This paper discusses the resilience of networks based on graph theory and stochastic process. The electric power network where edges may fail simultaneously and the performance of the network is measured by the ratio of connected nodes is supposed for the target network. For the restoration, under the constraint that the resources are limited, the failed edges are repaired one by one, and the order of the repair for several failed edges is determined with the priority to the edge that the amount of increasing system performance is the largest after the completion of repair. Two types of resilience are discussed, one is resilience in the recovery stage according to the conventional definition of resilience and the other is steady state operational resilience considering the long-term operation in which the network state changes stochastically. The second represents a comprehensive capacity of resilience for a system and is analytically derived by Markov analysis. We assume that the large-scale disruption occurs due to the simultaneous failure of edges caused by the common cause failures in the analysis. Marshall-Olkin type shock model and α factor method are incorporated to model the common cause failures. Then two resilience measures, “operational resilience” and “operational resilience in recovery stage” are proposed. We also propose approximation methods to obtain these two operational resilience measures for complex networks.

In this paper, we propose DSVMA (Data Steal into Voice Multiple Access) scheme for integration of voice and data in wireless information networks. By using speech activity detectors and effective downstream control signals, DSVMA enables data terminals to transmit multi-packet messages when voice terminals are in silent periods. The S-G (throughput versus offered load) performance of the DSVMA system and the blocking probabilities of both the second generation systems and the DSVMA systems are evaluated by the static analysis. A dynamic analysis of a system with finite number of terminals is also presented using an approximate Markov analysis method. Some numerical examples are given in the paper. As a result, it is shown that DSVMA can improve the channel utility efficiency of a circuit-switched TDMA (Time Division Multiple Access) wireless communication system and is directly applicable for second generation wireless information systems.