EPEC: an efficient privacy-preserving energy consumption scheme for smart grid communications

In this paper, we propose an efficient privacy-preserving energy consumption scheme with updating certificates, called EPEC, for secure smart grid communications. Specifically, the proposed EPEC scheme consists of four phases: gateways initialization, party registration, privacy-preserving energy consumption, and updating certificates. Based on the bilinear pairing, the identity-based encryption, and the strategy of updating certificates, EPEC can achieve data privacy, gateway privacy, and is robust to data replay attack, availability attack, modification attack, man-in-the-middle attack, and Sybil attack. Through extensive performance evaluations, we demonstrate the effectiveness of EPEC in terms of transmission delay performance at the HAN gateway and average delivery ratio, by implementing three types of curves including, the Barreto–Naehrig curve with modulus 256 bits, the Kachisa–Schaefer–Scott curve with modulus 512 bits, and the Barreto–Lynn–Scott curve with modulus 640 bits.     

Connection Management Protocols for Dynamic Lightpath Provisioning in Future WDM Networks

This paper investigates and compares the performance of two GMPLS-based distributed control and management protocols for dynamic lightpath provisioning in future IP networks. The first protocol is a global information-based link state approach that consists of both an integrated RWA algorithm and a signaling algorithm. Two triggering mechanisms for the LSAs update procedures are considered; one is periodic-based and the other is threshold-based. The second protocol is a local-information based fixed alternate link routing approach where the signaling protocol is closely integrated with the RWA protocols.     

A fast handover protocol for 6LoWPAN wireless mobile sensor networks

Node localization is one of the most critical issues for wireless sensor networks, as many applications depend on the precise location of the sensor nodes. To attain precise location of nodes, an improved distance vector hop (IDV-Hop) algorithm using teaching learning based optimization (TLBO) has been proposed in this paper. In the proposed algorithm, hop sizes of the anchor nodes are modified by adding correction factor. The concept of collinearity is introduced to reduce location errors caused by anchor nodes which are collinear. For better positioning coverage, up-gradation of target nodes to assistant anchor nodes has been used in such a way that those target nodes are upgraded to assistant anchor nodes which have been localized in the first round of localization. For further improvement in localization accuracy, location of target nodes has been formulated as optimization problem and an efficient parameter free optimization technique viz. TLBO has been used. Simulation results show that the proposed algorithm is overall 47, 30 and 22% more accurate than DV-Hop, DV-Hop based on genetic algorithm (GADV-Hop) and IDV-Hop using particle swarm optimization algorithms respectively and achieves high positioning coverage with fast convergence.     

Hilbert Transform and Statistical Analysis for Channel Selection and Epileptic Seizure Prediction

This paper is concerned with Electroencephalography (EEG) seizure prediction, which means the detection of the pre-ictal state prior to ictal activity occurrence. The basic idea of the proposed approach for EEG seizure prediction is to work on the signals in the Hilbert domain. The operation in the Hilbert domain guarantees working on the low-pass spectra of EEG signal segments to avoid artifacts. Signal attributes in the Hilbert domain including amplitude, derivative, local mean, local variance, and median are analyzed statistically to perform the channel selection and seizure prediction tasks. Pre-defined prediction and false-alarm probabilities are set to select the channels, the attributes, and bins of probability density functions (PDFs) that can be useful for seizure prediction. Due to the multi-channel nature of this process, there is a need for a majority voting strategy to take a decision for each signal segment. Simulation results reveal an average prediction rate of 96.46%, an average false-alarm rate of 0.028077/h and an average prediction time of 60.1595 min for a 90-min prediction horizon.

     

Environmentally Friendly Graphene Inks for Touch Screen Sensors

Graphene-based materials have attracted significant attention in many technological fields, but scaling up graphene-based technologies still faces substantial challenges. High-throughput top-down methods generally require hazardous, toxic, and high-boiling-point solvents. Here, an efficient and inexpensive strategy is proposed to produce graphene dispersions by liquid-phase exfoliation (LPE) through a combination of shear-mixing (SM) and tip sonication (TS) techniques, yielding highly concentrated graphene inks compatible with spray coating. The quality of graphene flakes (e.g., lateral size and thickness) and their concentration in the dispersions are compared using different spectroscopic and microscopy techniques. Several approaches (individual SM and TS, and their combination) are tested in three solvents (N-methyl-2-pyrrolidone, dimethylformamide, and cyrene). Interestingly, the combination of SM and TS in cyrene yields high-quality graphene dispersions, overcoming the environmental issues linked to the other two solvents. Starting from the cyrene dispersion, a graphene-based ink is prepared to spray-coat flexible electrodes and assemble a touch screen prototype. The electrodes feature a low sheet resistance (290 Ω □⁻¹) and high optical transmittance (78%), which provide the prototype with a high signal-to-noise ratio (14 dB) and multi-touch functionality (up to four simultaneous touches). These results illustrate a potential pathway toward the integration of LPE-graphene in commercial flexible electronics.     

Survey of ICIC techniques in LTE networks under various mobile environment parameters

LTE networks’ main challenge is to efficiently use the available spectrum, and to provide satisfying quality of service for mobile users. However, using the same bandwidth among adjacent cells leads to occurrence of Inter-cell Interference especially at the cell-edge. Basic interference mitigation approaches consider bandwidth partitioning techniques between adjacent cells, such as frequency reuse of factor m schemes, to minimize cell-edge interference. Although SINR values are improved, such techniques lead to significant reduction in the maximum achievable data rate. Several improvements have been proposed to enhance the performance of frequency reuse schemes, where restrictions are made on resource blocks usage, power allocation, or both. Nevertheless, bandwidth partitioning methods still affect the maximum achievable throughput. In this proposal, we intend to perform a comprehensive survey on Inter-Cell Interference Coordination (ICIC) techniques, and we study their performance while putting into consideration various design parameters. This study is implemented throughout intensive system level simulations under several parameters such as different network loads, radio conditions, and user distributions. Simulation results show the advantages and the limitations of each technique compared to frequency reuse-1 model. Thus, we are able to identify the most suitable ICIC technique for each network scenario.     

Catalyst Design by NH4OH Treatment of USY Zeolite

Hierarchical zeolites are a class of superior catalysts which couples the intrinsic zeolitic properties to enhanced accessibility and intracrystalline mass transport to and from the active sites. The design of hierarchical USY (Ultra‐Stable Y) catalysts is achieved using a sustainable postsynthetic room temperature treatment with mildly alkaline NH₄OH (0.02 m ) solutions. Starting from a commercial dealuminated USY zeolite (Si/Al = 47), a hierarchical material is obtained by selective and tuneable creation of interconnected and accessible small mesopores (2–6 nm). In addition, the treatment immediately yields the NH₄⁺ form without the need for additional ion exchange. After NH₄OH modification, the crystal morphology is retained, whereas the microporosity and relative crystallinity are decreased. The gradual formation of dense amorphous phases throughout the crystal without significant framework atom leaching rationalizes the very high material yields (>90%). The superior catalytic performance of the developed hierarchical zeolites is demonstrated in the acid‐catalyzed isomerization of α‐pinene and the metal‐catalyzed conjugation of safflower oil. Significant improvements in activity and selectivity are attained, as well as a lowered susceptibility to deactivation. The catalytic performance is intimately related to the introduced mesopores, hence enhanced mass transport capacity, and the retained intrinsic zeolitic properties.     

Best Minimum Summation Scheduler for Long Term Evolution

Resource scheduling in Long Term Evolution (LTE) is an open and rising issue. It has an enormous impact on the entire system performance. Due to the nature of LTE system, the scheduler has to be designed carefully. It has to overcome many challenges such as limited processing time and the high dynamic behavior. This paper proposes a novel scheduling policy for the MAC layer in LTE called the Best Minimum Summation (BMS). The main aim of this scheduling policy is to achieve high performance with low complexity. Three sub-schedulers have been developed. Each one of these schedulers deals with scheduling table in different dimension. The first one operates on the scheduling table through the user dimension (BMS.UE); while the second one operates on the scheduling table through the resource block dimension (BMS.RB). The third scheduler operates on the scheduling table correlating both of these dimensions (BMS.2D). All of the proposed solutions were intensively evaluated in a system level simulator. Three performance metrics were used which are throughput, error rate and fairness. The results have shown that the ability of the BMS.UE scheduler to outperform other existing schedulers of LTE.     

Nonsinusoidal radar signal design for stealth targets

The detection of stealth point targets challenges the design of conventional radars using sinusoidal carriers since the objective of stealth technology is to reduce the radar cross section (RCS) of targets to a level where the radar receiver cannot detect the target. While there are a number of techniques employing different technologies to reduce the RCS of targets, shaping and coating the target with absorbing material are the most useful ones. The analysis and design of nonsinusoidal radar signals is based on modeling stealth point targets by a two-layer structure consisting of a metal surface covered with a coat of absorbing material. The design is presented for two classes of signals: uncoded signals and pulse compression signals using Barker codes. The relationship between target response, absorbing material time delay, time variation of transmitted pulses and coding features are determined and analyzed. While sliding correlators are used for detection and selection of various target responses, their output autocorrelation functions are determined analytically in terms of transmitted signal autocorrelation functions. Thumbtack range-velocity resolution functions are obtained for transmitted signal characters with a single pulse and characters with coded waveforms, for different pulse duration. It is shown that the range resolution can be improved by the proper choice of the transmitted signal duration relative to absorbing material time delay. Thumbtack range-velocity resolution functions similar to those of conventional point targets can also be realized