Limited static and dynamic delivering capacity allocations in scale-free networks

In traffic networks, it is quite important to assign proper packet delivering capacities to the routers with minimum cost. In this respect, many allocation models based on static and dynamic properties have been proposed. In this paper, we are interested in the impact of limiting the packet delivering capacities already allocated to the routers; each node is assigned a packet delivering capacity limited by the maximal capacity [Formula: see text] of the routers. To study the limitation effect, we use two basic delivering capacity allocation models; static delivering capacity allocation (SDCA) and dynamic delivering capacity allocation (DDCA). In the SDCA, the capacity allocated is proportional to the node degree, and for DDCA, it is proportional to its queue length. We have studied and compared the limitation of both allocation models under the shortest path (SP) routing strategy as well as the efficient path (EP) routing protocol. In the SP case, we noted a similarity in the results; the network capacity increases with increasing [Formula: see text]. For the EP scheme, the network capacity stops increasing for relatively small packet delivering capability limit [Formula: see text] for both allocation strategies. However, it reaches high values under the limited DDCA before the saturation. We also find that in the DDCA case, the network capacity remains constant when the traffic information available to each router was updated after long period times [Formula: see text].

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An efficient routing strategy on spatial scale-free networks

International Journal of Modern Physics C ◽

10.1142/s012918311450017x ◽

2014 ◽

Vol 25 (07) ◽

pp. 1450017 ◽

Cited By ~ 8

Author(s):

Xiang-Min Guan ◽

Xue-Jun Zhang ◽

Yanbo Zhu ◽

Inseok Hwang ◽

Deng-Feng Sun

Keyword(s):

Spatial Scale ◽

Euclidean Distance ◽

Network Capacity ◽

Traffic Load ◽

System Throughput ◽

Traffic Dynamics ◽

Space Factor ◽

Scale Free ◽

Routing Strategy ◽

Traffic Systems

Traffic dynamics has drawn much more attention recently, but most current research barely considers the space factor, which is of critical importance in many real traffic systems. In this paper, we focus our research on traffic dynamics of a spatial scale-free network with the restriction of bandwidth proportional to link Euclidean distance, and a new routing strategy is proposed with consideration of both Euclidean distance and betweenness centralities (BC) of edges. It is found that compared with the shortest distance path (SDP) strategy and the minimum betweenness centralities (MBC) of links strategy, our strategy under some parameters can effectively balance the traffic load and avoid excessive traveling distance which can improve the spatial network capacity and some system behaviors reflecting transportation efficiency, such as average packets traveling time, average packets waiting time and system throughput, traffic load and so on. Besides, though the restriction of bandwidth can trigger congestion, the proposed routing strategy always has the best performance no matter what bandwidth becomes. These results can provide insights for research on real networked traffic systems.

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Efficient packet navigation method on scale-free networks with finite and diversiform node delivery capacity

International Journal of Modern Physics C ◽

10.1142/s0129183116500984 ◽

2016 ◽

Vol 27 (09) ◽

pp. 1650098

Author(s):

Xuan He ◽

Kai Niu ◽

Zhiqiang He ◽

Jiaru Lin ◽

Hui Zhang ◽

...

Keyword(s):

Capacity Allocation ◽

Traffic Load ◽

Allocation Mechanism ◽

Good Correspondence ◽

Shortest Path Routing ◽

Scale Free ◽

Routing Strategy ◽

Traffic Capacity ◽

Network Diameter ◽

Node Capacity

Routing strategy is essential for high transport efficiency on realistic networked complex systems. Beginning from the consideration of finite and diversiform node delivery capacity distributions, a general node capacity allocation mechanism with a tunable parameter [Formula: see text] is presented. A node capacity, based routing strategy is proposed to improve the network traffic capacity. Compared with the traditional shortest path routing (SPR) and the efficient routing (ER) methods, it suggests that routing strategy should be chosen heuristically according to the limited capacity resource distribution, instead of using one certain method for all cases. With proper range of parameter [Formula: see text], the new routing strategy achieves the highest traffic capacity and other preferable measure metrics including network diameter, average path length, efficient betweenness, average packet travel time and average traffic load. The theoretical analysis for traffic capacity has a good correspondence to the simulation results. This work studies routing mechanisms from a very practical perspective, and helps network researchers to understand the traffic dynamics on complex networks comprehensively.

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ANALYSIS OF TRAFFIC FLOW ON COMPLEX NETWORKS

International Journal of Modern Physics B ◽

10.1142/s0217979211100655 ◽

2011 ◽

Vol 25 (10) ◽

pp. 1419-1428 ◽

Cited By ~ 5

Author(s):

KUN LI ◽

XIAOFENG GONG ◽

SHUGUANG GUAN ◽

C.-H. LAI

Keyword(s):

Complex Networks ◽

Network Capacity ◽

Traffic Load ◽

Packet Routing ◽

Traffic Dynamics ◽

Scale Free ◽

Routing Strategy ◽

Scale Free Networks ◽

New Strategy ◽

Mixed Networks

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.

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An improved global dynamic routing strategy for scale-free network with tunable clustering

Modern Physics Letters B ◽

10.1142/s0217984916503024 ◽

2016 ◽

Vol 30 (22) ◽

pp. 1650302 ◽

Cited By ~ 1

Author(s):

Lina Sun ◽

Ning Huang ◽

Yue Zhang ◽

Yannan Bai

Keyword(s):

Shortest Path ◽

Path Length ◽

Network Capacity ◽

Network Routing ◽

Scale Free Network ◽

Scale Free ◽

Global Dynamic ◽

Routing Strategy ◽

Traffic Awareness ◽

Free Network

An efficient routing strategy can deliver packets quickly to improve the network capacity. Node congestion and transmission path length are inevitable real-time factors for a good routing strategy. Existing dynamic global routing strategies only consider the congestion of neighbor nodes and the shortest path, which ignores other key nodes’ congestion on the path. With the development of detection methods and techniques, global traffic information is readily available and important for the routing choice. Reasonable use of this information can effectively improve the network routing. So, an improved global dynamic routing strategy is proposed, which considers the congestion of all nodes on the shortest path and incorporates the waiting time of the most congested node into the path. We investigate the effectiveness of the proposed routing for scale-free network with different clustering coefficients. The shortest path routing strategy and the traffic awareness routing strategy only considering the waiting time of neighbor node are analyzed comparatively. Simulation results show that network capacity is greatly enhanced compared with the shortest path; congestion state increase is relatively slow compared with the traffic awareness routing strategy. Clustering coefficient increase will not only reduce the network throughput, but also result in transmission average path length increase for scale-free network with tunable clustering. The proposed routing is favorable to ease network congestion and network routing strategy design.

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INTEGRATING LOCAL AND GLOBAL ROUTING ON SCALE-FREE NETWORKS

International Journal of Modern Physics C ◽

10.1142/s0129183111016221 ◽

2011 ◽

Vol 22 (03) ◽

pp. 297-304

Author(s):

CUN-LAI PU ◽

WEN-JIANG PEI

Keyword(s):

Communication Networks ◽

Large Scale ◽

Target Selection ◽

Network Capacity ◽

Delivery Time ◽

Scale Free ◽

Routing Strategy ◽

Free Network ◽

Network Simulations ◽

Selection Of

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.

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EFFICIENT ROUTING STRATEGY ON SCALE-FREE NETWORKS

Modern Physics Letters B ◽

10.1142/s021798490901951x ◽

2009 ◽

Vol 23 (11) ◽

pp. 1377-1389

Author(s):

GANG YU ◽

XIAN-PENG WANG ◽

HONG-TAO LU

Keyword(s):

Queue Length ◽

Modern Society ◽

Node Degree ◽

Dynamic Information ◽

Scale Free ◽

Routing Strategy ◽

Static Information ◽

New Strategy ◽

Crucial Part ◽

Selection Of

With the development of information technology, networks become a crucial part in modern society. Therefore, the improvement in routing strategy of networks is of great importance and significance. For the purpose of improving the efficiency of network traffic, we propose a new routing strategy with two tunable parameters based on local information of network. In our strategy, we include the static information, node degree, and dynamic information, buffer queue length, to guide the selection of the next transmission node. Since the importing of buffer queue length information, packets can be distributed more evenly in the network, which can reduce the congestion possibility of network. In addition, for the sake of evaluation of a routing strategy, we propose four criterions to assess the performance of network. Based on the four criterions, we first compare the experimental results of our strategy with the original strategy only including node degree information and then give some insights of our new strategy according to the simulation results.

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The effect of data exchange policy on traffic flow between interconnected networks

International Journal of Modern Physics C ◽

10.1142/s0129183120500357 ◽

2020 ◽

Vol 31 (03) ◽

pp. 2050035

Author(s):

S. Lazfi ◽

N. Ben Haddou ◽

A. Rachadi ◽

H. Ez-Zahraouy

Keyword(s):

Traffic Flow ◽

Data Exchange ◽

Network Capacity ◽

Important Place ◽

Scale Free ◽

Routing Strategy ◽

Optimal Functioning ◽

Optimal Network ◽

Exchange Policy ◽

Traffic Systems

In order to understand and achieve an optimal functioning in real traffic systems, the problem of congestion in complex networks takes an important place in many recent researches. In this paper, we study the effect of different types of interconnections between two scale free networks on the traffic flow. Two interconnection strategies are used: in the first, we create links between nodes chosen at random from the two subnets [Formula: see text] and [Formula: see text] and, while in the second one, we link nodes selected among the hubs of the subnets. The resulting network [Formula: see text] is under a new routing strategy inspired from the minimal traffic model introduced in [D. De Martino, Phys. Rev. E 79, 015101 (2009); S. Lamzabi, S. Lazfi, H. Ez-Zahraouy, A. Benyoussef, A. Rachadi and S. Ziti, Int. J. Mod. Phys. C 25, 1450019 (2014)]. We find that in case of this routing method, the interconnection pattern has no effect on the results. Further, to control the exchange of packets between the subnets, we propose two adjusting parameters [Formula: see text] and [Formula: see text]. The study of the variation of these parameters shows that the optimal network capacity is obtained when the two subnets are allowed to exchange data more openly.

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Delivering capacity allocation strategy for traffic dynamics on scale-free networks

International Journal of Modern Physics C ◽

10.1142/s0129183120500291 ◽

2019 ◽

Vol 31 (02) ◽

pp. 2050029

Author(s):

Jinlong Ma ◽

Wei Sui ◽

Changfeng Du ◽

Xiangyang Xu ◽

Guanghua Zhang

Keyword(s):

Network Capacity ◽

Capacity Allocation ◽

Allocation Strategy ◽

Traffic Dynamics ◽

Shortest Path Routing ◽

Scale Free ◽

Optimal Value ◽

Scale Free Networks ◽

Resource Allocation Strategy ◽

Traffic Systems

The traffic dynamics of complex networks are largely determined by the node’s resource distribution. In this paper, based on the shortest path routing strategy, a node delivering capacity distribution mechanism is proposed into the traffic dynamics in Barabási and Albert (BA) scale-free networks; the efficiency of the mechanism on the network capacity measured by the critical point ([Formula: see text]) of phase transition from free flow to congestion is primarily explored. Based on the proposed strategy, the total delivering capacity is reallocated according to both degree and betweenness of each node, and an optimal value of parameter [Formula: see text] is found, leading to the maximum traffic capacity. The results of numerical experiments on scale-free networks suggest that the resource allocation strategy proposed here is capable of effectively enhancing the transmission capacity of networks. Furthermore, this study may provide novel insights into research on networked traffic systems.

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Heterogeneous delivering capability promotes traffic efficiency in complex networks

International Journal of Modern Physics C ◽

10.1142/s0129183115500692 ◽

2015 ◽

Vol 26 (06) ◽

pp. 1550069

Author(s):

Yan-Bo Zhu ◽

Xiang-Min Guan ◽

Xue-Jun Zhang

Keyword(s):

Network Capacity ◽

Dynamic Routing ◽

Transportation Systems ◽

Networked Systems ◽

Dynamic Information ◽

Scale Free ◽

Traffic Efficiency ◽

Global Dynamic ◽

Routing Strategy ◽

Scale Free Networks

Traffic is one of the most fundamental dynamical processes in networked systems. With the homogeneous delivery capability of nodes, the global dynamic routing strategy proposed by Ling et al. [Phys. Rev. E81, 016113 (2010)] adequately uses the dynamic information during the process and thus it can reach a quite high network capacity. In this paper, based on the global dynamic routing strategy, we proposed a heterogeneous delivery allocation strategy of nodes on scale-free networks with consideration of nodes degree. It is found that the network capacity as well as some other indexes reflecting transportation efficiency are further improved. Our work may be useful for the design of more efficient routing strategies in communication or transportation systems.

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