1,572 research outputs found

    Learning algorithms for the control of routing in integrated service communication networks

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    There is a high degree of uncertainty regarding the nature of traffic on future integrated service networks. This uncertainty motivates the use of adaptive resource allocation policies that can take advantage of the statistical fluctuations in the traffic demands. The adaptive control mechanisms must be 'lightweight', in terms of their overheads, and scale to potentially large networks with many traffic flows. Adaptive routing is one form of adaptive resource allocation, and this thesis considers the application of Stochastic Learning Automata (SLA) for distributed, lightweight adaptive routing in future integrated service communication networks. The thesis begins with a broad critical review of the use of Artificial Intelligence (AI) techniques applied to the control of communication networks. Detailed simulation models of integrated service networks are then constructed, and learning automata based routing is compared with traditional techniques on large scale networks. Learning automata are examined for the 'Quality-of-Service' (QoS) routing problem in realistic network topologies, where flows may be routed in the network subject to multiple QoS metrics, such as bandwidth and delay. It is found that learning automata based routing gives considerable blocking probability improvements over shortest path routing, despite only using local connectivity information and a simple probabilistic updating strategy. Furthermore, automata are considered for routing in more complex environments spanning issues such as multi-rate traffic, trunk reservation, routing over multiple domains, routing in high bandwidth-delay product networks and the use of learning automata as a background learning process. Automata are also examined for routing of both 'real-time' and 'non-real-time' traffics in an integrated traffic environment, where the non-real-time traffic has access to the bandwidth 'left over' by the real-time traffic. It is found that adopting learning automata for the routing of the real-time traffic may improve the performance to both real and non-real-time traffics under certain conditions. In addition, it is found that one set of learning automata may route both traffic types satisfactorily. Automata are considered for the routing of multicast connections in receiver-oriented, dynamic environments, where receivers may join and leave the multicast sessions dynamically. Automata are shown to be able to minimise the average delay or the total cost of the resulting trees using the appropriate feedback from the environment. Automata provide a distributed solution to the dynamic multicast problem, requiring purely local connectivity information and a simple updating strategy. Finally, automata are considered for the routing of multicast connections that require QoS guarantees, again in receiver-oriented dynamic environments. It is found that the distributed application of learning automata leads to considerably lower blocking probabilities than a shortest path tree approach, due to a combination of load balancing and minimum cost behaviour

    Simulation and analysis of adaptive routing and flow control in wide area communication networks

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    This thesis presents the development of new simulation and analytic models for the performance analysis of wide area communication networks. The models are used to analyse adaptive routing and flow control in fully connected circuit switched and sparsely connected packet switched networks. In particular the performance of routing algorithms derived from the L(_R-I) linear learning automata model are assessed for both types of network. A novel architecture using the INMOS Transputer is constructed for simulation of both circuit and packet switched networks in a loosely coupled multi- microprocessor environment. The network topology is mapped onto an identically configured array of processing centres to overcome the processing bottleneck of conventional Von Neumann architecture machines. Previous analytic work in circuit switched work is extended to include both asymmetrical networks and adaptive routing policies. In the analysis of packet switched networks analytic models of adaptive routing and flow control are integrated to produce a powerful, integrated environment for performance analysis The work concludes that routing algorithms based on linear learning automata have significant potential in both fully connected circuit switched networks and sparsely connected packet switched networks

    Modelling adaptive routing in Wide Area Networks

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    Bibliography: leaves 132-138.This study investigates the modelling of adative routing algorithms with specific reference to the algorithm of an existing Wide Area Network (WAN). Packets in the network are routed at each node on the basis of routing tables which contain internal and external delays for each route from the node. The internal delay on a route represents the time that packets queued for transmission will have to wait before being transmitted, while the external delay on a route represents the delay to other nodes via that route. Several modelling methods are investigated and compared for the purpose of identifying the most appropriate and applicable technique. A model of routing in the WAN using an analytic technique is described. The hypothesis of this study is that dynamic routing can be modelled as a sequence of models exhibiting fixed routing. The modelling rationale is that a series of analytic models is run and solved. The routing algorithm of the WAN studied is such that, if viewed at any time instant, the network is one with static routing and no buffer overflow. This characteristic, together with a real time modelling requirement, influences the modelling technique which is applied. Each model represents a routing update interval and a multiclass open queueing network is used to solve the model during a particular interval. Descriptions of the design and implementation of X wan, an X Window based modelling system, are provided. A feature of the modelling system is that it provides a Graphical User Interface (GUI), allowing interactive network specification and the direct observation of network routing through the medium of this interface. Various applications of the modelling system are presented, and overall network behaviour is examined. Experimentation with the routing algorithm is conducted, and (tentative) recommendations are made on ways in which network performance could be improved. A different routing algorithm is also implemented, for the purpose of comparison and to demonstrate the ease with which this can be affected

    Proceedings of the Second International Mobile Satellite Conference (IMSC 1990)

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    Presented here are the proceedings of the Second International Mobile Satellite Conference (IMSC), held June 17-20, 1990 in Ottawa, Canada. Topics covered include future mobile satellite communications concepts, aeronautical applications, modulation and coding, propagation and experimental systems, mobile terminal equipment, network architecture and control, regulatory and policy considerations, vehicle antennas, and speech compression
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