Performance Analysis of Multi-Channel and Multi-Traffic on Wireless Communication Networks

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Delay-throughput analysis of multi-channel MAC protocols in ad hoc networks

Du kanske gillar. Spara som favorit. Skickas inom vardagar. Laddas ned direkt. With the rapidly increasing penetration of laptop computers and mobile phones, which are primarily used by mobile users to access Internet s- vices like e-mail and World Wide Web WWW access, support of Internet services in a mobile environment is an emerging requirement. Wireless n- works have been used for communication among fully distributed users in a multimedia environment that has the needs to provide real-time bursty traffic such as voice or video and data traffic with excellent reliability and service quality.

To satisfy the huge wireless multimedia service demand and improve the system performance, efficient channel access methods and analytical methods must be provided. In this way very accurate models, that faithfully reproduce the stochastic behavior of multimedia wireless communication and computer networks, can be constructed. Most of these system models are discrete-time queueing systems. Queueing networks and Markov chains are commonly used for the p- formance and reliability evaluation of computer, communication, and m- ufacturing systems. Although there are quite a few books on the individual topics of queueing networks and Markov chains, we have found none that covers the topics of discrete-time and continuous-time multichannel mul- traffic queueing networks.

On the other hand, the design and development of multichannel mul- hop network systems and interconnected network systems or integrated n- works of multimedia traffic require not only such average performance m- sures as the throughput or packet delay but also higher moments of traffic departures and transmission delay.

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Passar bra ihop. Bloggat om Performance Analysis of Multi-Channel and There are two forms of traffic engineering: online planning and offline planning. Offline traffic engineering simultaneously examines each channel's resource constraints and the requirements of each Local Service Provider LSP to provide global calculations and solutions for the communication networks in a centralized view.

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We develop stochastic traffic engineering optimization models focusing on both the random traffic demand and the network performance optimization, such as loss rate and network risk management. By using mean-variance approach and conditional Value-at-Risk, we study the impact of risk averseness on the network profit function and introduce a penalty cost in the optimization model for network bandwidth allocation. We give numerical results to show the impacts of relationship between the revenue and the cost, loss rate constraint and risk averseness on the network performance.

In our researches, we present new methodologies for discounted Markov decision processes MDPs. This is to reduce the scale of MDPs models based on action reduction and state decomposition. The idea of the action reduction is that an action can be eliminated if any policy use it would not be optimal. The main ideas about the state decomposition are that we decompose the state space of the model into several sub-spaces.

In each subspace, we know an optimal policy or we can easily solve the MDPs model. The purpose to reduce the scale of MDPs model is mainly to separate the case with finite optimal value from the cases with positive or negative infinite optimal value, and then we can just study the case with finite optimal value. By using these methodologies above, we study discrete time MDPs models and continuous time MDPs models with the discounted criterion under the necessary condition. We also present new optimal control problems for discrete event systems and study them by using these methodologies and study optimal replacement problems in stochastic environments.

What are the most interesting unsolved problems in the optimization branch you are working on:. The three entities that are the main important points to traffic analysis and design are external traffic load, engineered resources, and observed performance.

Antonio's Publications

Given the amount of resources and the traffic load, we should evaluate the system performance such as channel utilization, throughput, packet delay, call blocking, and high moments about traffic characters. The random service demands and multimedia service demands complicate mobile wireless communication systems to process traffic loads.

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In mobile wireless communication networks, several multimedia sources are statistically multiplexed over the network links with user mobility and user's random multi-traffic demand. Efficient channel access protocols must be employed to utilize the limited spectrum among all the mobiles efficiently.


Wireless communication system designers need methods for the quantification of system design factors such as performance and reliability. We usually want to know which network protocol gives the best delay throughput characteristic under specified conditions, how coefficients of variation of the packet delay and the packet interdeparture time change with the offered traffic load, what size buffers must be employed by a network to keep the probability of buffer overflow below a particular value, and what is the maximum number of voice calls that can be accepted by a network in order to keep the voice packet transfer delay within reasonable bounded, what is the optimal network performance and so on.

We can answer these and other related questions for the wireless communication networks by developing queueing models and Markovian models, and then analyze these models to obtain such performance measures and offer numerical results for network performance optimization.

Bibliographic Information

Probabilistic and statistical methods are commonly employed for the purpose of performance and reliability evaluation. The most direct method for performance evaluation is based on actual measurement of the system under study. However during the design phase the system is not available for such experiments and yet performance of a given design needs to be predicted to verify that it meets design requirements and to carry out necessary trade-offs.

Hence abstract models are necessary for performance prediction of designs. On the other hand, mobile wireless communications with the demand for voice, Internet, and multimedia services for fixed and mobile user have a bright future. We would like to suggest several important future research topics for wireless communication networks. We offer some discussions as to the kinds of wireless communication systems that will emerge over the next few year and our considerations on the model and methodology for these wireless communication systems.

Performance optimization problems arising in the study of telecommunication networks basically consist of two components: traffic modeling and queuing analysis. Traffic is the driving force behind all telecommunications activity, and its models are of crucial importance for evaluating network performance.

Probability models for traffic streams are needed to the extent that they allow prediction of system performance measures to a reasonable degree of accuracy. However, traffic modeling and queuing analysis based on traditional Poisson arrival and exponential call holding time assumptions, which have performed successfully in the design and analysis of circuit-switched telephone networks, are no longer valid for high-speed packet-switched networks carrying LAN-to-LAN data, compressed video, and so on with considering the use mobility and multi-hop.

In most cases where very complex queuing models are encountered, we believe that our performance analysis methods will be successfully employed and sometimes preferred to analysis due to the intractability of such models and will be useful for performance optimization of next generation wireless communication network systems. What kinds of topics excite your research interests? Performance optimization and performance evaluation are key tools in reliable networks operation, and for managing network services.

Resource control algorithm in high-speed communication networks is a resource-sharing policy. Resource control of large-scale communications networks involves making decisions on the type of network: centralized or distributed; type of communication network architecture; type of switching: circuit switching or packet switching; type of routing: static or dynamic; and type of network control and monitoring: centralized or distributed.

Given node locations and peak traffic demand, user mobility, variables such as topology, link capacities, routing policy must be considered. Each constraint of link capacity, node capacity and delay, then must also be considered to minimize total network cost, call blocking probability, packet delay or maximize the network utilization.

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  • Due to its widespread applications, network optimization is an important subfield within the broad field of optimization. Our researches are still related to communication network optimization problems: maximum network utilization , shortest-path problem, minimum-cost single-commodity flow problem and minimum-cost multicommodity flow problem. These applications are intended to illustrate a range of problem contexts and to be suggestive of how network optimization problems arise in practice. How did you develop these interests?

    What would you say is one of the most interesting topics you have studied? Still another problem is the routing of traffic on the network.

    Performance Analysis of Multi-Channel and Multi-Traffic on Wireless Communication Networks

    In a resource-sharing communication environment, transmission route choice models or transmission assignment models aim to describe traffic resources on communication networks, which operate at known switches. The route choice models or traffic assignment models are also resource control problems with a waiting phenomenon: traffic experiences a waiting time for the switch of the line on which traffic is chosen.

    The modeling of such communication networks is taken to be the minimization of expected waiting and transmission time, or the expected total generalized cost if waiting times and transmission times may have different weights. Given potential sites for network node location, traffic data, and available link types and their cost, the lowest-cost local access network configuration must be obtained considering optimum variables.

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    That being a network with an optimum number of network nodes and their locations, optimum set of links interconnecting the network nodes, their capacities, routing paths, subject to constraints on delay, throughput, reliability and link capacity. To round off the interview, what are some highlights of your career?

    W ireless communication network systems with the demand for voice, Internet, and multimedia services for fixed and mobile user have a bright future.