MTCR-CR Routing Strategy for Connection-Oriented Routing over Satellite Networks

The high-speed movement of satellites makes it not feasible to directly apply the mature routing scheme on the ground to the satellite network.DT-DVTR in the snapshot-based connectionoriented routing strategy is one of the representative solutions,but it still has room for improvement in terms of routing stability.In this paper,we propose an improved scheme for connection-oriented routing strategy named the Minimal Topology Change Routing based on Collaborative Rules(MTCR-CR).The MTCR-CR uses continuous time static topology snapshots based on satellite status to search for intersatellite link(ISL)construction solutions that meet the minimum number of topology changes to avoid route oscillations.The simulation results in Beidou-3 show that compared with DT-DVTR,MTCR-CR reduces the number of routing changes by about 92%,the number of path changes caused by routing changes is about38%,and the rerouting time is reduced by approximately 47%.At the same time,in order to show our algorithm more comprehensively,the same experimental index test was also carried out on the Globalstar satellite constellation.

Improved routing strategy based on gravitational field theory

Routing and path selection are crucial for many communication and logistic applications. We study the interaction between nodes and packets and establish a simple model for describing the attraction of the node to the packet in transmission process by using the gravitational field theory, considering the real and potential congestion of the nodes. On the basis of this model, we propose a gravitational field routing strategy that considers the attractions of all of the nodes on the travel path to the packet. In order to illustrate the efficiency of proposed routing algorithm, we introduce the order parameter to measure the throughput of the network by the critical value of phase transition from a free flow phase to a congested phase,and study the distribution of betweenness centrality and traffic jam. Simulations show that, compared with the shortest path routing strategy, the gravitational field routing strategy considerably enhances the throughput of the network and balances the traffic load, and nearly all of the nodes are used efficiently.

Migration routes and differences in migration strategies of Whooper Swans between spring and autumn

Long-distance migratory birds travel more rapidly in spring than in autumn,as they face temporal breeding constraints.However,several species travel slower in spring owing to environmental influences,such as food availability and wind conditions.GPS trackers were attached to 17 Whooper Swans(Cygnus cygnus) inhabiting northeastern Mongolia,to determine their migration routes and stopover sites in spring and autumn.Differences between spring and autumn migrations,migration-influencing parameters,and the effect of spring stopover site temperatures were analyzed.Six swans completed perfect tours between their wintering and breeding sites,and these data were used for analysis.Spring migration lasted 57 days,with 49.2 days spent at 3.7 stopover sites.Autumn migration lasted 21.5 days,with 17.5 days spent at 1.0 stopover sites.Thus,the swans traveled more rapidly in autumn than in spring.Migration distance,number of stopovers,migration speed,and straightness were important migration determinants in both spring and autumn.Migration distance,stopover duration,number of stopovers,daily travel speed,travel duration,and migration speed differed significantly between spring and autumn.During spring migration,the temperature at the current stopover sites and that at the future stopover sites displayed significant variations(t=1585.8,df=631.6,p <0.001).These findings are critical for the conservation and management of Whooper Swans and their key habitats in East Asian regions,and the data are anticipated to make a particularly significant contribution toward developing detailed management plans for the conservation of their key habitats.

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.

A Contention-Based MAC and Routing Protocol for Wireless Sensor Network

Advance development of wireless technologies and micro-sensor systems have enabled Wireless Sensor Network (WSN) to emerge as a leading solution in many crucial sensor-based applications. WSN deploys numerous resource-constrained sensor nodes which have limited power supply, memory and computation capability in a harsh environment. Inefficient routing strategy results in degraded network performance in terms of reliability, latency and energy efficiency. In this paper, a cross-layer design, Contention-based MAC and Routing protocol is proposed, termed Contention/SNIR-Based Forwarding (CSBF) protocol. CSBF utilizes the geographical information of sensor nodes to effectively guide the routing direction towards destination node, thereby enhancing reliability. Furthermore, Signal-to-Noise-plus-Interference Ratio (SNIR) metric is used as a routing parameter to guarantee high quality link for data transmission. A Contention-Winner Relay scheme is utilized to reduce the delays caused by the contention procedure. Energy efficiency is also improved by introducing sleep mode technique in CSBF. The simulation work is carried out via OMNeT++ network simulator. The performance of CSBF is compared with other existing routing protocols such as AODV and DSDV in terms of packet delivery ratio (PDR), average end-to-end (ETE) delay and energy consumption per packet. Simulation results highlight that CSBF outperforms AODV and DSDV protocols in respect of PDR and energy efficiency. CSBF also has the most consistent overall network performance.

Design Strategies of Expressway Routes and Interchanges

Road traffic conditions can have an important impact on the economic development of various regions.Under the background of rapid social and economic development,more and more expressway construction projects are initiated in various regions,including both new expressways and expansion of old expressways,and interchange design plays an important role.Scientific and reasonable interchange design can not only realize energy saving and low carbon footprint,but also be people-oriented and promote regional economic development.Therefore,this paper mainly analyzes the highway route and its interchange design strategy for reference.

Super Node Routing Strategy in Content-Centric Networking

There were two strategies for the data forwarding in the content-centric networking(CCN): forwarding strategy and routing strategy. Forwarding strategy only considered a separated node rather than the whole network performance, and Interest flooding led to the network overhead and redundancy as well. As for routing strategy in CCN, each node was required to run the protocol. It was a waste of routing cost and unfit for large-scale deployment.This paper presents the super node routing strategy in CCN. Some super nodes selected from the peer nodes in CCN were used to receive the routing information from their slave nodes and compute the face-to-path to establish forwarding information base(FIB). Then FIB was sent to slave nodes to control and manage the slave nodes. The theoretical analysis showed that the super node routing strategy possessed robustness and scalability, achieved load balancing,reduced the redundancy and improved the network performance. In three topologies, three experiments were carried out to test the super node routing strategy. Network performance results showed that the proposed strategy had a shorter delay, lower CPU utilization and less redundancy compared with CCN.

Optimized routing strategy for complex network with multiple priorities

Different loads in the network require distinct Qo S standard, while present routing strategies for complex networks ignored this fact. To solve this problem, we designed a routing strategy RS-MP with multiple priorities by which packets are classified into privileged-packets and common-packets. In RS-MP, privileged-packets route by the Shortest Path Algorithm, and do not need to queue up. Common-packets＇ routes are determined by a new factor BJmax of the network. The BJmax stands for the largest betweenness centrality. By minimizing BJmax, the throughout capacity of the network can be maximized. The simulation results show that RS-MP can guarantee privileged-packets with the shortest path length and smallest delay, and maximized throughout capacity for common packets in the no-congestion state.

Load Balance Strategy of Data Routing Algorithm Using Semantics for Deduplication Clusters

The backup requirement of data centres is tremendous as the size of data created by human is massive and is increasing exponentially.Single node deduplication cannot meet the increasing backup requirement of data centres.A feasible way is the deduplication cluster,which can meet it by adding storage nodes.The data routing strategy is the key of the deduplication cluster.DRSS（data routing strategy using semantics） improves the storage utilization of MCS（minimum chunk signature） data routing strategy a lot.However,for the large deduplication cluster,the load balance of DRSS is worse than MCS.To improve the load balance of DRSS,we propose a load balance strategy used for DRSS,namely DRSSLB.When a node is overloaded,DRSSLB iteratively migrates the current smallest container of the node to the smallest node in the deduplication cluster until this overloaded node becomes non-overloaded.A container is the minimum unit of data migration.Similar files sharing the same features or file names are stored in the same container.This ensures the similar data groups are still in the same node after rebalancing the nodes.We use the dataset from the real world to evaluate DRSSLB.Experimental results show that,for various numbers of nodes of the deduplication cluster,the data skews of DRSSLB are under predefined value while the storage utilizations of DRSSLB do not nearly increase compared with DRSS,with the low penalty（the data migration rate is only6.5% when the number of nodes is 64）.

Adaptive Agent Model with Hybrid Routing Selection Strategy for Improving the Road-Network Congestion Problem

This paper proposes an adaptive agent model with a hybrid routing selection strategy for studying the road-network congestion problem. We focus on improving those severely congested links. Firstly,a multi-agent system is built,where each agent stands for a vehicle,and it makes its routing selection by considering the shortest path and the minimum congested degree of the target link simultaneously. The agent-based model captures the nonlinear feedback between vehicle routing behaviors and road-network congestion status.Secondly,a hybrid routing selection strategy is provided,which guides the vehicle routes adapting to the realtime road-network congestion status. On this basis, we execute simulation experiments and compare the simulation results of network congestion distribution,by Floyd agent with shortest path strategy and our proposed adaptive agent with hybrid strategy. The simulation results show that our proposed model has reduced the congestion degree of those seriously congested links of road-network. Finally,we execute our model on a real road map. The results finds that those seriously congested roads have some common features such as located at the road junction or near the unique road connecting two areas. And,the results also show an effectiveness of our model on reduction of those seriously congested links in this actual road network. Such a bottom-up congestion control approach with a hybrid congestion optimization perspective will have its significance for actual traffic congestion control.

Ants-Based On-Demand Routing Algorithm for Mobile Ad Hoc Networks

An ants-based on-demand routing algorithm （AORA） specialized for mobile ad hoc networks is proposed. AORA measures the network＇s traffic information including delivery time, route energy etc. by the continuous delivery of data packets, then calculates the compositive parameter for each route which can be seen as the stigmity and uses it to choose the comparatively optimal route in real time. To adjust the weight of each traffic information, the algorithm can meet the different demand of the network＇s user. Multipath source self repair routing （MSSRR） algorithm and dynamic source routing （DSR） can be seen as the special samples of AORA. The routing overhead is not increased in this algorithm. By using simulation, it can be seen that the performance of AORA is better than that of DSR in all scenarios obviously, especially the delivery fraction is increased by more than 100 96.

An Investigation on the Effect of Migration Strategy on Parallel GA-Based Shortest Path Routing Algorithm

Genetic algorithm (GA) is one of the alternative approaches for solving the shortest path routing problem. In previous work, we have developed a coarse-grained parallel GA-based shortest path routing algorithm. With parallel GA, there is a GA operator called migration, where a chromosome is taken from one sub-population to replace a chromosome in another sub-population. Which chromosome to be taken and replaced is subjected to the migration strategy used. There are four different migration strategies that can be employed: best replace worst, best replace random, random replace worst, and random replace random. In this paper, we are going to evaluate the effect of different migration strategies on the parallel GA-based routing algorithm that has been developed in the previous work. Theoretically, the migration strategy best replace worst should perform better than the other strategies. However, result from simulation shows that even though the migration strategy best replace worst performs better most of the time, there are situations when one of the other strategies can perform just as well, or sometimes better.

Topology Control for Ad-Hoc Networks: A Comprehensive Review for Table Driven and On-Demand Routing Protocols

Routing on ad-hoc network has become a major research issue among the networking communities due to its increasing complexity and the surge of challenging problems. One major factor contributing to this tendency is that every terminal of an ad-hoc network is also functioning as a network router. In this paper we provide a comprehensive review about the principles and mechanisms of routing protocols used in ad-hoc networks. For comparison purposes, we discuss some relevant technical issues of two well-known routing strategies, namely On-Demand (Proactive routing) and Table-Driven (Reactive routing). In particular, focus our attention on two major and well-known routing protocols: AODV (Ad-hoc On-Demand Distance Vector Protocol) and OLSR (Optimized Link State Routing Protocol). Our study has no intention to suggest any definite solution for any ad-hoc network, because it is the case depending on dictated by the nature and varying factors of networks. Instead, we demonstrate our major perception and describe general models that may assist us while modeling a given network.

Manual Order Picking Route Optimization in Distribution Warehouse of Chain Furniture Retail Enterprise

Due to the effects of the COVID-19 pandemic and the rise of online shopping, the offline sales of IKEA Fuzhou have been declining since 2020. Because the cost of distribution warehouse is a major expense for offline chain furniture retailers, and the picking process is a key activity in distribution warehouse operations. To reduce the cost of distribution warehouse and alleviate the survival pressure of the offline chain furniture retailers, this paper focuses on optimizing the picking route of the IKEA Fuzhou distribution warehouse. It starts by creating a two-dimensional coordinate system for the storage location of the distribution warehouse using the traditional S-type picking strategy to calculate the distance and time of the sorting route. Then, the problem of optimizing the picking route is then transformed into the travelling salesman problem (TSP), and picking route optimization model is developed using a genetic algorithm to analyze the sorting efficiency and picking route optimization. Results show that the order-picking route using the genetic algorithm strategy is significantly better than the traditional S-type picking strategy, which can improve overall sorting efficiency and operations, reduce costs, and increase efficiency. Thus, this establishes an implementation process for the order-picking path based on genetic algorithm optimization to improve overall sorting efficiency and operations, reduce costs, increase efficiency, and alleviate the survival pressure of pandemic-affected enterprises.

INCENTIVE MECHANISMS FOR TRUSTWORTHY ROUTING BASED ON GAME MODEL OF THE STRATEGIES OF NODES IN P2P NETWORKS

The trustworthiness and security of routing in the existing Peer-to-Peer (P2P) networks can not be ensured because of the diversity of the strategies of P2P nodes. This paper firstly uses game theory to establish game model of the strategies and profits of various types of routing nodes. Then,two incentive mechanisms for the corresponding stages of P2P trustworthy routing are proposed,namely trust associated mechanism and trust compensated mechanism. Simulation results show that the incentive mechanisms proposed in this paper will encourage cooperation actions of good nodes and restrain malicious actions of bad nodes,which ensure the trustworthiness of routing consequently.

Route strategy of satellite network in GNSS based on topology evolution law

As each type of satellite network has different link features, its data transmission must be designed based on its link features to improve the efficiency of data transferring. The transmission of navigation integrated services information （NISI） in a global navigation satellite system （GNSS） with inter-satellite links （ISLs） is studied by taking the real situation of inter-satellite communication links into account. An on-demand computing and buffering centralized route strategy is proposed based on dynamic grouping and the topology evolution law of the GNSS network within which the satellite nodes are operated in the manner of dynamic grouping. Dynamic grouping is based on satellites spatial relationships and the group role of the satellite node changes by turns due to its spatial relationships. The route strategy provides significant advantages of high efficiency, low complexity, and flexi- ble configuration, by which the established GNSS can possess the features and capabilities of feasible deployment, efficient transmission, convenient management, structural invulnerability and flexible expansion.

Improved Multicast Protocol Based on Routing Grid

Problems may occur in ad hoc network when packets are being multieast. Global routing structure may also produce extra processing cost because the dynamic topology will introduce frequent exchange of routing vector or routing state between nodes. To deal with these problems an improved multicast protocol based on routing grid is designed to ensure that the muhicast packets could be sent to destination through dynamic topology network using muhicast routing grid.

Global forward-predicting dynamic routing for traffic concurrency space stereo multi-layer scale-free network

Many real communication networks, such as oceanic monitoring network and land environment observation network,can be described as space stereo multi-layer structure, and the traffic in these networks is concurrent. Understanding how traffic dynamics depend on these real communication networks and finding an effective routing strategy that can fit the circumstance of traffic concurrency and enhance the network performance are necessary. In this light, we propose a traffic model for space stereo multi-layer complex network and introduce two kinds of global forward-predicting dynamic routing strategies, global forward-predicting hybrid minimum queue（HMQ） routing strategy and global forward-predicting hybrid minimum degree and queue（HMDQ） routing strategy, for traffic concurrency space stereo multi-layer scale-free networks. By applying forward-predicting strategy, the proposed routing strategies achieve better performances in traffic concurrency space stereo multi-layer scale-free networks. Compared with the efficient routing strategy and global dynamic routing strategy, HMDQ and HMQ routing strategies can optimize the traffic distribution, alleviate the number of congested packets effectively and reach much higher network capacity.

Energy Aware Routing Protocol for Cognitive Radio Networks

In this article, a routing protocol EARP (Energy Aware Routing Protocol) with the terminal node is proposed, to deal with the impact of the limited energy resources of Cognitive Radio Networks on the whole network routing. The protocol allows choosing the route from the neighbor nodes in different transmission paths, according to energy consumption of a single node and the full path. If the path breaks, the protocol will increase local routing maintenance strategy. It effectively reduces the retransmission caused by the situation, and improves the routing efficiency. It also can prevent the link transmission process selecting the fault route due to the energy depletion. Through simulation experiments compared with the LEACH (Low Energy Adaptive Clustering Hierarchy) routing protocol, the results showed that in the same experimental environment, the proposed EARP could obviously balance the load, protect low energy nodes, prolong the network survival time and reduce packet loss rate and packet delay of data delivery. So it can improve the energy consumption of sensing node and provide routing capabilities.

A ROUTING PROTOCOL BASED ON INTERFERENCE-AWARE AND CHANNEL-LOAD IN MULTI-RADIO MULTI-CHANNEL AD HOC NETWORKS

Improving capacity and reducing delay are the most challenging topics in wireless ad hoc networks. Nodes that equip multiple radios working on different channels simultaneously permit ef-fective utility of frequency spectrum and can also reduce interference. In this paper, after analyzing several current protocols in Multi-Radio Multi-Channel (MR-MC) ad hoc networks, a new multi-channel routing metric called Integrative Route Metric (IRM) is designed. It takes channel load, inter-flow, and intra-flow interference into consideration. In addition, an MR-MC routing protocol based on Interference-Aware and Channel-Load (MR-IACL) is also presented. The MR-IACL can assign channels and routings for nodes according to channel load and interference degree of links, and optimize channel distribution dynamically to satisfy the features of topology changing and traffic frequent fluctuation during network running. The simulation results show that the new protocol outperforms others in terms of network throughput, end-to-end delay, routing overhead, and network lifetime.