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Emerging real‐time multimedia services over IP have penetrated into the daily lives of normal people with the advent of advanced broadband communications and innovated interconnection technologies. To protect shared Internet from unfairness and further congestion collapse, rate control plays a crucial role for many multimedia services such as streaming applications. Streaming applications such as video on demand (VoD) or voice over IP (VoIP) services face some critical problems such as insufficient bandwidth and improper performance of transmission protocols. Besides, the new generation networks are anticipated to integrate all heterogeneous wired and wireless networks and offer seamless customized multimedia services anywhere, anytime. However, wireless networks usually with low and variable bandwidth, and non‐congestion related loss do bring the challenge to the existing transport protocol, such as TCP, TFRC etc.

The paper uses simulations and compares other methods. The purpose of this paper is to address these issues. The paper, proposes a rate control scheme named Jitter‐based Rate Control (JRC) to fit wired‐wireless hybrid network which has better performance than the current rate control scheme.

Extensive simulations and comparisons with other methods verify the effectiveness of our method for accurate and smooth estimation, no matter whether the wireless links are located.

The paper introduces the JRC.

Nowadays, e‐queues are built up everywhere where customer online service is necessary such as in banks' e‐service, enterprises' e‐business, etc. In order to enhance quality of service (QoS), active queue management (AQM) algorithms are frequently employed due to their efficiency in congestion avoidance as well as the differentiated forwarding of packets. This paper aims at developing a novel AQM algorithm to better QoS in terms of congestion prediction, queuing delay, packet loss and link utility, etc.

Upon the traditional designs of AQM, this paper establishes a new integrated AQM scheme (RQ‐AQM) by employing input rate and current queue length to calculate the packet dropping/marking probability. In this way, the rate feedback control enables to rapid response to congestion, decreasing the packet loss from buffer overflow. Meanwhile, the queue length feedback control stabilizes the queue length around a given target, achieving predictable queuing delay and lower delay jitter. Thus, the main feature of the design is to use coefficients of both proportional rate control and proportional‐integral queue length control, and to simplify parameter setting, the control parameters were scaled by the link capacity C to normalize the rate and by the bandwidth‐delay product BDP to normalize the queue length, respectively.

The stability performance of RQ‐AQM was tested via simulation under several conditions. The results proved that it is able to maintain the queue length around the given target. Also, the comparison results with other AQM schemes, including RED, ARED, PI controller, AVQ and REM, demonstrated the superiority of RQ‐AQM in low packet loss, faster convergence to target queue length and closest to the target queue length.

The main limitation of this study is that all the simulations were merely under a single bottleneck network topology. Furthermore, the system stability was examined under just a few cases. Other cases like TCP connections mixed with HTTP connections, or UDP flows, etc. can also be tested. Furthermore, the multiple bottleneck scenarios should be covered in the future work with more parameters set to enhance the proved results.

The paper sets clear but ideal conditions for the performance of proposed algorithm; so the simulation results can only be used as a rough reference instead of an exact practical one. But the concepts the paper attempted to advocate could be considered seriously.

The scope of the paper is within the general theory of AQM. So it can be referred to any specific field that employs AQM technology, no matter locally or globally.

There are not much new brand contents in the paper. The main contribution is on some extension of the known related work.

Inclusion of mobile nodes (MNs) in Internet of Things (IoT) further increases the challenges such as frequent network disconnection and intermittent connectivity because of high mobility rate of nodes. This paper aims to propose a proactive mobility and congestion aware route prediction mechanism (PMCAR) to find the congestion free route from leaf to destination oriented directed acyclic graph root (DODAG-ROOT) which considers number of MNs connected to a static node. This paper compares the proposed technique (PMCAR) with RPL (OF0) which considers the HOP-COUNT to determine the path from leaf to DODAG-ROOT. The authors performed a simulation with the proposed technique in MATLAB to present the benefits in terms of packet loss and energy consumption.

In this pandemic situation, mobile and IoT play major role in predicting and preventing the CoronaVirus Disease of 2019 (COVID-19). Huge amount of computations is happening with the data generated in this pandemic with the help of mobile devices. To route the data to remote locations through the network, it is necessary to have proper routing mechanism without congestion. In this paper, PMCAR mechanism is introduced to achieve the same. Internet of mobile Things (IoMT) is an extension of IoT that consists of static embedded devices and sensors. IoMT includes MNs which sense data and transfer it to the DODAG-ROOT. The nodes in the IoMT are characterised by low power, low memory, low computing power and low bandwidth support. Several challenges are encountered by routing protocols defined for IPV6 over low power wireless personal area networks to ensure reduced packet loss, less delay, less energy consumption and guaranteed quality of service.

The results obtained shows a significant improvement compared to the existing approach such as RPL (OF0). The proposed route prediction mechanism can be applied largely to medical applications which are delay sensitive, particularly in pandemic situations where the number of patients involved and the data gathered from them flows towards a central root for analysis. Support of data transmission from the patients to the doctors without much delay and packet loss will make the response or decisions available more quickly which is a vital part of medical applications.

The computational technologies in this COVID-19 pandemic situation needs timely data for computation without delay. IoMT is enabled with various devices such as mobile, sensors and wearable devices. These devices are dedicated for collecting the data from the patients or any objects from different geographical location based on the predetermined time intervals. Timely delivery of data is essential for accurate computation. So, it is necessary to have a routing mechanism without delay and congestion to handle this pandemic situation. The proposed PMCAR mechanism ensures the reliable delivery of data for immediate computation which can be used to make decisions in preventing and prediction.

The purpose of this paper is to optimally locate and size the FACTS device, namely, interline power flow controller in order to minimize the total cost and relieve congestion in a power system. This security analysis helps independent system operator (ISO) to have a better planning and market clearing criteria during any operating state of the system.

A multi-objective optimization problem has been developed including real power performance index (RPPI) and expected security cost (ESC). A security constrained optimal power flow has been developed as expected security cost optimal power flow problem which gives the probabilities of operating the system in all possible pre-contingency and post-contingency states subjected to various equality and inequality constraints. Maximizing social welfare is the objective function considered for normal state, while minimizing compensations for generations rescheduling and maximizing social welfare are the objectives in case of contingency states. The proposed work is viewed as a two level problem wherein the upper-level problem is to optimally locate IPFC using RPPI and the lower-level problem is to minimize the ESC subjected to various system constraints. Both upper-level and lower-level problem are solved using particle swarm optimization and The performance of the proposed algorithm is tested under severe line outages and has been validated using IEEE 30 bus system.

The proposed methodology shows that IPFC controls the power flows in the network without generation rescheduling or topological changes and thus improves the performance of the system. It is found that the benefit achieved in the ESC due to the installation of IPFC is greater than the annual investment cost of the device. ISO cannot achieve minimum total system cost by merely rescheduling generators. Instead of rescheduling, FACTS devices can be used for compensation by achieving minimum cost. IPFC can be used to compensate the congested lines and transfer cheaper power from generators to consumers.

Operational reliability, financial profitability and efficient utilization of the existing transmission system infrastructure has been achieved using single FACTS device. Instead of using multiple FATCS devices, if a single FACTS device like IPFC which itself can compensate several transmission lines is used, then in addition to the facility for independently controlled reactive (series) compensation of each individual line, it provides a capability to directly transfer real power between the compensated lines. Hence an attempt has been made in this paper to incorporate IPFC for relieving congestion in a deregulated environment. However, no previous researches have considered incorporating compensation of multi-transmission line using single IPFC in minimizing ESC. Thus, in this paper, the authors indicate how much the ESC is reduced by installing IPFC.

This paper aims to predict the traffic and helps to find a solution. Unpredictable traffic leads more vehicles on the road. The result of which is one of the factors that aggravate traffic congestion. Traffic congestion occurs when the available transport resources are less when compared to the number of vehicles that share the resource. As the number of vehicles increases the resources become scarce and congestion is more.

The population of the urban areas keeps increasing as the people move toward the cities in search of jobs and a better lifestyle. This leads to an increase in the number of vehicles on the road. However, the transport network, which is accessible to the citizens is less when compared to their demand.

The demand for resources is higher than the actual capacity of the roads and the streets. There are some circumstances, which will aggravate traffic congestion. The circumstances can be the road condition (pot holes and road repair), accidents and some natural calamities.

There is a lot of research being done to predict the traffic and model it to find a solution, which will make the condition better. However, still, it is an open issue. The accuracy of the predictions done is less.

This paper discusses various facets of quality of service (QOS), a technology that allows network managers to prioritize data to optimize bandwidth use and maintain data quality. Given the wide variety and high volume of data as well as bandwidth limitations on networks today, QOS has gained great importance in recent years. Successful implementation of QOS requires selecting from the wide array of models and algorithms available and careful consideration of other technical and organizational issues. Different QOS models and algorithms have been discussed to provide the network manager with an insight into these technologies that can aid in the selection of QOS models and algorithms. Various technical and organizational implementation issues, including how QOS is implemented in routers, have been discussed to assist the network manager to be aware of these issues and properly implement QOS.

Relief item distribution to victims is a key activity during disaster response. Currently many humanitarian organizations follow simple guidelines based on experience to assess need and distribute relief supplies. However, the interviews with practitioners suggest a problem in efficiency in relief distribution efforts. The purpose of this paper is to develop a model and solution methodology that can estimate relief center (RC) performance, measured by waiting time for victims and throughput, for any RC design and analyze the impact of key design decisions on these performance measures.

Interviews with practitioners and current practice guidelines are used to understand relief distribution and a queuing network model is used to represent the relief distribution. Finally, the model is applied to data from the 2015 Nepal earthquake.

The findings identify that dissipating congestion created by crowds, varying item assignment decisions to points of distribution, limiting the physical RC capacity to control congestion and using triage queue to balance distribution times, are effective strategies that can improve RC performance.

This research bases the RC designs on Federal Emergency Management Agency guidelines and assumes a certain area and volunteer availability.

This paper contributes to humanitarian logistics by discussing useful insights that can impact how relief agencies set up and operate RCs. It also contributes to the queuing literature by deriving analytic solutions for the steady state probabilities of finite capacity, state dependent queues with blocking.

Information-centric networking (ICN) is an innovative paradigm for the future internet architecture. This paper aims to provide a view on how academic video lectures can exploit the ICN paradigm. It discusses the design of academic video lectures over named data networking (NDN) (an ICN architecture) and speculates their future development. To the best of author’s knowledge, a similar study has not been presented.

The paper is a visionary essay that introduces the background, elaborates the basic concepts and presents the author’s views and insights into academic video lectures that exploit the latest development of NDN approach and its applications.

The ICN paradigm is closely related to the levels of automation and large-scale uptake of multimedia applications that provide video lectures. Academic video lectures over NDN have: improved efficiency, better scalability with respect to information/bandwidth demand and better robustness in challenging communication scenarios. A framework of academic video lectures over NDN must take into account various key issues such as naming (name resolution), optimized routing, resource control, congestion control, security and privacy. The size of the network in which academic video lectures are distributed, the content location dynamics and the popularity of the stored video lectures will determine which routing scheme must be selected. If semantic information is included into academic video lectures, the network dynamically may assist video (streaming) lecture service by permitting the network to locate the proper version of the requested video lecture that can be better delivered to e-learners and/or select the appropriate network paths.

The paper helps researchers already working on video lectures in finding a direction for designing and deploying platforms that will provide content-centric academic video lectures.

The paper pioneers the investigation of academic video lecture distribution in ICN and presents an in-depth view to its potentials and research trends.

In recent years, a number of alternatives for service differentiation and QoS provision have been proposed and standardized in communication networks. In the case of back‐bone networks the DiffServ architecture has prevailed, due to its scalability and deployment feasibility. The provisioning of differentiated services has raised the requirements for interdependent controlled resource allocation and service pricing, with particular needs for pricing mechanisms that preserve the potential and flexibility of the DiffServ framework. At the same time, such mechanisms should reflect resource usage, allocate resources efficiently, reimburse costs or maximize service provision profits and lead customers to requesting services that will maximize their revenue. Presents the key issues involved in the area of pricing DiffServ‐based services and the research work carried out in this field, while at the same time outlining the basic principles that such a pricing infrastructure should obey with respect to the particularities that apply to the case of DiffServ services provision.

Computer networks are very complex and somewhat unpredictable systems in dynamic operations. Cybernetic modelling, incorporating stochastic, fuzzy variables, wherever appropriate, approximating interactions not easily tractable via a black‐box systems approach, may be more accurate. A method of analysis of computer networks is considered by representing subsystems and interactions, accurately as far as possible, and then utilising the results of systems sciences for analysis, including specifics, e.g. queuing systems. The aim is to identify correspondences between the behaviour of subsystems of networks and suitable analytic tools. Automation along such lines for the analysis and design of networks and other systems may be a possibility.