Reliable Braided Multipath Routing with Network Coding for Underwater Sensor Networks

Owing to the long propagation delay and high error rate of acoustic channels, it is very challenging to provide reliable data transfer for underwater sensor networks. Moreover, network coding is proved to be an effective coding technique for throughput and robustness of networks. In this paper, we propose a Reliable Braided Multipath Routing with Network Coding for underwater sensor networks （RBMR-NC）. Disjoint multi-path algorithm is used to build independent actual paths, as called main paths. Some braided paths on each main path are built according to the braided multi-path algorithm, which are called logic paths. When a data packet is transmitted by these nodes, the nodes can employ network coding to encode packets coming from the same group in order to further reduce relativity among these packets, and enhance the probability of successful decoding at the sink node. Braided multi-path can make the main paths to be multiplexed to reduce the probability of long paths. This paper mainly employs successful delivery rate to evaluate RBMR-NC model with theoretical analysis and simulation methods. The results indicate that the proposed RBMR-NC protocol is valuable to enhance network reliability and to reduce system redundancy.

AN OPTIMUM VEHICULAR PATH ALGORITHM FOR TRAFFIC NETWORK BASED ON HIERARCHICAL SPATIAL REASONING

Human beings’ intellection is the characteristic of a distinct hierarchy and can be taken to construct a heuristic in the shortest path algorithms.It is detailed in this paper how to utilize the hierarchical reasoning on the basis of greedy and directional strategy to establish a spatial heuristic,so as to improve running efficiency and suitability of shortest path algorithm for traffic network.The authors divide urban traffic network into three hierarchies and set forward a new node hierarchy division rule to avoid the unreliable solution of shortest path.It is argued that the shortest path,no matter distance shortest or time shortest,is usually not the favorite of drivers in practice.Some factors difficult to expect or quantify influence the drivers’ choice greatly.It makes the drivers prefer choosing a less shortest,but more reliable or flexible path to travel on.The presented optimum path algorithm,in addition to the improvement of the running efficiency of shortest path algorithms up to several times,reduces the emergence of those factors,conforms to the intellection characteristic of human beings,and is more easily accepted by drivers.Moreover,it does not require the completeness of networks in the lowest hierarchy and the applicability and fault tolerance of the algorithm have improved.The experiment result shows the advantages of the presented algorithm.The authors argued that the algorithm has great potential application for navigation systems of large_scale traffic networks.

Optimal paths planning in dynamic transportation networks with random link travel times

A theoretical study was conducted on finding optimal paths in transportation networks where link travel times were stochastic and time-dependent(STD). The methodology of relative robust optimization was applied as measures for comparing time-varying, random path travel times for a priori optimization. In accordance with the situation in real world, a stochastic consistent condition was provided for the STD networks and under this condition, a mathematical proof was given that the STD robust optimal path problem can be simplified into a minimum problem in specific time-dependent networks. A label setting algorithm was designed and tested to find travelers' robust optimal path in a sampled STD network with computation complexity of O(n2+n·m). The validity of the robust approach and the designed algorithm were confirmed in the computational tests. Compared with conventional probability approach, the proposed approach is simple and efficient, and also has a good application prospect in navigation system.

Dynamic Shortest Path Algorithm in Stochastic Traffic Networks Using PSO Based on Fluid Neural Network

The shortest path planning issure is critical for dynamic traffic assignment and route guidance in intelligent transportation systems. In this paper, a Particle Swarm Optimization (PSO) algorithm with priority-based encoding scheme based on fluid neural network (FNN) to search for the shortest path in stochastic traffic networks is introduced. The proposed algorithm overcomes the weight coefficient symmetry restrictions of the traditional FNN and disadvantage of easily getting into a local optimum for PSO. Simulation experiments have been carried out on different traffic network topologies consisting of 15-65 nodes and the results showed that the proposed approach can find the optimal path and closer sub-optimal paths with good success ratio. At the same time, the algorithms greatly improve the convergence efficiency of fluid neuron network.

A modification of local path marginal cost on the dynamic traffic network

Path marginal cost （PMC） is the change in totaltravel cost for flow on the network that arises when timedependentpath flow changes by 1 unit. Because it is hardto obtain the marginal cost on all the links, the local PMC,considering marginal cost of partial links, is normallycalculated to approximate the global PMC. When analyzingthe marginal cost at a congested diverge intersection, ajump-point phenomenon may occur. It manifests as alikelihood that a vehicle may unsteadily lift up （down） inthe cumulative flow curve of the downstream links. Previously,the jump-point caused delay was ignored whencalculating the local PMC. This article proposes an analyticalmethod to solve this delay which can contribute toobtaining a more accurate local PMC. Next to that, we usea simple case to calculate the previously local PMC and themodified one. The test shows a large gap between them,which means that this delay should not be omitted in thelocal PMC calculation.

MRBCH: A Multi-Path Routing Protocol Based on Credible Cluster Heads for Wireless Sensor Networks

Wireless sensor networks are widely used for its flexibility, but they also suffer from problems like limited capacity, large node number and vulnerability to security threats. In this paper, we propose a multi-path routing protocol based on the credible cluster heads. The protocol chooses nodes with more energy remained as cluster heads at the cluster head choosing phase, and then authenticates them by the neighbor cluster heads. Using trust mechanisms it creates the credit value, and based on the credit value the multi-path cluster head routing can finally be found. The credit value is created and exchanged among the cluster heads only. Theoretical analysis combined with simulation results demonstrate that this protocol can save the resource, prolong the lifetime, and ensure the security and performance of the network.

The Shortest Path Analysis Based on Road Network

Rational planning of agricultural product transport route from initial node to destination node can effectively reduce the cost price of agricultural products,and the calculation of shortest path between any two points also affects people’s daily travel.Taking Heze Railway Station to Heze College for example,with remote sensing image data as the base map,we conduct vectorization and topological analysis on roads in the target area.With Dijkstra as theoretical basis of shortest path algorithm,we use ArcG IS network analysis method to build road network,and calculate the planning program of the shortest distance path,the shortest path by driving and the shortest path by walking.

Finding Multiple Length-Bounded Disjoint Paths in Wireless Sensor Networks

In a wireless sensor network, routing messages between two nodes s and t with multiple disjoint paths will increase the throughput, robustness and load balance of the network. The existing researches focus on finding multiple disjoint paths connecting s and t efficiently, but they do not consider length constraint of the paths. A too long path will be useless because of high latency and high packet loss rate. This paper deals with such a problem: given two nodes s and t in a sensor network, finding as many as possible disjoint paths connecting s and t whose lengths are no more than L, where L is the length bound set by the users. By now, we know that this problem is not only NP hard but also APX complete [1,2], which means that there is no PTAS for this problem. To the best of our knowledge, there is only one heuristic algorithm proposed for this problem [3], and it is not suitable for sensor network because it processes in a centralized way. This paper proposes an efficient distributed algorithm for this problem. By processing in a distributed way, the algorithm is very communication efficient. Simulation results show that our algorithm outperforms the existing algorithm in both aspects of found path number and communication efficiency.

Shortest Path Routing Algorithm Based on Chaotic Neural Network

A shortest path routing algorithm based on transient chaotic neural network is proposed in this paper. Gam-pared with previous models adopting Hopfield neural network, this algorithm has a higher ability to overcome the local minimum, and achieves a better performance. By introducing a special post-processing technique for the output matrixes, our algorithm can obtain an optimal solution with a high probability even for the paths that need more hops in large-size networks.

Generalized minimum information path routing strategy on scale-free networks

This paper presents a new routing strategy by introducing a tunable parameter into the minimum information path routing strategy we proposed previously. It is found that network transmission capacity can be considerably enhanced by adjusting the parameter with various allocations of node capability for packet delivery. Moreover, the proposed routing strategy provides a traffic load distribution which can better match the allocation of node capability than that of traditional efficient routing strategies, leading to a network with improved transmission performance. This routing strategy, without deviating from the shortest-path routing strategy in the length of paths too much, produces improved performance indexes such as critical generating rate, average length of paths and average search information.

3D multipath planning for UAV based on network graph

According to the characteristic and the requirement of multipath planning, a new multipath planning method is proposed based on network. This method includes two steps： the construction of network and multipath searching. The construction of network proceeds in three phases： the skeleton extraction of the configuration space, the judgment of the cross points in the skeleton and how to link the cross points to form a network. Multipath searching makes use of the network and iterative penalty method （IPM） to plan multi-paths, and adjusts the planar paths to satisfy the requirement of maneuverability of unmanned aerial vehicle （UAV）. In addition, a new height planning method is proposed to deal with the height planning of 3D route. The proposed algorithm can find multiple paths automatically according to distribution of terrain and threat areas with high efficiency. The height planning can make 3D route following the terrain. The simulation experiment illustrates the feasibility of the proposed method.

SOPA:Source Routing Based Packet-Level Multi-Path Routing in Data Center Networks

Many ＂rich - connected＂ topologies with multiple parallel paths between smwers have been proposed for data center networks recently to provide high bisection bandwidth, but it re mains challenging to fully utilize the high network capacity by appropriate multi- path routing algorithms. As flow-level path splitting may lead to trafl＇ic imbalance between paths due to flow- size difference, packet-level path splitting attracts more attention lately, which spreads packets from flows into multiple available paths and significantly improves link utilizations. However, it may cause packet reordering, confusing the TCP congestion control algorithm and lowering the throughput of flows. In this paper, we design a novel packetlevel multi-path routing scheme called SOPA, which leverag- es OpenFlow to perform packet-level path splitting in a round- robin fashion, and hence significantly mitigates the packet reordering problem and improves the network throughput. Moreover, SOPA leverages the topological feature of data center networks to encode a very small number of switches along the path into the packet header, resulting in very light overhead. Compared with random packet spraying （RPS）, Hedera and equal-cost multi-path routing （ECMP）, our simulations demonstrate that SOPA achieves 29.87%, 50.41% and 77.74% higher network throughput respectively under permutation workload, and reduces average data transfer completion time by 53.65%, 343.31% and 348.25% respectively under production workload.

Novel multi-path routing scheme for UWB Ad hoc network

The routing protocols play an important role for ad hoc networks performance.As some problems with DSR,SMR,and AMR protocols were analyzed,a new routing protocol suitable for UWB Ad hoc networks was proposed in this paper.The new routing protocol utilize an act of orientation of UWB and tries to get sufficient route information and decrease the network load caused by route discovery at the same time.Simulation results show that the routing load of the new protocol is lower and throughput is higher than that of DSR.While the node’s mobility increases,these advantages become more obvious.

Multi-Path Routing and Resource Allocation in Active Network

An algorithm of traffic distribution called active multi-path routing (AMR)in active network is proposed. AMR adopts multi-path routing and applies nonlinear optimizeapproximate method to distribute network traffic among multiple paths. It is combined to bandwidthresource allocation and the congestion restraint mechanism to avoid congestion happening and worsen.So network performance can be improved greatly. The frame of AMR includes adaptive trafficallocation model, the conception of supply bandwidth and its' allocation model, the principle ofcongestion restraint and its' model, and the implement of AMR based on multi-agents system in activenetwork. Through simulations, AMR has distinct effects on network performance. The results show AMRisa valid traffic regulation algorithm.

System Vulnerability Analysis Using Graph Pathfinding Strategies in Partitioned Networks

In this paper, a new method has been introduced to find the most vulnerable lines in the system dynamically in an interconnected power system to help with the security and load flow analysis in these networks. Using the localization of power networks, the power grid can be divided into several divisions of sub-networks in which, the connection of the elements is stronger than the elements outside of that division. By using our proposed method, the probable important lines in the network can be identified to do the placement of the protection apparatus and planning for the extra extensions in the system. In this paper, we have studied the pathfinding strategies in most vulnerable line detection in a partitioned network. The method has been tested on IEEE39-bus system which is partitioned using hierarchical spectral clustering to show the feasibility of the proposed method.

A self-organizing shortest path finding strategy on complex networks

The shortcomings of traditional methods to find the shortest path are revealed, and a strategy of finding the self- organizing shortest path based on thermal flux diffusion on complex networks is presented. In our method, the shortest paths between the source node and the other nodes are found to be self-organized by comparing node temperatures. The computation complexity of the method scales linearly with the number of edges on underlying networks. The effects of the method on several networks, including a regular network proposed by Ravasz and Barabasi which is called the RB network, a real network, a random network proposed by Ravasz and Barabasi which is called the ER network and a scale-free network, are also demonstrated. Analytic and simulation results show that the method has a higher accuracy and lower computational complexity than the conventional methods.

城市游径网络的非连续路段识别及空间活力推演

自组织游径网络的活力提升是城市更新规划的重要目标。由于老城区游径网络存在不连续性和断头路现象,居民游憩活动的舒适性受到了挑战,而游径网络的自组织性意味着自上而下的规划设计模式难以匹配市民需求。如何自下而上地推演游憩规划的空间活力,进而识别潜力地块,是提升城市游径网络品质的重要命题。文中以广州市老城区为案例,基于复杂网络理论,构建游径网络的非连续性和空间活力测度指标;以GPS轨迹数据识别既有游径网络的非连续区段,定量探讨了基于市民游憩行为的非连续路段空间的识别和城市更新改造项目的活化作用,推演更新项目实施带来的潜在影响。游径网络的非连续性分析表明,当前广州市老城区游径路段的非连续度总体较低,连接程度较好,但由于区位和历史遗留问题,仍有部分路段存在明显的非连续现象。城市游径网络的空间活力推演结果表明,城市更新项目对自组织游径网络会产生一定的正面影响,可依据推演分析来判定城市游憩品质提升项目的实施计划和日程。本研究从规划和交通维度出发,对城市的自组织特性进行了有益探索,弥补了“自上而下”式规划对城市自组织游径网络考虑不足的缺陷。

基于最优独立通路的通风网络调节位置优化

独立通路在通风网络中具有重要的作用,寻找一种能够快速搜索复杂网络独立通路的算法具有重要意义。采用通路法进行网络调节可以优化通风网络的调节效果。传统的通路搜索算法搜索的通路一般较长,无法处理特殊网络的搜索问题且无法同时保证通路的独立性和完备性。为了解决传统通路搜索算法存在的问题,系统研究了独立通路搜索的关键技术,在分析传统通路搜索算法局限性的基础上,提出了1种改进的独立通路搜索算法。该算法处理了网络中的割边、割点问题,避免了算法陷入死循环或异常中断;结合BFS法改进了通路搜索的性能,便于控制通路中关键分支的搜索;分析独立通路完备性搜索失败的原因,并通过记忆搜索策略解决了含有单向回路的通路搜索问题。利用改进的独立通路搜索算法,提出了1种自适应通路调节法,该方法可以获得1棵具有最优调节位置的最佳通路调节树,从而得到一组最优增阻调节解。

从场空间到流网络:粤港澳大湾区城市群空间结构特征及优化路径研究

检视粤港澳大湾区城市群空间结构演化趋势,对纵深推动大湾区高质量发展意义重大。本研究因应数字经济对区域要素流动结构的影响,提出粤港澳大湾区“流网络”分析框架,并以首位度和齐普夫法则测度传统空间结构特征,以上市企业的“总部—分支”机构分布测度流网络特征。结果表明:大湾区总体经历了先集聚再分散的发展过程;各城市人口分布梯度不合理,核心城市的人口扩张推动了城市群的定型。大湾区经济规模结构呈现帕累托分布模式,各城市经济规模变差较大。从城际联系来看,广州深圳之间具有高联通度,形成了联通走廊,2000年以来深圳的相对联通度高居首位,区域网络日渐完善。未来,应织密高效的综合交通网络,加速市场一体化进程、构建“双核三圈”网络型城市群体系、设立“广深接合片区”并加快打造“广深联动走廊”,开创大湾区高质量协同发展新格局。