Toward the Optimized Spintronic Response of Sn‐Doped IrO2 Thin Films

Amorphous and polycrystalline Sn‐doped IrO₂ thin films, Ir_1‐xSn_xO₂, are grown for the first time. Their electrical response and strength of the spin–orbit coupling are studied in order to better understand and tailor its performance as spin current detector material. These experiments prove that the resistivity of IrO₂ can be tuned over several orders of magnitude by controlling the doping content in both the amorphous and the polycrystalline state. In addition, growing amorphous samples increase the resistivity, thus improving the spin current to charge current conversion. As far as the spin–orbit coupling is concerned, the system not only remains in a strong spin–orbit coupling regime but it seems to undergo a slight enhancement in the amorphous state as well as in the Sn‐doped samples.     

Impact of Fiber Non-linearity in High Capacity WDM Systems and in Cross-Connected Backbone Networks

The rapidly increasing data traffic volumes will demand for very high transmission capacity and network nodes throughput. Wavelength division multiplexing (WDM) technology will be asked to support many channels on the same fiber, both in point-to-point links and in WDM optical networks. The transmission of a high number of wavelength channels in all these systems is a key issue. This paper analyzes this topic, in both high capacity links and optical networks, highlighting the impact of fiber non-linearity, and addressing the main source of impairments. This is done through the use of a semi-analytical model recently upgraded to account for all the contributions deriving from Kerr effects, particularly four-wave mixing and cross-phase modulation. The analysis reveals that more than one hundred of channels at 2.5 Gbit/s can be transmitted in point-to-point links whose length can span until the order of 1000 km, and 32 channels per fiber, at the previous bit rate, can be handled in WDM networks, without dispersion compensation. For a higher number of channels (e.g., 64) dispersion compensation is needed.     

Network efficiency maximization exploiting WCDMA spectrum nature for enhancement of D2D underlaying communications

In this paper, devices to devices communications underlaying cellular network techniques are proposed as an alternative to maximize spectral efficiency. This gain is obtained by the reuse of spectrum when different links are simultaneously established using the same resources. The cost of this technique is additional interference in cellular networks. The techniques presented in this paper propose a coordinated power control mechanism to allow resource sharing with low impact on cellular subscribers. Solutions are addressed for both OFDMA and WCDMA networks taking into account the unique requirements of both networks. In both situations, WCDMA–OFDMA coexistence is exploited and analyzed, using the nature of WCDMA spectrum and its robustness against narrowband interference thereby improving the probability of obtaining the sharing of cellular resources. For OFDM networks, WCDMA is used for mitigating the interference of cellular users and to obtain considerable gain in probability of reuse. For WCDMA networks, OFDMA is used to obtain higher throughput using the side frequencies of the spectrum where the cellular signal power is lower compared to the central frequencies.     

A Tutorial on Multiplierless Design of FIR Filters: Algorithms and Architectures

Finite impulse response (FIR) filtering is a ubiquitous operation in digital signal processing systems and is generally implemented in full custom circuits due to high-speed and low-power design requirements. The complexity of an FIR filter is dominated by the multiplication of a large number of filter coefficients by the filter input or its time-shifted versions. Over the years, many high-level synthesis algorithms and filter architectures have been introduced in order to design FIR filters efficiently. This article reviews how constant multiplications can be designed using shifts and adders/subtractors that are maximally shared through a high-level synthesis algorithm based on some optimization criteria. It also presents different forms of FIR filters, namely, direct, transposed, and hybrid and shows how constant multiplications in each filter form can be realized under a shift-adds architecture. More importantly, it explores the impact of the multiplierless realization of each filter form on area, delay, and power dissipation of both custom (ASIC) and reconfigurable (FPGA) circuits by carrying out experiments with different bitwidths of filter input, design libraries, reconfigurable target devices, and optimization criteria in high-level synthesis algorithms.     

Three-dimensional optical data storage through multi-photon confocal microscopy and imaging

Three dimensional optical data storage is one of the most promising tools to respond to the always growing demand for high data storage capacity. Here, we focused a femtosecond laser source by means of a confocal microscope onto different transparent recording media. The purpose of the study is to probe the capability of the system to independently address different data layers within the storage medium achieving thus three dimensional data storage. We demonstrated the possibility to write superposed independent layers of data due to either multiphoton excitation or to local optical breakdown and the performances observed in the different types of media used are compared.     

Hungarian algorithm for subcarrier assignment problem using GPU and CUDA

General purpose graphics processing units (GPGPUs) have gained much popularity in scientific computing to speedup computational intensive workloads. Resource allocation in terms of power and subcarriers assignment, in current wireless standards, is one of the challenging problems due to its high computational complexity requirement. The Hungarian algorithm (HA), which has been extensively applied to linear assignment problems (LAPs), has been seen to provide encouraging result in resource allocation for wireless communication systems. This paper presents a compute unified device architecture (CUDA) implementation of the HA on graphics processing unit (GPU) for this problem. HA has been implemented on a parallel architecture to solve the subcarrier assignment problem and maximize spectral efficiency. The proposed implementation is achieved by using the “Kuhn‐Munkres” algorithm with effective modifications, in order to fully exploit the capabilities of modern GPU devices. A cost matrix for maximum assignment has been defined leading to a low complexity matrix compression along with highly optimized CUDA reduction and parallel alternating path search process. All these optimizations lead to an efficient implementation with superior performance when compared with existing parallel implementations.     

SDN‐DMM for intelligent mobility management in heterogeneous mobile IP networks

Mobility management applied to the traditional architecture of the Internet has become a great challenge because of the exponential growth in the number of devices that can connect to the network. This article proposes a Software‐Defined Networking (SDN)‐based architecture, called SDN‐DMM (SDN‐Distributed Mobility Management), that deals with the distributed mode of mobility management in heterogeneous access networks in a simplified and efficient way, ensuring mainly the continuity of IP sessions. Intent‐based mobility management with an IP mapping schema for mobile node identification offers optimized routing without tunneling techniques, hence, an efficient use of the network infrastructure. The simplified mobility control API reduces both signaling and handover latency costs and provides a better scalability and performance in comparison with traditional and SDN‐based DMM approaches. An analytical evaluation of such costs demonstrated the better performance of SDN‐DMM, and a proof of concept of the proposal was implemented in a real environment.     

Improved Thermal Behavior of Multiple Linked Arrays of Silicon Nanowires Integrated into Planar Thermoelectric Microgenerators

Low-dimensional structures have been shown to be promising candidates for enhancing the thermoelectric properties of semiconductors, paving the way for integration of thermoelectric generators into silicon microtechnology. With this aim, dense arrays of well-oriented and size-controlled silicon nanowires (Si NWs) obtained by the chemical vapor deposition (CVD)-vapor–liquid–solid (VLS) mechanism have been implemented into microfabricated structures to develop planar unileg thermoelectric microgenerators (μTEGs). Different low-thermal-mass suspended structures have been designed and microfabricated on silicon-on-insulator (SOI) substrates to operate as microthermoelements using p-type Si NW arrays as the thermoelectric material. To obtain nanowire arrays with effective lengths larger than normally attained by the VLS technique, structures composed of multiple ordered arrays consecutively bridged by transversal microspacers have been fabricated. The successive linkage of multiple Si NW arrays enabled the development of larger temperature differences while preserving good electrical contact. This gives rise to small internal thermoelement resistances, enhancing the performance of the devices as energy harvesters.     

Towards a Sustainable Green Design for Next-Generation Networks

Recently distributed real-time database systems are intended to manage large volumes of dispersed data. To develop distributed real-time data processing, a reality and stay competitive well defined protocols and algorithms must be required to access and manipulate the data. An admission control policy is a major task to access real-time data which has become a challenging task due to random arrival of user requests and transaction timing constraints. This paper proposes an optimal admission control policy based on deep reinforcement algorithm and memetic algorithm which can efficiently handle the load balancing problem without affecting the Quality of Service (QoS) parameters. A Markov decision process (MDP) is formulated for admission control problem, which provides an optimized solution for dynamic resource sharing. The possible solutions for MDP problem are obtained by using reinforcement learning and linear programming with an average reward. The deep reinforcement learning algorithm reformulates the arrived requests from different users and admits only the needed request, which improves the number of sessions of the system. Then we frame the load balancing problem as a dynamic and stochastic assignment problem and obtain optimal control policies using memetic algorithm. Therefore proposed admission control problem is changed to memetic logic in such a way that session corresponds to individual elements of the initial chromosome. The performance of proposed optimal admission control policy is compared with other approaches through simulation and it depicts that the proposed system outperforms the other techniques in terms of throughput, execution time and miss ratio which leads to better QoS.

     

A study of drilling performances with minimum quantity of lubricant using fuzzy logic rules

Nowadays the increasing interest to perform machining operations is in dry/near-dry environments. The reason includes health and safety of operator, cost, ease of chip recyclability, etc. However one important process, which is difficult to perform in dry, is drilling. Without coolant, drilling leads to excessive thermal distortion and poor tool life. In order to tackle these conflicting requirements, the essentiality of study on machining performances with minimum quantity lubricant (MQL) becomes important.Fuzzy logic rules, which are derived based on fuzzy set theory, are used to develop fuzzy rule based model (FRBM). The performance of FRBM depends on two different aspects: structures of fuzzy rules and the associated fuzzy sets (membership function distributions, MFDs). The aim of this study is to investigate the performances of FRBMs based on Mamdani and TSK-types of fuzzy logic rules with different shapes of MFDs for prediction and performance analysis of machining with MQL in drilling of aluminum alloy. A comparison of the model predictions with experimental results and those published in the literature shows that FRBM with TSK-type fuzzy rules describes excellent trade-off with experimental measurements.