Computer Science

Data transmission in multimedia WSNs are required high bandwidth and reliable transfer because of large amount of data size. However, some applications of WSNs are required high quality. In this context, main factor in quality of services (QoS) metrics in WSNs becomes longevity of the network and high quality. In sensor nodes, choosing relevant transceiver and microcontroller components plays important role in assembling sensor devices, in which data controls should be designed so that packet loss is minimized. Available QoS metrics based on queuing/buffer management in wired and other wireless networks don't applicable in WSNs because of its unique characteristics. In this paper the simplest model of QoS model-bufferless system were proposed. In the proposed model, measurement of the probability of blocking of the arrival packets was suggested by using queuing theory in order to increase QoS. Given probability of blocking (PB) illustrates clear picture how system specification should be chosen so that blocking state would be minimized.

A Markov model of two stage queuing network with feedback is proposed. Poisson flows arriving to both stages from outside and part of already serviced calls in the first node instantaneously enter to the second node (if there is free space here) while the remaining part leaves the network. At the completion of call processing in the second node there are three possibilities: (1) it leaves the network; (2) it instantaneously feeds back to the first node (if there is free space here); (3) it feeds back to the first node after some delay in orbit. All feedbacks are determined by known probabilities. Both nodes have finite capacities. The mathematical model of the investigated network is a three dimensional Markov chain (3-D MC) and hierarchical space merging algorithm to calculate its steady-state probabilities is developed. This algorithm allows asymptotic analysis of the quality of service (QoS) metrics of the investigated network as well.

The authors propose a model of queueing-inventory system with perishable inventory and server vacations in which service times are positive random quantities. Server takes vacations if either inventory level is zero or queue is empty or both cases happen. At the end of vacation, server immediately starts serving the calls if inventory level is not zero; otherwise it takes new vacation. Calls in the queue are impatient and restocking follows the two-level policy. The method of asymptotic system analysis is developed and results of numerical experiments are presented.

In this paper, exact and approximate approaches for studying queuing models with state-dependent jump priorities are developed. Both models with finite separate buffers and finite common buffer for heterogeneous calls are investigated. It is shown that both models might be described by twodimensional Markov Chains (2-D MC). Exact approach based on solution of appropriate system of balance equations (SBE) for state probabilities faced with big computational challenges for large scale models. To overcome the indicated difficulties an approximate approach based on the state space merging algorithms is developed. This approach allows to construct simple algorithms to calculate the Quality of Service (QoS) metrics of the examined models. The results of numerical experiments are demonstrated.

The objective of the paper is to analyzed QoS metric of cloud computing with large-scale of web server from queue management perspective. We propose a new method in order to effectively calculate the steady-state probabilities of cloud system with a large number of web servers. Numerical results showed that the proposed algorithms have higher accuracy and negligible computation time. Taking into account that in the cloud computing repair of server is taking some hours and response time is handling within some seconds, we can correctly apply space-merging algorithm.