Search results for: Security of networks.

Authors: Ahmad M. Shafiee, Mehrdad Montazeri, Mahdi Nikdast

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Every day human life experiences new equipments more automatic and with more abilities. So the need for faster processors doesn-t seem to finish. Despite new architectures and higher frequencies, a single processor is not adequate for many applications. Parallel processing and networks are previous solutions for this problem. The new solution to put a network of resources on a chip is called NOC (network on a chip). The more usual topology for NOC is mesh topology. There are several routing algorithms suitable for this topology such as XY, fully adaptive, etc. In this paper we have suggested a new algorithm named Intermittent X, Y (IX/Y). We have developed the new algorithm in simulation environment to compare delay and power consumption with elders' algorithms.

Keywords: Computer architecture, parallel computing, NOC, routing algorithm.

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Authors: Prof. Chokri SLIM

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A Novel fuzzy neural network combining with support vector learning mechanism called support-vector-based fuzzy neural networks (SVBFNN) is proposed. The SVBFNN combine the capability of minimizing the empirical risk (training error) and expected risk (testing error) of support vector learning in high dimensional data spaces and the efficient human-like reasoning of FNN.

Keywords: Neural network, fuzzy inference, machine learning, fuzzy modeling and rule extraction, support vector regression.

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Authors: Md. Asraful Haque, Babbar Imam

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Information Security is the most describing problem in present times. To cop up with the security of the information, the passwords were introduced. The alphanumeric passwords are the most popular authentication method and still used up to now. However, text based passwords suffer from various drawbacks such as they are easy to crack through dictionary attacks, brute force attacks, keylogger, social engineering etc. Graphical Password is a good replacement for text password. Psychological studies say that human can remember pictures better than text. So this is the fact that graphical passwords are easy to remember. But at the same time due to this reason most of the graphical passwords are prone to shoulder surfing. In this paper, we have suggested a shoulder-surfing resistant graphical password authentication method. The system is a combination of recognition and pure recall based techniques. Proposed scheme can be useful for smart hand held devices (like smart phones i.e. PDAs, iPod, iPhone, etc) which are more handy and convenient to use than traditional desktop computer systems.

Keywords: Authentication, Graphical Password, Text Password, Information Security, Shoulder-surfing.

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Authors: Hazem M. El-Bakry, Ahmed A. Mohammed

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In this paper, an intelligent algorithm for optimal document archiving is presented. It is kown that electronic archives are very important for information system management. Minimizing the size of the stored data in electronic archive is a main issue to reduce the physical storage area. Here, the effect of different types of Arabic fonts on electronic archives size is discussed. Simulation results show that PDF is the best file format for storage of the Arabic documents in electronic archive. Furthermore, fast information detection in a given PDF file is introduced. Such approach uses fast neural networks (FNNs) implemented in the frequency domain. The operation of these networks relies on performing cross correlation in the frequency domain rather than spatial one. It is proved mathematically and practically that the number of computation steps required for the presented FNNs is less than that needed by conventional neural networks (CNNs). Simulation results using MATLAB confirm the theoretical computations.

Keywords: Information Storage and Retrieval, Electronic Archiving, Fast Information Detection, Cross Correlation, Frequency Domain.

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Authors: Hidehiko Okada

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The author proposes an extension of genetic algorithm (GA) for solving fuzzy-valued optimization problems. In the proposed GA, values in the genotypes are not real numbers but fuzzy numbers. Evolutionary processes in GA are extended so that GA can handle genotype instances with fuzzy numbers. The proposed method is applied to evolving neural networks with fuzzy weights and biases. Experimental results showed that fuzzy neural networks evolved by the fuzzy GA could model hidden target fuzzy functions well despite the fact that no training data was explicitly provided.

Keywords: Evolutionary algorithm, genetic algorithm, fuzzy number, neural network, neuroevolution.

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Authors: Tadatsugu Kitamoto

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Recently, a quality of motors is inspected by human ears. In this paper, I propose two systems using a method of speech recognition for automation of the inspection. The first system is based on a method of linear processing which uses K-means and Nearest Neighbor method, and the second is based on a method of non-linear processing which uses neural networks. I used motor sounds in these systems, and I successfully recognize 86.67% of motor sounds in the linear processing system and 97.78% in the non-linear processing system.

Keywords: Acoustical diagnosis, Neural networks, K-means, Short-time Fourier transformation

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Authors: Julien Romieux, Fabio Verdicchio

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Wireless Sensor Networks (WSNs), which sense environmental data with battery-powered nodes, require multi-hop communication. This power-demanding task adds an extra workload that is unfairly distributed across the network. As a result, nodes run out of battery at different times: this requires an impractical individual node maintenance scheme. Therefore we investigate a new Cooperative Sensing approach that extends the WSN operational life and allows a more practical network maintenance scheme (where all nodes deplete their batteries almost at the same time). We propose a novel cooperative algorithm that derives a piecewise representation of the sensed signal while controlling approximation accuracy. Simulations show that our algorithm increases WSN operational life and spreads communication workload evenly. Results convey a counterintuitive conclusion: distributing workload fairly amongst nodes may not decrease the network power consumption and yet extend the WSN operational life. This is achieved as our cooperative approach decreases the workload of the most burdened cluster in the network.

Keywords: Cooperative signal processing, power management, signal representation, signal approximation, wireless sensor networks.

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Authors: Hyunsang Park, Kwangwoo Lee, Yunho Lee, Seungjoo Kim, Dongho Won

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The online office is one of web application. We can easily use the online office through a web browser with internet connected PC. The online office has the advantage of using environment regardless of location or time. When users want to use the online office, they access the online office server and use their content. However, recently developed and launched online office has the weakness of insufficient consideration. In this paper, we analyze the security vulnerabilities of the online office. In addition, we propose the evaluation criteria to make secure online office using Common Criteria. This evaluation criteria can be used to establish trust between the online office server and the user. The online office market will be more active than before.

Keywords: Online Office, Vulnerabilities, CommonCriteria(CC)

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Authors: Dongwan Kang, Joohyung Oh, Chaetae Im

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Advancement of communication technologies and smart devices in the recent times is leading to changes into the integrated wired and wireless communication environments. Since early days, businesses had started introducing environments for mobile device application to their operations in order to improve productivity (efficiency) and the closed corporate environment gradually shifted to an open structure. Recently, individual user's interest in working environment using mobile devices has increased and a new corporate working environment under the concept of BYOD is drawing attention. BYOD (bring your own device) is a concept where individuals bring in and use their own devices in business activities. Through BYOD, businesses can anticipate improved productivity (efficiency) and also a reduction in the cost of purchasing devices. However, as a result of security threats caused by frequent loss and theft of personal devices and corporate data leaks due to low security, companies are reluctant about adopting BYOD system. In addition, without considerations to diverse devices and connection environments, there are limitations in detecting abnormal behaviors, such as information leaks, using the existing network-based security equipment. This study suggests a method to detect abnormal behaviors according to individual behavioral patterns, rather than the existing signature-based malicious behavior detection, and discusses applications of this method in BYOD environment.

Keywords: BYOD, Security, Anomaly Behavior Detection.

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Authors: Farshad Zeinali, Sajedeh Norouzi, Nader Mokari, Eduard A. Jorswieck

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The capacity of fifth-generation (5G)vehicle-to-everything (V2X) networks poses significant challenges.To address this challenge, this paper utilizes New Radio (NR) and New Radio Unlicensed (NR-U) networks to develop a vehicular heterogeneous network (HetNet). We propose a framework, named joint BS assignment and resource allocation (JBSRA) for mobile V2X users and also consider coexistence schemes based on flexible duty cycle (DC) mechanism for unlicensed bands. Our objective is to maximize the average throughput of vehicles, while guarantying the WiFi users throughput. In simulations based on deep reinforcement learning (DRL) algorithms such as deep deterministic policy gradient (DDPG) and deep Q network (DQN), our proposed framework outperforms existing solutions that rely on fixed DC or schemes without consideration of unlicensed bands.

Keywords: Vehicle-to-everything, resource allocation, BS assignment, new radio, new radio unlicensed, coexistence NR-U and WiFi, deep deterministic policy gradient, Deep Q-network, Duty cycle mechanism.

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Authors: Mirjana Ruppel, Rajendra Persad, Amit Bahl, Sanja Dogramadzi, Chris Melhuish, Lyndon Smith

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Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images ˆA, ˆB which were registered to ˜B, ˜A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph.

Keywords: Multimodal image registration, GAN, cycle consistency, deep learning.

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Authors: Akram M. Othman, May H. Riadh

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This research work is aimed at speech recognition using scaly neural networks. A small vocabulary of 11 words were established first, these words are “word, file, open, print, exit, edit, cut, copy, paste, doc1, doc2". These chosen words involved with executing some computer functions such as opening a file, print certain text document, cutting, copying, pasting, editing and exit. It introduced to the computer then subjected to feature extraction process using LPC (linear prediction coefficients). These features are used as input to an artificial neural network in speaker dependent mode. Half of the words are used for training the artificial neural network and the other half are used for testing the system; those are used for information retrieval. The system components are consist of three parts, speech processing and feature extraction, training and testing by using neural networks and information retrieval. The retrieve process proved to be 79.5-88% successful, which is quite acceptable, considering the variation to surrounding, state of the person, and the microphone type.

Keywords: Feature extraction, Liner prediction coefficients, neural network, Speech Recognition, Scaly ANN.

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Authors: Abdul Basit Kiani, Maryam Kiani

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The art of web development in new technologies is a dynamic journey, shaped by the constant evolution of tools and platforms. With the emergence of JavaScript frameworks and APIs, web developers are empowered to craft web applications that are not only robust but also highly interactive. The aim is to provide an overview of the developments in the field. The integration of artificial intelligence (AI) and machine learning (ML) has opened new horizons in web development. Chatbots, intelligent recommendation systems, and personalization algorithms have become integral components of modern websites. These AI-powered features enhance user engagement, provide personalized experiences, and streamline customer support processes, revolutionizing the way businesses interact with their audiences. Lastly, the emphasis on web security and privacy has been a pivotal area of progress. With the increasing incidents of cyber threats, web developers have implemented robust security measures to safeguard user data and ensure secure transactions. Innovations such as HTTPS protocol, two-factor authentication, and advanced encryption techniques have bolstered the overall security of web applications, fostering trust and confidence among users. Hence, recent progress in web development has propelled the industry forward, enabling developers to craft innovative and immersive digital experiences. From responsive design to AI integration and enhanced security, the landscape of web development continues to evolve, promising a future filled with endless possibilities.

Keywords: Web development, software testing, progressive web apps, web and mobile native application.

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Authors: Amin Sedighfar, M. R. Moniri

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Determination of state of charge (SOC) in today’s world becomes an increasingly important issue in all the applications that include a battery. In fact, estimation of the SOC is a fundamental need for the battery, which is the most important energy storage in Hybrid Electric Vehicles (HEVs), smart grid systems, drones, UPS and so on. Regarding those applications, the SOC estimation algorithm is expected to be precise and easy to implement. This paper presents an online method for the estimation of the SOC of Valve-Regulated Lead Acid (VRLA) batteries. The proposed method uses the well-known Kalman Filter (KF), and Neural Networks (NNs) and all of the simulations have been done with MATLAB software. The NN is trained offline using the data collected from the battery discharging process. A generic cell model is used, and the underlying dynamic behavior of the model has used two capacitors (bulk and surface) and three resistors (terminal, surface, and end), where the SOC determined from the voltage represents the bulk capacitor. The aim of this work is to compare the performance of conventional integration-based SOC estimation methods with a mixed algorithm. Moreover, by containing the effect of temperature, the final result becomes more accurate. 

Keywords: Kalman filter, neural networks, state-of-charge, VRLA battery.

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Authors: Anwar Hassen Tsega

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International labor migration is an integral part of the modern globalized world. However, the phenomenon has its roots in some earlier periods in human history. This paper discusses the relatively new phenomenon of female migration in Africa. In the past, African women migrants were only spouses or dependent family members. But as modernity swept most African societies, with rising unemployment rates, there is evidence everywhere in Africa that women labor migration is a growing phenomenon that deserves to be understood in the context of human security research. This work explores these issues further, focusing on the experience of Ethiopian women labor migrants to Sudan. The migration of Ethiopian people to Sudan is historical; nevertheless, labor migration mainly started since the discovery and subsequent exploration of oil in the Sudan. While the paper is concerned with the human security aspect of the migrant workers, we need to be certain that the migration process will provide with a decent wage, good working conditions, the necessary social security coverage, and labor protection as a whole. However, migration to Sudan is not always safe and female migrants become subject to violence at the hands of brokers, employers and migration officials. For this matter, the paper argued that identifying the vulnerable stages and major problem facing female migrant workers at various stages of migration is a prerequisite to combat the problem and secure the lives of the migrant workers. The major problems female migrants face include extra degrees of gender-based violence, underpayment, various forms of abuse like verbal, physical and sexual and other forms of torture which include beating and slaps. This peculiar situation could be attributed to the fact that most of these women are irregular migrants and fall under the category of unskilled and/or illiterate migrants.

Keywords: Labor migration, human security, trafficking, smuggling, Ethiopia, Sudan.

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Authors: R. Geetha, T. Padmavathy

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Security audit is an important aspect or feature to be considered in cloud service customer. It is basically a certification process to audit the controls that deliver the security requirements. Security audits are conducted by trained and qualified staffs that belong to an independent auditing organization. Security audits must be carried as a standard of security controls. Proper check to be made that the cloud user has a proper reporting and logging facilities with the customer's system and hence ensuring appropriate business and operational flow of data through cloud service. We propose a cloud-based secure auditing framework, which enables confided in power to safely store their mystery information on the semi-believed cloud specialist co-ops, and specifically share their mystery information with a wide scope of information recipient, to diminish the key administration intricacy for power proprietors and information collectors. Unique in relation to past cloud-based information framework, data proprietors transfer their mystery information into cloud utilizing static and dynamic evaluating plan. Another propelled determination is, if any information beneficiary needs individual record to download, the information collector will send the solicitation to the expert. The specialist proprietor has the Access Control. At the off probability, the businessman must impart the primary record to the knowledge collector, acknowledge statistics beneficiary solicitation. Once the acknowledgement for the records is over, the recipient downloads the first record and this record shifting time with date and downloading time with date are monitored by the inspector. In addition to deduplication concept, diminished cloud memory area using dynamic document distribution has been proposed.

Keywords: Cloud computing, cloud storage auditing, data integrity, key exposure.

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Authors: Y. Harold Robinson, M. Rajaram, E. Golden Julie, S. Balaji

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A mobile ad hoc network (MANET) is a wireless communication network where nodes that are not within direct transmission range establish their communication via the help of other nodes to forward data. Routing protocols in MANETs are usually categorized as proactive. Tree Based Opportunistic Routing (TBOR) finds a multipath link based on maximum probability of the throughput. The simulation results show that the presented method is performed very well compared to the existing methods in terms of throughput, delay and routing overhead.

Keywords: Mobile ad hoc networks, opportunistic data forwarding, proactive Source routing, BFS.

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Authors: Mahanijah Md Kamal., Dingli Yu

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This paper presents a new method of fault detection and isolation (FDI) for polymer electrolyte membrane (PEM) fuel cell (FC) dynamic systems under an open-loop scheme. This method uses a radial basis function (RBF) neural network to perform fault identification, classification and isolation. The novelty is that the RBF model of independent mode is used to predict the future outputs of the FC stack. One actuator fault, one component fault and three sensor faults have been introduced to the PEMFC systems experience faults between -7% to +10% of fault size in real-time operation. To validate the results, a benchmark model developed by Michigan University is used in the simulation to investigate the effect of these five faults. The developed independent RBF model is tested on MATLAB R2009a/Simulink environment. The simulation results confirm the effectiveness of the proposed method for FDI under an open-loop condition. By using this method, the RBF networks able to detect and isolate all five faults accordingly and accurately.

Keywords: Polymer electrolyte membrane fuel cell, radial basis function neural networks, fault detection, fault isolation.

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Authors: Sarah Barrere

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The area of liberty, security and justice within the European Union is still a work in progress. No one can deny that the EU struggles between a monistic and a dualist approach. The aim of our essay is to first review how the European law is perceived by the rest of the international scene. It will then discuss two main mechanisms at play: the interpretation of larger international treaties and the penal mechanisms of European law. Finally, it will help us understand the role of a penal Europe on the international scene with concrete examples. Special attention will be paid to cases that deal with fundamental rights as they represent an interesting case study in Europe and in the rest of the World. It could illustrate the aforementioned duality currently present in the Union’s interpretation of international public law. On the other hand, it will explore some specific European penal mechanism through mutual recognition and the European arrest warrant in the transnational criminality frame. Concerning the interpretation of the treaties, it will first, underline the ambiguity and the general nature of some treaties that leave the EU exposed to tension and misunderstanding then it will review the validity of an EU act (whether or not it is compatible with the rules of International law). Finally, it will focus on the most complete manifestation of liberty, security and justice through the principle of mutual recognition. Used initially in commercial matters, it has become “the cornerstone” of European construction. It will see how it is applied in judicial decisions (its main event and achieving success is via the European arrest warrant) and how European member states have managed to develop this cooperation.

Keywords: European penal law, International scene, Liberty security and justice area, mutual recognition.

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Authors: M. de Miguel Molina, V. Santamarina Campos, M. V. Segarra Oña, B. de Miguel Molina

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Safety and security concerns play a key role during the design of civil UAs (aircraft controlled by a pilot who is not onboard it) by the producers and the offer of different services by the operators. At present, European countries have fragmented regulations about the manufacture and use of civil drones, therefore the European institutions are trying to approach all these regulations into a common one. In this sense, not only law but also ethics can give guidelines to the industry in order to obtain better reports from their clients. With our results, we would like to give advice to the European industry, as well as give new insights to the academia and policymakers.

Keywords: Ethics, regulation, safety, security.

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: Deep learning, artificial neural networks, energy price forecasting, Turkey.

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Authors: Inom S. Normatov, Abulqosim Muminov, Parviz I. Normatov

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Problems of food security and the preservation of reserved zones in the region of Central Asia under the conditions of the climate change induced by the placement and construction of large reservoirs are considered. The criteria for the optimum placement and construction of reservoirs that entail the minimum impact on the environment are established. The need for the accounting of climatic parameters is shown by the calculation of the water quantity required for the irrigation of agricultural lands.

Keywords: Reservoir, Central Asia, food, reserved zones, adaptation, agriculture.

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Authors: Hind Bouami, Patrick Millot

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Medication dispensing system is a life-critical system whose failure may result in preventable adverse events leading to longer patient stays in hospitals or patient death. Automation has led to great improvements in life-critical systems as it increased safety, efficiency, and comfort. However, critical risks related to medical organization complexity and automated solutions integration can threaten drug dispensing security and performance. Knowledge about the system’s complexity aspects and human machine parameters to control for automated equipment’s security and performance will help operators to secure their automation process and to optimize their system’s reliability. In this context, this study aims to document the operator’s situation awareness about automation risks and parameters involved in automation security and performance. Our risk management approach has been deployed in the North Luxembourg hospital center’s pharmacy, which is equipped with automated drug dispensing systems since 2009. With more than 4 million euros of gains generated, North Luxembourg hospital center’s success story was enabled by the management commitment, pharmacy’s involvement in the implementation and improvement of the automation project, and the close collaboration between the pharmacy and Sinteco’s firm to implement the necessary innovation and organizational actions for automated solutions integration security and performance. An analysis of the actions implemented by the hospital and the parameters involved in automated equipment’s integration security and performance has been made. The parameters to control for automated equipment’s integration security and performance are human aspects (6.25%), technical aspects (50%), and human-machine interaction (43.75%). The implementation of an anthropocentric analysis system before automation would have prevented and optimized the control of risks related to automation.

Keywords: Automated drug delivery systems, hospitals, human-centered automated system, risk management.

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Authors: Z.M. Hanapi, M. Ismail, K. Jumari, M. Mahdavi

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Routing security is a major concerned in Wireless Sensor Network since a large scale of unattended nodes is deployed in ad hoc fashion with no possibility of a global addressing due to a limitation of node-s memory and the node have to be self organizing when the systems require a connection with the other nodes. It becomes more challenging when the nodes have to act as the router and tightly constrained on energy and computational capabilities where any existing security mechanisms are not allowed to be fitted directly. These reasons thus increasing vulnerabilities to the network layer particularly and to the whole network, generally. In this paper, a Dynamic Window Secured Implicit Geographic Forwarding (DWSIGF) routing is presented where a dynamic time is used for collection window to collect Clear to Send (CTS) control packet in order to find an appropriate hoping node. The DWIGF is expected to minimize a chance to select an attacker as the hoping node that caused by a blackhole attack that happen because of the CTS rushing attack, which promise a good network performance with high packet delivery ratios.

Keywords: sensor, security, routing, attack, random.

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Authors: Jamel Miri, Bechir Nsiri, Ridha Bouallegue

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Ultra WidBand-IR physical layer technology has seen a great development during the last decade which makes it a promising candidate for short range wireless communications, as they bring considerable benefits in terms of connectivity and mobility. However, like all wireless communication they suffer from vulnerabilities in terms of security because of the open nature of the radio channel. To face these attacks, distance bounding protocols are the most popular counter measures. In this paper, we presented a protocol based on distance bounding to thread the most popular attacks: Distance Fraud, Mafia Fraud and Terrorist fraud. In our work, we study the way to adapt the best secure distance bounding protocols to mapping code of ultra-wideband (TH-UWB) radios. Indeed, to ameliorate the performances of the protocol in terms of security communication in TH-UWB, we combine the modified protocol to ultra-wideband impulse radio technology (IR-UWB). The security and the different merits of the protocols are analyzed.

Keywords: Distance bounding, mapping code ultra-wideband, Terrorist Fraud.

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Authors: Mojca Ciglaric, Andrej Krevl, Matjaž Pancur, Tone Vidmar

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P2P Networks are highly dynamic structures since their nodes – peer users keep joining and leaving continuously. In the paper, we study the effects of network change rates on query routing efficiency. First we describe some background and an abstract system model. The chosen routing technique makes use of cached metadata from previous answer messages and also employs a mechanism for broken path detection and metadata maintenance. Several metrics are used to show that the protocol behaves quite well even with high rate of node departures, but above a certain threshold it literally breaks down and exhibits considerable efficiency degradation.

Keywords: Network dynamics, overlay network, P2P system, routing efficiency.

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Authors: Sami Baraketi, Jean-Marie Garcia, Olivier Brun

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Wavelength Division Multiplexing (WDM) is the dominant transport technology used in numerous high capacity backbone networks, based on optical infrastructures. Given the importance of costs (CapEx and OpEx) associated to these networks, resource management is becoming increasingly important, especially how the optical circuits, called “lightpaths”, are routed throughout the network. This requires the use of efficient algorithms which provide routing strategies with the lowest cost. We focus on the lightpath routing and wavelength assignment problem, known as the RWA problem, while optimizing wavelength fragmentation over the network. Wavelength fragmentation poses a serious challenge for network operators since it leads to the misuse of the wavelength spectrum, and then to the refusal of new lightpath requests. In this paper, we first establish a new Integer Linear Program (ILP) for the problem based on a node-link formulation. This formulation is based on a multilayer approach where the original network is decomposed into several network layers, each corresponding to a wavelength. Furthermore, we propose an efficient heuristic for the problem based on a greedy algorithm followed by a post-treatment procedure. The obtained results show that the optimal solution is often reached. We also compare our results with those of other RWA heuristic methods

Keywords: WDM, lightpath, RWA, wavelength fragmentation, optimization, linear programming, heuristic

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Authors: Viktor R. Stoynov, Zlatka V. Valkova-Jarvis

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The intelligent management and optimisation of radio resource technologies will lead to a considerable improvement in the overall performance in Next Generation Networks (NGNs). Carrier Aggregation (CA) technology, also known as Spectrum Aggregation, enables more efficient use of the available spectrum by combining multiple Component Carriers (CCs) in a virtual wideband channel. LTE-A (Long Term Evolution–Advanced) CA technology can combine multiple adjacent or separate CCs in the same band or in different bands. In this way, increased data rates and dynamic load balancing can be achieved, resulting in a more reliable and efficient operation of mobile networks and the enabling of high bandwidth mobile services. In this paper, several distinct CA deployment strategies for the utilisation of spectrum bands are compared in indoor-outdoor scenarios, simulated via the recently-developed Realistic Indoor Environment Generator (RIEG). We analyse the performance of the User Equipment (UE) by integrating the average throughput, the level of fairness of radio resource allocation, and other parameters, into one summative assessment termed a Comparative Factor (CF). In addition, comparison of non-CA and CA indoor mobile networks is carried out under different load conditions: varying numbers and positions of UEs. The experimental results demonstrate that the CA technology can improve network performance, especially in the case of indoor scenarios. Additionally, we show that an increase of carrier frequency does not necessarily lead to improved CF values, due to high wall-penetration losses. The performance of users under bad-channel conditions, often located in the periphery of the cells, can be improved by intelligent CA location. Furthermore, a combination of such a deployment and effective radio resource allocation management with respect to user-fairness plays a crucial role in improving the performance of LTE-A networks.

Keywords: Comparative factor, carrier aggregation, indoor mobile network, resource allocation.

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Authors: A. Safari, R. Jahani, H. A. Shayanfar, J. Olamaei

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This paper shows the results obtained in the analysis of the impact of distributed generation (DG) on distribution losses and presents a new algorithm to the optimal allocation of distributed generation resources in distribution networks. The optimization is based on a Hybrid Genetic Algorithm and Particle Swarm Optimization (HGAPSO) aiming to optimal DG allocation in distribution network. Through this algorithm a significant improvement in the optimization goal is achieved. With a numerical example the superiority of the proposed algorithm is demonstrated in comparison with the simple genetic algorithm.

Keywords: Distributed Generation, Distribution Networks, Genetic Algorithm, Particle Swarm Optimization.

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Authors: Qingqing Wang, Shouming Zhong

Abstract:

This paper is concerned with the stability problem with two additive time-varying delay components. By choosing one augmented Lyapunov-Krasovskii functional, using some new zero equalities, and combining linear matrix inequalities (LMI) techniques, two new sufficient criteria ensuring the global stability asymptotic stability of DNNs is obtained. These stability criteria are present in terms of linear matrix inequalities and can be easily checked. Finally, some examples are showed to demonstrate the effectiveness and less conservatism of the proposed method.

Keywords: Neural networks, Globally asymptotic stability, LMI approach, Additive time-varying delays.

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