An Analytical Model for Service Discovery Architectures in Next-Generation Networks

Next-Generation Networks (NGNs) are all IP-based converged networks which comprise wired and wireless networks together. With the proliferation of services, Service Discovery (SD) has become an essential feature of NGNs. Many efforts have been made in the research of SD. However, only one paper theoretically analyzed the cache usage for decentralized architectures in ad-hoc networks. In this paper, we proposed an analytical model for characterizing the performances of SD architectures. Our model is suitable for both centralized and decentralized architectures. Thus, the proposed model can be a generic basis for further studies on SD architectures. Moreover, our model was validated with simulations. Since SD architectures use Time-To-Live (TTL)-based control mechanisms to save the bandwidth, we modeled the impact of the TTL's value. The results show that the success rate of centralized architectures can be improved by increasing the TTL's value without introducing additional network overheads. For the decentralized architectures, our model is very useful in deciding the optimal value of TTL.