Accurate and simple synthesis formulas for coplanar waveguides

Simple and accurate closed‐form formulas obtained by using a differential evolution algorithm are presented for the synthesis of coplanar waveguides (CPW). The results of the synthesis formulas proposed in this article are compared with those of the quasi‐static analysis, the synthesis formulas reported by the other researchers and also the experimental works available in the literature. The accuracy of the proposed synthesis formulas is found to be better than 0.75% for 9256 CPWs samples. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2008.     

Prediction of software vulnerability based deep symbiotic genetic algorithms: Phenotyping of dominant-features

The detection of software vulnerabilities is considered a vital problem in the software security area for a long time. Nowadays, it is challenging to manage software security due to its increased complexity and diversity. So, vulnerability detection applications play a significant part in software development and maintenance. The ability of the forecasting techniques in vulnerability detection is still weak. Thus, one of the efficient defining features methods that have been used to determine the software vulnerabilities is the metaheuristic optimization methods. This paper proposes a novel software vulnerability prediction model based on using a deep learning method and SYMbiotic Genetic algorithm. We are first to apply Diploid Genetic algorithms with deep learning networks on software vulnerability prediction to the best of our knowledge. In this proposed method, a deep SYMbiotic-based genetic algorithm model (DNN-SYMbiotic GAs) is used by learning the phenotyping of dominant-features for software vulnerability prediction problems. The proposed method aimed at increasing the detection abilities of vulnerability patterns with vulnerable components in the software. Comprehensive experiments are conducted on several benchmark datasets; these datasets are taken from Drupal, Moodle, and PHPMyAdmin projects. The obtained results revealed that the proposed method (DNN-SYMbiotic GAs) enhanced vulnerability prediction, which reflects improving software quality prediction.

     

A comprehensive survey: artificial bee colony (ABC) algorithm and applications

Swarm intelligence (SI) is briefly defined as the collective behaviour of decentralized and self-organized swarms. The well known examples for these swarms are bird flocks, fish schools and the colony of social insects such as termites, ants and bees. In 1990s, especially two approaches based on ant colony and on fish schooling/bird flocking introduced have highly attracted the interest of researchers. Although the self-organization features are required by SI are strongly and clearly seen in honey bee colonies, unfortunately the researchers have recently started to be interested in the behaviour of these swarm systems to describe new intelligent approaches, especially from the beginning of 2000s. During a decade, several algorithms have been developed depending on different intelligent behaviours of honey bee swarms. Among those, artificial bee colony (ABC) is the one which has been most widely studied on and applied to solve the real world problems, so far. Day by day the number of researchers being interested in ABC algorithm increases rapidly. This work presents a comprehensive survey of the advances with ABC and its applications. It is hoped that this survey would be very beneficial for the researchers studying on SI, particularly ABC algorithm.     

Augmented grasshopper optimization algorithm by differential evolution: a power scheduling application in smart homes

With the increasing number of electricity consumers, production, distribution, and consumption problems of produced energy have appeared. This paper proposed an optimization method to reduce the peak demand using smart grid capabilities. In the proposed method, a hybrid Grasshopper Optimization Algorithm (GOA) with the self-adaptive Differential Evolution (DE) is used, called HGOA. The proposed method takes advantage of the global and local search strategies from Differential Evolution and Grasshopper Optimization Algorithm. Experimental results are applied in two scenarios; the first scenario has universal inputs and several appliances. The second scenario has an expanded number of appliances. The results showed that the proposed method (HGOA) got better power scheduling arrangements and better performance than other comparative algorithms using the classical benchmark functions. Moreover, according to the computational time, it runs in constant execution time as the population is increased. The proposed method got 0.26?% enhancement compared to the other methods. Finally, we found that the proposed HGOA always got better results than the original method in the worst cases and the best cases.

     

Investigation of Ant System parameter interactions by using design of experiments for job-shop scheduling problems

In recent years, one of the most important and promising research fields has been metaheuristics to find optimal or near-optimal solutions for NP-hard combinatorial optimization problems. Improving the quality of the solution or the solution time is basic research area on metaheuristics. Modifications of the existing ones or creation of hybrid approaches are the focus of these efforts. Another area of improving the solution quality of metaheuristics is finding the optimal combination of algorithm control parameters. This is usually done by design of experiments or one-at-a-time approach in genetic algorithms, simulated annealing and similar metaheuristics. We observe that, in studies which use Ant Colonies Optimization (ACO) as an optimization technique; the levels of control parameters are determined by some non-systematic initial experiments and the interactions of the parameters are not studied yet.In this study, the parameters of Ant System have been investigated on different sized and randomly generated job-shop scheduling problems by using design of experiments. The effects and interactions of the parameters have been interpreted with the outputs of the experiments. Referring to the statistical analysis it is observed that none of the interactions between the Ant System parameters has a significant effect on makespan value. A specific fractional experimental design is suggested instead of the full factorial design. Depending on the findings from the benchmark problems it will be a reliable approach to use the suggested design for saving time and effort in experiments without sacrificing the solution quality.     

A new QoS-aware TDMA/FDD MAC protocol with multi-beam directional antennas

With the ever-increasing demand for wireless real-time services and continuing emergence of new multimedia applications especially for mobile users, it is necessary for the network to support various levels of quality of service (QoS) while maximizing the utilization of scarce and expensive wireless channel resources. Considering this fact, a new TDMA/FDD MAC protocol integrating a novel QoS management algorithm and multi-beam Directional Antennas (DAs) to efficiently exploit wireless resources has been developed and presented in this paper. It supports all ATM CBR, VBR, ABR and UBR service classes by adopting a well-managed dynamic guarantee-based QoS scheduling algorithm. The work mainly aims at increasing the wireless system throughput as well as improving the call-blocking ratios and end-to-end delays for real-time applications. This seamless communication enables both handling real-time multimedia traffics in a fair manner and granting call requests on the basis of the connection types. The system has been developed, modeled and simulated using OPNET Modeler. The simulation results show that the QoS-aware TDMA/FDD MAC with multi-beam DAs has substantially increased the system throughput and that the call-blocking ratio has been reduced from 86% to 18%, when the proposed MAC with 8-Beam antennas is employed instead of the regular MAC.     

WSANFlow: An Interface Protocol Between SDN Controller and End Devices for SDN-Oriented WSAN

When dealing with a Wireless Sensor and Actuator Network (WSAN) structure, one of the challenging problems is lack of flexibility in such network operations as establishment, management, and configuration. Software-defined Networking (SDN) is a promising technology for a simpler, more flexible, and less overworked network structure. Integration of SDN as a solution into the existing WSAN structures seems to be a strong candidate of deployment solutions for next generation WSAN systems. In order to get enhanced performance results for WSAN systems, we proposed an interface protocol, referred to as WSANFlow, which is responsible for all the communications between SDN controller (SDNC) and SDN-oriented end devices. The SDNC in this approach has the network intelligence and is capable of handling all the control and management operations related to the network. Thus, advanced communication operations can be managed and efficiently optimized efficiently by the SDN controller and then, subsequently, corresponding instructions can be delivered to end devices using the proposed WSANFlow protocol. In the study, we analyzed the proposed framework performance, in terms of power consumption ratio, throughput, and end to end delay metrics. Then, we compared the results with those of a ZigBee-based counterpart for different workloads such as; light, heavy and heavier load which modelizes a video stream of mild parameters. The results show that not only has the overall performance of the existing WSAN system been enhanced, but also control and management operations have been simplified by the proposed model.     

Fully sequential selection procedures with a parabolic boundary

We present two fully sequential indifference-zone procedures to select the best system from a number of competing simulated systems when best is defined in terms of the maximum or minimum expected performance. These two procedures have parabola shaped continuation regions rather than the triangular continuation regions employed in several papers in the existing literature. The procedures we present accommodate unequal and unknown variances across systems and the use of common random numbers. However, we assume that basic observations are independent and identically normally distributed. We compare the performance of our procedures with those of other fully sequential procedures available in the literature.     

Case study on handoff strategies for wireless overlay networks

One of the most challenging topics for next‐generation wireless networks is the process of vertical handoff since many of wireless technologies overlap each other and build a heterogeneous topology. Several parameters, pertaining to user/application requirements and network conditions, such as data rate, service cost, network latency, speed of mobile, and etc. must be considered in the handoff process of heterogeneous networks along with RSSI information. In this paper, adaptive fuzzy logic‐based vertical handoff decision‐making algorithms are presented for wireless overlay networks which consist of GSM/GPRS/Wi-Fi/UMTS/WiMAX technologies. The parameters data rate, monetary cost, speed of mobile and RSSI information are processed as inputs of the proposed fuzzy‐based systems. According to these parameters, an output value, which varies between 1 and 10, is produced. This output value is utilized to determine whether a handoff process is necessary or not and to select the best candidate access point in the vicinity. The results show that, compared to the traditional RSSI‐based algorithm significantly enhanced outcomes can be achieved for both user and network as a consequence of the proposed fuzzy‐based handoff systems. The simulation results are also compared with those of classical MADM (Multiple Attribute Decision Making) method, i.e. SAW (Simple Additive Weighting). According to the results obtained, the proposed vertical handoff decision algorithms are able to determine whether a handoff is necessary or not, properly, and select the best candidate access network considering the aforementioned parameters. Moreover, fuzzy‐based algorithm noticeably reduces the number of handoffs compared to SAW‐based algorithm.