Survey on: A variety of AQM algorithm schemas and intelligent techniques developed for congestion control

The congestion on the internet is the main issue that affects the performance of transition data over the network. An algorithm for congestion control is required to keep any network efficient and reliable for transfer traffic data of the users. Many Algorithms had been suggested over the years to improve the control of congestion that occurs in the network such as drop tail packets. Recently there are many algorithms have been developed to overcome the drawback of the drop tail procedure. One of the important algorithms developed is active queue management (AQM) that provides efficient congestion control by reducing drop packets, this technique considered as a base for many other congestion control algorithms schema. It works at the network core (router) for controlling the drop and marking of packets in the router's buffer before the congestion inception. In this study, a comprehensive survey is done on the AQM Algorithm schemas that proposed and modification these algorithms to achieve the best performance, the classification of AQM algorithms based on queue length, queue delay, or both. The advantages and limitations of each algorithm have been discussed. Also, debate the intelligent techniques procedure with AQM algorithm to achieve optimization in performance of algorithm operation. Finally, the comparison has been discussed among algorithms to find the weakness and powerful of each one based on different metrics.

Bus Queue Time Estimation Model for a Curbside Bus Stop Considering the Blocking Effect

Bus queue time estimation of a curbside bus stop is essential to evaluate the operation, reliability and performance of a bus system. Arriving buses and served buses on upstream berths form an overflow queue considering the no overtaking principle and limited overtaking principle. Therefore, the bus dwelling time at the C-th berth may directly influence the stop capacity. The bus queue delay is modeled as a function of bus dwell time at the C-th berth and the dwell time at every berth using different distributions (normal and lognormal distributions) and data fitting approaches. This study aims to estimate the queue time attributed to dwell time at the C-th berth. The results indicate that the queue time should be evaluated by bus dwell time and joint probability density to quantify the negative influence on queue delay. Therefore, in some cases, where decisions must be taken into consideration for more than two buses, the relationship between dwell time at a downstream berth and dwell time at the C-th berth must be considered.

Best strategy to control data on internet-of-robotic-things in heterogeneous networks

The control and transmission of huge data constitute an immense challenge in various types of networks (wired and wireless). Congestion caused by the high traffic and low throughput of huge data continues to be major problems in a heterogeneous platforms such as internet of things (IoT) technology and internet-of-robotic-things (IoRT). The heterogeneous network requires new models and mechanisms to deal with the increased challenges posed by IoT and IoRT. Accordingly, eliminating the issues that emerge has compelled finding improved solutions as a new strategy. This study proposed a new strategy called routing information and distance vector (RIDV) to create the best improvement of a heterogeneous network. The RIDV strategy activates the routing information protocol (RIPv2) on a router in wire network parallel with the ad-hoc on-demand distance vector (AODV) protocol on the wireless network. The RIDV strategy is used to solve the problems of the diversity of heterogeneous networks as the basis of the infrastructure IoRT technology. Hence, this strategy can reduce or avoid congestion through the use of enhanced and effective best routing protocols. Simulation results using OPNET show that the proposed method improved the quality of service (QoS) compared with other related strategies and AODV and RIPv1 protocols in terms of data drop, traffic drop, queue delay, and throughput.

Effects of Charging Infrastructure and Non-Electric Taxi Competition on Electric Taxi Adoption Incentives in New York City

With major investments in electric taxis emerging around the world, there is a need to better understand resource allocation trade-offs in subsidizing electric vehicle taxis (e-taxis) and investing in electric charging infrastructure. This is addressed using simulation experiments conducted in New York City: 2016 taxi pickups/drop-offs, a Manhattan road network (16,782 nodes, 23,337 links), and 212 charging stations specified by a 2013 Taxi & Limousine Commission study. The simulation is based on a platform used to evaluate taxi operations in California and Seoul. Eleven scenarios are analyzed: a baseline of 7,000 non-electric taxis, five scenarios ranging from 1,000 e-taxis to 5,000 e-taxis, and another five scenarios in which the e-taxis have infinite chargers as an upper bound. The study finds that the number of charging locations recommended in the earlier study may be insufficient at some locations even under the 3,000+ e-taxi scenarios. More importantly, despite an average revenue of $260 per taxi for the 7,000 non-electric taxis and about $247 per taxi for electric taxis over the finite charger scenarios, the revenue gap between e-taxis and non-electric taxis in a mixed fleet increases significantly as the e-taxi share increases. This is because the increasing queue delay imposed on e-taxis gives non-electric taxis an increasing competitive advantage, raising their average revenue from $260 per taxi (1,000 e-taxis) up to $286 per taxi (5,000 e-taxis, 150% revenue gap increase), all other operating costs being equal. This has implications for individual versus whole-fleet policies, as the individual-oriented policies may be less effective.

Strategic experimentation in queues

We analyze the social and private learning at the symmetric equilibria of a queueing game with strategic experimentation. An infinite sequence of agents arrive at a server that processes them at an unknown rate. The number of agents served at each date is either a geometric random variable in the good state or zero in the bad state. The queue lengthens with each new arrival and shortens if the agents are served or choose to quit the queue. Agents can observe only the evolution of the queue after they arrive; they, therefore, solve a strategic experimentation problem when deciding how long to wait to learn about the probability of service. The agents, in addition, benefit from an informational externality by observing the length of the queue and the actions of other agents. They also incur a negative payoff externality, as those at the front of the queue delay the service of those at the back. We solve for the long‐run equilibrium behavior of this queue and show there are typically mass exits from the queue, even if the server is in the good state.

ANALISIS KEBUTUHAN PARKIR B BANDAR UDARA INTERNASIONAL KUALANAMU ( STUDI KASUS KENDARAAN RODA EMPAT )

Kebutuhan akan ruang parkir merupakan hal yang penting dalam pusat kegiatan karena dapat menimbulkan masalah seperti antrian, tundaan atau kemacetan serta akan mengganggu terhadap kelancaran lalu lintas jika ketersediaan kapasitas jalan dan area parkir tidak memadai.Tujuan dari penelitian ini adalah untuk menganalisis kapasitas dan kebutuhan ruang parkir B di Bandar Udara Intenasional Kualanamu Medan. Penelitian yang dilakukan yaitu berupa survey dengan mencatat waktu kendaraan yang masuk dan keluar dari lokasi parkir untuk melihat volume parkir, akumulasi parkir, durasi rata-rata parkir kendaraan, indeks parkir, tingkat pergantian parkir dan kapasitas parkir. Waktu pengamatan dilakukan pada hari minggu sampai hari kamis.Berdasarkan hasil perhitungan, akumulasi parkir tertinggi yaitu 251 kendaraan yang terjadi pada pukul 15.00 - 16.00 WIB dengan indeks parkir 37,74%, hal ini menunjukkan bahwa satuan ruang parkir (SRP) mobil masih dapat menampung kendaraan yang akan parkir sehingga membuat batasan-batasan parkir sesuai dengan sudut parkir yang di tentukan dan memperbaiki sirkulasi kendaraan yang masuk dan keluar dari lokasi parkir. Kata Kunci : kapasitas parkir, karakteristik parker, Kebutuhan ruang parkir ABSTRACT Parking space requirement is important in the activity because it can be a problem such as queue, delay or congestion will interfere with the smooth traffic if availability of road capacity and inadequate parking area.The goal of this research is to analyze capacity and parking B needs at Internasional Kualanamu Airport Medan. This research are obtained by doing survey to record the time the vehicle entry and exit parking location to see volume parking, accumulation of parking, mean parking duration, parking index, parking turn over and parking capacity. Time observations were made on Sunday and Monday. Based on calculation, accumulated the highest parking of 251 vehicle at 15.00 - 16.00 WIB with parking index 37.74 %, it is indicate the unit parking spaces of car can not accomodate vehicles to be parked so the needs for additional parking plots, improvement of road conditions and parking lot, create a progressive parking rates, make parking retrictions with angle parking planned and improve vehicle circulation the entry and exit parking location. Keywords: parking capacity, parking characteristics, Parking space requirements