Jiajing Wu

Traffic congestion in interconnected complex networks

Traffic congestion in isolated complex networks has been investigated extensively over the last decade. Coupled network models have recently been developed to facilitate further understanding of real complex systems. Analysis of traffic congestion in coupled complex networks, however, is still relatively unexplored. In this paper, we try to explore the effect of interconnections on traffic congestion in interconnected Barabási-Albert scale-free networks. We find that assortative coupling can alleviate traffic congestion more readily than disassortative and random coupling when the node processing capacity is allocated based on node usage probability. Furthermore, the optimal coupling probability can be found for assortative coupling. However, three types of coupling preferences achieve similar traffic performance if all nodes share the same processing capacity. We analyze interconnected Internet autonomous-system-level graphs of South Korea and Japan and obtain similar results. Some practical suggestions are presented to optimize such real-world interconnected networks accordingly.

Analysis of Communication Network Performance From a Complex Network Perspective

In this paper we study the performance of communication networks from a network science perspective. Our analysis and simulation results reveal the effects of network structure, resource allocation and routing algorithm on the communication performance. Performance parameters, including packet drop rate, time delay, and critical generation rate, are considered. For efficient data transmission, the traffic load should be as uniformly distributed as possible in the network and the average distance of it should be short. We propose to use the node usage probability, which depends on both the network topology and routing algorithm, to characterize the traffic load distribution, and show that resource allocation based on the node usage probability outperforms the uniform and degree-based allocation scheme. On the basis of the proposal analysis and routing algorithms, we compare the performances of regular networks, scale-free networks, random networks, and the Internet constructed at the autonomous system (AS) level. Results from this study provide important insights into the relationship between the structural properties of communication networks and their performances.

Optimizing Performance of Communication Networks: An Application of Network Science

For efficient and reliable data transmission, the traffic load should be as uniformly distributed as possible in the network, and the average distance traveled by the data should be short. This criterion has been shown to be fundamental. The key design problem is therefore to find the optimal solution that achieves this criterion. With a fixed network topology, the traffic load distribution and the transmission efficiency are determined by the specific routing algorithm. In this brief, we apply a simulated annealing algorithm to find the near optimal configuration of routing paths, which effectively balances traffic loads and improves the overall traffic performance.

Concept of Node Usage Probability From Complex Networks and Its Applications to Communication Network Design

In this paper, we study the traffic performance in communication networks from a complex network perspective. We introduce a new metric, namely, node usage probability, for characterizing the traffic load distribution and how frequently a node is chosen to relay packets in a network. Based on the concept of node usage probability, effective network design strategies, including routing algorithms and resource allocation schemes, can be developed to improve the overall traffic performance. We compare the performance of a minimum-node-usage routing algorithm with that based on other popular routing algorithms, such as shortest path (SP) and minimum degree (MD) routing algorithms, for various network topologies and resource allocation schemes. Simulation results show that routing algorithms based on minimizing node usage (MNU) can effectively balance traffic loads and resource allocation based on the node usage probability outperforms the uniform and degree-based allocation schemes. Our analysis and simulation results provide insights into how networks should be designed, including the choice of topology, the routing method, and the resource allocation scheme, for achieving optimal network performance.

Robustness of Interdependent Power Grids and Communication Networks: A Complex Network Perspective

In this brief, by considering realistic network operational settings, we propose a novel model to investigate the cascading failures in interdependent power grids and communication networks. We perform a critical node analysis on single networks to identify the vital nodes from the perspective of network robustness. Moreover, we assess the robustness of an interdependent system composed of an Internet AS-level network and the IEEE 118 Bus. Our simulation results show that assortative coupling of node destructiveness is more robust for densely coupled networks, whereas disassortative coupling of node robustness and node destructiveness performs better for sparsely coupled cases.

Effective routing algorithms based on node usage probability from a complex network perspective

In this paper, we study the traffic performance in communication networks from a complex network perspective. The node usage probability is an effective metric for characterizing the traffic load distribution and how frequently a node is chosen to relay packets in a network. Based on the concept of node usage probability, we propose an effective routing strategy to maintain balanced traffic loads in the network nodes by avoiding overuse of certain nodes. Simulation results show that routing algorithms based on the proposed strategy can effectively balance traffic loads and improve the overall traffic performance.

An adaptive routing algorithm for load balancing in communication networks

In this paper, we study the packet routing process in communication networks. For efficient and reliable data transmission, the traffic load should be as uniformly distributed as possible in the network and the average distance travelled by the data should be short. The Internet has been demonstrated to have small-world and scale-free properties in its topology. Under the shortest path routing strategy, the traffic intensity of high degree nodes is much higher, thus causing congestion of the whole network. We propose an adaptive routing algorithm, which takes into consideration both the network structure property and the dynamic traffic information. Simulation results show that the proposed algorithm can effectively balance the traffic in the network and improve the overall traffic performance.

Optimal design of coupling preferences to mitigate traffic congestion in interconnected networks

The issue of traffic congestion on single complex networks has been extensively studied in the past decade. Recently, interconnected network models have been developed to model the interactions between real-world systems. In interconnected networks, the coupling preference, i.e., the way to add coupling links, has great impact on the overall traffic performance. In this paper, we employ a simulated annealing algorithm to find a near-optimal configuration of the coupling links, which effectively balances the traffic loads and improves the overall traffic capacity.

An effective rewiring strategy for optimizing traffic performance of communication networks

Much prior work has demonstrated that the underlying network topology of communication networks is highly relevant to the intended communication performance of the networks. For reliable and efficient traffic transmission, the traffic load distribution in the network should be uniform and the average data transmission distance should be short. In this paper, we aim to find the optimal network topology that can achieve the most balanced traffic loads and the shortest average distance. We propose a rewiring strategy using the simulated annealing algorithm to optimize the traffic performance of a given communication network while keeping its degree distribution fixed. Our simulation results show that our proposed strategy can effectively balance traffic loads and improve the overall network traffic capacity for both the artificial scale-free and the Internet AS-level networks.

Concept of Node Usage Probability for Analysis and Design of Communication Networks

In this paper we study the performance of communication networks from a network science perspective. We study the traffic performance of scale-free network under shortest path and minimum degree routing. We introduce the node usage probability, which depends on both the network topology and routing algorithm, to characterize the traffic load distribution and show that resource allocation based on the node usage probability outperforms the uniform and degree-based allocation scheme.