Routing Structure Research Articles

WINDMILL: A Scalable Multicast Routing Protocol for Mobile Ad-Hoc Networks

Multicasting supports various applications that need a high collaboration and require data transmission to numerous destinations concurrently. In environments where nodes are continuously moving, as in mobile Ad-hoc networks, seeking efficient routes from a specific source leading to anticipated destinations became an important issue. In this paper a novel scalable multicast routing procedure for mobile Ad-hoc networks is proposed. Our new protocol, WINDMILL, tries to improve performance by introducing a hierarchal routing algorithm and dealing with the area as zones. Furthermore, WINDMILL tries to demonstrate better scalability, performance and robustness through applying the restricted directional flooding. WINDMILL utilizes the network partitioning to forward the route request and reply packets in an efficient way and avoid forwarding duplicate packets. A qualitative comparison between WINDMILL, multicast Ad-hoc on-demand distance vector (MAODV), on-demand multicast routing protocol (ODMRP) and location aware multicasting protocol (LAMP) protocols is presented in this paper. This comparison has considered the used routing category, main contribution, routing structure and network structure maintenance, request and reply packets sending mechanisms, route activation time, selected routes length, and data packet copies number. Our investigation reveals that WINDMILL will be able to achieve scalability by attaining reduced control overhead and low number of data packets copies even within large networks. Hence, WINDMILL can be a good choice for multicasting in Ad-hoc networks established for example among students on a campus or soldiers in a battlefield, where scalability is a key issue.

Design of travel route recommendation system based on fast Spark artificial intelligence architecture

In order to overcome the problems of low accuracy of current system tourism route prediction and poor accuracy of route recommendation, this paper proposes a tourism route recommendation system design based on fast Spark artificial intelligence architecture. In the hardware part, the search process structure of tourist route, web page information classification and extraction module and tourist document classification process structure are designed. For the software part, firstly the problem is defined for the tourist route recommendation, secondly the Markov model is constructed, and finally the tourist route is mined. By ranking the transfer probability of tourist attractions, the tourist route can be obtained, and finally the tourist route recommendation is realised. The experimental results show that the designed system has a prediction accuracy of more than 70% and a recommendation accuracy of more than 80%, with high prediction accuracy and route recommendation accuracy.

Сегментная маршрутизация как основа программно-конфигурируемой сети

In this article the structure, main components and functioning of Segment Routing (SR) are analyzed. Segment routing is a WAN traffic routing technique existing on MPLS and only-BGP networks. Segment routing is also considered as a way of improving the infrastructure performance and efficiency. The main advantages of SR are achieved through the implementation of the SDN concept approach, without changing the standard data transferring plane for each of the technologies, above which SR can be applied. The article also covers the main areas of SR technology application, interaction in a centralized and decentralized network. The article provides the examples of controllers for SDN implementation using SR. The presence of a controller in the network permits the realization of bandwidth on demand, traffic prioritize, selection of the most suitable route in the network for different types of traffic easier and more often without any protocols or devices. Another important advantage of controller's implementation on networks using SR can be a reduction of the services recovery time after a failure, because the route will be rebuilt faster (compared to MPLS). SR can be considered as an opportunity to refuse from such protocols as LDP or RSVP for situation when used on a network in tandem with a controller. IPv6 networks, using SR, are able to acquire additional capabilities in programmability and flexibility.

Environmental tourism in Crimea: experience in implementing the sustainable development principles

The conceptual basis of modern changes in tourism is a sustainable development, the basic principles of which are most translated into the idea of ecological tourism. The paper presents the results of a study of the organization of ecological tourist routes and programs in protected areas of the Crimean peninsula. Spatial differences in the density of ecological route network, the functional structure of routes and trails, the degree of their infrastructure and information support were revealed. Attractiveness of the routes is dueto the high concentration of socially significant objects of natural and cultural heritage within boundaries of protected areas. For ecological tourism, the most developed are mountain-forest and coastal areas located in the south-west, south and south-east of Crimea. The implementation heterogeneity on the principles of environmental, economic and social sustainability in regional ecotourism development was established. Violations of the regulation principles of recreational load on natural complexes, preservation and reproduction of the resource quality, insufficient use of potential of local communities in the management system of ecological tourism were revealed. Constructive suggestions for optimizing ecotourism in Crimea on the sustainability principles were formulated.

Оценка качества маршрутов учебных водных походов

The model of the reference training and sports water trip route for training tourism instructors and methodologists at the Belarusian State University of Physical Culture (Minsk, Republic of Belarus) has been developed. The model determines the route structure and its indicators of educational, sports, recreational and technological qualities. The results of comparative assessment are provided for reference model’s quality and qualities of several water routes. A high-quality training and sports route is proposed for long-term use.

Evaluation of Routing Protocols and Mobility in Flying Ad-hoc Network

The ability of dynamic reconfigurability, quick response and ease of deployment has made Unmanned Aerial Vehicles (UAVs), a paramount solution in several areas such as military applications. Flying ad-hoc network (FANET) is a net-work of UAVs connected wirelessly and configured continuously without infrastructures. Routing on its own is not significant, but the mobility sequence of a UAV in FANETs is a more significant factor and an interesting research topic. The routing protocols gives us a certain and better perception of routing structure for FANETs. In this paper, routing protocols such as Ad-hoc On-Demand Vector (AODV), Dynamic Source Routing (DSR), Temporally Ordered Routing Algorithm (TORA), Geographic Routing Protocol (GRP) and Optimized Link State Routing (OLSR) are compared using performance parameters such as number-of-hops, packet loss ratio, throughput, end-to-end delay and throughput. The mobility models like Pursue Mobility Model (PRS), Semi-Circular Random Movement (SCRM), Manhattan Grid Mobility Model (MGM) and Random Waypoint Mobility (RWPM). The evaluation is carried out with three scenarios including one sender node and one receiver node, all senders one receiver and all senders all receivers are considered for above protocols and mobility models. For all evaluation scenarios, the performance of OLSR is the most efficient among the five routing protocols under four different performance parameters due to its proactive nature which makes the routing information up to date with the help of MPR (Multi Point Relay) in the network, resulting in the reduction of routing overhead in the network.

Synthesis of 2D and 3D hierarchical β-FeOOH nanoparticles consisted of ultrathin nanowires for efficient hexavalent chromium removal

The self-assembly of 1-dimensional nanorods into free-standing multi-dimensional (2D and 3D) nanostructures is a considerable challenge. Here, 2D β-FeOOH nanobundles (NBs) and 3D spiky particles (SPs) were prepared without a substrate using a one-pot hydrothermal method. The oriented aggregation of nanoparticles (NPs) induced at the initial stage an unusual growth pathway beyond a reversed crystal growth route, forming spindle-like or spiky structure, which was confirmed by structural analyses. Then, with a surface-to-core extension of crystallization and nanorod self-assembly, 2D NBs with ultrathin and well-aligned nanorods and 3D SPs were finally generated. The reduction of the surface free energy served as a primary driving force for the oriented self-assembly. The initial concentrations of sodium sulfate and polyethyleneimine, which are used as reducing reagent and electrostatic stabilizer, are crucial adsorption parameters. The adsorption capacity of the NBs and SPs for Cr(VI) was 68.3 mg g−1 and 83.4 mg g−1, respectively. The adsorption mechanism study showed that electrostatic interaction and reduction concomitantly affected the adsorption. The molecular dynamic simulation indicated that the adsorption performance depends on the crystallographic surface of the materials. The suggested synthesis route provides an atypical strategy to prepare 2D and 3D nanostructures with promising sorbent characteristics.

Modularization of 2- and 3-DoF Coupled Tendon-Driven Joints

This article proposes coupled tendon-driven joint modules for anthropomorphic robots. Fully actuated 2-degree-of-freedom (DoF) and 3-DoF joint modules are classified and analyzed based on the motor-joint routing matrix that describes the tendon routing structure between the motors and the joints. Two-motor 2-DoF (2M2D) modules, which share the same form of motor-joint routing matrix, are classified into four types: externally actuated, internally coaxially actuated, internally separately actuated, and hybrid-actuated according to the location of the motors. Three-motor 3-DoF (3M3D) modules are classified into four forms based on the four possible forms of motor-joint routing matrix: fully routed motor-joint, 1-unrouted motor-joint, 2-unrouted motor-joint, and 3-unrouted motor-joint. The 2M2D and 3M3D coupled tendon-driven joint modules are analyzed and compared with respect to the relationship between the motor torque and the joint torque. A 7-DoF anthropomorphic robot arm was implemented with one 3M3D module for the shoulder joint and two 2M2D modules for the elbow and wrist joints, respectively, to demonstrate the utility of the proposed joint modules. The arm weighed 2.2 kg and was able to lift a 1.5-kg load with full outreach. The characteristics of the joint modules were evaluated in a current consumption experiment and a position accuracy experiment, and the performance of the robot arm was evaluated in a master-slave manipulation experiment involving dexterous movements.

FUNCTIONAL DIFFERENTIATION OF SPACE AND THE TEN-ELEMENT NUMERICAL MODEL OF ANCIENT CULTURES

The probabilistic regularities in the principles of functional diff erentiation of ordered structures that arise in the process of human space exploration are analyzed. The authors provide the rationale for the ten-element functional model in the context of the wave approach of D.V. Denisov and the fractal-cluster model. Comparable results were obtained for the administrative division into inner-city districts, the structure of tram routes, and the distribution of premises of a Russian university. The analysis is carried out on the example of Samara and Samara State University of Railways.

AI-Enabled Next-Generation Communication Networks: Intelligent Agent and AI Router

Nowadays, network users' demands for low latency services and individual data security grow rapidly. In this article, we conceive a new communication network architecture based on the concept of intelligent agents. The proposed intelligent agent serves as a virtual secretary of the corresponding user to request desired service from Internet companies or neighboring agents, which can reduce Internet surfing latency and prevent privacy leakage. Moreover, to improve the forwarding efficiency of data packages, a new mixed routing structure and the AI router are also introduced, to support various on-demand services with low latency. Overall, the proposed communication network architecture is expected to be more efficient than the existing one, and inspire readers to deliberate the revolution of future communications networks.

Accounting for Product Impact in the Airlines Industry

We apply the product impact measurement framework of the Impact-Weighted Accounts Initiative (IWAI) in two competitor companies within the airlines industry. We design a monetization methodology that allows us to calculate monetary impact estimates of fare affordability, timeliness and gate control, among other factors. Our results indicate substantial differences in the impact that competitors have through their products. These differences demonstrate how impact reflects corporate strategy and informs decision-making on industry-specific areas, including airline route structure choices.

An augmented Tabu search algorithm for the green inventory-routing problem with time windows

Abstract Transportation allocates a significant proportion of Gross Domestic Product (GDP) to each country, and it is one of the largest consumers of petroleum products. On the other hand, many efforts have been made recently to reduce Greenhouse Gas (GHG) emissions by vehicles through redesigning and planning transportation processes. This paper proposes a novel Mixed-Integer Linear Programming (MILP) mathematical model for Green Inventory-Routing Problem with Time Windows (GIRP-TW) using a piecewise linearization method. The objective is to minimize the total cost including fuel consumption cost, driver cost, inventory cost and usage cost of vehicles taking into account factors such as the volume of vehicle load, vehicle speed and road slope. To solve the problem, three meta-heuristic algorithms are designed including the original and augmented Tabu Search (TS) algorithms and Differential Evolution (DE) algorithm. In these algorithms, three heuristic methods of improved Clarke-Wright algorithm, improved Push-Forward Insertion Heuristic (PFIH) algorithm and heuristic speed optimization algorithm are also applied to deal with the routing structure of the problem. The performance of the proposed solution techniques is analyzed using some well-known test problems and algorithms in the literature. Furthermore, a statistical test is conducted to efficiently provide the required comparisons for large-sized problems. The obtained results demonstrate that the augmented TS algorithm is the best method to yield high-quality solutions. Finally, a sensitivity analysis is performed to investigate the variability of the objective function.

Sustainability-oriented configurational analysis of the street network of China's superblocks: Beyond Marshall's model

The duality in China's traffic planning has given rise to the basic unit of urban form and function called the superblock, which is defined and bound by an arterial street network. The street network of China's superblock underpins the coexistence and interaction of global and local movement, the public and daily space, and affects place diversity and local characteristics. However, its configuration remains to be articulated because of the lack of a systematic representation method, and the associations between configuration and performance, cognition and design cannot be determined. This study proposes an improved representation method for the street network of China's superblocks based on Marshall's route structure analysis to explore the configurational characteristics and sustainability of the network. To fit local conditions, this study improves Marshall's route structure analysis from four perspectives, namely, the judgement of relative hierarchy, the node construction principle, and the deletion and addition of the original indicators. The improved method is then applied to calculate and compare the depth, connectivity, and complexity of the street networks of 10 sample superblocks in Nanjing, which are classified into six types by construction backgrounds, each having two scenarios differing by the level of publicity. Results indicate that the types formed in accordance with the “The Capital Plan” of the Republic of China, which presents a combination of fine orthogonal grids and radiations, and by the renewal of the traditional street-and-lane network, which has the “characteristic structure” defined by Marshall, perform best in terms of configurational sustainability. The analysis also reveals that the addition of semipublic streets formed mainly from the bottom up narrows the sustainability gap among the samples. This study provides a tool for elaborate urban study and design and provides insights into the cognitive and practical aspects of China's urban planning and design.

Data Fusion Algorithm for Heterogeneous Wireless Sensor Networks Based on Extreme Learning Machine Optimized by Particle Swarm Optimization

Data fusion can reduce the data communication time between sensor nodes, reduce energy consumption, and prolong the lifetime of the network, making it an important research focus in the field of heterogeneous wireless sensor networks (HWSNs). Normal sensor nodes are susceptible to external environmental interferences, which affect the measurement results. In addition, raw data contain redundant information. The transmission of redundant information consumes excess energy, thereby reducing the lifetime of the network. We propose a data fusion method based on an extreme learning machine optimized by particle swarm optimization for HWSNs. The spatiotemporal correlation between the data of the HWSNs is determined, and the extreme learning machine method is used to process the data collected by the sensor nodes in the hierarchical routing structure of the HWSN. The particle swarm optimization algorithm is used to optimize the input weight matrix and the hidden layer bias of the extreme learning machine. An output weight matrix is created to reduce the number of hidden layer nodes and improve the generalization ability of the model. The data fusion model fuses the original data collected by the sensor nodes. The simulation results show that the proposed algorithm reduces network energy consumption and improves the lifetime of the network, the efficiency of data fusion, and the reliability of data transmission compared with other data fusion methods.

Application of Modified NSGA-II to the Transit Network Design Problem

The transit network design problem involves determining a certain number of routes to operate in an urban area to balance the costs of the passengers and the operator. In this paper, we simultaneously determine the route structure of each route and the number of routes in the final solution. A novel initial route set generation algorithm and a route set size alternating heuristic are embedded into a nondominated sorting genetic algorithm-II- (NSGA-II-) based solution framework to produce the approximate Pareto front. The initial route set generation algorithm aims to generate high-quality initial solutions for succeeding optimization procedures. To explore the solution space and to have solutions with a different number of routes, a route set size alternating heuristic is developed to change the number of routes in a solution by adding or deleting one route. Experiments were performed on Mandl’s network and four larger Mumford’s networks. Compared with a fixed route set size approach, the proposed NSGA-II-based solution method can produce an approximate Pareto front with much higher solution quality as well as improved computation efficiency.

Fast Sensory Data Aggregation in IoT Networks: Collision-Resistant Dynamic Approach

Internet-of-Things (IoT) systems and their applications rely on sensory data for operating context-aware functions. To ensure reliability, these data must arrive at the base station in a timely manner. Because IoT sensors are battery powered and expected to last for years, energy consumption has always been a dominant concern. The duty cycling mechanism efficiently extends the lifespan of sensor nodes; however, it increases data aggregation time. This article studies the minimum time aggregation scheduling problem in duty-cycled sensor networks. The existing solutions route the sensory data through a predefined structure, but such structures are constructed without full awareness of collisions in the wireless medium. Therefore, in this study, the collision-resistant dynamic (CORD) scheduling approach has been proposed with an aim to provide fresh data for emerging IoT applications. The proposed approach is applicable to any initial routing structure and it dynamically changes the receiver of a transmission whenever this change can reduce aggregation time. The receiver-changing decision is made on the fly, resisting all collisions between the determined transmissions. We evaluate CORD in various simulation scenarios, and the results demonstrate that the proposed approach yields a notable improvement of up to 62% from the viewpoint of aggregation time while having comparable time complexity compared to state-of-the-art methods.

A Self-Biased Adaptive Reconfigurable Rectenna for Microwave Power Transmission

A self-biased adaptive reconfigurable rectenna, consisting of a microstrip patch antenna and a self-biased reconfigurable rectifying circuit, is proposed in this letter. To eliminate the need of bias networks, a dc power routing structure is introduced to link the reconfigurable matching stub and the load. Hence, the output dc current obtained by the rectifier can be divided/split, thereby letting a part of the dc current flow back to the matching stub for providing a bias voltage. According to the input power level, the states of the p-i-n switch can be automatically changed in order to connect/disconnect the matching stub to the rectifying circuit for achieving improved matching performance at different power levels. Simulated and measured results show that the proposed rectenna reaches more than 50% conversion efficiency over a broadened input power range from 0–20 dBm with the peak efficiency of 68% at 9 dBm. It is evident that the proposed self-biased reconfigurable matching scheme is a promising and effective solution to facilitate the less-complicated reconfigurable rectenna integration and realize high efficiency at higher operating frequency bands (e.g., >5 GHz).

A Comparative Study of Energy Retaining Objective Functions in RPL for Improving Network Lifetime in IoT Environment

Internet of Things will be inevitable in all walks of our life, where it becomes necessary for all smart devices to have end-to-end data transfer capability. These low power and low-cost end devices need to be enabled with IPv6 address and corresponding routing mechanism for participating in Internet of Things environment. To enable fast and efficient routing in Internet of Things network and constrained with limited energy, Routing Protocol for Low-power Lossy Network (RPL) has been developed by ROLL-Work Group. As RPL is proactive and energyconserving, it has become the most promising routing protocol for Internet of Things. Nodes in Low-power Lossy Network (LLN) are designed to conserve energy by maintaining radio silence over 90% of its lifetime. It is possible to further improve the node’s lifetime and thereby considerably extending network’s longevity by performing sensible routing. Different routing structure in Internet of Things network can be attained by carefully crafting the objective function for the same set of nodes which satisfies different goals. This paper focuses on different objective functions in RPL which have been developed over time with the emphasis on energy conservation and maximizing the lifetime of the network. In this work, we have carefully studied different metric compositions used for creating an objective function. The study revealed that combining metrics provides better results in terms of energy conservation when compared to single metric defined as part of RPL standard. It was also noted that considering some metric as a constraint can increase the rate of route convergence without affecting the performance of the network.

Data Processing Platform of Cloud Computing and Its Performance Analysis Based on Photoelectric Hybrid Interconnection Architecture

Data processing platform is the core support platform of cloud computing. The use of electric interconnection architecture will increase the complexity of network topology, while optical interconnection architecture is ideal, so cloud computing platform based on optical interconnection has become a research hotspot. The distributed optical interconnection architecture of cloud computing data processing platform is focused on. Combining the hybrid mechanism of optical circuit switching and electric packet switching, it can meet a variety of traffic requirements. Meanwhile, it improves the switching mechanism, communication strategy, and router structure. Moreover, considering that the hybrid optoelectronic interconnection architecture can improve the network delay and throughput, but there is still a problem of network consumption. Combined with the network characteristics of the data processing platform (wireless mesh structure) of cloud computing, the network topology algorithm is studied, and the relationship between the topology and the maximum number of allocable channels is analyzed. Furthermore, the equation of topological reliability calculation is defined, and the optimization model of topological design is proposed, according to which the data processing platform of cloud computing is further optimized under the photoelectric hybrid interconnection architecture. During the experiment, before topology optimization, by changing the message length, it is found that adding optical circuit switching can help achieving large capacity and new type of transmission, and can effectively reduce the time delay. After topology optimization structure is adopted, the photoelectric hybrid-data processing platform of cloud computing without topology optimization is compared. It is found that under different reliability constraints, the throughput and end-to-end delay of the network are significantly improved, which proves that the data processing platform of cloud computing based on the photoelectric hybrid interconnection architecture is a feasible cloud computing platform.

Energy Efficient Data Gathering Technique Based on Optimal Mobile Sink Node Selection for Improved Network Life Time in Wireless Sensor Network (WSN)

The utilization of mobile sink in spite of its points of interest carries new difficulties to WSNs. The principle disputes are the position update of sink node to the hub. Every sensor hub should know about the sink position all together that it can move its information to the sink. Existing Flooding technique proposed that the portable sink needs to consistently spread its situation all through the system to advise sensor hubs regarding the sink position. In any case, visit position refreshes from the sink can prompt both maximum power utilization and amplified crashes in the network. To diminish the updation of sink position, different types of routing structures can be utilized. A routing mechanism dependent on the mobile sink is effective if it limits the power utilization and delays in the system network. The primary intention of the study is to design an energy embedded routing protocol based on optimal updation of the mobile sink. Here, the most recent sink position will be spared in the hubs developing the implicit environment. Accordingly, in Embedded routing, the position of the sink node is proliferated to the sensor hubs situated at the discs instead of the solicitation of hubs in the system. The remainder of the hubs can locate the most recent sink position by forwarding solicitation information to the closest disc. Based on the received information, the receiver of the message is identified. This will be performed by optimal fuzzy based clustering technique. The optimization can be done by Oppositional grey wolf optimization (OGWO) algorithm. The efficiency is analyzed by maximum network lifetime, minimum delay etc. The results will be analyzed and compared with existing routing protocols to ensure the efficiency.