This thesis is devoted to the study of different stochastic processes which have a common feature: they are Markov-modulated, which means that their evolution rules depend on the state occupied by an underlying Markov process. In the first part of this thesis, we analyse the stationary distribution and various first passage problems for Markov-modulated Brownian motions (MMBMs) as well as for two extensions: MMBMs with jumps and MMBMs modified by a temporary change of regime upon visits to level zero. The second part of this thesis is devoted to the use of Markov-modulated processes in mathematical finance, more precisely for the calculation of different option prices. We use a Fourier transform approach to price different European options (vanilla, exchange and quanto options) in the case where the value of the considered risky assets evolves like the exponential of a Markov-modulated Lévy process. The third part of this thesis is devoted to the study of some stochastic epidemic processes, namely the SIR processes. In our models, a Markov process is used to modulate the behaviour of the individuals who bring the disease. We use different martingale approaches as well as matrix analytic methods to obtain various information about the state of the population when the epidemic is over. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

"A distributed queueing Medium Access Control (MAC) protocol is used in Distributed Queue Dual Bus (DQDB) networks. A modified version of the MAC protocol was proposed by R.R. Pillai and U. Mukherji in an attempt to overcome some of the shortcomings of the DQDB MAC protocol. They analyzed the performance of the system for Bernoulli arrivals and for large propagation delays between the nodes. We extend the performance analysis of the modified MAC protocol for a DQDB type of Network. The parameter of interest to us is the bus access delay. This has two components, viz., the request bus access delay and the data bu6 access delay. We use the model at the request point at node and present methods to evaluate the delay experienced in such a model. The model is an n-priority ./D/l queue with D vacations (non-preemptive priority) where n is the number of nodes sending requests on the request bus for transmission on the data bus. The methods presented help to evaluate the request bus access delay when the arrivals at each node are Markovian Arrival Processes (MAPs). The algorithms for evaluating the mean request bus access delay are based on matrix geometric techniques. Thus, one can use the algorithms developed in the literature to solve for the finite buffers case too. This model, for the request bus access delay, holds irrespective of the propagation delay between the nodes. We also evaluate the inter-departure time of class 1 customers and virtual customers in a 2-priority M/G/l system with G vacations (non-preemptive priority). In the case of Poisson arrivals at all the nodes, we would have a 2-priority M/D/l system with D vacations (non-preemptive priority). We thus evaluate the inter-arrival time of the free slots on the data bus as seen by Node 2. Note that this is independent of the number of active nodes in the network We then develop methods to evaluate the mean data bus access delay experienced by the customers at Node 2 in a three-node network with 2 nodes communicating with the third when the propagation delay between the nodes is large. We consider the case of finite Local Queue buffers at the two nodes. Using this assumption we arrive at process of arrivals to the Combined Queue and the process of free slots on the data bus to be Markov Modulated Bernoulli processes. The model at the combined queue at Node 2 then has a Quasi Birth-Death evolution. Thus, this system is solved by using the Ramaswami-Latouche algorithm. The stationary probabilities are then used to evaluate the mean data bus access delay experienced at Node 2. The finite buffer case of this system can be solved by G.Wi Stewart's algorithm. The method in modelling the system and the results are presented in detail for Poisson arrivals. The extension of this to more complex processes is also explained. We encounter in the analysis an explosion of the state-space of the system. We try to counter this by considering approximations to the process of free slots on the data bus. The approximations considered are on the basis of what are known as Idealized Aggregates. The performance of the approximation is also detailed. It works very well under low and moderate load but underestimates the mean delay under heavy load. Thereafter, we discuss the performance of the system with reference to the mean of the access delay and the standard deviation of the access delay under varying traffic at the two nodes. For this part we use simulation results to discuss the performance. The comparison between the performance measures at both the nodes is also done. Then we develop methods/techniques to understand the performance of the system when we have finite propagation delays between the nodes. We concentrate on the 3-node problem and calculate performance bounds based on linear programs. This is illustrated in detail for Bernoulli arrivals for the case of 1 slot propagation delay between the nodes as well as for the case of 2 slots propagation delay. The performance of the bounds obtained is also detailed. The presence of an idling system at the combined queue of Node 2 makes the bounds somewhat loose. Finally, we discuss the performance of the system with reference to the mean access delay and the standard deviation of the access delay under varying load on the system. Again, we rely on simulation studies. Finally, we study the performance of the system as a multiplexer. For this, we re­strict the traffic to Markov Modulated Processes (or those which would satisfy the Gartner-Ellis Theorem requirements). The traffic is characterized by what are known as Envelope Processes - Lower and Upper. The class of processes which satisfy the conditions of the Gartner-Ellis theorem come under the category where both the Envelope Processes exist and the Minimum Envelope Rate and the Maximum Lower Envelope Rate are the same. We use the system evolution equations at the combined queue at any node to develop re­lations between the various input and output processes. First, this is done for a. system of this kind, in isolation. Then, we consider this system as a part of the modified protocol and present relations, among the various input and output processes, which are specific to the modified protocol. The possible use of all of the above to do Admission Control at the entry point to the Asynchronous Transfer Mode (ATM) network is also presented.