Analysis of leaky bucket mechanism based on burstiness characterization

In high-speed networks, a congestion control strategy has to manage bandwidth allocation based on the characteristics of input traffic sources. Accordingly, the definition of traffic characterization becomes significant in all aspects concerning network performance. In this paper, the burstiness characterization of a traffic stream is based on a virtual queue principle. We study the leaky bucket mechanism as a regulator element that controls input traffic before access to a newwork, as well as inside a network. To protect an input traffic stream, we investigate the optimal parameter settings of a leaky bucket. In addition, we analyse the worst case performance, and obtain upper bounds on loss probability and packet delay. We also determine the characteristics of an output stream in the worst case. Such performance bounds reveal the effectiveness of a leaky bucket, and provide enough information for the QOS satisfaction of the network users.     

Data broadcasting strategies for cognitive radio based AMI networks

Wireless Networks - Communication systems play an important role in smart grid (SG). Advanced Metering Infrastructure (AMI) is hybrid architecture in smart grid comprising of smart meters and...     

Magneto‐Thermal Metrics Can Mirror the Long‐Term Intracellular Fate of Magneto‐Plasmonic Nanohybrids and Reveal the Remarkable Shielding Effect of Gold

Multifunctional nanoparticles such as magneto‐plasmonic nanohybrids are rising theranostic agents. However, little is yet known of their fate within the cellular environment. In order to reach an understanding of their biotransformations, reliable metrics for tracking and quantification of such materials properties during their intracellular journey are needed. In this study, their long‐term (one month) intracellular fate is followed within stem‐cell spheroids used as tissue replicas. A set of magnetic (magnetization) and thermal (magnetic hyperthermia, photothermia) metrics is implemented to provide reliable insightsinto the intracellular status. It shows that biodegradation is modulated by the morphology and thickness of the gold shell. First a massive dissolution of the iron oxide core (nanoflower‐like) is observed, starting with dissociation of the multigrain structure. Second, it is demonstrated that an uninterrupted gold shell can preserve the magnetic core and properties (particularly magnetic hyperthermia). In addition to the magnetic and thermal metrics, intracellular high‐resolution chemical nanocartography evidences the gradual degradation of the magnetic cores. It also shows different transformation scenarios, from the release of small gold seeds when the magnetic core is dissolved (interesting for long‐term elimination) to the protection of the magnetic core (interesting for long‐term therapeutic applicability).     

MDP-Based Network Selection Scheme by Genetic Algorithm and Simulated Annealing for Vertical-Handover in Heterogeneous Wireless Networks

The hybrid algorithm for real-time vertical handover using different objective functions has been presented to find the optimal network to connect with a good quality of service in accordance with the user’s preferences. Markov processes are widely used in performance modelling of wireless and mobile communication systems. We address the problem of optimal wireless network selection during vertical handover, based on the received information, by embedding the decision problem in a Markov decision process (MDP) with genetic algorithm (GA), we use GA to find a set of optimal decisions that ensures the best trade-off between QoS based on their priority level. Then, we emerge improved genetic algorithm (IGA) with simulated annealing (SA) as leading methods for search and optimization problems in heterogeneous wireless networks. We formulate the vertical handoff decision problem as a MDP, with the objectives of maximizing the expected total reward and minimizing average number of handoffs. A reward function is constructed to assess the QoS during each connection, and the AHP method are applied in an iterative way, by which we can work out a stationary deterministic handoff decision policy. As it is, the characteristics of the current mobile devices recommend using fast and efficient algorithms to provide solutions near to real-time. These constraints have moved us to develop intelligent algorithm that avoid the slow and massive computations. This paper compares the formulation and results of five recent optimization algorithms: artificial bee colony, GA, differential evolution, particle swarm optimization and hybrid of (GA–SA). Simulation results indicated that choosing the SA rules would minimize the cost function, and also that, the IGA–SA algorithm could decrease the number of unnecessary handovers, and thereby prevent the ‘Ping-Pong’ effect.     

A Novel Artificial Intelligence Based Timing Synchronization Scheme for Smart Grid Applications

The smart grid control applications necessitate real-time communication systems with time efficiency for real-time monitoring, measurement, and control. Time-efficient communication systems should have the ability to function in severe propagation conditions in smart grid applications. The data/packet communications need to be maintained by synchronized timing and reliability through equally considering the signal deterioration occurrences, which are propagation delay, phase errors and channel conditions. Phase synchronization plays a vital part in the digital smart grid to get precise and real-time control measurement information. IEEE C37.118 and IEC 61850 had implemented for the synchronization communication to measure as well as control the smart grid applications. Both IEEE C37.118 and IEC 61850 experienced a huge propagation and packet delays due to synchronization precision issues. Because of these delays and errors, measurement and monitoring of the smart grid application in real-time is not accurate. Therefore, it has been investigated that the time synchronization in real-time is a critical challenge in smart grid applications, and for this issue, other errors raised consequently. The existing communication systems are designed with the phasor measurement unit (PMU) along with communication protocol IEEE C37.118 and uses the GPS timestamps as the reference clock stamps. The absence of GPS increases the clock offsets, which surely can hamper the synchronization process and the full control measurement system that can be imprecise. Therefore, to reduce this clock offsets, a new algorithm is needed which may consider any alternative reference timestamps rather than GPS. The revolutionary Artificial Intelligence (AI) enables the industrial revolution to provide a significant performance to engineering solutions. Therefore, this article proposed the AI-based Synchronization scheme to mitigate smart grid timing issues. The backpropagation neural network is applied as the AI method that employs the timing estimations and error corrections for the precise performances. The novel AIFS scheme is considered the radio communication functionalities in order to connect the external timing server. The performance of the proposed AIFS scheme is evaluated using a MATLAB-based simulation approach. Simulation results show that the proposed scheme performs better than the existing system.

     

Efficient Photomodulation of Visible Eu(III) and Invisible Yb(III) Luminescences using DTE Photochromic Ligands for Optical Encryption

This work describes a class of complex combining three dithienylethene units and a lanthanide ion used as an optical system displaying a double encryption method: i) a colorful code, drawn and erased under UV and visible irradiations respectively, due to coloration and discoloration of the photochromic entities, and ii) a concomitant gradual disappearance and progressive restoration of the associated lanthanide ion luminescence triggered with the same stimuli. The innovation of the system stems from the emission color tunability, i.e., with either a lanthanide ion emitting only in the visible range (Eu³⁺) or with another lanthanide ion emitting only in the near infrared (NIR) range (Yb³⁺), therefore observable, or not, to the naked eye. This system is the very first one to achieve efficient repeatable modulation of pure NIR luminescence on photochemical command. Furthermore, it is proven to be highly efficient when embedded in a PDMS polymer opening real opportunities for practical applications as anti‐counterfeiting.     

Design and Analysis of a Channel Assignment Scheme for CDMA/TDMA Mobile Networks

In this paper, a channel assignment scheme is proposed for use in CDMA/TDMA mobile networks carrying voice and data traffic. In each cell, three types of calls are assumed to compete for access to the limited number of available channels by the cell: new voice calls, handoff voice calls, and data calls. The scheme uses the movable boundary concept in both the code and time domains in order to guarantee the quality of service (QoS) requirements of each type. A traditional Markov analysis method is employed to evaluate the performance of the proposed scheme. Measures, namely, the new call blocking probability, the handoff call forced termination probability, the data call loss probability, the expected number of handoff and the handoff link maintenance probability are obtained from the analysis. The numerical results, which are validated by simulation, indicate that the scheme helps meet the QoS requirements of the different call types.     

Optimal Resource Allocation in Heterogeneous MIMO Cognitive Radio Networks

The optimal resource allocation in MIMO cognitive radio networks with heterogeneous secondary users, centralized and distributed users, is investigated in this work. The core aim of this work is to study the joint problems of transmission time and power allocation in a MIMO cognitive radio scenario. The optimization objective is to maximize the total capacity of the secondary users (SUs) with the constraint of fairness. At first, the joint problems of transmission time and power allocation for centralized SUs in uplink is optimized. Afterwards, for the heterogeneous case with both the centralized and distributed secondary users, the resource allocation problem is formulated and an iterative power water-filling scheme is proposed to achieve the optimal resource allocation for both kinds of SUs. A dynamic optimal joint transmission time and power allocation scheme for heterogeneous cognitive radio networks is proposed. The simulation results illustrate the performance of the proposed scheme and its superiority over other power control schemes.     

Improving vehicular safety message delivery through the implementation of a cognitive vehicular network

The Wireless Access in Vehicular Environments (WAVE) protocol stack has been recently defined to enable vehicular communication on the Dedicated Short Range Communication (DSRC) frequencies. Some recent studies have demonstrated that the WAVE technology might not provide sufficient spectrum for reliable exchange of safety information over congested urban scenarios. In this paper, we address this issue, and present a novel cognitive network architecture in order to dynamically extend the Control Channel (CCH) used by vehicles to transmit safety-related information. To this aim, we propose a cooperative spectrum sensing scheme, through which vehicles can detect available spectrum resources on the 5.8 GHz ISM band along their path, and forward the data to a fixed infrastructure known as Road Side Units (RSUs). We design a novel Fuzzy-Logic based spectrum allocation algorithm, through which the RSUs infer the actual CCH contention conditions, and dynamically extend the CCH bandwidth in network congestion scenarios, by using the vacant frequencies detected by the sensing module. The simulation results reveal the effectiveness of our architecture in providing dynamic and scalable allocation of spectrum resources, and in increasing the performance of safety-related applications.     

A BIST-DFT technique for DC test of analog modules

Among test techniques for analog circuits, DC test is one of the simplest method for BIST application since easy to integrate test pattern generator and response analyzer are conceivable. Precisely, this paper presents such an investigation for a CMOS operational amplifier that is latter extended to active analog filters. Since the computation of fault coverage is still a controversy question for analog cells, we develop first an evaluation technique for optimizing the tolerance band of the measurements to test. Then, using some DFT solutions we derive single DC pattern and discuss the minimal number of points to test for the detection of defects. A response analyzer is integrated with a Built-in Voltage Sensor (BIVS) and provides directly a logic pass/fail test result. Finally, the extra circuitry introduced by this BIST technique for analog modules does not exceed 5% of the total silicon area of the circuit under test and detects most of the faults.