The National Institute of Standards and Technology defines the fundamental characteristics of cloud computing as: on-demand computing, offered via the network, using pooled resources, with rapid elastic scaling and metered charging. The rapid dynamic allocation and release of resources on demand to meet heterogeneous computing needs is particularly challenging for data centres, which process a huge amount of data characterised by its high volume, velocity, variety and veracity (4Vs model). Data centres seek to regulate this by monitoring and adaptation, typically reacting to service failures after the fact. We present a real cloud test bed with the capabilities of proactively monitoring and gathering cloud resource information for making predictions and forecasts. This contrasts with the state-of-the-art reactive monitoring of cloud data centres. We argue that the behavioural patterns and Key Performance Indicators (KPIs) characterizing virtualized servers, networks, and database applications can best be studied and analysed with predictive models. Specifically, we applied the Boosted Decision Tree machine learning algorithm in making future predictions on the KPIs of a cloud server and virtual infrastructure network, yielding an R-Square of 0.9991 at a 0.2 learning rate. This predictive framework is beneficial for making short- and long-term predictions for cloud resources.

High-power high-frequency air-cooled induction heating transformers, mostly used as current multiplier and isolation purposes, are custom designed. For their reliable performance and long life, the thermal evaluation at rated load is necessary. Creating an equivalent load as test facility for reliability testing of such type of transformer is difficult. Characteristics of such loads drastically change after Curie temperature. Moreover, prolonged heating could increase the nearby ambient temperature and, more importantly, the traditional heat run test wastes large amount of energy. Whenever the coil is energized, windings of transformer draw respective rated current; even at no load condition the copper loss is at rated value. While both windings drawing rated current at desired frequency, using the concept of localized eddy current loss as well as excess eddy current loss, this article proposes a novel method to inject requisite core loss to the magnetic circuit to emulate the characteristics of full load condition but the power drawn from the transformer would be zero. The proposed idea would be validated where only 200 W resonant inverter would be used to inject power loss equivalent to full-load condition of 30 kW transformer to emulate the heat run test.

Global Navigation Satellite System Reflectometry (GNSS-R) has emerged as a promising remote sensing technique for coastal sea level monitoring. The GNSS-R based on signal-to-noise ratio (SNR) observations employs a single antenna and a conventional receiver. It performs best for low elevation satellites, where direct and reflected radio waves are very similar in polarization and direction of arrival. One of the disadvantages of SNR-based GNSS-R for sea level altimetry is its low temporal resolution, which is of the order of one hour for each independent satellite pass. Here we present a proof-of-concept based on a synthetic vertical array. It exploits the mechanical movement of a single antenna at high rate (about 1 Hz). SNR observations can then be fit to a known modulation, of the order of the antenna sweeping rate. We demonstrate that centimetric altimetry precision can be achieved in a 5-minute session. [©2021 IEEE]

This paper presents the design, prototyping, and testing of an S-Band conformal array on a partial wing surface. The array elements are series fed microstrip patch antennas fabricated entirely through additive manufacturing (AM) technology using a combination of fused deposition modeling and thermal spray. A robust material set of ULTEM 9085 and copper alloy is used for a good balance of mechanical/environmental robustness and RF performance, while also offering a viable path forward for a future fielded design. The focus of this paper is on AM multi-material fabrication, fundamental print settings and material characterization, and antenna testing. AM characterization coupons are utilized to improve the accuracy of the RF antenna model, which showed excellent agreement with the prototype measurements.

This paper presents analytic solutions for an optimal modulation scheme featuring low switching losses for a bidirec- tional single-phase dual active bridge (DAB) DC-DC converter used for charging high-voltage batteries of electric vehicles. The proposed modulation scheme facilitates zero-voltage switching (ZVS) for either the primary- or secondary-side full bridge of the DAB converter throughout the whole operating range while maintaining low conduction losses. The expressions are derived based on the current required for an ideal ZVS transition and enable for a direct computation of the respective optimal modulation parameters.

A document by Adnan Qayyum . Click on the document to view its contents.

This work studies the meta distribution in a partial-NOMA network to obtain fine-grained information about the network performance. As the meta distribution is approximated using the beta distribution via moment matching of the first two moments, reduced integral expressions are derived for the first two moments of the meta distribution. Accurate approximate moments are also proposed to further simplify the calculation. Security is an issue in partial-NOMA because the strong user may decode the weak user’s message in the process of decoding its own message using flexible successive interference cancellation (FSIC). Therefore, a measure of secrecy is defined in this context and the secrecy probability is derived for the case of: 1) a malicious strong user that prioritizes eavesdropping, 2) an innocent strong user that decodes the weak user’s message only when it is required to do so. The obtained results highlight the superiority of partial-NOMA over traditional NOMA in terms of secrecy. They also show that receive filtering and FSIC have a significant positive impact on the secrecy of partial- OMA. Furthermore, partial-NOMA with a small overlap of the resource-block can secure the network from the additional deterioration a malicious eavesdropper may cause.

There is a simple concept that can significantly improve the environmental balance of battery electric vehicles and at the same time avoid the known disadvantages of these vehicles (short range, long charging times, high acquisition costs) without having to wait for further developed batteries or a higher proportion of green electricity. For this purpose, the vehicles are equipped with built-in batteries for short and medium distances and are therefore sufficient for the majority of daily journeys. For long-distance journeys, the driver borrows charged additional battery packs at swapping stations, which are automatically inserted into a standardised exchange slot within a few minutes. This paper focuses on the improvements in electric vehicles that can be achieved by combining built-in and exchangeable battery technique and also on the practical feasibility of the concept. It is shown that the battery capacity required for the entire vehicle fleet can be significantly reduced. The resulting ecological advantages on the one hand and grid-stabilising effects of a nationwide network of swapping stations on the other hand, support the transition to environmentally sustainable mobility. The characteristics of the concept presented are advantageous for its practical implementation. The acceptance by customers and manufacturers can thus be improved compared to previous battery swapping systems. The loan system for the exchange batteries may be designed conveniently and information security as well as data protection will be strictly complied.

The dq-frame admittance of closed-loop controlled three-phase converters is a linearized model that is dependent on the operating points of the system. Yet, it is impractical to measure the converter admittance at all operating points. This paper, thus, proposes an approach to estimating the dq-frame admittance of three-phase converters at a wide range of operating points. The method applies multidimensional interpolation to a given set of admittance data, which is measured from the pre-defined operating points. The accuracy of interpolation is then evaluated by using the posterior error estimation method. The number of pre-defined operating points is next adjusted to find a good compromise between the accuracy and efficiency of the approach. Simulations and experimental results verify the effectiveness of the approach.

We report an octave-spanning coherent supercontinuum (SC) fiber laser with excellentnoise and polarization properties. This was achieved by pumping a highly birefringent all-normaldispersion (ANDi) photonic crystal fiber with a compact high-power ytterbium femtosecond laserat 1049 nm. This system generates an ultra-flat SC spectrum from 670 nm to 1390 nm with apower spectral density higher than 0.4 mW/nm and a polarization extinction ratio of 17 dB acrossthe entire bandwidth. An average pulse-to-pulse relative intensity noise (RIN) down to 0.54%from 700 nm to 1100 nm has been measured and found to be in good agreement with numericalsimulations. This highly-stable broadband source could find strong potential applications inbiomedical imaging and spectroscopy where improved signal to noise ratio is essential.

Abstract— The present work proposes a new approach of hetero-cladding for silicon photonic directional couplers and outlines its contributions towards realization of a compact, tunable and energy efficient directional coupler. The proposed hetero-cladding comprises ferroelectric BaTiO3 (BTO) and SiO2, to control the evanescent mode within the structure. The results show very small and identical coupling length for both TE and TM modes with reduced device cross-section, which promises for a huge reduction in the footprint of both conventional and programmable photonic integrated circuits (PICs). The proposed concept could also be utilized to design compact, low loss and energy efficient phase shifters and other types of couplers.

Peer to Peer (P2P) or direct connection IoT has become increasingly popular owing to its lower latency and higher privacy compared to database-driven or server-based IoT. However, wireless vulnerabilities raise severe concerns on IoT device-to-device communication. This is further aggravated by the challenge to achieve lightweight direct mutual authentication and secure key exchange between IoT peer nodes in P2P IoT applications. Physical unclonable function (PUF) is a key enabler to lightweight, low-power and secure authentication of resource-constrained devices in IoT. Nevertheless, current PUF-enabled authentication protocols, with or without the challenge-response pairs (CRPs) of each of its interlocutors stored in the verifier’s side, are incompatible for P2P IoT scenarios due to the security, storage and computing power limitations of IoT devices. To solve this problem, a new lightweight PUF-based mutual authentication and key-exchange protocol is proposed. It allows two resource-constrained PUF embedded endpoint devices to authenticate each other directly without the need for local storage of CRP or any private secrets, and simultaneously establish the session key for secure data exchange without resorting to public-key algorithm. The proposed protocol is evaluated using the Mao and Boyd logic as well as the automatic security analysis tool ProVerif to corroborate its mutual authenticity, secrecy, and resistance against replay and man-in-the-middle attacks. Using two Avnet Ultra96-V2 boards to emulate the two IoT endpoint devices of a network, a physical prototype system is also constructed to demonstrate and validate the feasibility of the proposed secure P2P connection scheme.

Modeling real-world phenomena is a focus of many science and engineering efforts, from ecological modeling to financial forecasting. Building an accurate model for complex and dynamic systems improves understanding of underlying processes and leads to resource efficiency. Knowledge-driven modeling builds a model based on human expertise, yet is often suboptimal. At the opposite extreme, data-driven modeling learns a model directly from data, requiring extensive data and potentially generating overfitting. We focus on an intermediate approach, model revision, in which prior knowledge and data are combined to achieve the best of both worlds. We propose a genetic model revision framework based on tree-adjoining grammar (TAG) guided genetic programming (GP), using the TAG formalism and GP operators in an effective mechanism making data-driven revisions while incorporating prior knowledge. Our framework is designed to address the high computational cost of evolutionary modeling of complex systems. Via a case study on the challenging problem of river water quality modeling, we show that the framework efficiently learns an interpretable model, with higher modeling accuracy than existing methods.

Abstract – We define the average contiguous duration (ACD) of the received fading signal as the average time duration during which the signal envelope contiguously remains within a bounded amplitude interval. Also, the multi-interval ACD or K-ACD function is defined as the set of ACD values for K non-overlapping amplitude-intervals whose union spans the received envelope’s amplitude range. We derive closed-form expressions of the ACD for Rayleigh, Rice, and Nakagami-m fading signals, which are widely analyzed in the literature. The derived expressions hold practical significance for several signal processing applications such as non-uniform quantization of channel samples for secret key generation (SKG) in physical layer security (PLS) techniques. The well-known channel fading metric of average fade duration (AFD) is shown as a special case of the proposed ACD metric and the proposed theoretical analysis is validated by simulations.

Cuckoo search algorithm is one the efficient algorithms in solving global optimization problems.

The paper reveals analytical expressions linking the coefficients of PI controller, typically employed as voltage loop compensator of power factor correction rectifiers (PFCR), with two major performance merits (namely, total harmonic distortion (THD) of grid-side current and DC-link voltage deviation upon sudden load increase) and DC link capacitance to rated power ratio. The proposed methodology allows to concretize the commonly used “8–10Hz crossover frequency, 45 degree–70 degree phase margin” rule-of-thumb, typically utilized in application notes of commercial PFC controllers. Relations between voltage loop gain crossover frequency and phase margin as well as settling time of DC-link voltage response to a step load increase to the above mentioned performance merits are also derived in the paper. Provided design guidelines allow to precisely achieve desired values of the two mentioned performance merits and indicate the feasible range of possible DC link capacitance values. Proposed quantitative design guidelines are well-supported by experiments.

The paper addresses the multimodal sensor selection problem where selected collocated sensor nodes are employed to effectively monitor and efficiently predict multiple spatial random fields. It is first proposed to exploit multivariate Gaussian processes (MGP) to model multiple spatial phenomena jointly. By the use of the Matern cross-covariance function, cross covariance matrices in the MGP model are sufficiently positive semi-definite, concomitantly providing efficient prediction of all multivariate processes at unmeasured locations. The multimodal sensor selection problem is then formulated and solved by an approximate algorithm with an aim to select the most informative sensor nodes so that prediction uncertainties at all the fields are minimized. The proposed approach was validated in the real-life experiments with promising results.

As organizations move most of their workloads to public cloud and remote work becomes more prevalent today, enterprise networks become more exposed to threats both from inside and outside the organization. The traditional Perimeter Security Model assumes that threats are always from the outside. It assumes that firewalls, proxies, IDS, IPS and other state-of-the-art infrastructure and software solutions curb most of the cyberattacks. However, there are loopholes in this assumption, which the Zero Trust Model addresses. This paper discusses the Zero Trust Model and it's mandates and evaluates the model based on the various implementations by the leading industry players like Google and Microsoft.