A longstanding problem with the Internet is that it is vulnerable to outages, black holes, hijacking and denial of service. Although architectural solutions have been proposed to address many of these issues, they have had difficulty being adopted due to the need for widespread adoption before most users would see any benefit. This is especially relevant as the Internet is increasingly used for applications where correct and continuous operation is essential.In this paper, we study whether a simple, easy to implement model is sufficient for addressing the aforementioned Internet vulnerabilities. Our model, called ARROW (Advertised Reliable Routing Over Waypoints), is designed to allow users to configure reliable and secure end to end paths through participating providers. With ARROW, a highly reliable ISP offers tunneled transit through its network, along with packet transformation at the ingress, as a service to remote paying customers. Those customers can stitch together reliable end to end paths through a combination of participating and non-participating ISPs in order to improve the faulttolerance, robustness, and security of mission critical transmissions. Unlike efforts to redesign the Internet from scratch, we show that ARROW can address a set of well-known Internet vulnerabilities, for most users, with the adoption of only a single transit ISP. To demonstrate ARROW, we have added it to a small-scale wide-area ISP we control. We evaluate its performance and failure recovery properties in both simulation and live settings.

Abstract-Delay-sensitive Internet traffic, such as live streaming video, voice over IP, and multimedia teleconferencing, requires low end-to-end delay in order to maintain its interactive and streaming nature. In recent years, the popularity of delay-sensitive applications has been rapidly growing. This paper provides a protocol that minimizes the end-to-end delay experienced by inelastic traffic. We take a known convex optimization formulation of the problem and use an optimization decomposition to derive a simple distributed protocol that provably converges to the optimum. Through the use of multipath routing, our protocol can achieve optimal load balancing as well as increased robustness. By carrying out packet level simulations with realistic topologies, feedback delays, link capacities, and traffic loads, we show that our distributed protocol is adaptive and robust. Our results demonstrate that the protocol performs significantly better than other techniques such as shortest path routing or equal splitting among multiple paths.

Power system planning in numerous electric utilities merely relies on the conventional statistical methodologies, such as ARIMA for short-term electrical load forecasting, which is incapable of determining the non-linearities induced by the non-linear seasonal data, which affect the electrical load. This research work presents a comprehensive overview of modern linear and non-linear parametric modeling techniques for short-term electrical load forecasting to ensure stable and reliable power system operations by mitigating non-linearities in electrical load data. Based on the findings of exploratory data analysis, the temporal and climatic factors are identified as the potential input features in these modeling techniques. The real-time electrical load and meteorological data of the city of Lahore in Pakistan are considered to analyze the reliability of different state-of-the-art linear and non-linear parametric methodologies. Based on performance indices, such as Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE), the qualitative and quantitative comparisons have been conferred among these scientific rationales. The experimental results reveal that the ANN–LM with a single hidden layer performs relatively better in terms of performance indices compared to OE, ARX, ARMAX, SVM, ANN–PSO, KNN, ANN–LM with two hidden layers and bootstrap aggregation models.

Consumers all over the world are increasingly using their smartphones on the go and expect consistent, high quality connectivity at all times. A key network primitive that enables continuous connectivity in cellular networks is handoff. Although handoffs are necessary for mobile devices to maintain connectivity, they can also cause short-term disruptions in application performance. Thus, applications could benefit from the ability to predict impending handoffs with reasonable accuracy, and modify their behavior to counter the performance degradation that accompanies handoffs. In this paper, we study whether attributes relating to the cellular network conditions measured at handsets can accurately predict handoffs. In particular, we develop a machine learning framework to predict handoffs in the near future. An evaluation on handoff traces from a large US cellular carrier shows that our approach can achieve 80% accuracy -27% better than a naive predictor.

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The concept of hybrid high-voltage alternating current (HVAC) and high-voltage direct current (HVDC) grid systems brings a massive advantage to reduce AC line loading, increased utilization of network infrastructure, and lower operational costs. However, it comes with issues, such as integration challenges, control strategies, optimization control, and security. The combined objectives in hybrid HVAC–HVDC grids are to achieve the fast regulation of DC voltage and frequency, optimal power flow, and stable operation during normal and abnormal conditions. The rise in hybrid HVAC–HVDC grids and associated issues are reviewed in this study along with state-of-the-art literature and developments that focus on modeling robust droop control, load frequency control, and DC voltage regulation techniques. The definitions, characteristics, and classifications of key issues are introduced. The paper summaries the key insights of hybrid HVAC–HVDC grids, current developments, and future research directions and prospects, which have led to the evolution of this field. Therefore, the motivation, novelty, and the main contribution of the survey is to comprehensively analyze the integration challenges, implemented control algorithms, employed optimization algorithms, and major security challenges of hybrid HVAC–HVDC systems. Moreover, future research prospects are identified, such as security algorithms’ constraints, dynamic contingency modeling, and cost-effective and reliable operation.

Abstract. The Mediterranean is a climatically sensitive region located at the crossroads of air masses from three continents: 15Europe, Africa and Asia. The chemical processing of air masses over this region has implications not only for the air quality, but also for the long-range transport of air pollution. To obtain a comprehensive understanding of oxidation processes over the Mediterranean, atmospheric concentrations of the hydroxyl radical (OH) and the hydroperoxyl radical (HO2) were measured during an intensive field campaign (CYprus PHotochemistry EXperiment, CYPHEX-2014) in the north-west of Cyprus in the summer of 2014. Very low local anthropogenic and biogenic emissions around the measurement location 20 provided a vantage point to study the contrasts in atmospheric oxidation pathways under highly processed marine air masses and those influenced by relatively fresh emissions from mainland Europe.The CYPHEX measurements were used to evaluate OH and HO2 simulations using a photochemical box model (CAABA/MECCA) constrained with CYPHEX observations of O3, CO, NOx, hydrocarbons, peroxides and other major HOx (OH + HO2) sources and sinks in a low NOx environment (<100 pptv NO). The model simulations for OH showed very good 25 agreement with in-situ OH observations. Model simulations for HO2 also agreed fairly well with in-situ observations except when pinene levels exceeded 80 pptv. Different schemes to improve the agreement between observed and modelled HO2, including changing the rate coefficients for the reactions of terpene generated peroxy radicals (RO2) with NO and HO2 as well as the autoxidation of terpene generated RO2 species, are explored in this work. The main source of OH in Cyprus was its primary production from O3 photolysis during the day and HONO photolysis during early morning. Recycling contributed 30 about one-third of the total OH production, and the maximum recycling efficiency was about 70 %. CO, which was the largest OH sink was also the largest HO2 source. Lowest HOx production and losses occurred when the air masses had higher residence time over the oceans.Atmos. Chem. Phys. Discuss., https://doi.org/10. 5194/acp-2018-25 Manuscript under review for journal Atmos. Chem. Phys. Air pollution and HOx chemistryThe chemical and photochemical processing of air pollutants, in conjunction with local emissions, meteorology and atmospheric transport, strongly influences the air quality over a region. The regional air quality impacts human health, agriculture, the overall condition of the biosphere and subsequently the climate. Studies attribute 2-4 million premature 5 deaths globally to outdoor air pollution (Silva et al., 2013;Lelieveld et al., 2015). Oxidants in the Earth's atmosphere prevent the pollutants released into it from building up to toxic levels. These oxidants not only convert many toxic pollutants into less toxic forms (e.g. CO to CO2) but also help in their removal (e.g. NOx and SO2 are converted into soluble HNO3 and H2SO4 respectively), although some toxic chemicals may s...

Abstract. Laser induced fluorescence (LIF) is a widely used technique for both laboratory-based and ambient atmospheric chemistry measurements. However, LIF instruments require calibrations in order to translate instrument response into concentrations of chemical species. Calibration of LIF instruments measuring OH and HO2 (HOX), typically involves the photolysis of water vapor by 184.9 nm light thereby producing quantitative amounts of OH and HO2. For ground-based systems HOX instruments, this method of calibration is done at one pressure (typically ambient pressure) at the instrument inlet. However, airborne HOX instruments can experience varying cell pressures, internal residence times, temperatures, and humidity during flight. Therefore, replication of such variances when calibrating are essential to acquire the appropriate sensitivities. This requirement resulted in the development of the APACHE (All Pressure Altitude-based Calibrator for HOX Experimentation) chamber. It utilizes photolysis of water vapor, but has the additional ability to alter the pressure at the inlet of the HOX instrument thus relating instrument sensitivity to the external pressure ranges experienced during flight (275 to 1000 mbar). Measurements supported by COMSOL multiphysics and its computational fluid dynamics calculations revealed that, for all pressures explored in this study, APACHE is capable of initializing homogenous flow and maintain near uniform flow speeds across the internal cross-section of the chamber. This reduces the uncertainty regarding average exposure times across the mercury (Hg) UV ring lamp. Two different actinometrical approaches characterized the APACHE UV ring lamp flux as 6.3 x 1014 (± 0.9 x 1014) s-1 depending on pressure. Data presented in this study are the first direct calibrations, performed in a controlled environment using APACHE of an airborne HOX system instrument.