Design a novel routing criterion based on channel features and internal backup routes for cognitive radio network

Telecommunication Systems - In the routing process, the cost (or weight) of routes determine via a function named routing criterion. Therefore, the design of Optimal Routing Criterion (ORC) is one...     

Joint routing and channel assignment using online learning in cognitive radio networks

Cognitive radio networks (CRNs) are the solution for the problem of underutilizing the licensed spectrum for which there are more requests in the last couple of decades. In CRNs, Secondary users (SUs) are permitted to access opportunistically the licensed spectrum owned by primary users (PUs). In this paper, we address the problem of joint routing and channel assignment for several flows generated by source SUs to a given destination. We consider a more realistic model based on Markov modulated Poisson process for modeling the PUs traffic at each channel and the SUs try to exploit short lived spectrum holes between the PUs packets at the selected channel. The SUs want to cooperatively minimize the end-to-end delay of source SUs flows meanwhile the quality of service requirements of the PUs would be met. To consider partial observation of SUs about PUs activity at all channels and quick adaptation of SUs decisions to environment changes and cooperative interaction of SUs, we use decentralized partially observable markov decision process for modeling the problem. Then, an online learning based scheme is proposed for solving the problem. Simulation results show that the performance of the proposed method and the optimal method is close to each other. Also, simulation results show that the proposed method greatly outperforms related works at control of interference to the PUs while maintains the end-to-end delay of SU flows in a low level.

     

Dependability analysis for characterizing Google cluster reliability

Cloud solutions are emerging as a new suitable way of transforming traditional IT data centers to highly available and reliable computing resources for hosting critical applications and data. However, software and hardware failures are a common problem in cloud datacenters that can lead to harmful damages. In this paper, we analyze the physical server failures in the Google cloud datacenter. We study the Google cluster properties to investigate the relationship among physical servers' failure rate and jobs failure events. The failure rate of Google cluster executed jobs and servers is taken into consideration during a 29‐day period. We present a reliability model for Google cluster physical machines using the continuous time Markov chains according to this observation. We attempt to analyze the obtained model through SHARPE software packages to improve the understanding of failure events in the Google cloud cluster. We also explore the cluster availability based on parameters like steady‐state availability, steady‐state unavailability, mean time to failure, and mean time to repair in the Google cluster.     

Nature‐inspired meta‐heuristic algorithms for solving the load balancing problem in the software‐defined network

The growth of the networks has difficult network management. Recently, a concept called software‐defined network (SDN) has been proposed to address this issue, which makes network management more adaptable. Control and forwarding planes are separated in SDN. The control plane is a centralized logical controller that controls the network. The forwarding plane that consists of transfer devices is responsible for transmitting packets. Because the network resources are limited, optimizing the use of resources in the networks is an important issue. Load balancing improves the balanced distribution of loads across multiple resources in order to maximize the reliability and network resources efficiency. SDN controllers can create an optimal load balancing compared to traditional networks because they have a network global view. The load‐balancing problem can be solved using many different nature‐inspired meta‐heuristic techniques because it has the NP‐complete nature. Hence, for solving load balancing problem in SDN, nature‐inspired meta‐heuristic techniques are important methods. However, to the best of our knowledge, there is not a survey or systematic review on studying these matters. Accordingly, in the area of the load balancing in the SDN, this paper reviews systematically the nature‐inspired meta‐heuristic techniques. Also, this study demonstrates advantages and disadvantages regarded of the chosen nature‐inspired meta‐heuristic techniques and considers their algorithms metrics. Moreover, to apply better load balancing techniques in the future, the important challenges of these techniques have been investigated.     

An anti‐collision algorithm based on balanced incomplete block design in RFID systems

An important challenge in radio frequency identification (RFID) systems is the collision concern. When an interrogator send a request, it has several tags to answer to in its transmission range, and a tag collision has occurred. The interrogator must be able to recognize tags as rapidly as possible. A collision problem is a power‐consuming occurrence that diminishes the operation of RFID structure. This article proposes a tag anti‐collision power‐clustering RFID algorithm for all tag identification. The tags are boundaries into the several power level clusters based on distances of the reader. Specifically, in the proposed algorithm, tags and readers use of balanced incomplete blocks design (BIBD) to reach a fast identification. In a BIBD matrix, any two columns intersect exactly in one component that makes it possible for easy transmission of any two tags via the tag's identification in their read cycles. The aim of this article is to propose a joint organization that while decreases power consumption increases the working lifetime of RFID structure. The reader can get each tag ID by distinguishing each unit of BIBD symbols, one by one. The use of proposed algorithm brings about a great improvement in the power consumption and identification time.     

Compact bilayer substrate integrated waveguide leaky wave antenna with dumbbell‐shaped slot based on the TE20 mode

In this article, a compact dual layer leaky wave antenna array is simulated and constructed using the substrate integrated waveguide (SIW) based on the TE₂₀ mode at the X‐ and Ku‐bands. The proposed antenna is designed by creating dumbbell‐shaped slots on the upper layer of the SIW. These slots have increased the antenna bandwidth so that the proposed antenna has a bandwidth of 9.5 to 13.7 GHz and a fractional bandwidth of 36%. In addition, to excite the TE₂₀ mode, an SIW power divider is used in the feeding network of the antenna located in the bottom layer. Moreover, the gain and directivity are other advantages of the proposed antenna so that at 12.5 GHz the antenna peak gain reaches to 15.7 dB. Antenna beam scanning angle is from 5° to 81°. This antenna is simulated and analyzed by the CST Microwave Studio software. The obtained results from the antenna test lab confirm the simulation results.     

Fault detection and identification using combination of EKF and neuro-fuzzy network applied to a chemical process (CSTR)

Pattern Analysis and Applications - In this paper, a new algorithm is proposed for fault detection and identification (FDI) in a class of nonlinear systems by combining the extended Kalman filter...     

Uncertain Method for Optimal Control Problems With Uncertainties Using Chebyshev Inclusion Functions

In this paper, a new uncertain analysis method is developed for optimal control problems, including interval variables (uncertainties) based on truncated Chebyshev polynomials. The interval arithmetic in this research is employed for analyzing the uncertainties in optimal control problems comprising uncertain‐but‐bounded parameters with only lower and upper bounds of uncertain parameters. In this research, the Chebyshev method is utilized because it generates sharper bounds for meaningful solutions of interval functions, rather than the Taylor inclusion function, which is efficient in handling the overestimation derived from the wrapping effect due to interval computations. For utilizing the proposed interval method on the optimal control problems with uncertainties, the Lagrange multiplier method is first applied to achieve the necessary conditions and then, by using some algebraic manipulations, they are converted into the ordinary differential equation. Afterwards, the Chebyshev inclusion method is employed to achieve the solution of the system. The final results of the Chebyshev inclusion method are compared with the interval Taylor method. The results show that the proposed Chebyshev inclusion function based method better handle the wrapping effect than the interval Taylor method.     

Damage evaluation of laminated composite material using a new acoustic emission Lamb-based and finite element techniques

In this paper, a very promising procedure is proposed to evaluate delamination using Acoustic Emission (AE) technique in composite laminates. First, a new procedure was developed to decompose the fundamental Lamb wave modes in small size specimens. The damage mechanisms in End Notched Flexure (ENF) in woven and unidirectional specimens were then discriminated using Fuzzy Clustering Method (FCM). Afterwards, the crack-arrest phenomenon was examined in each specimen. After that, experimental and Cohesive Zone Modeling (CZM) techniques were conducted to characterize the delamination using ENF specimens. The results showed how, it is possible to successfully decrease the effect of propagating media such as attenuation of AE signals using the new proposed methodology. As a final point, the results of this study could lead to efficiently distinguishing different damages in laminated composite using AE Lamb-based technique.     

A cross-entropy method for optimising robotic automated storage and retrieval systems

In this paper, we consider a robotic automated storage and retrieval system (AS/RS) where a Cartesian robot picks and palletises items onto a mixed pallet for any order. This robotic AS/RS not only retrieves orders in an optimal sequence, but also creates an optimal store ready pallet of any order. Adapting the Travelling Salesman Problem to warehousing, the decision to be made includes finding the optimal sequence of orders, and optimal sequence of items inside each order, that jointly minimise total travel times. In the first phase, as a control problem, we develop an avoidance strategy for the robot (or automatic stacker crane) movement sequence. This approach detects the collision occurrence causing unsafe handling of hazardous items and prevents the occurrence of it by a collision-free robot movement sequence. Due to the complexity of the problem, the second phase is attacked by a Cross-Entropy (CE) method. To evaluate the performance of the CE method, a computational analysis is performed over various test problems. The results obtained from the CE method are compared to those of the optimal solutions obtained using CPLEX. The results indicate high performance of the solution procedure to solve the sequencing problem of robotic AS/RSs.