Cascading Failure Tolerance in Large-Scale Service Networks

The rapid growth of services and the Internet of Things vision lead to the future of Internet in which a massive number of services are available and connected to each other. In such service network, dependency between services potentially causes cascading failure, where the failure of one service can cause the failure of dependent services. Cascading failure tolerance is determined by the topology of the network and the degree of service interdependency. As to the former, we analyze cascading failure in scale-free, exponential, and random service networks. We find that scale-free topology has generally the highest tolerance. This is contrast to cascading failure in power network, where random topology provides better tolerance. For the latter, we find that the number of cascade failed nodes increases as the inverse of the average number of alternate services, e.g. Functionally equivalent services. This suggests that increasing the number of alternate services can significantly improve the network tolerance if each service only has few alternate services available.