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The existing models of servers work on the M/G/1 model which is in some ways predictable and offers us an opportunity to compare the various other server queuing models. Mathematical analysis on the M/G/1 model is available in detail. This paper presents some mathematical analysis which aims at reducing the mean service time of a multiple server model. The distribution of the Mean Service Time has been derived using Little’s Law and a C++ simulation code has been provided to enable a test run so that the QoS of a multi-server system can be improved by reducing the Mean Service Time

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This paper aims to examine the various methods of protecting and securing a SIP architecture and also propose a new model to enhance SIP security in certain selected, specific and confidential environments as this proposed method cannot be generalized. Several security measures and techniques have already been experimented with, proposed and implemented by several authors as SIP security is an issue of utmost impor-tance in today’s world. This paper however, aims to summarize some of the better known techniques and propose a unique method of its own. It also aims to mathematically represent SIP fitness values graphically as well via a simulation using the popular Fuzz Data Generation Algorithm. Thus this paper not only aims to contribute to the already vast field of SIP security in an effective manner but also aims to acknowledge and represent some of the fail proof methods and encryption techniques that have helped in making SIP a more secure and less wobbly network for all of us to function in