Local Routing Strategy Research Articles

Improved local routing strategy for enhancing the traffic capacity of scale-free networks

The study of network traffic capacity is of significant importance, and it has received increasing attention across various scientific disciplines. In this paper, the improved local routing (ILR) strategy is utilized to enhance network traffic capacity. In the context of current routing strategies and network structures, packets can be transmitted along either the most efficient paths or the shortest paths. By optimizing the combination of nodes' degree centrality and betweenness centrality to bypass hub nodes, the ILR strategy can reasonably distribute the traffic load. According to simulation results, the ILR strategy significantly enhances network traffic capacity and shortens average path length, surpassing the performance of the effective routing strategy (ERS). Furthermore, the findings indicate that networks employing the ILR strategy exhibit strong robustness against both random and deliberate attacks.

A Link Status-Based Multipath Scheduling Scheme on Network Nodes

Traditional internet protocol (IP) networks, adhering to a “best-effort” service model, typically utilize shortest-path routing for data transmission. Nevertheless, this methodology encounters limitations, especially considering the increasing demands for both high reliability and high bandwidth. These demands reveal shortcomings in this routing strategy, notably its inefficient bandwidth utilization and fault recovery capabilities. The method of multipath transmission has been extensively researched as a solution to these challenges. With the emergence of innovative Internet architectures, notably information-centric networking (ICN), network nodes have gained enhanced capabilities, opening new avenues for multipath transmission design. This paper introduces a multipath scheduling approach for network nodes, capitalizing on the advanced features of these modern nodes. It reimagines the conventional next-hop node as a group of potential next-hop nodes based on both global and local routing strategies and assigns traffic shares to each node within this group for balanced traffic distribution. Network nodes are configured to periodically review and adjust traffic shares according to the link statuses. If scheduling cannot be completed within the set, feedback is sent to upstream nodes. Simulations demonstrate that this approach effectively leverages network path variety, improves bandwidth usage and throughput, and minimizes average data transmission time.

An improved local efficient routing strategy on scale-free networks

To improve the traffic capacity of scale-free networks, we propose an improved local efficient routing (ILER) strategy based on node degree and network constraint index (NCI). NCI describes how closely a node is maintained directly or indirectly with other nodes, and it only considers the relationship between nodes and their neighbors, not the topology of the network. Both the node degree and NCI are a parameter to describe the importance of nodes, and the combination of the two can make up for their own shortcomings, making it particularly important. Under the ILER strategy, packets can bypass some central nodes in the network for transmission, so that the central nodes in the network are not prone to congestion, thereby increasing the network traffic capacity. Through simulation comparison, the network traffic capacity under ILER strategy is significantly higher than that under probability routing (PR) strategy and efficient routing (ER) strategy. Under the ILER strategy, the average path length (APL) of the network is also shorter than that under the PR and ER strategies. In addition, whether target attack or random attack, the network has strong robustness under ILER strategy.

VeriORouting: Verification on intelligent routing outsourced to the cloud

Current research on machine learning-based intelligent routing focuses on algorithm design and performance optimization. How to deploy it in practice remains a pressing issue. Existing deep learning-based intelligent routing algorithms suffer from a high computational cost, which is hard to be afforded by routers. Considering that the cloud can assist the routers with limited resources to handle complex computation, outsourcing deep learning-based intelligent routing computations to the cloud becomes a feasible solution to support intelligent routing. However, due to the untrustworthiness of the cloud, it is necessary for the routers to verify the truth of outsourced routing results. However, the literature has not yet explored this issue. In this paper, we proposed VeriORouting, a scheme to verify the correctness of outsourced deep learning-based intelligent routing results provided by the cloud. Facing a lazy cloud, VeriORouting allows routers to check the reliability of intelligent routing models by testing model accuracy, and to verify the routing results returned by the cloud without knowing the model by using verification functions generated with multilayer perceptron (MLP) and locality-sensitive hashing (LSH) in advance. We show the robustness of VeriORouting under two attacks raised by the cloud. We evaluate the performance of VeriORouting and compare it with a local intelligent routing scheme. The results show that VeriORouting outperforms the local scheme in terms of computational overhead and storage overhead, especially when the number of routers in the network increases. In terms of communication, VeriORouting reduces communication overhead between routers compared to the local scheme. In addition, we measure the verification performance of VeriORouting under a random attack. VeriORouting achieves a detection success rate of 73% with a false positive rate of 3%, and a detection success rate of 90% with a false positive rate of 25%.

Traffic dynamics based on dynamic local routing protocol in a finite buffer network

This paper proposed a novel routing strategy with two tunable parameters, [Formula: see text], [Formula: see text], based on the dynamic local information in a finite buffer network. The system behaves differently from that with a local routing strategy based on the degree with an adjustable parameter [Formula: see text]. Simulations show that, under dynamic local strategy, the maximal capacity of the network system increases with [Formula: see text] whereas it increases with the decrement of [Formula: see text] in the case of all the nodes having identical delivering ability. The dynamic local routing performs much better than the local routing, which is demonstrated by a larger value of the critical packet generation rate. We found that buffer coefficient has a limited impact on the performance of network system. We also demonstrate that a smaller [Formula: see text] would be better if we want to have an excellent traffic capacity considering the travel time, average path length and waiting time. Our study will be helpful to improve traffic performance in finite buffer networks.

Local Routing in Sparse and Lightweight Geometric Graphs

Online routing in a planar embedded graph is central to a number of fields and has been studied extensively in the literature. For most planar graphs no O(1)-competitive online routing algorithm exists. A notable exception is the Delaunay triangulation for which Bose and Morin (SIAM J Comput 33(4):937–951, 2004) showed that there exists an online routing algorithm that is O(1)-competitive. However, a Delaunay triangulation can have varOmega (n) vertex degree and a total weight that is a linear factor greater than the weight of a minimum spanning tree. We show a simple construction, given a set V of n points in the Euclidean plane, of a planar geometric graph on V that has small weight (within a constant factor of the weight of a minimum spanning tree on V), constant degree, and that admits a local routing strategy that is O(1)-competitive. Moreover, the technique used to bound the weight works generally for any planar geometric graph whilst preserving the admission of an O(1)-competitive routing strategy.

Utilization of Network Layer Protocols for Systematic Routing

A clean framework for designing protocols for wireless networks includes localized routing and broadcasting. The clean framework is based definitely on the ratio of the cost of making certain picks along with cut price in distance count. Routing protocol is one in each of the most important networks found in this application of wireless networks. The normally used routing techniques withinside the network layers are described as follows. In [1]Distributed routing approach each node checks whether or not or now no longer the cost of routing via a given neighbor is smaller than that of currently used nodes. In the ‘adhoc’ networks, it has bandwidth quandary of the wireless channel. In dynamic ad hoc networks, a localized approach based definitely on ‘on-demand direction discovery’ with the useful resource of the use of flooding excursion spot is used. But it’s a ways inefficient to use flooding as routing scheme in wireless networks as it has power and bandwidth quandary. Localized protocols describes the amount of information required (i.e.) it gives the not unusual place variety of messages transmitted in step with node in a protocol. In a strictly localized protocol it’s a ways each local or global in nature. Thus the aim of the challenge describes the concept as a modern framework of some gift protocols. The Proposed framework of the localized routing scheme is based definitely on the cost measure, which is based upon on the assumptions for the minimal routing direction to be determined on and the improvement measure is based upon on the advances towards the excursion spot. Network simulator is used to implement this scenario.

Constrained routing between non-visible vertices

In this paper we study local routing strategies on geometric graphs. Such strategies use geometric properties of the graph like the coordinates of the current and target nodes to route. Specifically, we study routing strategies in the presence of constraints which are obstacles that edges of the graph are not allowed to cross. Let P be a set of n points in the plane and let S be a set of line segments whose endpoints are in P, with no two line segments intersecting properly. We present the first deterministic 1-local O(1)-memory routing algorithm that is guaranteed to find a path between two vertices in the visibility graph of P with respect to a set of constraints S. The strategy never looks beyond the direct neighbors of the current node and does not store more than O(1)-information to reach the target.We then turn our attention to finding competitive routing strategies. We show that when routing on any triangulation T of P such that S⊆T, no o(n)-competitive routing algorithm exists when the routing strategy restricts its attention to the triangles intersected by the line segment from the source to the target (a technique commonly used in the unconstrained setting). Finally, we provide an O(n)-competitive deterministic 1-local O(1)-memory routing algorithm on any such T, which is optimal in the worst case, given the lower bound.

Local routing in WSPD-based spanners

The well-separated pair decomposition (WSPD) of the complete Euclidean graph defined on points in $R^2$, introduced by Callahan and Kosaraju [JACM, 42 (1): 67-90, 1995], is a technique for partitioning the edges of the complete graph based on length into a linear number of sets. Among the many different applications of WSPDs, Callahan and Kosaraju proved that the sparse subgraph that results by selecting an arbitrary edge from each set (called WSPD-spanner) is a $1 + 8/(s − 4)$-spanner, where $s > 4$ is the separation ratio used for partitioning the edges.Although competitive local-routing strategies exist for various spanners such as Yao-graphs, $\Theta$-graphs, and variants of Delaunay graphs, few local-routing strategies are known for any WSPD-spanner. Our main contribution is a local-routing algorithm with a near-optimal competitive routing ratio of $1 + O(1/s)$ on a WSPD-spanner.Specifically, using Callahan and Kosaraju’s fair split-tree, we show how to build a WSPD-spanner with spanning ratio $1 + 4/s + 4/(s − 2)$ which is a slight improvement over $1 + 8/(s − 4)$. We then present a 2-local and a 1-local routing algorithm on this spanner with competitive routing ratios of $1 + 6/(s − 2) + 4/s$ and $1 + 8/(s − 2) + 4/s + 8/s^2$, respectively. Moreover, we prove that there exists a point set for which our WSPD-spanner has a spanning ratio of at least $1 + 8/s$, thereby proving the near-optimality of its spanning ratio and the near-optimality of the routing ratio of both our routing algorithms.

Local routing protocols performance for computer virus elimination in complex networks

Although extensive research has been devoted to treat virus propagation over decades, the effect of local routing protocols algorithms on it has been ignored. In this paper, we studied the effectiveness of local routing protocols and their additional algorithms; next-nearest neighbors (NNN) and restrictive queue- length algorithm (RQL) in term of robustness in computer virus spreading. It is found that, the local routing protocols without additional algorithms favor the virus spreading, due to the blind transmission of packets between source and destination, while in local routing protocols under (NNN) algorithm, the virus propagation is reduced remarkably. Moreover in local routing protocols under RQL, the virus propagation continues to be reduced more and more compared with NNN algorithm. Furthermore our results show that the node duplication avoidance (NDA) algorithm favors the computer virus spreading especially in sparse networks. Moreover, in comparison with shortest path (SP) and efficient path (EP) global routing strategies ,local routing protocols under the restrictive queue- length algorithm (RQL), the virus propagation is highly reduced and becomes unexpectedly comparable to the traditional shortest path strategy and overcomes the efficient path strategy which shows a high vulnerability and sensitivity to computer virus propagation. These results could be very helpful for network routing protocols designers to give more attention to local routing strategies and their additional algorithms in order to benefit from high capacity and high level of security plus the adaptability with the large scale free networks as the internet.

Routing Strategy of Complex Networks Based on Topology Information

A routing strategy using nodes’ effective path and dynamic information weight distribution was proposed, which based on the improved efficient path routing strategy in complex network. The strategy’s weight factor was optimized by the new strategy, Considering the insufficient of local routing strategies in global performance and the community division technology in complex network, a kind of local visibility routing strategy according to the thought of community division was presented. On the condition of community division of the Bgll condensation algorithm, the topology structure information of neighbor nodes and all the community nodes were only stored in each node’s routing list in the new strategy. When node transaction in community, global routing strategy was adopted and when between communities, minimum load strategy will be used. The simulation results indicate that in the different connection density networks, the performance of the new strategy achieves the best when community division’s degree of modularization is the highest. Contrasted to other local routing strategy, the optimized strategy holds incomparable superiority on throughput, transmission delay and the packet loss.

Modeling and analyzing cascading dynamics of the Internet based on local congestion information

Cascading failure has already become one of the vital issues in network science. By considering realistic network operational settings, we propose the congestion function to represent the congested extent of node and construct a local congestion-aware routing strategy with a tunable parameter. We investigate the cascading failures on the Internet triggered by deliberate attacks. Simulation results show that the tunable parameter has an optimal value that makes the network achieve a maximum level of robustness. The robustness of the network has a positive correlation with tolerance parameter, but it has a negative correlation with the packets generation rate. In addition, there exists a threshold of the attacking proportion of nodes that makes the network achieve the lowest robustness. Moreover, by introducing the concept of time delay for information transmission on the Internet, we found that an increase of the time delay will decrease the robustness of the network rapidly. The findings of the paper will be useful for enhancing the robustness of the Internet in the future.

Enhancing network capacity by weakening community structure in scale-free network

The community structure of the network will affect information transmission and the pronounced community structure will significantly reduce the network traffic capacity. In this paper, we propose a community weakening control strategy (CWCS) to enhance the network capacity by logically closing or cutting some links with high link importance to communities. We implement the strategy in both a global shortest-path routing policy and local routing policy, and compare it with the High-Degree-First strategy that removes the links among hub nodes. The simulation results show that the traffic capacity can be greatly enhanced and the average transport time is effectively reduced under the shortest path routing strategy. The traffic capacity can also be greatly enhanced under the local routing strategy when the tunable parameter α lies in a range from 0 to 2. WCS not only provides a method for enhancing network capacity, but also may be applied for suppressing the spread of malicious information in the network.

Advanced Algorithms for Local Routing Strategy on Complex Networks.

Despite the significant improvement on network performance provided by global routing strategies, their applications are still limited to small-scale networks, due to the need for acquiring global information of the network which grows and changes rapidly with time. Local routing strategies, however, need much less local information, though their transmission efficiency and network capacity are much lower than that of global routing strategies. In view of this, three algorithms are proposed and a thorough investigation is conducted in this paper. These algorithms include a node duplication avoidance algorithm, a next-nearest-neighbor algorithm and a restrictive queue length algorithm. After applying them to typical local routing strategies, the critical generation rate of information packets Rc increases by over ten-fold and the average transmission time 〈T〉 decreases by 70–90 percent, both of which are key physical quantities to assess the efficiency of routing strategies on complex networks. More importantly, in comparison with global routing strategies, the improved local routing strategies can yield better network performance under certain circumstances. This is a revolutionary leap for communication networks, because local routing strategy enjoys great superiority over global routing strategy not only in terms of the reduction of computational expense, but also in terms of the flexibility of implementation, especially for large-scale networks.

Finding the biased-shortest path with minimal congestion in networks via linear-prediction of queue length

In this paper, we propose a biased-shortest path method with minimal congestion. In the method, we use linear-prediction to estimate the queue length of nodes, and propose a dynamic accepting probability function for nodes to decide whether accept or reject the incoming packets. The dynamic accepting probability function is based on the idea of homogeneous network flow and is developed to enable nodes to coordinate their queue length to avoid congestion. A path strategy incorporated with the linear-prediction of the queue length and the dynamic accepting probability function of nodes is designed to allow packets to be automatically delivered on un-congested paths with short traveling time. Our method has the advantage of low computation cost because the optimal paths are dynamically self-organized by nodes in the delivering process of packets with local traffic information. We compare our method with the existing methods such as the efficient path method (EPS) and the optimal path method (OPS) on the BA scale-free networks and a real example. The numerical computations show that our method performs best for low network load and has minimum run time due to its low computational cost and local routing scheme.

Effective local dynamic routing strategy for air route networks

With the rapid development of air transportation, network service ability has attracted a lot of attention in academe. Aiming to improve the throughput of the air route network (ARN), we propose an effective local dynamic routing strategy in this paper. Several factors, such as the routing distance, the geographical distance and the real-time local traffic, are taken into consideration. When the ARN is in the normal free-flow state, the proposed strategy can recover the shortest path routing (SPR) strategy. When the ARN undergoes congestion, the proposed strategy changes the paths of flights based on the real-time local traffic information. The throughput of the Chinese air route network (CARN) is evaluated. Results confirm that the proposed strategy can significantly improve the throughput of CARN. Meanwhile, the increase in the average flying distance and time is tiny. Results also indicate the importance of the distance related factors in a routing strategy designed for the ARN.

On Asymptotic Statistics for Geometric Routing Schemes in Wireless Ad Hoc Networks

In this paper, we present a methodology employing statistical analysis and stochastic geometry to study geometric routing schemes in wireless ad hoc networks. In particular, we analyze the network-layer performance of one such scheme, the random [ 1/ 2]disk routing scheme, which is a localized geometric routing scheme in which each node chooses the next relay randomly among the nodes within its transmission range and in the general direction of the destination. The techniques developed in this paper enable us to establish the asymptotic connectivity and the convergence results for the mean and variance of the routing path lengths generated by geometric routing schemes in random wireless networks. In particular, we approximate the progress of the routing path toward the destination by a Markov process and determine the sufficient conditions that ensure the asymptotic connectivity for both dense and large-scale ad hoc networks deploying the random [ 1/ 2]disk routing scheme. Furthermore, using this Markov characterization, we show that the expected length (hop count) of the path generated by the random [ 1/ 2]disk routing scheme normalized by the length of the path generated by the ideal direct-line routing, converges to 3π/4 asymptotically. Moreover, we show that the variance-to-mean ratio of the routing path length converges to 9π <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> /64-1 asymptotically. Through simulation, we show that the aforementioned asymptotic statistics are in fact quite accurate even for finite granularity and size of the network.

Based on the complex network of local routing strategy scale-free networks

This paper, the factors to consider the dynamic and static local routing strategy of scalefree networks. Don't have access to global information for large network, put forward a kind of combined with the current static topology information of network and node of the traffic flow situation of considering the dynamic factors of routing strategy of local information. Based on scale-free networks in the simulation model, analyses the network congestion in the shift. Through simulation experiments and research, found that there are optimal control parameters, makes the network throughput can reach maximum.

Degree-energy-based local random routing strategies for sensor networks

This paper proposes several comparable degree-energy-based local random routing strategies for wireless sensor networks and reports a detailed numerical study of the new strategies. Specifically, energy consumption and lifetime efficiency of sensor networks are investigated for five different structural topologies and five different routing methods under the degree-energy-awareness principle, regarding their performances and costs. The new findings could provide some references and guidelines for designing more efficient sensor networks under various conditions for future applications. Based on these findings, a few rules of thumb for the design of more energy-efficient sensor networks are suggested.

Congestion control in complex network based on local routing strategy

In this paper, we propose a local routing strategy in a complex network, use the node contraction method to evaluate the node importance. The probability of the node transmit packet to its neighbors is adaptively adjusted based on the importance of neighbor nodes and the state of the network. The strategy can take advantage of key nodes when the network is in free flow state, ensure that packets can arrive at their destination faster, protect the key nodes by accurately identifying its importance, and fully use the capabilities of all nodes when the network is in a congestion state, and stop some key nodes from becoming the bottleneck of network. Simulation results show that the proposed local routing strategy can effectively control the network congestion, enhance the network capacity.