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Abstract:In this paper, we study the throughput capacity of wireless networks considering the selfish feature of interaction between nodes. In our proposed network model, each node has a probability of cooperating to relay transmission. According to the extent of selfishness, we, by the application of percolation theory, construct a series of highways crossing the network. The transmission strategy is then divided into three consecutive phases. Comparing the rate in each phase, we find the bottleneck of rate is always in the highway phase. Finally, the result reveals that the node's selfishness degrades the throughput with a factor of square root of the cooperative probability, whereas the node density has trivial impact on the throughput.

We consider wireless multi-hops networks in which each node desires to securely transmit the message. To guarantee secure transmission, we employ an independent randomization encoding strategy to encode the confidential message. We formulate the problem as network utility maximization. Based on the secure communication strategy, we first propose a simple and provable dynamic control algorithm for the case that the length of secrecy codewords is infinite. The control algorithm not only satisfies end-to-end perfect secrecy constraint, but also keeps the network stability. Next, we further consider the case that a finite length of secrecy codewords is performed, in which the possibility of perfect secrecy is eliminated. For this case, we develop an improved control algorithm, subject to network stability and secrecy outage requirement. On the basis of the Lyapunov optimization method, we obtain the optimal algorithm, which is decomposed into end-to-end secrecy encoding, flow control, and routing schedule. The simulation results show that both of the proposed algorithms can achieve a utility result, arbitrarily close to optimal value. Finally, the performance of the proposed control policies is validated with various network conditions.INDEX TERMS Wireless networks, secrecy encoding, network control, Lyapunov optimization.