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Network navigation is one of the main problems in large communication networks. We propose a new routing strategy in which some smart nodes in networks deliver messages to next hops on the paths towards destinations according to Yan's algorithm while the other nodes just deliver messages randomly. We test our routing strategy in a large scale-free network. Simulations show that the average delivery time decreases with increase of number of smart nodes, while the maximal network capacity increases with number of smart nodes in the network. Moreover our strategy is much more efficient when employed with target selection than with random selection of the smart nodes.

Global static routing is one kind of important routing algorithms for complex networks, especially in large communication networks. In this paper, we propose a heuristic global static routing algorithm to mitigate traffic congestion on two-layer complex networks. The proposed routing algorithm extends the relevant static weighted routing algorithm in the literature [Y. Zhou, Y. F. Peng, X. L. Yang and K. P. Long, Phys. Sci.84, 055802 (2011)]. Our routing path is constructed from a proper assignment of edge weights by considering the static information of both layers and an adjustable parameter α. When this routing algorithm is adopted on BA–BA two-layer networks with an appropriate parameter α, it can achieve the maximum network traffic capacity compared with the shortest path (SP) routing algorithm and the static weighted routing algorithm.

In this paper, we study how the lifetime of packets impacts the overall transmission capacity of scale-free communication networks. In our model, we observed an abrupt phase transition of packet loss rate when the packet generation rate increases, based on which we redefined the network capacity as the critical packet generation rate of packet loss. Then, we found a sharp phase transition of network capacity with the increase of packet lifetime, which is also predicted by our analytical results of network capacity. Moreover, we obtained that there is an optimal routing parameter of the tunable path routing algorithm corresponding to the maximum network capacity. Finally, we discussed the influence of network topological structure on the network capacity.

We propose a new routing strategy for controlling packet routing on complex networks. The delivery capability of each node is adopted as a piece of local information to be integrated with the load traffic dynamics to weight the next route. The efficiency of transport on complex network is measured by the network capacity, which is enhanced by distributing the traffic load over the whole network while nodes with high handling ability bear relative heavier traffic burden. By avoiding the packets through hubs and selecting next routes optimally, most travel times become shorter. The simulation results show that the new strategy is not only effective for scale-free networks but also for mixed networks in realistic networks.

We propose a novel medium access control protocol for ad hoc wireless networks data to send can contend simultaneously for the channel. Nodes contend for access using a synchronous signaling mechanism that achieves two objectives: it arbitrates contentions locally and it selects a subset of nodes across the network that attempt to transmit simultaneously. The subset of nodes that survive the signaling mechanism can be viewed as an orchestrated set of transmissions that are spatially reusing the channel shared by the nodes. Thus the 'quality' of the subset of nodes selected by the signaling mechanism is a key factor in determining the spatial capacity of the system. In this paper, we propose a general model for such synchronous signaling mechanisms and recommend a preferred design. We then focus via both analysis and simulation on the spatial and capacity characteristics of these access control mechanisms. Our work is unique in that it specifically focuses on the spatial capacity aspects of a MAC protocol, as would be critical for ad hoc networking, and shows SCR is a promising solution. Specifically, it does not suffer from congestion collapse as the density of contending nodes grows, it does not suffer from hidden or exposed node effects, it achieves high capacities with a spatial usage exceeding 1 (i.e. more than one packet exchange in the area covered by a transmission), and it facilitates the integration of new physical layer capacity increasing technologies.

A multi-UAV system relies on communications to operate. Failure to communicate remotely sensed mission data to the base may render the system ineffective, and the inability to exchange command and control messages can lead to system failures. This paper describes a unique method to control network communications through distributed task allocation to engage under-utilized UAVs to serve as communication relays and to ensure that the network supports mission tasks. This work builds upon a distributed algorithm previously developed by the authors, CBBA with Relays, which uses task assignment information, including task location and proposed execution time, to predict the network topology and plan support using relays. By explicitly coupling task assignment and relay creation processes, the team is able to optimize the use of agents to address the needs of dynamic complex missions. In this work, the algorithm is extended to explicitly consider realistic network communication dynamics, including path loss, stochastic fading, and information routing. Simulation and flight test results validate the proposed approach, demonstrating that the algorithm ensures both data-rate and interconnectivity bit-error-rate requirements during task execution.