Design of Probability Density Function Targeting Energy Efficient Network for Coalition Based WSNs

Energy consumption is one of the important issues in wireless sensor network that rely on non chargeable batteries for power. Also, the sensor network has to maintain a desired sensing coverage area along with periodically sending of the sensed data to the base station. Therefore, coverage and the lifetime are the two important issues that need to be addressed. Effective deployment of wireless sensors is a major concern as the coverage and lifetime of any wireless sensor network depends on it. In this paper, we propose the design of a Probability Density Function (PDF) targeting the desired coverage, and energy efficient node deployment scheme. The suitability of the proposed PDF based node distribution to model the network architecture considered in this work has been analyzed. The PDF divides the deployment area into concentric coronas and provides a probability of occurrence of a node within any corona. Further, the performance of the proposed PDF is evaluated in terms of the coverage, the number of transmissions of packets and the lifetime of the network. The scheme is compared with the existing node deployment schemes based on various distributions. The percentage gain of the proposed PDF based node deployment is 32\(\%\) more than that when compared with the existing schemes. Thus, the simulation results obtained confirm the schemes superiority over the other existing schemes.     

Performance improvement of 60‐GHz wireless optical systems with reverse‐parallel hybrid modulation scheme

This paper improves the performance of 60‐GHz wireless optical system including radio over fibre (RoF) and radio over free space optics (RoFSO), based on novel reverse‐parallel (RP) hybrid modulation scheme. This scheme combines the chromatic dispersion compensation technique of parallel modulation with energy efficiency manipulation technique of reverse modulation. Superior functioning of RoFSO is provided with reverse modulation compared with normal modulation. Comparative investigations are performed by loading 60‐GHz RF signal with 2.5 and 10‐Gbps data and modulating it with both reverse and hybrid modulators. Hybrid modulation performed better with improved BER of 10^?23 at distance of 51 km for 2.5‐Gbps data compared with reverse modulation with BER of 10^?7.     

Analog and radio-frequency performance analysis of silicon-nanotube MOSFETs

This work presents a comparative study of the influence of various parameters on the analog and RF properties of silicon-nanotube MOSFETs and nanowire-based gate-all-around (GAA) MOSFETs. The important analog and RF performance parameters of SiNT FETs and GAA MOSFETs, namely drain current (I_d), transconductance to drain current ratio (g_m/I_d), I_on/I_off, the cut-off frequency (f_T) and the maximum frequency of oscillation (f_MAX) are evaluated with the help of Y- and H-parameters which are obtained from a 3-D device simulator, ATLAS^TM. It is found that the silicon-nanotube MOSFETs have far more superior analog and RF characteristics (g_m/I_d, f_T and f_MAX) compared to the nanowire-based gate-all-around GAA MOSFETs. The silicon-nanotube MOSFET shows an improvement of~2.5 and 3 times in the case of f_T and f_MAX values respectively compared with the nanowire-based gate-all-around (GAA) MOSFET.     

Atomically Thin MoS2: A Versatile Nongraphene 2D Material

Two‐dimensional inorganic materials are emerging as a premiere class of materials for fabricating modern electronic devices. The interest in 2D layered transition metal dichalcogenides is especially high. Particularly, 2D MoS₂ is being heavily researched due to its novel functionalities and its suitability for a wide range of electronic and optoelectronic applications. In this article, the progress in mono/few layer(s) MoS₂ research is reviewed by focusing primarily on the layer dependent evolution of crystal, phonon, and electronic structure. The review includes extensive detail into the methodologies adapted for single or few layer(s) MoS₂ growth. Further, the review covers the versatility of 2D MoS₂ for a broad range of device applications. Recent advancements in the field of van der Waals heterostructures are also highlighted at the end of the review.     

Efficient ID-based multiproxy multisignature without bilinear maps in ROM

Most of the previously proposed identity-based multiproxy multisignature (IBMPMS) schemes used pairings in their construction. But pairing is regarded as an expensive cryptographic primitive in terms of complexity. The relative computation cost of a pairing is approximately more than ten times of the scalar multiplication over elliptic curve group. So, to reduce running time, we first define a model of a secure MPMS scheme, then propose an IBMPMS scheme without using pairings. We also prove the security of our scheme against chosen message attack in random oracle model. Our scheme’s construction avoids bilinear pairing operations but still provides signature in the ID-based setting and reduces running time heavily. Therefore, proposed scheme is more applicable than previous schemes in terms of computational efficiency for practical applications.     

Photochemistry on a polarisable semi-conductor: what do we understand today?

The continued development of ferroelectric materials into more and more consumer led applications has been at the forefront of recent ferroelectric material research. It is, however, possible to view a ferroelectric as a wide band gap semi-conductor that can sustain a surface charge density. This charge density arises from the movement of ions in the crystal lattice and the need to compensate for this charge. When viewing ferroelectrics as polarisable semi-conductors a large number of new interactions are possible. One such is the use of super band gap illumination to generate electron–hole pairs. These photogenerated carriers can then perform local electrochemistry. What is most interesting for ferroelectric materials is that the REDOX chemistry can be chosen by selectively modifying the domain structure of the ferroelectric—we can perform oxidation and reduction on the surface of the same material at spatially separate locations, or use the material to drive photoexcited carriers apart. This means we can separate the REDOX products or produce patterns of photogenerated material in places we have predetermined. This review aims to introduce the background research that has led to the current understanding as well a highlight some of the current areas that require further development.     

Estimation of internal heat transfer coefficients of a hybrid (PV/T) active solar still

In this paper, an attempt is made to estimate the internal heat transfer coefficients of a deep basin hybrid (PV/T) active solar still. The estimation is based on outdoor experimental observation of hybrid (PV/T) solar still for composite climate of New Delhi (latitude 28°35′N and longitude 77°12′E). The internal heat transfer coefficients are evaluated by using thermal models proposed by various researchers. The comparison of hourly yield predicted using various thermal models to the experimental has also been carried out by evaluating the correlation coefficient and percentage deviation. It is observed that, Kumar and Tiwari model (KTM) better validate the results than the others model. The average annual values of convective heat transfer coefficient for the passive and hybrid (PV/T) active solar still are observed as 0.78 and 2.41 W m⁻² K⁻¹, respectively at 0.05 m water depth.     

Tuning parallel applications in parallel

In this paper, we present and evaluate a parallel algorithm for parameter tuning of parallel applications. We discuss the impact of performance variability on the accuracy and efficiency of the optimization algorithm and propose a strategy to minimize the impact of this variability. We evaluate our algorithm within the Active Harmony system, an automated online/offline tuning framework. We study its performance on three benchmark codes: PSTSWM, HPL and POP. Compared to the Nelder–Mead algorithm, our algorithm finds better configurations up to seven times faster. For POP, we were able to improve the performance of a production sized run by 59%.     

Detection of local community structures in complex dynamic networks with random walks

Identification of interaction patterns in complex networks via community structures has gathered a lot of attention in recent research studies. Local community structures provide a better measure to understand and visualise the nature of interaction when the global knowledge of networks is unknown. Recent research on local community structures, however, lacks the feature to adjust itself in the dynamic networks and heavily depends on the source vertex position. In this study the authors propose a novel approach to identify local communities based on iterative agglomeration and local optimisation. The proposed solution has two significant improvements: (i) in each iteration, agglomeration strengthens the local community measure by selecting the best possible set of vertices, and (ii) the proposed vertex and community rank criterion are suitable for the dynamic networks where the interactions among vertices may change over time. In order to evaluate the proposed algorithm, extensive experiments and benchmarking on computer generated networks as well as real-world social and biological networks have been conducted. The experiment results reflect that the proposed algorithm can identify local communities, irrespective of the source vertex position, with more than 92% accuracy in the synthetic as well as in the real-world networks.     

Solving distributed FMS scheduling problems subject to maintenance: Genetic algorithms approach

In general, distributed scheduling problem focuses on simultaneously solving two issues: (i) allocation of jobs to suitable factories and (ii) determination of the corresponding production scheduling in each factory. The objective of this approach is to maximize the system efficiency by finding an optimal planning for a better collaboration among various processes. This makes distributed scheduling problems more complicated than classical production scheduling ones. With the addition of alternative production routing, the problems are even more complicated. Conventionally, machines are usually assumed to be available without interruption during the production scheduling. Maintenance is not considered. However, every machine requires maintenance, and the maintenance policy directly affects the machine's availability. Consequently, it influences the production scheduling. In this connection, maintenance should be considered in distributed scheduling. The objective of this paper is to propose a genetic algorithm with dominant genes (GADG) approach to deal with distributed flexible manufacturing system (FMS) scheduling problems subject to machine maintenance constraint. The optimization performance of the proposed GADG will be compared with other existing approaches, such as simple genetic algorithms to demonstrate its reliability. The significance and benefits of considering maintenance in distributed scheduling will also be demonstrated by simulation runs on a sample problem.