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This paper proposes a novel estimation scheme for angular quantities extraction under disturbed network conditions; a robust identification of the network angular frequency and of its derivative are crucial for the synthetic inertia provision from grid-connected converters. The newly proposed architecture is derived from the Second Order / Second Order Generalized Integrator scheme (SO-SOGI), an algorithm exploited to extract the fundamental harmonic component from phase voltages measurements, with the introduction of an additional decoupling feedback for negative sequence compensation. The effectiveness and robustness of the proposed technique are compared, both analytically and experimentally, with other schemes already available in literature.

Pervasive sensing and actuation applications are increasingly being built using distributed devices connected with low-power wireless links. Most of these applications exploit anarchic protocols in which devices independently attempt to seize communication resources, supporting only best-effort applications as the communication they rely on cannot be guaranteed. For strict quality of service requirements, a few, non-anarchic, disciplined approaches exist in which nodes coordinate and resources are guaranteed to individual devices. Unfortunately, these solutions come at a considerable cost to form and conform to rigid communication schedules while considering the inherent volatility of the wireless environment. This work proposes Reins-MAC, a fully distributed solution that adapts to changes in the wireless environment and forms a flexible communication schedule able to support quality of service requirements. Inspired by pulse-coupled oscillators, the mathematical formulation of firefly flash synchronization, our approach forms and reserves communication slots of variable size in an online and adaptive manner. Reins-MAC tailors communication resources to network conditions that vary in time and space as well as to the explicit communication needs of devices by enabling distributed, dynamic changes to established schedules. Ultimately, Reins-MAC allows higher level abstractions to rein in the protocol anarchy, laying the foundation for reliable wireless applications.

In underwater wireless sensor networks (UWSNs), geographic routing paradigm seems promising choice for data transmission in severely limited acoustic communication channel conditions. The main challenge of geographic routing in sparse network conditions is communication void. In this context, we propose geospatial division based geo-opportunistic routing scheme for interference avoidance (GDGOR-IA) focusing on interference in the network. The scheme is twofold, selection of target cube and selection of optimal next hop forwarder node in the target cube.

Market displacement effect is identified as a result of sustained and cumulative police attacks on the Big Circle Boys (BCB) where they ceased trading heroin to focus on other drugs. Evidence showed that throughout the 1990s as they supplied heroin to both Canada and Australia, they contributed to causing the heroin glut and drought not only in Canada but also in Australia during the same period. Contrary to research, this showed that police attacks can and did have a significant disruptive effect given certain market and network conditions of the players. The network effect of the cohesive and tight decentralised BCB network structure played a part in the way they adapted to the attacks and the external factors of the market dynamics, including Southeast Asia’s shift from opium and heroin to amphetamine-type stimulants in the 1990s. This is in contrast to Bouchard’s framework but offered a new and revised theoretical angle.

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Elastic Optical Networks (EON) are considered as a valuable solution to enhance optical networks efficiency due to their superior network spectrum use. By breaking the traditional fixed grid of WDM networks, the spectrum assigned to connection demands is adapted to their requirements. On the other hand, connection parameters such as baud-rate or modulation format are dynamically adjusted taking into account the current network conditions. Therefore, EONs fit perfectly with the heterogeneous characteristics of current and future network traffic loads. Nevertheless, when EONs are in operation, they present some weaknesses mainly derived from the spectrum fragmentation generated by the dynamic establishment and torn-down of these diverse connections. The randomness of connections generation results in the blocking of some connections even when the total load supported by the network is not so high. In this work, we analyse how traffic tolerance to delay impacts on the EON performance, and present simulation obtained results when connection demands have no strict delay constraints compared with demands which need to be real-time served. This work was partially supported by the EC through the METRO-HAUL project (G.A. 761727), and from the Spanish MINECO TWINS project (TEC2017-90097-R).

Owing to limited transmission capacities of networks and some devices in closed-loop systems, data transmitted in practical NCSs should be quantized [157]. A “zoom” strategy has been proposed on quantized control in [8, 71]. Stabilization of nonlinear continuous-time systems with input quantization and packets dropout has been investigated actively in [156]. Design and stability analysis of NCSs with quantization effect and noisy measurement have been discussed based on a Kalman filter in [146]. Stability analysis of NCSs with quantized feedback inputs and measurements has been given in [147]. Although fruitful results on quantization have been given in recent publications, there is still a lot of space for further investigation, such as quantization problems under network conditions.

Russian Abstract: в статье рассматриваются проблемы трансформации информационной среды и процессов управления образовательным пространством в условиях сетевого взаимодействия при переходе к цифровой модели, основная цель которого заключается в поддержке высокого качества образовательного процесса и информационной безопасности English Abstract: The article discusses the problems of transformation of the information environment and educational space management processes in the context of network interaction during the transition to a digital model, whose main goal is to maintain a high quality of the educational process and information security.

Since from last decade, there is significant growth in using the wireless networking based communications. The applications like video streaming, audio streaming, and file transfers need the huge bandwidth for wireless data transfer processing. Integrating the higher delay and channel error based wireless networks with the conventional wired networks poses the significant problems to the research group. For wireless networks, the first challenge is consolidating the end to end congestion control. To achieve the congestion control in wireless networks, TCP is the most commonly suggested congestion control method. The TCP protocol was initially designed and used on the wired networks, later the issues of compatibility necessitate its use over wireless networks like MANET, WSN etc. However using the TCP in dynamic wireless networks effectively is a challenging research problem. The wireless network is dynamic in nature without any fixed topology and infrastructure with various data applications. The TCP protocol required to cope up with the mobility and high dynamics of wireless networks. There are several TCP variants reported for wireless networks, in this paper we present the analysis of five such TCP protocols with various wireless communication scenarios. We present the working and evaluation of TCP variants ranging from traditional to recent such as New-Reno, Vegas, Sack, Cubic, and FNC. The simulation results for different network conditions claims the current research problems and future roadmap in the design of TCP protocol for wireless networks.

This article investigates a new current control strategy for grid connected doubly fed induction generators (DFIG) under unbalanced grid voltage conditions. DFIG dynamic model is represented in synchronously rotating symmetrical component dq frames of references. A proportional controller which feed forwards estimated disturbance terms is proposed for power control in unbalanced voltage conditions to accomplish positive sequence power demand and also to dissipate negative sequence components which cause double frequency oscillations in power. DFIG parameters are not required to be known since it estimates the machine parameters relevant nonlinear terms with a disturbance observer (DOB). The novel controller structure is implemented by using dSPACE ds1103 digital controller which controls a 1.1 kW DFIG experimental setup.

In this paper, we proposed a novel algorithm to dynamically enable and disable IEEE 802.11 DCF's RTS/CTS handshake. We start by conducting an experimental characterization of the performance of RTS/CTS as a function of packet size, transmission rate, and network contention, which complements existing work that evaluated RTS/CTS performance analytically and empirically. Motivated by our experimental evaluation of RTS/CTS performance, our algorithm uses current packet size and transmission rate, as well as an estimate of network contention to dynamically decide whether to use RTS/CTS or not. To the best of our knowledge, the proposed algorithm is the first to enable and disable the RTS/CTS handshake based on a set of current network conditions, and automatically adapt as these conditions change. Simulation results using a variety of WLAN scenarios, including synthetic and real traffic traces, demonstrate that the proposed approach consistently outperforms current best practices, such as never enabling RTS/CTS or setting the RTS Threshold (RT), which is used to decide whether to switch RTS/CTS on or off, to a static value.

This paper presents the findings of our study into the performance of two popular instant messaging applications: WhatsApp and Skype. We have evaluated the performance of WhatsApp and Skype in terms of their data consumption/usage when sending text messages and making VoIP calls, as well as the quality of the VoIP calls made with these applications. Our results show that WhatsApp uses less data compared to Skype when sending text messages and making VoIP calls. We also find that both applications have similar VoIP call quality (mean opinion scores) when network conditions are good. However under poor network conditions, WhatsApp VoIP call quality is better than that of Skype. Our results will be useful to smart phone users who have mobile plans with limited data allowance, and provides guidance to them in terms of their selection of which instant messaging app is more suitable for them.

In HPC, endpoint congestion is a bottleneck in the network and seriously affects the performance of the system. The endpoint congestion can be effectively mitigated by quickly responding to the network and reducing the injection rate of the source. However, most of the prior works do not consider the impact of flow completion time on system performance, but only focus on the packet latency and perform scheduling at packet granularity. For HPC applications, the flow completion time and throughput are the metrics that determines the speed of application execution. Although prior works reduce package latency, they do not fundamentally reduce the flow latency in flow level. In this paper, we propose the bilateral flow-based reservation protocol (BFRP). BFRP quickly responds to network conditions through light-weight bilateral reservation mechanism and can effectively avoid the formation of endpoint congestion. BFRP also schedules packets based on flows, and smallest flow is preferentially sent to decrease the average flow latency. BFRP ensures the source and destination send or receive flows according to the allocated time slices without any conflict at both ends. We evaluate our BFRP protocol against state-of-the-art reservation-based protocol, speculative reservation protocol(SRP), and the simulation results show that the flow latency can be reduced by 27.68% under hotspot traffic with fixed flow size and 24.59% under uniform traffic with fixed flow size.

The performance of Wireless Local Area Network (WLAN) is highly dependent on the processes that are implemented in the Medium Access Control (MAC) sublayer regulated by the IEEE 802.11 standard. In turn, various parameters affect the performance of the MAC sublayer, the most important of which is the number of stations in the network and the offered load. With the massive growth of multimedia traffic, research of the network performance depending on traffic types is relevant. In this paper, we present the impact of a high-/low-priority traffic ratio on WLAN performance with different numbers of access categories. The simulation results show different impact of high-/low-priority traffic ratio on the performance of the MAC sublayer of wireless LANs depending on different network-sizes and on network conditions. Performance of the large network with two access categories and with the prevalent high-priority traffic is significantly higher than in the case of using four categories on the MAC sublayer. This allows us to conclude that the performance improvement of the large network with the prevalent high-priority traffic can be achieved by an adaptive adjustment of the access categories number on the MAC sublayer.

In recent years, the deployment of wireless sensor networks has become an imperative requisite for revolutionary areas such as environment monitoring and smart cities. The en-route filtering schemes primarily focus on energy saving by filtering false report injection attacks while network lifetime is usually ignored. These schemes also suffer from fixed path routing and fixed response to these attacks. Furthermore, the hot-spot is considered as one of the most crucial challenges in extending network lifetime. In this paper, we have proposed a genetic algorithm based fuzzy optimized re-clustering scheme to overcome the said limitations and thereby minimize the effect of the hot-spot problem. The fuzzy logic is applied to capture the underlying network conditions. In re-clustering, an important question is when to perform next clustering. To determine the time instant of the next re-clustering (i.e., number of nodes depleted&mdash, energy drained to zero), associated fuzzy membership functions are optimized using genetic algorithm. Simulation experiments validate the proposed scheme. It shows network lifetime extension of up to 3.64 fold while preserving detection capacity and energy-efficiency.

HTTP Adaptive Streaming (HAS) is a technique that adapts its video quality to network conditions for providing Quality of Experience. In the HAS approach, a video content is encoded at multiple bitrates and the encoded video content is divided into several video segments. A HAS player estimates the network bandwidth and adjusts the video bitrate based on estimated bandwidth. However, the segment scheduler in the conventional HAS player requests video segments periodically without considering TCP. If the waiting duration for the next segment request is quite long, the TCP connection can be initialized and it restarts slow-start. Slow-start causes the reduction in TCP throughput and consequentially leads to low-quality video streaming. In this study, we propose a TCP-aware segment scheduling scheme to improve performance of HAS service. The proposed scheme adjusts request time for the next video request to prevent initialization of TCP connection and also considers the point of scheduling time. The simulation proves that our scheme improves the Quality of Service of the HAS service without buffer underflow issue.

The national road network has a significant role in promoting the national economy in Indonesia. But the national road network conditions in general are still not satisfactory although the government continues to improve the technical standards of road maintenance which contributes to the high unit cost of road maintenance. To overcome this classical problem, now the road agencies began to implement alternative road maintenance contracts known as Performance Based Contract (PBC). Successful practice of PBC implementation in various countries indicates that the PBC is able to produce a good road service performance compared with the implementation of in-house system or contract-based input on road maintenance projects. This study aims to measure the impact of PBC implementation on the national road maintenance project in Indonesia with the type of flexible pavement. The impact of PBC is focused on the functional performance, which is measured using a model of IIRMS and expressed in the International Roughness Index (IRI) value. The case study conducted on one of the PBC pilot projects that are in the segment of northern coast of West Java. The results showed that the implementation of PBC for national road maintenance projects proven to ensure the quality and road service performance for the long term.

Existing channel-aware scheduling work has mainly focused on scheduling in small timescales, that is, tens to hundreds of seconds. We propose to use long-term user profiles to provide useful statistical information on future network conditions in large timescales. We design scheduling algorithms based on Markov decision theory. We collect and use a large set of real-life traces from the general public. Extensive trace-driven evaluations show that many real mobile users can benefit from our framework. In addition, we compare our framework against state-of-the-art algorithms and observe significant performance differences because the existing algorithms were not designed for the large timescale scenario.

The availability of telecommunication infrastructure affects the development of an area, especially areas that have the potential for tourism and agricultural products such as Tenjolaya Village. The development of RT RW net as internet network infrastructure using Wi-Fi technology can be a supporting sector for the economic development of the village. Network deployment is carried out in three stages: preparation, construction and measurement. In the preparation stage, the number of users is calculated and a survey of the installation location is carried out. Furthermore, network development is carried out based on the network architecture that has been designed with CPE totaling four points. In the final stage, four parameters are measured to check the network conditions. The parameters are throughput, signal strength, CCQ, and SNR. From the measurement results, the measured throughput at the access point has a value range of 17 to 30 dBm. The measured Tx signal strength has a value of -75 to -39 dBm while the Rx signal strength is between -72 to -37 dBm. The CCQ value is between 76 and 100%. The measured SNR parameter has a value of 38 to 77 dBm.

Rapidly growing and fluctuating traffic demands lead to unbalanced traffic scenarios in optical access networks, which have an impact on network efficiency. Thus, the flexible software-defined reconfigurable passive optical network (PON) architecture has been proposed to handle this challenge. To improve the efficiency of a reconfigurable PON facing unbalanced traffic demands, this paper proposes a global load-balancing (GLB) optical network unit (ONU) assignment method, which aims to achieve load balancing among the optical line terminals (OLTs) in the OLT pool as well as among the aggregation switch ports that connect the OLTs by optimizing the affiliations between the OLTs and the ONUs. For on-line optimization, a greedy GLB algorithm is introduced that regroups the ONUs and generates load-balanced target ONU-OLT affiliations in accordance with dynamic traffic demands. For off-line optimization, bee colony optimization (BCO) is invoked to search for better ONU regrouping solutions for GLB. Simulation results show that the proposed GLB algorithm can significantly improve the throughput and delay performance of an optical access network faced with unbalanced traffic demands, especially when the network load is heavy. Moreover, the proposed BCO technique for GLB can obviously improve the worst delay performance and reduce the migrated traffic of the GLB solution, especially under network conditions with high peer-to-peer traffic proportions and heavy network loads. Thus, the proposed global load-balancing ONU assignment method is effective for helping a software-defined reconfigurable PON to cope with unbalanced traffic demands.

Travel information is expected by many scholars and practitioners alike to be successful in reducing traffic congestion and thereby improving road network efficiency. Yet, traditional (personalized) travel information aims at generating benefits to individual travellers, stimulating their personal optimization of their own route choices; it is well-known that this may lead to an inefficient user equilibrium. Examples on network efficiency have shown that in order to achieve system optimal network conditions, at least some travellers need to act non-selfish and take a detour to the benefit of others (i.e. the network as a whole). An important question in this regard is how to motivate those travellers to take this detour. This thesis deals with the problem of improving road network efficiency by stimulating social choice behaviour using social routing advice. Stated choice and revealed choice experiments provide insights into individual compliance behaviour, while network simulation indicates the resulting network impacts. Results show that travellers are sometimes willing to choose the social detour over their usual route. Travellers are willing to choose the social route when travel time sacrifices are not too large, when information messages are aiming at alleviating congestion as opposed to safety or environmental concerns, and when these messages are framed according to certain strategies that nudge travellers towards the social route, that reinforce social norms towards taking the social route or that educate travellers on the importance of taking the social route. Moreover, travellers are most likely to comply with the received advice when they are cooperatively oriented and when they make their choices in a non-habitual manner. As a result, network efficiency improves; structural congestion and unstable flows reduce, especially on major city roads. However, individual benefits will be marginal; the majority of travellers experience a travel time gain of less than two minutes. Finally, I show that the lower the compliance among travellers, the more social travellers need to compensate for the selfish behaviour of others by taking longer detours.

High-speed night train is a new personalized product of high-speed railway to meet the market demand in China. Based on the existing operation conditions of high-speed night train, by recapitulating its relevant advantages and comparing with characteristics of high-speed day train, conventional train, and civil flight products, it comes to a conclusion that the high-speed night train has certain competitiveness and has well expanded the high-speed railway service portfolio. By analyzing the passenger flow characteristics of high-speed night train according to the ticketing data, it is found that the passenger flow characteristics of Beijing–Guangzhou and Shanghai–Shenzhen high-speed night trains are similar, both have relatively stable passenger flows, and also have a certain share in the passenger transportation market. Through analysis on passenger flow composition of high-speed night train, it is found that the high-speed night train is a supplement to high-speed day trains, and the passenger flow basically consists of transfer passengers. At last, based on calculation of passenger transfer inclination, neural network method, time series method, curve estimation method, and multiple regression method are used to, respectively, predict the passenger flow of high-speed night train during the “13th Five-Year Plan”. The result can provide certain data support to the reasonable operation of high-speed night train under network conditions.

Most content providers are interested in providing good video delivery QoE for all users, not just on average. State-of-the-art ABR algorithms like BOLA and MPC rely on parameters that are sensitive to network conditions, so may perform poorly for some users and/or videos. In this paper, we propose a technique called Oboe to auto-tune these parameters to different network conditions. Oboe pre-computes, for a given ABR algorithm, the best possible parameters for different network conditions, then dynamically adapts the parameters at run-time for the current network conditions. Using testbed experiments, we show that Oboe significantly improves BOLA, MPC, and a commercially deployed ABR. Oboe also betters a recently proposed reinforcement learning based ABR, Pensieve, by 24% on average on a composite QoE metric, in part because it is able to better specialize ABR behavior across different network states.

The Internet of things (IoT) is defined as connected devices that can communicate with consumers, transmit data back to companies, and compile data for third parties such as researchers, health care providers, or even other consumers [1]. Wireless Body Area Networks (WBAN) is an emerging category of IoT where the QoS is key to the functioning and performance of the network. In WBAN applications are very sensitive and need mechanisms to respect the requirement of their sensed data. IEEE 802.15.6 [2] - is a BAN management protocol that provides mechanisms for multiple accesses to shared medium - supported QoS-based channel access models. In this paper we focus on CSMA/CA and slotted Aloha algorithms. These two algorithms are compared in terms of delay performance and total drop throughout. The simulation results are clearly showing that under heavily-loaded network conditions both algorithms is underperforming with respect to various QoS parameters. Most importantly, our simulations have proven that CSMA/CA provides shorter end-to-end delay. This preliminary evaluation suggests that CSMA/CA is more suitable for BAN networks aiming to optimize the communication delay

Load balancer is an essential part of a computer network. Its primary purpose is to distribute incoming traffic across multiple target servers. There are numerous load balancing techniques and each of them excels on specific network topology and server capability. However, due to vendor dependency, implementing a quintessential load balancer requires additional hardware cost and knowledge in vendor-specific configurations. Using software-defined networking (SDN) approach, testing of various load balancing techniques becomes easier and cheaper than traditional hardware-based approach. Despite the promising advantages of SDN, the novel approach is still unstable. Hence, in this experiment, performances of five different load balancing techniques—namely, random, round-robin (RR), weighted round-robin (WRR), least-connections (LC), and weighted least-connections (WLC)—were tested. The experiment was done on a single-switch topology. Mininet and POX controller were used to setup the network environment. The load balancers were also tested in two types of network conditions: with and without TCP SYN floods. After several iPerf tests, results in both network conditions indicated that RR and LC load balancers were both more than twice as fast as the one without load balancing implementation and moderately faster than random load balancer. LC and WLC were slightly faster than RR and WRR without SYN floods while RR and WRR were slightly faster with SYN floods. Future works, like testing the framework on other types of network topologies or low-level load balancing techniques, could strengthen the substantiation of stability of using SDN approach.

If there is an ultra-large scale disaster happened, the important messages such as life safety or rescues would not be transferred because of the serious damages of information networks. It is supposed that the Delay Tolerant Networking (DTN) is one of the effective routing methods for realizing against such robust network conditions, but some problems such as IP configurations or gateway functions have been considered for the realistic mobile networks. Therefore, this paper proposed the layer 2 level DTN routing methods by using WiFi P2P and the gateway functions between the DTN and IP networks. Then, the implementations of the prototype systems by Android smartphones and the field experiments are reported in the paper, and the experimental results are discussed for the effectiveness of the proposed methods and future studies.

Adaptive bit rate streaming using HTTP delivery is now widely used to provide live audio-visual content services. However, the quality of experience is often considered inferior to that of conventional broadcast services due to the high end to end latency, which is mostly due to the large amount of buffering required to provide resilience to variable network conditions. In this paper we present our initial research to address this issue of high latency. If each segment of content could be delivered in a consistent period of time, the amount of buffering required could be reduced. We present the results of simulations where we have changed the timing of the TCP congestion response to consider the timing requirements of content segments, while trying to retain fairness to competing flows. We show that with this simple modification to TCP the variation in the delivery time of content segments can be reduced and much lower end to end latency achieved. With no changes to the network or client devices required, this solution may be straightforward to deploy to make the user experience of streaming services much closer to that of conventional broadcast services.

We study the equilibrium behavior in a multi-commodity selfish routing game with many types of uncertain users where each user over- or under-estimates their congestion costs by a multiplicative factor. Surprisingly, we find that uncertainties in different directions have qualitatively distinct impacts on equilibria. Namely, contrary to the usual notion that uncertainty increases inefficiencies, network congestion actually decreases when users over-estimate their costs. On the other hand, under-estimation of costs leads to increased congestion. We apply these results to urban transportation networks, where drivers have different estimates about the cost of congestion. In light of the dynamic pricing policies aimed at tackling congestion, our results indicate that users' perception of these prices can significantly impact the policy's efficacy, and "caution in the face of uncertainty" leads to favorable network conditions., Currently under review

The paper presents detailed time-domain models of three commercially available single-phase photo voltaic (PV) inverters for harmonic studies. The inverters are used for rooftop applications and are expected to be distributed in low voltage (LV) networks in large numbers. The models are used to compare the sensitivity of the three PV inverters regarding different supply voltage distortions and grid impedance conditions. The effect of resonant harmonic amplification of inverter current is studied based on the harmonic impedance concept. Characteristical features of the PV inverter structure defining its harmonic emission in case of weak grids with voltage distortion are analyzed.

This work considers Gaussian linear control systems where the goal is to guarantee system-state mean-square stability (i.e., $E(\Vert{\mathrm{x}}(t)\Vert^{2})\ \leq\ \mathsf{D}$ ) while minimizing the traffic rate $R$ between the sensor(s) and the controller. Most existing results either assume zero delay or focus on the asymptotic setting that overlooks the impact of delay. Nonetheless, in practice the communication delay is randomly distributed due to varying channel/network conditions. When the sensor measurement finally arrives at the controller, the age-of-information is thus random. Heuristically, an “old” measurement provides less valuable information than a “young” measurement but the quantitative impact of random delay on the optimal rate-cost tradeoff $R^{\ast}(\mathsf{D})$ remains an open problem. This work provides the first lower bound $R_{\mathrm{LB}}(\mathsf{D})$ for the random delay setting and designs a simple scheme that leads to a numerically evaluated upper bound $R_{\mathrm{UB}}(\mathsf{D})$ . Jointly $R_{\mathrm{LB}}(\mathsf{D})$ and $R_{\mathrm{UB}}(\mathsf{D})$ bracket the optimal tradeoff $R^{\ast}(\mathrm{D})$ . The new $R_{\mathrm{LB}}(\mathsf{D})$ is asymptotically tight when either $\mathsf{D}\rightarrow\infty$ or $R\rightarrow\infty$ , and sheds further insights on how the (random) age of information could impact the performance of a cyber-physical control system.

Modern telemetry-based applications enable farmers to work more efficiently and to improve the utilization of their farmland. However, connectivity between agricultural machines and central farm management information systems is almost exclusively realized via mobile networks and, thus, suffers from the challenging network conditions, which often characterize agricultural scenarios. Robust networking with reliable communication across multiple machines is one of the fundamental challenges in highly distributed agricultural processes, such as the harvesting of crops. In this paper, we present the design and evaluation of a new hybrid-opportunistic network architecture that combines multiple Internet and ad-hoc machine-to-machine (M2M) connections simultaneously to provide robust and reliable communication in a decentralized network.

In many emerging data retrieval applications, in response to queries, consumers are interested in getting a summarized version of content quickly rather than retrieving all available data. Recently, Named Data Networks (NDN) have been considered for efficient transfer of summarized information, but the research is still in its infancy. In this paper, we propose NEST, a novel transport protocol for delivering extractive summaries of a dataset distributed across multiple producers over NDN. The goal is to exploit diversity in network conditions between a consumer and different producers towards delivering the consumer-specified summary while minimizing latency. NEST first creates a unified hierarchical representation of the available distributed content using state-of-the-art distributed clustering. Then, using this representation of the dataset, the protocol creates interest messages based on which consumers can opportunistically retrieve representative data objects from the best producers while adapting to dynamic network conditions by capitalizing on the flexibility offered by the NDN infrastructure. We implement NEST on the Mini-NDN network emulator and evaluate its performance using datasets collected from Twitter. Our experimental results show that NEST takes advantage of producer diversity achieving large latency reduction gains of up to 50% compared to baseline protocols.

Increasing Photovoltaic (PV) penetration and low-carbon demand can potentially lead to two different flow peaks, generation, and load, within distribution networks. This will not only constrain PV penetration but also pose serious threats to network reliability. This paper uses energy storage (ES) to reduce system congestion cost caused by the two peaks by sending cost-reflective economic signals to affect ES operation in responding to network conditions. First, a new charging and discharging (C/D) strategy based on binary search method is designed for ES, which responds to system congestion cost over time. Then, a novel pricing method, based on locational marginal pricing (LMP), is designed for ES. The pricing model is derived by evaluating ES impact on the network power flows and congestions from the loss and congestion components in LMP. The impact is then converted into an hourly economic signal to reflect ES operation. The proposed ES C/D strategy and pricing methods are validated on a real local grid supply point area. Results show that the proposed LMP-based pricing is efficient to capture the feature of ES and provide signals for affecting its operation. This work can further increase network flexibility and the capability of networks to accommodate increasing PV penetration.

This paper presents a crowdsourced dataset of a large-scale event with more than 1000 measuring participants. The detailed dataset consists of various location data and network measurements of all national carrier collected during a four-day event. The concentrated samples for this short time period enable detailed analysis, e.g., by correlating movement patterns and experienced network conditions.

In this article, we propose error and energy-aware improved adaptive-head algorithm which is an extension of improved adaptive head algorithm. It uses a new nodes' tracker selection mechanism. It also reduces the number of times the cluster head can change. In addition, it uses a multi-hop routing technique for the reason of maintaining shorter communication distances. Many Matlab simulation experiments were conducted to evaluate the performance of our proposed algorithm and further its contributions over improved adaptive head algorithm under different network conditions.

Over the last decade wireless data streaming has progressively become an important aspect of our life. However, the lack of appropriate mechanisms to handle wireless network disruptions and delays, causes mobile applications to frequently suffer from unstable wireless connectivity, which makes data streaming particularly challenging leading to unstable streaming rates, long delays and often network failures. This paper proposes a framework that utilizes performance monitoring, machine learning and scheduling techniques to effectively schedule data streaming for mobile applications. The framework monitors the current network conditions through a set of performance metrics and evaluates its availability using a machine learning approach. To meet real-time performance objectives, if the network is characterized eligible for streaming, we use a deadline-first scheduling order for the data streaming. Our experimental evaluation, using different network traffic scenarios, illustrates the performance and benefits of the approach proposed.

Stochastic User Equilibrium (SUE) models allow the representation of the perceptual and preferential differences that exist when drivers compare alternative routes through a transportation network. However, as an effect of the used choice models, conventional applications of SUE are based on the assumption that all available routes have a positive probability of being chosen, however unattractive. In this paper, a novel choice model, the Bounded Choice Model (BCM), is presented along with network conditions for a corresponding Bounded SUE. The model integrates an exogenously-defined bound on the random utility of the set of paths that are used at equilibrium, within a Random Utility Theory (RUT) framework. The model predicts which routes are used and unused (the choice sets are equilibrated), while still ensuring that the distribution of flows on used routes accords to a Discrete Choice Model. Importantly, conditions to guarantee existence and uniqueness of the Bounded SUE are shown. Also, a corresponding solution algorithm is proposed and numerical results are reported by applying this to the Sioux Falls network.

This article deals with results of performed studies of transient phenomena in application of controlled switching technique by switching high voltage 123 kV, 100 MVAr shunt reactor. First, for switching a single-pole hydraulically operated SF6 circuit breaker has been selected and after that, one with electric motor-drive. In preparing of experimental part of studies the EMTP-ATP software has been used in computer simulations, further for analyses the cases of optimal controlled switching and switching within time deviation limits. For simulation of uncontrolled switching with current chopping and arc-reignition dynamic model of arc behavior has been implemented. The field tests with both circuit breakers have been repeated in similar network conditions for further statistical analyses. During some tests, the transient phenomena of uncontrolled switching have been observed. The achieved experimental results were compared with the computer simulations.

International audience; Ulysses is an intelligent TPF client that takes advantage of replicated datasets to distribute the load of SPARQL query processing and provides fault-tolerance. By reducing the load on a TPF server, Ulysses improves the Linked Data availability and distributes the financial costs of queries execution among data providers. This demonstration presents the Ulysses web client and shows how users can run SPARQL queries in their browsers against TPF servers hosting replicated data. It also provides various visualizations that show in real-time how Ulysses performs the actual load distribution and adapts to network conditions during SPARQL query processing.

Transformer terminal equivalents obtained via admittance measurements are suitable for simulating high-frequency transient interaction between the transformer and the network. This paper augments the terminal equivalent approach with a measurement-based voltage transfer function model which permits calculation of voltages at internal points in the regulating winding. The approach is demonstrated for a single-phase three-winding transformer with its tap setting in the middle position. Three internal points in the regulating winding are included that represent the mid-point and the two extreme ends. The terminal equivalent modeling makes use of additional common-mode measurements to avoid error magnifications to result from the ungrounded tertiary winding. The final model is used in a time domain simulation where ground-fault initiation results in a resonant voltage build-up in the winding. It is shown that that the peak value of the resonant overvoltage can be higher than during the lightning impulse test, with unfavorable network conditions. Additional measurements show that the selected tap position affects the terminal behavior of the transformer, changing the frequency and peak value of the lower resonance point in the voltage transfer between windings.

Video streaming has become an indispensable technology in people’s lives, while its usage keeps constantly increasing. The variability, instability and unpredictability of network conditions pose one of the biggest challenges to video streaming. In this chapter, we analyze HTTP Adaptive Streaming, a technology that relieves these issues by adapting the video reproduction to the current network conditions. Particularly, we study how context awareness can be combined with the adaptive streaming logic to design a proactive client-based video streaming strategy. Our results show that such a context-aware strategy manages to successfully mitigate stallings in light of network connectivity problems, such as an outage. Moreover, we analyze the performance of this strategy by comparing it to the optimal case, as well as by considering situations where the awareness of the context lacks reliability.

This paper presents a quality of service analysis conducted for real-time multimedia communication services particularly over limited capacity network. This research aims to examine quality of videoconference service based on WebRTC technology. We investigate several implementation challenges of videoconferencing in bandwidth limited network by conducting a thorough experimental study. We analyze videoconference quality from the implementation of WebRTC based system for supporting distance learning between two schools in Cianjur, West Java, Indonesia. Further, we study adaptability feature of WebRTC by performing experiments for several network conditions. Result of the experiment shows that fair quality of video (peak signal-to-noise ratio, PSNR, between 30dB to 33dB) can be reached when bandwidth capacity is 2048kbps. On the other hand, the experiment shows acceptable audio and video stream quality with packet loss rate (PLR) less than 1% and jitter less than 100ms can be reached in network condition with bandwidth capacity higher than 128kbps. Outcome of this research supports understanding and addressing of the challenges of real-time videoconferencing on bandwidth limited network.

Several adaptive quorum-based protocols are proposed for multi-hop ad hoc networks and all these methods have their pros and cons. The main drawback of many current adaptive quorum-based protocols is that they have defined some fixed thresholds. Therefore, nodes can change their quorum size based on network conditions, just when they reach these thresholds. In this paper, we propose a new adaptive quorum-based protocol, called adaptive stepped grid (AS-Grid), which is based on stepped-grid quorum-based system (S-Grid). In AS-Grid, nodes can increase their quorum size gradually based on network conditions and their remaining energy adaptively and there are no fix thresholds. We also derive the EQOS and the active ratio values for the AS-Grid(t X w), and we define an approach for nodes in a same network to change their system size based on network conditions and their remaining energy adaptively. We compare our results with the EQOS values of all the popular quorum systems by analysis. Analyses results show that the AS-Grid(t × w) has comparably high EQOS values and consequently better neighbor sensibility than the FPP, Grid, torus, ge-torus and S-Grid quorum systems.

This paper explores the potential benefits and pitfalls of Multipath TCP (MPTCP) in smartphones via an extensive experimental study over real Android applications. We consider different types of applications - upload vs. download intensive, network intensive vs. interactive - and a variety of network conditions, and we study the impact of MPTCP on performance, energy consumption, and CPU utilization. Our results reveal that the benefits of MPTCP in smartphone apps are lower than expected in theory; in several cases, MPTCP in fact can hurt both performance and energy consumption. Our findings can provide insights to smartphone designers and mobile app developers towards improving user experience and extending smartphone battery life.

However, wind energy conversion system (WECS) is usually located in rural areas with weak grid connection, in which grid voltage unbalance may arise even during normal operation. The unbalanced grid voltage may be caused by unbalanced transmission line impedance, three-phase unbalanced load, and single-phase high-power load. Hence, the strategies to improve the performance of DFIGs under unbalanced network conditions have obtained a worldwide concern.

It is necessary to concern the deficient network resources if there happened to be a severe disaster, and the DTN is widely known as the suitable network routing methods for such a robust network conditions. On the contrary, the DTN has pointed out the subjects of low date delivery rate and the high latency for the uses. Therefore, this paper proposed the enhanced DTN routing methods based on the Data Triage, the Dynamic FEC controls, and the antenna directional controls. Also, it is reported the implementations of the Data Triage methods in the prototype system, and the experimental results are used for the effectiveness of the proposed methods and the future studies.

Despite the massive adoption of HTTP adaptive streaming technology, buffering is still the most harmful event for QoE in video streaming. Previous studies have shown that buffering is not only detrimental for the overall user experience, but is also highly correlated to viewer engagement. The occurrence of buffering is particularly critical in cellular networks and mobile video deployments, as network conditions are less stable and network resources more limited. In this context, monitoring and properly predicting the QoE of video streaming services becomes paramount to cellular network operators, who need to offer high quality levels to reduce the risks of customers churning for quality dissatisfaction. In this paper, we present a novel approach to multi-dimensional QoE prediction in mobile video using machine learning models. Contrary to previous models for QoE prediction in video streaming, which are generally uni- or low-dimensional and model the impact of single video descriptors independently, we use a high-dimensional input space to model the impact of buffering and initial delay on QoE. We train and test the proposed models on a publicly available mobile video dataset, generated from subjective QoE tests with real viewers. Besides improving prediction performance, the proposed models show that there is a clear influence of other buffering pattern descriptors generally neglected in previous models — in particular those linked to the occurrence of the last stalling event, shedding light on new KPIs to monitor for better QoE assessment in video streaming.

Connected cars are a rapidly growing segment of Internet of Things (IoT). While they already use cellular networks to support emergency response, in-car WiFi hotspots and infotainment, there is also a push towards updating their firmware over-the-air (FOTA). With millions of connected cars expected to be deployed over the next several years, and more importantly persist in the network for a long time, it is important to understand their behavior, usage patterns, and impact --- both in terms of their experience, as well as other users. Using one million connected cars on a production cellular network, we conduct network-scale measurements of over one billion radio connections to understand various aspects including their spatial and temporal connectivity patterns, the network conditions they face, use and handovers across various radio frequencies and mobility patterns. Our measurement study reveals that connected cars have distinct sets of characteristics, including those similar to regular smartphones (e.g. overall diurnal pattern), those similar to IoT devices (e.g. mostly short network sessions), but also some that belong to neither type (e.g. high mobility). These insights are invaluable in understanding and modeling connected cars in a cellular network and in designing strategies to manage their data demand.

In the recent gaming industry, the paradigm has been changed with upcoming core-platform as time goes by. Arcade, console, PC online and smart device platforms are representative ones. In recently, the platform is changed to multi-platform which connecting to smart device and other platforms. Besides, the multi-platform without PC is up-coming. This paper suggests that a kind of multi-platform which connecting from smart devices to arcade devices be aware of lack of continuous. It provides a new arcade gaming condition connecting to smart devices, then supplies online network conditions to the arcade gaming machine. The original arcade game was lack of continuous and the game platform was so simple, but now, it could be focused from players by connecting to smart devices to increase the gaming machines' continuity. Furthermore, Bluetooth communication module and wireless Wi-Fi communication module are used to adapt various communication environments. The Unity3D engine would make contents' expandability.

It is widely accepted that the growth of Internet and the improvement of Internet's network conditions helped real-time applications to flourish. The demand for Ultra-High Definition video is constantly increasing. Apart from video and sound, a new kind of real-time data is making its appearance, haptic data. The efficient synchronization of video, audio, and haptic data is a rather challenging effort. The new High-Efficiency Video Coding (HEVC) is quite promising for real-time ultra-high definition video transferring through the Internet. This paper presents related work on High-Efficiency Video Coding. It points out the challenges and the synchronization techniques that have been proposed for synchronizing video and haptic data. Comparative tests between H.264 and HEVC are undertaken. Measurements for the network conditions of the Internet are carried out. The equations for the transferring delay of all the inter-prediction configurations of the HEVC are defined. Finally, it proposes a new efficient algorithm for transferring a real-time HEVC stream with haptic data through the Internet.

SUMMARYIn this paper, we present a novel stochastic framework for network-based bilateral teleoperation systems. A Bayesian approach, which provides robust tracking performance in real-world applications, is proposed to estimate and predict the stochastic variables and compensate for the unreliable network conditions. Combining with a practical approach in transport and application layers of the Internet, this paper demonstrates a high performance and efficient prediction and estimation method for bilateral teleoperation system. Experimental results show that the proposed Bayesian approach estimates and predicts true position and force data over unreliable network conditions, and therefore, improves the performance of overall teleoperation systems.