No. 4 (2011)
Published:
2011-12-30
ARTICLES FROM THIS ISSUE
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Evolutionary Computation for Global Optimization – Current Trends
Abstract
This article comments on the development of Evolutionary Computation (EC) in the field of global optimization. A brief overview of EC fundamentals is provided together with the discussion of issues of parameter settings and adaptation, advances in the development of theory, new ideas emerging in the EC field and growing availability of massively parallel machines.
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Self-Adaptive Stable Mutation Based on Discrete Spectral Measure for Evolutionary Algorithms
Abstract
In this paper, the concept of a multidimensional discrete spectral measure is introduced in the context of its application to the real-valued evolutionary algorithms. The notion of a discrete spectral measure makes it possible to uniquely define a class of multivariate heavy-tailed distributions, that have recently received substantial attention of the evolutionary optimization community. In particular, an adaptation procedure known from the distribution estimation algorithms (EDAs) is considered and the resulting estimated distribution is compared with the optimally selected referential distribution.
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Self-Adaptive Differential Evolution with Hybrid Rules of Perturbation for Dynamic Optimization
Abstract
In this paper an adaptive differential evolution approach for dynamic optimization problems is studied. A new benchmark suite Syringa is also presented. The suite allows to generate test-cases from a multiple number of dynamic optimization classes. Two dynamic benchmarks: Generalized Dynamic Benchmark Generator (GDBG) and Moving Peaks Benchmark (MPB) have been simulated in Syringa and in the presented research they were subject of the experimental research. Two versions of adaptive differential evolution approach, namely the jDE algorithm have been heavily tested: the pure version of jDE and jDE equipped with solutions mutated with a new operator. The operator uses a symmetric α-stable distribution variate for modification of the solution coordinates.
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Improving Population-Based Algorithms with Fitness Deterioration
Abstract
This work presents a new hybrid approach for supporting sequential niching strategies called Cluster Supported Fitness Deterioration (CSFD). Sequential niching is one of the most promising evolutionary strategies for analyzing multimodal global optimization problems in the continuous domains embedded in the vector metric spaces. In each iteration CSFD performs the clustering of the random sample by OPTICS algorithm and then deteriorates the fitness on the area occupied by clusters. The selection pressure pushes away the next-step sample (population) from the basins of attraction of minimizers already recognized, speeding up finding the new ones. The main advantages of CSFD are low memory an computational complexity even in case of large dimensional problems and high accuracy of deterioration obtained by the flexible cluster definition delivered by OPTICS. The paper contains the broad discussion of niching strategies, detailed definition of CSFD and the series of the simple comparative tests.
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Topological Synthesis of Tree Shaped Structures Based on a Building Blocks Hypothesis
Abstract
In this paper a new approach to evolutionary controlled creation of electronic circuit connection topology is proposed. Microwave circuits consisting of a tree like connection of ideal transmission lines are considered. Assuming that a reasonable number of transmission lines in a tree network ranges from 10 to 100, the number of connection combinations is immense. From the engineering practice comes the hypothesis that any device can be decomposed into some functional building blocks consisting of one to dozen transmission lines. The variety of linking combinations in a tree with a limited depth is confined to hundreds or thousands of shapes. Therefore we can decrease the dimensionality of research space, applying evolution to building blocks only. Evolutionary algorithm (EA) which processes simultaneously the population of λ functional blocks and population of μ circuits is proposed. A μ, λ selection scheme with tournament together with specific encoding of solutions, and custom operators is implemented. The μ, λ, α EA was tested on an example of the design of a microwave transistor matching circuit.
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Evolutionary Algorithm that Designs the DNA Synthesis Procedure
Abstract
Chemical synthesis of nucleotide chains is very erroneous for long sequences. Often a gene is constructed from short fragments joined with the use of complementary helper chains. The number of possible potential solutions for a long gene synthesis is very large, therefore a fast automated search is required. In the presented approach a modified method of long DNA construction is proposed. A computer program that searches for an optimal solution in the space of potential synthesis methods has been developed. This software uses an evolutionary algorithm for global optimization and a hillclimbing algorithm for local optimization. The long DNA construction method was tested on random sequences. The results are very promising. The next step is to perform experiments in a biotechnological wet laboratory involving DNA strand synthesis using the method designed by the presented software.
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Localization in Wireless Sensor Networks Using Heuristic Optimization Techniques
Abstract
Many applications of wireless sensor networks (WSN) require information about the geographic location of each sensor node. Devices that form WSN are expected to be remotely deployed in large numbers in a sensing field, and to self-organize to perform sensing and acting task. The goal of localization is to assign geographic coordinates to each device with unknown position in the deployment area. Recently, the popular strategy is to apply optimization algorithms to solve the localization problem. In this paper, we address issues associated with the application of heuristic techniques to accurate localization of nodes in a WSN system. We survey and discuss the location systems based on simulated annealing, genetic algorithms and evolutionary strategies. Finally, we describe and evaluate our methods that combine trilateration and heuristic optimization.
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Incrementally Solving Nonlinear Regression Tasks Using IBHM Algorithm
Abstract
This paper considers the black-box approximation problem where the goal is to create a regression model using only empirical data without incorporating knowledge about the character of nonlinearity of the approximated function. This paper reports on ongoing work on a nonlinear regression methodology called IBHM which builds a model being a combination of weighted nonlinear components. The construction process is iterative and is based on correlation analysis. Due to its iterative nature, the methodology does not require a priori assumptions about the final model structure which greatly simplifies its usage. Correlation based learning becomes ineffective when the dynamics of the approximated function is too high. In this paper we introduce weighted correlation coefficients into the learning process. These coefficients work as a kind of a local filter and help overcome the problem. Proof of concept experiments are discussed to show
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Benchmarking Procedures for Continuous Optimization Algorithms
Abstract
Reliable comparison of optimization algorithms requires the use of specialized benchmarking procedures. This paper highlights motivations which influence their structure, discusses evaluation criteria of algorithms, typical ways of presenting and interpreting results as well as related statistical procedures. Discussions are based on examples from CEC and BBOB benchmarks. Moreover, attention is drawn to these features of comparison procedures, which make them susceptible to manipulation. In particular, novel application of the weak axiom of revealed preferences to the field of benchmarking shows why it may be misleading to assess algorithms on basis of their ranks for each of test problems. Additionally, an idea is presented of developing massively parallel implementation of benchmarks. Not only would this provide faster computation but also open the door to improving reliability of benchmarking procedures and promoting research into parallel implementations of optimization algorithms.
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The “Second Derivative” of a Non-Differentiable Function and its Use in Interval Optimization Methods
Abstract
The paper presents an idea to use weak derivatives in interval global optimization. It allows using the Newton operator to narrow domains of non-differentiable functions. Preliminary computational experiments are also presented.
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Enhancement of Power Efficiency in OFDM System by SLM with Predistortion Technique
Abstract
Orthogonal Frequency Division Multiplexing (OFDM) is considered as a strong candidate for future wireless communication because it is marked by its higher frequency multiplicity and greater immunity to multipath fading. However, the main drawback of OFDM is its high amplitude fluctuations measured by peak-to-average power ratio (PAPR), which leads to power inefficiency and requires expensive high power amplifier (HPA) with very good linearity. In this paper, we propose selected mapping (SLM) with predistortion technique to decrease the nonlinear distortion and to improve the power efficiency of the nonlinear HPA. In the proposed method SLM reduces the PAPR and improves the power efficiency, the predistorter improves the bit error rate (BER) performance of the system. The PAPR reduction is possible with SLM when compared with original OFDM. After reducing the PAPR with SLM the data goes into the HPA with and without predistorter. The BER performance curves of SLM method with or without predistorter shows that, predistorter operates more effectively in SLM method than original OFDM system. At 4 dB IBO (input backoff) the conventional method with predistorter achieves 1.8 dB SNR gain than conventional method without a predistorter and at 6 dB IBO the BER performance is towards the ideal linear amplifier. The proposed system will be evaluated for OFDM system in the presence of a nonlinear power amplifier.
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Providing QoS Guarantees in Broadband Ad Hoc Networks
Abstract
This paper presents a novel QoS architecture for IEEE 802.11 multihop broadband ad hoc networks integrated with infrastructure. The authors describe its features, including MAC layer measurements, traffic differentiation, and admission control. The modules required by the network elements as well as their integration are also presented. Additionally, the paper presents results which validate its correct operation and prove its superiority over plain IEEE 802.11. The authors are convinced that the proposed solution will provide QoS support for a variety of services in future mobile ad hoc networks.
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SVD Audio Watermarking: A Tool to Enhance the Security of Image Transmission over ZigBee Networks
Abstract
The security is important issue in wireless networks. This paper discusses audio watermarking as a tool to improve the security of image communication over the IEEE 802.15.4 ZigBee network. The adopted watermarking method implements the Singular-Value Decomposition (SVD) mathematical technique. This method is based on embedding a chaotic encrypted image in the Singular Values (SVs) of the audio signal after transforming it into a 2-D format. The objective of chaotic encryption is to enhance the level of security and resist different attacks. Experimental results show that the SVD audio watermarking method maintains the high quality of the audio signals and that the watermark extraction and decryption are possible even in the presence of attacks over the ZigBee network.
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Guaranteed Protection in Survivable WDM Mesh Networks – New ILP Formulations for Link Protection and Path Protection
Abstract
In this paper we propose new simple integer linear programs (ILPs) formulations for minimizing capacity (in wavelength link) utilization in survivable WDM network. The study examines the performance of shared based protection schemes, such as path protection scheme and link protection scheme under single fiber failure. The numerical results obtained show a reduction in capacity utilization using random traffic compared to the reported ILP formulation. We also present the results using Poisson’s traffic to identify the frequently used links for the widely used NSF network. The proposed work not only reduces the wavelength consumption in different traffic scenarios but also efficient in terms of simulation time. In this paper we propose new simple integer linear programs (ILPs) formulations for minimizing capacity (in wavelength link) utilization in survivable WDM network. The study examines the performance of shared based protection schemes, such as path protection scheme and link protection scheme under single fiber failure. The numerical results obtained show a reduction in capacity utilization using random traffic compared to the reported ILP formulation. We also present the results using Poisson’s traffic to identify the frequently used links for the widely used NSF network. The proposed work not only reduces the wavelength consumption in different traffic scenarios but also efficient in terms of simulation time.
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Privacy Preserving and Secure Iris-Based Biometric Authentication for Computer Networks
Abstract
The iris biometrics is considered one of the most accurate and robust methods of the identity verification. The unique iris features of an individual can be presented in a compact binary form which can be easily compared with the reference template to confirm identity. However in contrast to passwords and PINs biometric authentication factors cannot be revoked and changed as they are inherently connected to our characteristics. Once the biometric information is compromised or disclosed it became useless for the purpose of authentication. Therefore there is a need to perform iris features matching without revealing the features itself and the reference template. We propose an extension of the standard irisbased verification protocol which introduces a features and template locking mechanism, which guarantee that no sensitive information is exposed. Presented solutions can be easily integrated into authentication mechanisms used in modern computer networks.
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Trends and Differences of Applying Intelligence to an Agent
Abstract
The agent technology has recently become one of the most vibrant and fastest growing areas in information technology. On of the most promising characteristics of agent is its intelligence. Intelligent agent is the agent that percepts its environment, collects all information about its environment that it needs, processes these information and then generate proper actions according to these information. This paper discusses trends and differences between two main types of intelligence that can be applied to agent: accumulative intelligence and dynamic intelligence. Accumulative intelligence is discussed with its two perspectives: moment perspective and historical perspective. Auto-vehicle driver is also discussed as an application example of accumulative intelligence. Also, MOSAIC, Mimesis, and MINDY models are reviewed as the pioneering works of dynamic intelligence.
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A Comparative Study of Single- and Dual-Threshold Voltage SRAM Cells
Abstract
In this paper, a comparison has been drawn between 5 transistor (5T), 6T and 7T SRAM cells. All the cells have been designed using both single-threshold (conventional) and dual-threshold (dual-Vt) voltage techniques. Their respective delays and power consumption have been calculated at 180 nm and 65 nm CMOS technology. With technology scaling, power consumption decreases by 80% to 90%, with some increase in write time because of the utilization of high- Vt transistors in write critical path. The results show that the read delay of 7T SRAM cell is 9% lesser than 5T SRAM cell and 29% lesser than 6T SRAM cell due to the lower resistance of the read access delay path. While read power of 5T SRAM cell is reduced by 10% and 24% as compared to 7T SRAM, 6T SRAM cell respectively. The write speed, however, is degraded by 1% to 3% with the 7T and 5T SRAM cells as compared to the 6T SRAM cells due to the utilization of single ended architecture. While write power of 5T SRAM cell is reduced by up to 40% and 67% as compared to 7T SRAM, 6T SRAM cell respectively.
