Network design and operation of a mobile network infrastructure, especially its base station systems, need to consider survivability as a fundamental requirement. To this end, quantifiable approaches to survivability analysis of such infrastructures are crucial. The objective of this paper is to propose a model for quantification of the survivability of wireless communication networks subject to massive failures, e.g., caused by natural disasters, common mode hardware and software failures, and security attacks. This means to analyze the transient behavior of the recovery phases. We use a Markov model approach, and apply this in a case study of a two-tier infrastructure-based wireless network. To take location information of base stations into consideration, the spatial average network performance is estimated by means of a stochastic geometry based approach. Further, in order to avoid state space explosion while addressing large networks, an approximate product-form analysis approach is also presented, where the two base stations tiers are decoupled such that their survivability analysis can be studied independently. The assumptions used in the proposed models, including Poisson point process (PPP) assumption and product-form decomposition assumption, are validated on real data. Numerical experiments are also performed to investigate the approximation accuracy and computational efficiency of the product-form analysis approach, as well as to examine the effect of different parameters on the network's survivability. The results show that 1 Lang Xie is the corresponding author with email address langxie 77@163.com.
Preprint submitted to Journal of L A T E X TemplatesDecember 12, 2016 the approximate product-form approach is more scalable with reasonably good accuracy and hence may be more preferred for analysis of large size networks.