An optimized hardware calibration technique for transmission of real-time applications in VoIP network

Voice over Internet Protocol (VoIP) uses packet switching to transmit voice, video, data and chat services. VoIP applications depend upon various speech codecs which vary in speech quality, bandwidth and computational requirements. The key challenges for improving the VoIP Quality of Service (QoS) and Quality of Experience (QoE) is to use best codec by considering network traffic and selecting the optimal hardware. Hardware Calibration is a mechanism to aid service providers by selecting a suitable hardware for Call Manager to transmit different real-time based applications. The paper focuses on proposing a computational model which suggests the most suitable hardware for a specific load handling requirement. The selection of processor is done by taking into consideration the effect of different codecs when it takes calls per second as input and gives output as whichever hardware is recommended for Call Manager to handle different types of applications like Peer-To-Peer (P2P) application, Back-To-Back (BTB) application, enabling voice logging, etc. The emulations demonstrate that the proposed model is suitable for selection of hardware which provides better QoS and QoE for the transmission VoIP based real-time applications. Further, a multi-criteria decision-making method based on Analytic Hierarchy Process (AHP) is also proposed to decide which hardware can be chosen as Call Manager. The results obtained from AHP are used to validate the outcome of the proposed computational model. The computational model is applicable only when the tests are run on particular systems and it suggests the best hardware among them for the particular offered load. However, to suggest the best configuration corresponding to the input load from the possible configurations available in the market, benchmarking is performed. A common scale model for hardware benchmark estimation particularly has been proposed for different scenarios.

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