrier of the involved research group. Based on the their theses summarizing parts of the results of the project Bodrog Levente and Saffer Zsolt were awarded the doctor of philosophy degree. The cumulated impact factor of the journal papers publish the research results of the project is about 22. The most remarkable research results are in the paper summarizing some basic properties of Markov arrival processes (A minimal representation of Markov arrival processes and a moments matching method), which become a basic reference for subsequent works dealing with the fitting properties of these processes

    Online QoS/Revenue Management for Third Generation Mobile Communication Networks

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    This thesis shows how online management of both quality of service (QoS) and provider revenue can be performed in third generation (3G) mobile networks by adaptive control of system parameters to changing traffic conditions. As a main result, this approach is based on a novel call admission control and bandwidth degradation scheme for real-time traffic. The admission controller considers real-time calls with two priority levels: calls of high priority have a guaranteed bit-rate, whereas calls of low priority can be temporarily degraded to a lower bit-rate in order to reduce forced termination of calls due to a handover failure. A second contribution constitutes the development of a Markov model for the admission controller that incorporates important features of 3G mobile networks, such as code division multiple access (CDMA) intra- and inter-cell interference and soft handover. Online evaluation of the Markov model enables a periodical adjustment of the threshold for maximal call degradation according to the currently measured traffic in the radio access network and a predefined goal for optimization. Using distinct optimization goals, this allows optimization of both QoS and provider revenue. Performance studies illustrate the effectiveness of the proposed approach and show that QoS and provider revenue can be increased significantly with a moderate degradation of low-priority calls. Compared with existing admission control policies, the overall utilization of cell capacity is significantly improved using the proposed degradation scheme, which can be considered as an 'on demand' reservation of cell capacity.To enable online QoS/revenue management of both real-time and non real-time services, accurate analytical traffic models for non real-time services are required. This thesis identifies the batch Markovian arrival process (BMAP) as the analytically tractable model of choice for the joint characterization of packet arrivals and packet lengths. As a key idea, the BMAP is customized such that different packet lengths are represented by batch sizes of arrivals. Thus, the BMAP enables the 'two-dimensional', i.e., joint, characterization of packet arrivals and packet lengths, and is able to capture correlations between the packet arrival process and the packet length process. A novel expectation maximization (EM) algorithm is developed, and it is shown how to utilize the randomization technique and a stable calculation of Poisson jump probabilities effectively for computing time-dependent conditional expectations of a continuous-time Markov chain required by the expectation step of the EM algorithm. This methodological work enables the EM algorithm to be both efficient and numerical robust and constitutes an important step towards effective, analytically/numerically tractable traffic models. Case studies of measured IP traffic with different degrees of traffic burstiness evidently demonstrate the advantages of the BMAP modeling approach over other widely used analytically tractable models and show that the joint characterization of packet arrivals and packet lengths is decisively for realistic traffic modeling at packet level
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