Congestion Rate Research Articles

Optimal Path Planning for a Biomedical Combined WSN System via RSSI and LQI

In practical WSNs, such as biomedical monitoring system applications, the sensor nodes are deployed indoors. The obstacles may exist because of the area setting which may reduce the communicatiuon range of nodes. Those nodes will be isolated from network. In this paper, we present path plannning algorithm for the isolated node with the ability to choose the optimal path for data communication based on fuzzy. In addition, we utilize the RSSI and LQI value in making decision for selecting the optimal path. Our goal is to create high-performance bio-information collection in a biomedical combined WSN system. We focus our contribution on reducing the waiting time for bio-data gathering by diverting the communication path through the empty channel surroundings. Thus, the optimal solution yields the shortest time, not the shortest path. Compared with the traditional algorithm, our algorithm effectively reduces the congestion rate of data transfers, avoids the long waiting times caused by packet loss problems and achieves optimal path planning for objects.

Assessment of Call Voice Quality of GSM Network Operators in 5 Cities in Kwara State

This paper evaluates voice quality of four Global System for Mobile (GSM) Communication providers in five selected cities in Kwara State with thoughtfulness of network performance evaluation and the quality of service (QoS) improvement of GSM network system. Three assessment components/parameters which are network accessibility, service retainability and connection quality for evaluating QoS on the network were mainly adopted. The parameters were applied on four GSM networks in the studied areas using customers’ complaints method. Also, a standard method known as Perceptual Evaluation of Speech Quality (PESQ) — (International Telecommunication Union-Telecommunication Standardization Sector) ITU-T standard P.862, used for measuring call voice quality and Mean Opinion Score (MOS) is adopted. The two methods were therefore compared to assess call voice quality of the four GSM networks. The Key Performance Indicators (KPIs) on which the GSM networks were tested include call set-up success rates (CSSR), call drop rate (CDR), call completion success rates (CCSR), handover success rates (HSR) and traffic channel congestion rate (TCHR). The result of the study shows that the Quality of Service of GSM system in the selected cities is unreliable. The study also shows that the GSM network accessibility and retainability in the country are unsatisfactory. However, the call voice quality was observed to be on the peak in these cities across the four network providers. At the end of this manuscript, suggestions are given on how to advance both the Quality of Service and the positive impact of GSM network in the selected areas and the country as a whole.

The Impact of Hospital Specialization on Congestion and Efficiency

The purpose of this study is to verify the existence of congestion in Korean hospitals, to identify the causes of congestion, and to suggest directions for efficiency improvement of hospitals. The result showed that congestion occurred in 71.90% of 1185 hospitals. In addition, it was found that hospital specialization has a negative effect on congestion. In other words, the higher the hospital specialization, the lower the overall congestion rate of the hospital. More specifically, the specialization of hospitals also showed a negative effect on congestion of nurses. On the other hand, hospital specialization was found to have a positive effect on the congestion of the number of doctors, but it does not have a significant effect on the congestion of hospital beds. It was also found that hospital size has an effect on the relationship between hospital specialization and congestion, but the location of the hospital and the type of ownership did not act as a moderator.

Survivability Analysis of LEO Satellite Networks Based on Network Utility

The LEO satellite network is threatened by accidental faults, malicious attacks and other factors during its operation. This paper proposed a model of survivability evaluation based on network utility. First, calculate the communication performance indicators of delay, congestion rate and throughput of LEO satellite networks by different types of queue theory birth and death model; then, combined these performance indicators with reliability and cost planning to construct network utility function which is used for evaluating the survivability of LEO satellite networks under natural failure, random attack, deliberate attack and saturation attack modes. The case study shows that: the greater the arrival rate of natural faults, the shorter the time required to descend to the network utility threshold, the network is more vulnerable to intentional attacks; the survivability can’t be enhanced by adding buffers; the importance of nodes and links is related to the proportion of real-time and non-real-time services and the traffic of different satellite coverage areas.

Drone transportation cost analysis for emergency medical products

A faster mode of transportation that carries emergency medical supplies such as blood bags is consequential to saving lives. Although different road vehicles (e.g., ambulances) are used for this, with increasing rate of congestion, it is becoming increasingly challenging to perform this task on time. The objective of this study is to demonstrate the applicability of drones in transporting emergency medical products and investigate how different parameters (technical and environmental) that affect the drone flight, contribute to the cost of transportation. A number of 'to-be scenarios' have been generated by varying different parameters. Similarly, a case study has been conducted to illustrate the use of different drones on different operational conditions. The outcomes of this study have the potential to help concerned officials make decisions on the feasibility of using drones in transporting emergency medical products, assist policy makers on policy decisions, and contribute to saving the life of victims of traffic accidents.

Dashboards for Monitoring Congestion and Crashes in Interstate Work Zones

Work zones present challenges to safety and mobility that require agencies to balance limited resources with vital traffic management activities. Extensive literature exists regarding the impact of congestion and recommendations for work zone design to provide safe and efficient traffic operations. However, it is often infeasible or unsafe to inspect every work zone within an agency’s jurisdiction, so it is important to obtain operational feedback regarding congestion and crashes in work zones to prioritize inspection activities. This paper outlines the use of connected vehicle speed data and crash report data to identify operational performance problems in work zones. This is a way to provide feedback to queuing models used to design maintenance-of-traffic (MOT) plans. A weekly work zone report and dashboards were developed for use by the Indiana Department of Transportation (INDOT) for the purpose of assessing and improving both mobility and safety in work zones. The study has developed a mile-hours of congestion graph, frequency of speed delta heat map, congestion profile graph, and the Route Builder interactive application to comprehensively visualize work zone performance. This weekly report provides a mechanism for agency staff to maintain situational awareness of which work zones were most challenging for queues and during what periods those were likely to occur. In one case study, the reports were used to identify and mitigate operational performance problems in a work zone within 4 weeks, reducing congestion and crash rates. The integration of these data provided project managers with quantitative information about traffic mobility and performance of work zones for informed decision-making during the construction season.

Projeto Victor: perspectivas de aplicação da inteligência artificial ao direito

Este artigo analisa o potencial que a inteligência artificial (IA) tem para im­pactar o Direito, discutindo como as ferramentas tecnológico-algorítmicas podem contribuir para diminuição da elevada taxa de congestionamento do Poder Judiciário brasileiro. Examinando as inovações que a IA permite, apresenta o Projeto Victor, fruto de parceria do Supremo Tribunal Federal com a Universidade de Brasília, que prevê a criação de modelos de machine learning para análise dos recursos recebidos pelo STF quanto aos temas de repercussão geral. Como se buscou comprovar, o projeto poderá se constituir em ferramenta que afetará positivamente o controle de constitucionalidade difuso realizado pela Corte.

Vehicular Ad hoc Network for Intelligent Transport System: A review

the numbers of accidents are increasing in an exponential manner with the growing of vehicles numbers on roads in recent years. This huge number of vehicles increases the traffic congestion rates. Therefore, new technologies are so important to reduce the victims in the roads and improve the traffic safety. The Intelligent Transportation Systems (ITS) represents an emerging technology to improve the road's safety and traffic efficiency. ITS have various safety and not safety applications. Numerous methods are intended to develop the smart transport systems. The crucial form is the Vehicular Ad hoc Networks (VANET). VANET is becoming the most common network in ITS. It confirms human’s safety on streets by dissemination protection messages among vehicles. Optimizing the traffic management operations represent an urgent issue in this era a according to the massive growing in number of circulating vehicles, traffic congestions and road accidents. Street congestions can have significant negative impact on the life quality, passenger's safety, daily activities, economic and environmental for citizens and organizations. Current progresses in communication and computing paradigms fetched the improvement of inclusive intelligent devices equipped with wireless communication capability and high efficiency processors.

Energy-constrained transmission on hybrid communication networks

The real communication systems usually consist of different types of agents, e.g. computers, routers, base stations and mobile phones, forming various hybrid communication networks. Furthermore, in many cases, those agents are energy-constrained resulting in a limited lifetime of the communication networks. We proposed a hybrid communication network model composed of energy-constrained base stations and mobile users, and further gave a novel energy-aware gateway selection strategy to balance the energy consumption of base stations. We developed a new metric of nodes, called node forwarding strength, which measures the intrinsic forwarding capability of nodes and is basically dependent on the network structure and routing protocol. Based on this metric, we further derived the critical packet generation rate of traffic congestion, average number of transmission hops, and network lifetime. By investigating the influence of factors on the network lifetime, we obtained the optimal user moving speed and gateway selection parameter corresponding to the maximum network lifetime. Our work may provide some clues for the designing and optimization of real hybrid communication systems.

A Smart Congestion Control Mechanism for the Green IoT Sensor-Enabled Information-Centric Networking.

Information-Centric Networking (ICN) is a new Internet architecture design, which is considered as the global-scale Future Internet (FI) paradigm. Though ICN offers considerable benefits over the existing IP-based Internet architecture, its practical deployment in real life still has many challenges, especially in the case of high congestion and limited power in a sensor enabled-network for the Internet of Things (IoT) era. In this paper, we propose a smart congestion control mechanism to diminish the network congestion rate, reduce sensor power consumptions, and enhance the network performance of ICN at the same time to realize a complete green and efficient ICN-based sensor networking model. The proposed network system uses the chunk-by-chunk aggregated packets according to the content popularity to diminish the number of exchanged packets needed for data transmission. We also design the sensor power-based cache management strategy, and an adaptive Markov-based sensor scheduling policy with selective sensing algorithm to further maximize power savings for the sensors. The evaluation results using ndnSIM (a widely-used ICN simulator) show that the proposed model can provide higher network performance efficiency with lower energy consumption for the future Internet by achieving higher throughput with higher cache hit rate and lower Interest packet drop rate as we increase the number of IoT sensors in ICN.

Drivers Analysis of CO₂ Emissions from the Perspective of Carbon Density: The Case of Shandong Province, China.

Against the backgrounds of emission reduction targets promised by China, it is crucial to explore drivers of CO2 emissions comprehensively for policy making. In this study, Shandong Province in China is taken as an example to investigate drivers in carbon density by using an extended Kaya identity and a logarithmic mean Divisia index model (LMDI) with two layers. It is concluded that there are eight positive driving factors of carbon density during 2000–2015, including traffic congestion, land urbanization, etc., and seven negative driving factors comprising energy intensity, economic structure, etc. Among these factors, economic growth and energy intensity are the main positive and negative driving factor, respectively. The contribution rate of traffic congestion and land urbanization is gradually increasing. Meanwhile, 15 driving factors are divided into five categories. Economic effect and urbanization effect are the primary positive drivers. Contrarily, energy intensity effect, structural effect, and scale effect contribute negative effects to the changes in carbon density. In the four stages, the contribution of urbanization to carbon density is inverted U. Overall, the results and suggestions can give support to decision maker to draw up relevant government policy.

Studies on Several Issues of Electricity Price Forecast

The main models used in electricity price forecast have been reviewed in this paper. Several statistical models based on machine learning algorithms have been tested and compared to forecast the next-day hourly electricity price in Nordpool electricity market. Stationarity of electricity price has also been studied and it is concluded that electricity price is daily seasonal. Many features of both local region and neighboring regions from the past week have been respectively analyzed in terms of the importance to electricity price forecast. Results show that local zone, compared with neighbor zones, exerts the major influence on electricity price. Meanwhile, price is the most important category other than categories like demand, wind generation or transmission congestion rate. Hydro reserve is also an important parameter to electricity price forecast.

Congestion Window Scaling Method to Optimize Delay in TCP/IP

TCP (Transmission Control Protocol) is a protocol of layer four (Transport Layer), and IP (Internet Protocol) is in the Network Layer (Layer 3) of the OSI Model. The TCP protocol is the most used of the network applications on the Internet. TCP performance is strongly influenced by its congestion control algorithms that limit the amount of transmitted traffic based on the estimated network capacity and utilization. TCP is a connection-oriented protocol which guarantees the sent packets to the destination in accurate order whereas UDP is an unreliable/connectionless protocol which does not guarantee that the sent messages would reach the destination. A TCP connection is used to control packet sizes, the rate of data exchange, flow control and network congestion. Unfortunately, congestion/network overload happens in the TCP connection which affects the rate of data flow, loss in packets transmitted, packet transmission delay and delayed acknowledgment. In this paper, a method to scale the congestion window on the sender and receiver to optimize the delay of transmission in TCP in order to reduce the congestion rate is proposed. The proposed congestion control algorithm enables a sender to optimize and initialize the congestion window before transmitting packets. The proposed method is evaluated by simulating the transmission in Network Simulation 3 (NS3).

An efficient error prevention and recovery scheme for multicast traffic in data center networks

In cloud application services, data are generally transmitted by multicast-based group communications to avoid transmission of duplicate packets and reduce bandwidth waste. However, the data amount in data center networks (DCNs) has increased to the scale of tremendous data over time. Tremendous data can be processed only through DCNs by using distributed computing technologies. Consequently, a large flow of multicasts has been generated. DCNs comprise a high number of commodity servers and switches, which exhibit limited capabilities to process packets. Subsequently, the rate of multicast congestion in DCNs increases substantially, resulting in severe packet loss and transmission error. Packet loss and transmission error cause all transmitting devices to retransmit data, resulting in network bandwidth waste, transmission delay, and disrupted transmission of other data. Consequently, network congestion is exacerbated, and the entire multicast tree crashes. Therefore, this paper proposes an error prevention and recovery multicast, which enables areas of errors to be effectively inferred and reduces the chain effects of errors by using repair multicast trees and multiple multicast trees that share error information, thereby effectively reducing the costs of reconstructing multicast trees. Simulation results show that the proposed scheme significantly improves the costs of reconstructing multicast trees and the transmission delay.

Transmission power adaption scheme for improving IoV awareness exploiting: evaluation weighted matrix based on piggybacked information

As part of the new era the Internet of Things, an evolved form of Vehicle Ad-hoc Networks has recently emerged as the Internet of Vehicles (IoV). IoV has obtained a lot of attention among smart vehicle manufactures and illustrations due to its promising potential, but there are still some problems and challenges that need to be addressed. Transmission error occurs when an emergency message is disseminated to provide traffic awareness, and vehicles have to increase their channel transmission power to ensure further coverage and mitigate possible accidents. This might cause channel congestion and unnecessary power consumption due to an inaccurate transmission power setup. A promising solution could be achieved via periodically and predictively evaluating channel and GEO information that is transmitted over piggybacked beacons. Thus, in this paper we propose a Transmission Power Adaptation (TPA) scheme for obtaining better power tuning, which senses and examines the probability of channel congestion. Afterwards, it proactively predicts upcoming channel statuses using developed evaluation-weighted matrix, which observes correlations between coefficients of variance for estimated metrics. Considering beacon transmission error rate, crowding inter-vehicle distance, and channel delay, the matrix is periodically constructed and proavtively weighted for each metric based on a predefined threshold value. Eventually, predicted channel status is used as an indicator to adjust transmission power. This leads to decreased channel congestion and better awareness in IoV. The performance of the proposed TPA scheme is evaluated using OMNeT++ simulation tools. The simulation results show that our proposed TPA scheme performs better than existing method in terms of overall throughput, average beacon congestion rate, beacon recipient rate probabilities, channel-busy time, transmission power over distance, and accident probabilities.

A hybrid active queue management technique for QoS based unicasting protocols in MANETs

Mobile Ad hoc Networks (MANETs) is the interconnection of several self-energy dependent mobile nodes. It is one of the self-configured and infrastructure less network. In MANET the issues are security, Quality Of Services, Congestion etc. The major issue of MANET is to control the congestion. Congestion means the network capacity is larger than the no of packets transmitted across the network. In this paper, an effort has been made to evaluate and analyze the performance of the network by means of comparing two on-demand reactive routing protocols such as AODV [Ad-hoc On-demand Distance Vector] and DSR [Dynamic Source Routing] with each other along with also by comparing with DSDV [Destination Sequenced Distance Vector], which is a proactive routing protocol. The comparison is also being made under the light of two queue management techniques such as RED (Random Early Detection) and Droptail. A gateway discovery algorithm is being used by both AODV and DSR routing protocols, which uses the mechanism of connecting mobile nodes through gateway, however Bellman-Ford algorithm is being used by DSDV which uses the concept of including freedom from loops in the routing table. By means of simulation through NS-2 network simulator by varying the number of nodes, we observe that the performance differentials of AODV, DSR, and DSDV routing protocols are directed to foremost performance differentials to guarantee QoS for both of these protocols in RED and Droptail queue management techniques. There is a lot of queue management approach to minimize the congestion rate and transfer the data successfully to the destination. Two queue management techniques popularly used to manage queues in MANets are Active queue management and Passive queue management. Active queue management is widely used and RED is the most popular approach which gives low average delay, high throughput and lower packet drop rate. But RED algorithms have some drawback. So here we are using a hybrid approach, named as MRED by means of combining the features of both RED and ECN to overcome the drawbacks of RED.

Congestion control and packet recovery for cross layer approach in MANET

Mobile Adhoc network is a network, which has advances of dynamic topology, mobility of nodes and congestion control. It is also an infrastructure less networks. This paper “Congestion control and packet Recovery for cross layer approach” is proposed. Traffic of packets occurred due to congestion and contention problems are reduced in datalink layer and transport layer. Also ensuring that, the superior performance of congestion is a challenging model due to changes in link layer contentions, topological changes and characteristic of wireless channel. The features of this model were localized packet recovery, deterministic, ability to trade of efficiency and peer to peer recovery. It can retrieve the missing packets by storing the copy of packet. Also by assigning priority order to the packets, data traffic congestion rate of higher and lower priority packets are maintained. This will develop the high priority flow to get desired access to the medium and its flow rate of low priority is adjusted, in order to have high flow rate of higher priority. Therefore the overall performance gives the better result than existing method. The simulation of CCPRCLA is verified using ns2 simulator, then graph and experimental results are discussed.

Industry vs Services: Do Enforcement Institutions Matter for Specialization Patterns? Disaggregated Evidence from Spain

We exploit historical differences in foral law to consistently estimate the contribution of the quality of enforcement institutions to economic specialization across Spanish provinces in the period 1999-2014. The distribution of economic activity in Spain as of today shows a strong pattern of geographical specialization. Regions less specialized in manufacturing (industry) and oriented to services sectors (Andalusia, Extremadura) in the south are compared with industrialized/manufacturing regions in the north such as the Basque Country, Navarre or Aragon. We construct province-level congestion rates across three different jurisdictions (civil, labor and administrative) from real judicial data measuring the performance of the Spanish judicial system over time, and estimate the effect of judicial efficacy on the share of manufacturing and services in the total output. Using a variety of estimation techniques, the evidence unveils strong and persistent effects of judicial efficacy on province-level economic specialization with notable distributional differences. The provinces with a historical experience of foral law are significantly more likely to have more efficient enforcement institutions at the present day. In turn, greater judicial efficacy facilitates specialization in high-productivity manufacturing while greater judicial inefficacy encourages service-intensive specialization. The effect of judicial efficacy on economic specialization does not depend on confounders, holds across a number of specification checks and appears to be causal. Lastly, the three jurisdictions seem relevant to explain specialization, although the administrative jurisdiction appears to have a more pronounced impact than the labor or civil jurisdictions.

A procedure for individual design of an interchange

Abstract Over the course of 20 years, the population of Tyumen city and the Tyumen region grew by 69.8%. The population growth resulted in an increase in the number of cars, which led to heavy traffic both across the city and at individual transport hubs. An increase in the accident rate and transport time delays, high traffic congestion on road sections and intersections cause concern in specialists, lecturers, and students training in the field of the road sector regarding the current condition of urban infrastructure. Since Tyumen is a rapidly developing city, its technical traffic management system has become obsolete and most of the streets do not have the capacity to meet the modern requirements of the city automobilization level. All the above facts predetermine the need for a global reorganization of the city’s street and road network, namely, the expansion of streets and roads, rearrangement of transport hubs and reorganization of traffic in general. This article considers traffic optimization on one of the busy intersections in Tyumen city. A detailed elaboration of design options for hub improvement is carried out. The introduction of the proposed design solution will make it possible to reduce the congestion rate, improve safety on this intersection and, as a result, lead to an increasing economic effect due to the reduction of transport costs and costs on the remediation of road accident consequences.

Intelligent detection algorithm of MIMO wideband frequency modulated signal in complex multipath channel

The intelligent detection algorithm of MIMO wideband frequency modulated signal based on orthogonal matching tracking has the disadvantages of high network congestion rate, high noise content in signal and large memory space in complex multipath channel. Intelligent detection algorithm of MIMO wideband frequency modulated signal in complex multipath channel is proposed based on fractional Fourier transform. The noise in the signal is analyzed with the hierarchical search introducing into the signal detection process. The signal normalization process is performed to complete the signal detection algorithm. Experiments show that the algorithm can effectively reduce the noise content in the signal, occupying small memory space of the computer to reduce the impact of detection on the computer network.