Cooperative Channel and Optimized Route Selection in Adhoc Network

Over the last decade,mobile Adhoc networks have expanded dramati-cally in popularity,and their impact on the communication sector on a variety of levels is enormous.Its uses have expanded in lockstep with its growth.Due to its instability in usage and the fact that numerous nodes communicate data concur-rently,adequate channel and forwarder selection is essential.In this proposed design for a Cognitive Radio Cognitive Network(CRCN),we gain the confidence of each forwarding node by contacting one-hop and second level nodes,obtaining reports from them,and selecting the forwarder appropriately with the use of an optimization technique.At that point,we concentrate our efforts on their channel,selection,and lastly,the transmission of data packets via the designated forwarder.The simulation work is validated in this section using the MATLAB program.Additionally,steps show how the node acts as a confident forwarder and shares the channel in a compatible method to communicate,allowing for more packet bits to be transmitted by conveniently picking the channel between them.We cal-culate the confidence of the node at the start of the network by combining the reliability report for thefirst hop and the reliability report for the secondary hop.We then refer to the same node as the confident node in order to operate as a forwarder.As a result,we witness an increase in the leftover energy in the output.The percentage of data packets delivered has also increased.

Fundamental Ideas and Basic Concepts of HSR Route Selection in Complicated Urban Areas

Up till now,no systematic studies on railway route selection in urban areas,HSR route selection in particular,have been taken in China.Based on the Shenzhen Railway Terminal Project and the Shenzhen-Shanwei Railway Project,research on HSR route selection in complicated urban areas has been conducted.An optimal route selection plan is determined after studying the local geological and environmental conditions and the complexity of tunnel construction.The research concludes that there are four major concerns in HSR route selection:the match between the new route and the urban planning,the potential economic return for the massive investment,the likely impacts of land expropriation on social stability,and the best synthesis of multiple controlling factors to meet the HSR standard.Moreover,six principles should be followed in railway route selection in complicated urban areas:the new route should be in alignment with the railway deployment;the route should align with the existing passage as much as possible;extensive analysis and in-depth demonstrations should be done to find the most appropriate combination of open and hidden excavation in tunnel construction;geological conditions and tunnel construction complexities are among the priorities;environmental sensitive sites and environmental vibration noise should be avoided as much as possible;special attention should be paid to the relocation of the power supply,television and communication facilities and the rearrangement of tubes and wires.

A Throughput-Aware Joint Vehicle Route and Access Network Selection Approach Based on SMDP

In intelligent transportation system(ITS), the interworking of vehicular networks(VN) and cellular networks(CN) is proposed to provide high-data-rate services to vehicles. As the network access quality for CN and VN is location related, mobile data offloading(MDO), which dynamically selects access networks for vehicles, should be considered with vehicle route planning to further improve the wireless data throughput of individual vehicles and to enhance the performance of the entire ITS. In this paper, we investigate joint MDO and route selection for an individual vehicle in a metropolitan scenario. We aim to improve the throughput of the target vehicle while guaranteeing its transportation efficiency requirements in terms of traveling time and distance. To achieve this objective, we first formulate the joint route and access network selection problem as a semi-Markov decision process(SMDP). Then we propose an optimal algorithm to calculate its optimal policy. To further reduce the computation complexity, we derive a suboptimal algorithm which reduces the action space. Simulation results demonstrate that the proposed optimal algorithm significantly outperforms the existing work in total throughput and the late arrival ratio.Moreover, the heuristic algorithm is able to substantially reduce the computation time with only slight performance degradation.

Genetic algorithm for pareto optimum-based route selection

A quality of service （QoS） or constraint-based routing selection needs to find a path subject to multiple constraints through a network. The problem of finding such a path is known as the multi-constrained path （MCP） problem, and has been proven to be NP-complete that cannot be exactly solved in a polynomial time. The NPC problem is converted into a multiobjective optimization problem with constraints to be solved with a genetic algorithm. Based on the Pareto optimum, a constrained routing computation method is proposed to generate a set of nondominated optimal routes with the genetic algorithm mechanism. The convergence and time complexity of the novel algorithm is analyzed. Experimental results show that multiobjective evolution is highly responsive and competent for the Pareto optimum-based route selection. When this method is applied to a MPLS and metropolitan-area network, it will be capable of optimizing the transmission performance.

Criterions and Measures of Route Selection of Shallowly Embedded Long-Distance Oil and Gas Pipeline in Mountain Areas

According to the engineering investigation of long-distance oil and gas pipelines, the criterions and measures of route selection are drawn as follows： the flat landform is the first choice in route alignment. The foot of mountain is the first choice when the route passes by the valley. The route should pass by but the shady and deposited slope and not in sunny and erosive slope as possible as it can. The pipeline should be vertical to contour climbing and descending the mountain except steep slope. Tunnel can be used in crossing foothill. Perpendicularly traversing the river is better than beveling; the worst choice is to put the pipeline along the river. Bypass is the best choice in karsts area. The order of route selection should be pre-choosing, investigation, optimization and adjustment.

Research on Greenway Route Selection of Traditional Villages Based on GIS: A Case Study of Xingtai County, China

Greenway is a green linear corridor connecting scenic spots, residential areas, nature reserves, road traffic, etc. Rational greenway route selection can not only attract tourists to increase the income of local villages, but also arouse people’s awareness of the protection of traditional villages. This paper took Xingtai County, Hebei Province, China as an example to practice greenway route selection in the county territory. Eight factors were selected for greenway route planning, namely elevation, water body, mountain, ecological protection redline, cultural relics protection units, population density, road traffic network, and important transportation hub. These eight factors were assigned in the GIS platform, and the suitability evaluation system of each factor was constructed. The analytic hierarchy process (AHP) and entropy weight method were combined to calculate the weight of these eight factors. The raster calculator was used to weight and overlay the suitability evaluation system of each factor, and the comprehensive suitability evaluation map of greenway route selection was obtained. Based on an important transport hub, along with the water body and the road traffic, the final selection greenway route of traditional villages in Xingtai county was formed. The results of the research can provide a certain reference for the greenway route selection at the county scale.

Metaheuristics-based Clustering with Routing Technique for Lifetime Maximization in Vehicular Networks

Recently,vehicular ad hoc networks(VANETs)finds applicability in different domains such as security,rescue operations,intelligent transportation systems(ITS),etc.VANET has unique features like high mobility,limited mobility patterns,adequate topologymodifications,and wireless communication.Despite the benefits of VANET,scalability is a challenging issue which could be addressed by the use of cluster-based routing techniques.It enables the vehicles to perform intercluster communication via chosen CHs and optimal routes.The main drawback of VANET network is the network unsteadiness that results in minimum lifetime.In order to avoid reduced network lifetime in VANET,this paper presents an enhanced metaheuristics based clustering with multihop routing technique for lifetime maximization(EMCMHR-LM)in VANET.The presented EMCMHR-LM model involves the procedure of arranging clusters,cluster head(CH)selection,and route selection appropriate for VANETs.The presentedEMCMHR-LMmodel uses slime mold optimization based clustering(SMO-C)technique to group the vehicles into clusters.Besides,an enhanced wild horse optimization based multihop routing(EWHO-MHR)protocol by the optimization of network parameters.The presented EMCMHR-LMmodel is simulated usingNetwork Simulator(NS3)tool and the simulation outcomes reported the enhanced performance of the proposed EMCMHR-LM technique over the other models.

Fuzzy with Metaheuristics Based Routing for Clustered Wireless Sensor Networks

Wireless sensor network(WSN)plays a vital part in real time tracking and data collection applications.WSN incorporates a set of numerous sensor nodes(SNs)commonly utilized to observe the target region.The SNs operate using an inbuilt battery and it is not easier to replace or charge it.Therefore,proper utilization of available energy in the SNs is essential to prolong the lifetime of the WSN.In this study,an effective Type-II Fuzzy Logic with Butterfly Optimization Based Route Selection(TFL-BOARS)has been developed for clustered WSN.The TFL-BOARS technique intends to optimally select the cluster heads(CHs)and routes in the clustered WSN.Besides,the TFL-BOARS technique incorporates Type-II Fuzzy Logic(T2FL)technique with distinct input parameters namely residual energy(RE),link quality(LKQ),trust level(TRL),inter-cluster distance(ICD)and node degree(NDE)to select CHs and construct clusters.Also,the butterfly optimization algorithm based route selection(BOARS)technique is derived to select optimal set of routes in the WSN.In addition,the BOARS technique has computed afitness function using three parameters such as communication cost,distance and delay.In order to demonstrate the improved energy effectiveness and prolonged lifetime of the WSN,a wide-ranging simulation analysis was implemented and the experimental results reported the supremacy of the TFL-BOARS technique.

Accurate time synchronization of power reference station based on BD3 system

A Beidou 3(BD3)system-based power reference station can provide high-precision time synchronization for power distribution systems by sending synchronization data packets to devices in a multi-hop routing fashion.However,optimizing route selection to reduce both time synchronization error and delay is a challenging problem.In this paper,we establish a software-defined network-enabled power reference station time synchronization framework based on BD3.Then,we formulate the joint problem to minimize cumulative synchronization error and delay through multi-hop route selection optimization.A back propagation(BP)neural network-improved intelligent time synchronization route selection algorithm named BP-RS is proposed to learn the optimal route selection,which uses a BP neural network to dynamically adjust the exploration factor to achieve rapid convergence.Simulation results show the superior performance of BP-RS in synchronization delay,synchronization error,and adaptability with changing routing topologies.

Selection of Surgical Approach and Clinical Significance of Lower Cervical Spine Injuries Guided by SLIC Scoring System

Objective: To explore the feasibility and clinical significance of surgical approach selection for cervical spine injury guided by SLIC scoring system. Methods: The clinical data of 75 patients with lower cervical injury surgery from January 2020 to November 2022 were retrospectively analyzed, including 48 males and 27 females. Age: 28 - 65 years old. Causes of injury: 39 cases of traffic accidents, 15 cases of ice and snow sports, 12 cases of falling from high places, 9 cases of heavy objects. There were 12 cases of C3-4, 33 cases of C4-5, 21 cases of C5-6, and 9 cases of C6-7. Time from injury to medical treatment: 4 h - 2 d. Cervical spine X-ray, MRI, MDCT examination and preoperative SLIC score were performed on admission. Anterior approach was performed by subtotal cervical vertebrae resection or discectomy, titanium Cage or cage supported bone grafting and anterior titanium plate fixation. Posterior approach was performed with cervical laminoplasty, lateral mass or pedicle screw fixation and fusion. The combined anterior-posterior operation was performed by the anterior methods+ posterior methods. The time from injury to surgery is 12 h to 3 d. The function before and after operation was evaluated by JOA efficacy evaluation criteria. The correlation between the three surgical approaches and postoperative efficacy and SLIC score was compared. SPSS 22.0 software was used for statistical analysis of the data. Results: In this group of 75 patients, 32 cases of anterior operation, 22 cases of posterior operation and 21 cases of combined operation were followed up for no less than 12 months. There was no significant difference in age, gender, injury cause, injury segment, time from injury to treatment, and time from injury to operation among the three surgical approaches, which were comparable. The SLIC scores of mild, moderate and severe injuries of anterior surgery, posterior surgery and combined anterior and posterior surgery, They were (5.26 ± 1.24, 5.86 ± 1.67, 8.25 ± 0.21), (5.57 ± 1.43, 5.99 ± 1.85, 9.00 ± 0.25), (0, 5.98 ± 0.33, 9.44 ± 0.34), respectively. By comparing the SLIC scores and JOA scores of anterior surgery and posterior surgery, there was no difference in SLIC scores and JOA scores between the two groups for mild and moderate injuries (P > 0.05). However, the JOA scores at 3 months, 6 months and 12 months after surgery were different from those before surgery, and the postoperative efficacy and JOA scores were significantly improved (P & lt;0.05), indicating that the two surgical methods had the same therapeutic effect, that is, anterior or posterior surgery could be used to treat mild or moderate injuries (P > 0.05). There were differences in SLIC scores among the three surgical approaches for severe injury (P 0.05). The postoperative efficacy and JOA score of combined anterior-posterior approach were significantly improved compared with those before operation (P Conclusion: SLIC score not only provides accurate judgment for conservative treatment or surgical treatment of cervical spine injury, but also provides evidence-based medical basis and reference value for the selection of surgical approach and surgical method. According to the SLIC score, the surgical approach is safe and feasible. When the SLIC score is 4 - 7, anterior surgery is selected for type A injury, and posterior surgery is selected for type B injury. When the SLIC score is ≥8, combined anterior-posterior surgery should be selected. It is of great significance for clinical formulation of precision treatment strategy.

Power Control and Routing Selection for Throughput Maximization in Energy Harvesting Cognitive Radio Networks

This paper investigates the power control and routing problem in the communication process of an energy harvesting(EH)multi-hop cognitive radio network(CRN).The secondary user(SU)nodes(i.e.,source node and relay nodes)harvest energy from the environment and use the energy exclusively for transmitting data.The SU nodes(i.e.,relay nodes)on the path,store and forward the received data to the destination node.We consider a real world scenario where the EH-SU node has only local causal knowledge,i.e.,at any time,each EH-SU node only has knowledge of its own EH process,channel state and currently received data.In order to study the power and routing issues,an optimization problem that maximizes path throughput considering quality of service(QoS)and available energy constraints is proposed.To solve this optimization problem,we propose a hybrid game theory routing and power control algorithm(HGRPC).The EH-SU nodes on the same path cooperate with each other,but EH-SU nodes on the different paths compete with each other.By selecting the best next hop node,we find the best strategy that can maximize throughput.In addition,we have established four steps to achieve routing,i.e.,route discovery,route selection,route reply,and route maintenance.Compared with the direct transmission,HGRPC has advantages in longer distances and higher hop counts.The algorithm generates more energy,reduces energy consumption and increases predictable residual energy.In particular,the time complexity of HGRPC is analyzed and its convergence is proved.In simulation experiments,the performance(i.e.,throughput and bit error rate(BER))of HGRPC is evaluated.Finally,experimental results show that HGRPC has higher throughput,longer network life,less latency,and lower energy consumption.

A Drones Optimal Path Planning Based on Swarm Intelligence Algorithms

The smart city comprises various interlinked elements which communicate data and offers urban life to citizen.Unmanned Aerial Vehicles(UAV)or drones were commonly employed in different application areas like agriculture,logistics,and surveillance.For improving the drone flying safety and quality of services,a significant solution is for designing the Internet of Drones(IoD)where the drones are utilized to gather data and people communicate to the drones of a specific flying region using the mobile devices is for constructing the Internet-of-Drones,where the drones were utilized for collecting the data,and communicate with others.In addition,the SIRSS-CIoD technique derives a tuna swarm algorithm-based clustering(TSA-C)technique to choose cluster heads(CHs)and organize clusters in IoV networks.Besides,the SIRSS-CIoD technique involves the design of a biogeography-based optimization(BBO)technique to an optimum route selection(RS)process.The design of clustering and routing techniques for IoD networks in smart cities shows the novelty of the study.A wide range of experimental analyses is carried out and the comparative study highlighted the improved performance of the SIRSS-CIoD technique over the other approaches.

Some Considerations in Design and Construction of the Wei-Liu Water Supplying Submarine Pipeline

The Wei- Liu water supplying submarine pipeline is at present the longest one of the kind in China. It is about 4 kilometers long from Weihai City to Liugong Island in Shandong province. It took only half a year to design and construct it. The project was of a high economic efficiency and some practical experiences were achieved. In this paper a general introduction to the design and construction of this pipeline is presented and such problems as the stability of the pipeline in very soft clay, design of curved slide for launching and estimation of dragging forces are expounded.

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.

基于Vague集的最优路径选择方法（英文）

Optimal route selection is an important function of vehicle traffic flow guidance system. Its core is to determine the index weight for measuring the route merits and to determine the evaluation method for selecting route. In this paper, subjective weighting method which relies on driver preference is used to determine the weight and the paper proposes the multi-criteria weighted decision method based on vague sets for selecting the optimal route. Examples show that, the usage of vague sets to describe route index value can provide more decision-making information for route selection.

Computing a ground appropriateness index for route selection in permafrost regions

The reasonable calculation of ground appropriateness index in permafrost region is the precondition of highway route design in permafrost region. The theory of knowledge base and fuzzy mathematics are applied, and the damage effect of permafrost is considered in the paper. Based on the idea of protecting permafrost the calculation method of ground appro- priateness index is put forward. Firstly, based on the actual environment conditions, the paper determines the factors affecting the road layout in permafrost areas by qualitative and quantitative analysis, including the annual slope, the average annual ground temperature of permafrost, the amount of ice in frozen soil, and the interference engineering. Secondly, based on the knowledge base theory and the use of Delphi method, the paper establishes the knowledge base, the rule base of the permafrost region and inference mechanism. The method of selecting the road in permafrost region is completed and realized by using the software platform. Thirdly, taking the Tuotuo River to Kaixin Mountain section of permafrost region as an example, the application of the method is studied by using an ArcGIS platform. Results show that the route plan determined by the method of selecting the road in perma-frost region can avoid the high temperature and high ice content area, conform the terrain changes and evade the heat disturbance among the existing projects. A reasonable route plan can be achieved, and it can provide the basis for the next engineering construction.

An Improved Immune Genetic Algorithm for Solving the Optimization Problems of Computer Communication Networks

Obtaining the average delay and selecting a route in a communication networkare multi-constrained nonlinear optimization problems . In this paper, based on the immune geneticalgorithm, a new fuzzy self-adaptive mutation operator and a new upside-down code operator areproposed. This improved IGA is further successfully applied to solve optimal problems of computercommunication nets.

Immune Algorithm for Solving the Optimization Problems of Computer Communication Networks

The basic problem in optimizing communication networks is to assign a proper circuit for each origin destination pair in networks so as to minimize the average network delay, and the network optimal route selection model is a multi constrained 0 1 nonlinear programming problem. In this paper, a new stochastic optimization algorithm, Immune Algorithm, is applied to solve the optimization problem in communication networks. And the backbone network vBNS is chosen to illustrate the technique of evaluating delay in a virtual network. At last, IA is compared with the optimization method in communication networks based on Genetic Algorithm, and the result shows that IA is better than GA in global optimum finding.