Search results for: vehicular ad-hoc network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4834

Search results for: vehicular ad-hoc network

4684 An Algorithm to Depreciate the Energy Utilization Using a Bio-Inspired Method in Wireless Sensor Network

Authors: Navdeep Singh Randhawa, Shally Sharma

Abstract:

Wireless Sensor Network is an autonomous technology emanating in the current scenario at a fast pace. This technology faces a number of defiance’s and energy management is one of them, which has a huge impact on the network lifetime. To sustain energy the different types of routing protocols have been flourished. The classical routing protocols are no more compatible to perform in complicated environments. Hence, in the field of routing the intelligent algorithms based on nature systems is a turning point in Wireless Sensor Network. These nature-based algorithms are quite efficient to handle the challenges of the WSN as they are capable of achieving local and global best optimization solutions for the complex environments. So, the main attention of this paper is to develop a routing algorithm based on some swarm intelligent technique to enhance the performance of Wireless Sensor Network.

Keywords: wireless sensor network, routing, swarm intelligence, MPRSO

Procedia PDF Downloads 352
4683 MarginDistillation: Distillation for Face Recognition Neural Networks with Margin-Based Softmax

Authors: Svitov David, Alyamkin Sergey

Abstract:

The usage of convolutional neural networks (CNNs) in conjunction with the margin-based softmax approach demonstrates the state-of-the-art performance for the face recognition problem. Recently, lightweight neural network models trained with the margin-based softmax have been introduced for the face identification task for edge devices. In this paper, we propose a distillation method for lightweight neural network architectures that outperforms other known methods for the face recognition task on LFW, AgeDB-30 and Megaface datasets. The idea of the proposed method is to use class centers from the teacher network for the student network. Then the student network is trained to get the same angles between the class centers and face embeddings predicted by the teacher network.

Keywords: ArcFace, distillation, face recognition, margin-based softmax

Procedia PDF Downloads 146
4682 Dynamics of Chirped RZ Modulation Format in GEPON Fiber to the Home (FTTH) Network

Authors: Anurag Sharma, Manoj Kumar, Ashima, Sooraj Parkash

Abstract:

The work in this paper presents simulative comparison for different modulation formats such as NRZ, Manchester and CRZ in a 100 subscribers at 5 Gbps bit rate Gigabit Ethernet Passive Optical Network (GEPON) FTTH network. It is observed from the simulation results that the CRZ modulation format is best suited for the designed system. A link design for 1:100 splitter is used as Passive Optical Network (PON) element which creates communication between central offices to different users. The Bit Error Rate (BER) is found to be 2.8535e-10 at 5 Gbit/s systems for CRZ modulation format.

Keywords: PON , FTTH, OLT, ONU, CO, GEPON

Procedia PDF Downloads 707
4681 Climate Change Effects of Vehicular Carbon Monoxide Emission from Road Transportation in Part of Minna Metropolis, Niger State, Nigeria

Authors: H. M. Liman, Y. M. Suleiman A. A. David

Abstract:

Poor air quality often considered one of the greatest environmental threats facing the world today is caused majorly by the emission of carbon monoxide into the atmosphere. The principal air pollutant is carbon monoxide. One prominent source of carbon monoxide emission is the transportation sector. Not much was known about the emission levels of carbon monoxide, the primary pollutant from the road transportation in the study area. Therefore, this study assessed the levels of carbon monoxide emission from road transportation in the Minna, Niger State. The database shows the carbon monoxide data collected. MSA Altair gas alert detector was used to take the carbon monoxide emission readings in Parts per Million for the peak and off-peak periods of vehicular movement at the road intersections. Their Global Positioning System (GPS) coordinates were recorded in the Universal Transverse Mercator (UTM). Bar chart graphs were plotted by using the emissions level of carbon dioxide as recorded on the field against the scientifically established internationally accepted safe limit of 8.7 Parts per Million of carbon monoxide in the atmosphere. Further statistical analysis was also carried out on the data recorded from the field using the Statistical Package for Social Sciences (SPSS) software and Microsoft excel to show the variance of the emission levels of each of the parameters in the study area. The results established that emissions’ level of atmospheric carbon monoxide from the road transportation in the study area exceeded the internationally accepted safe limits of 8.7 parts per million. In addition, the variations in the average emission levels of CO between the four parameters showed that morning peak is having the highest average emission level of 24.5PPM followed by evening peak with 22.84PPM while morning off peak is having 15.33 and the least is evening off peak 12.94PPM. Based on these results, recommendations made for poor air quality mitigation via carbon monoxide emissions reduction from transportation include Introduction of the urban mass transit would definitely reduce the number of traffic on the roads, hence the emissions from several vehicles that would have been on the road. This would also be a cheaper means of transportation for the masses and Encouraging the use of vehicles using alternative sources of energy like solar, electric and biofuel will also result in less emission levels as the these alternative energy sources other than fossil fuel originated diesel and petrol vehicles do not emit especially carbon monoxide.

Keywords: carbon monoxide, climate change emissions, road transportation, vehicular

Procedia PDF Downloads 375
4680 Internet of Things: Route Search Optimization Applying Ant Colony Algorithm and Theory of Computer Science

Authors: Tushar Bhardwaj

Abstract:

Internet of Things (IoT) possesses a dynamic network where the network nodes (mobile devices) are added and removed constantly and randomly, hence the traffic distribution in the network is quite variable and irregular. The basic but very important part in any network is route searching. We have many conventional route searching algorithms like link-state, and distance vector algorithms but they are restricted to the static point to point network topology. In this paper we propose a model that uses the Ant Colony Algorithm for route searching. It is dynamic in nature and has positive feedback mechanism that conforms to the route searching. We have also embedded the concept of Non-Deterministic Finite Automata [NDFA] minimization to reduce the network to increase the performance. Results show that Ant Colony Algorithm gives the shortest path from the source to destination node and NDFA minimization reduces the broadcasting storm effectively.

Keywords: routing, ant colony algorithm, NDFA, IoT

Procedia PDF Downloads 444
4679 Impact of Series Reactive Compensation on Increasing a Distribution Network Distributed Generation Hosting Capacity

Authors: Moataz Ammar, Ahdab Elmorshedy

Abstract:

The distributed generation hosting capacity of a distribution network is typically limited at a given connection point by the upper voltage limit that can be violated due to the injection of active power into the distribution network. The upper voltage limit violation concern becomes more important as the network equivalent resistance increases with respect to its equivalent reactance. This paper investigates the impact of modifying the distribution network equivalent reactance at the point of connection such that the upper voltage limit is violated at a higher distributed generation penetration, than it would without the addition of series reactive compensation. The results show that series reactive compensation proves efficient in certain situations (based on the ratio of equivalent network reactance to equivalent network resistance at the point of connection). As opposed to the conventional case of capacitive compensation of a distribution network to reduce voltage drop, inductive compensation is seen to be more appropriate for alleviation of distributed-generation-induced voltage rise.

Keywords: distributed generation, distribution networks, series compensation, voltage rise

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4678 Securing Mobile Ad-Hoc Network Utilizing OPNET Simulator

Authors: Tariq A. El Shheibia, Halima Mohamed Belhamad

Abstract:

This paper is considered securing data based on multi-path protocol (SDMP) in mobile ad hoc network utilizing OPNET simulator modular 14.5, including the AODV routing protocol at the network as based multi-path algorithm for message security in MANETs. The main idea of this work is to present a way that is able to detect the attacker inside the MANETs. The detection for this attacker will be performed by adding some effective parameters to the network.

Keywords: MANET, AODV, malicious node, OPNET

Procedia PDF Downloads 295
4677 A Study on Using Network Coding for Packet Transmissions in Wireless Sensor Networks

Authors: Rei-Heng Cheng, Wen-Pinn Fang

Abstract:

A wireless sensor network (WSN) is composed by a large number of sensors and one or a few base stations, where the sensor is responsible for detecting specific event information, which is sent back to the base station(s). However, how to save electricity consumption to extend the network lifetime is a problem that cannot be ignored in the wireless sensor networks. Since the sensor network is used to monitor a region or specific events, how the information can be reliably sent back to the base station is surly important. Network coding technique is often used to enhance the reliability of the network transmission. When a node needs to send out M data packets, it encodes these data with redundant data and sends out totally M + R packets. If the receiver can get any M packets out from these M + R packets, it can decode and get the original M data packets. To transmit redundant packets will certainly result in the excess energy consumption. This paper will explore relationship between the quality of wireless transmission and the number of redundant packets. Hopefully, each sensor can overhear the nearby transmissions, learn the wireless transmission quality around it, and dynamically determine the number of redundant packets used in network coding.

Keywords: energy consumption, network coding, transmission reliability, wireless sensor networks

Procedia PDF Downloads 391
4676 Factors of Social Network Platform Usage and Privacy Risk: A Unified Theory of Acceptance and Use of Technology2 Model

Authors: Wang Xue, Fan Liwei

Abstract:

The trust and use of social network platforms by users are instrumental factors that contribute to the platform’s sustainable development. Studying the influential factors of the use of social network platforms is beneficial for developing and maintaining a large user base. This study constructed an extended unified theory of acceptance and use of technology (UTAUT2) moderating model with perceived privacy risks to analyze the factors affecting the trust and use of social network platforms. 444 participants completed our 35 surveys, and we verified the survey results by structural equation model. Empirical results reveal the influencing factors that affect the trust and use of social network platforms, and the extended UTAUT2 model with perceived privacy risks increases the applicability of UTAUT2 in social network scenarios. Social networking platforms can increase their use rate by increasing the economics, functionality, entertainment, and privacy security of the platform.

Keywords: perceived privacy risk, social network, trust, use, UTAUT2 model

Procedia PDF Downloads 99
4675 Assessing Artificial Neural Network Models on Forecasting the Return of Stock Market Index

Authors: Hamid Rostami Jaz, Kamran Ameri Siahooei

Abstract:

Up to now different methods have been used to forecast the index returns and the index rate. Artificial intelligence and artificial neural networks have been one of the methods of index returns forecasting. This study attempts to carry out a comparative study on the performance of different Radial Base Neural Network and Feed-Forward Perceptron Neural Network to forecast investment returns on the index. To achieve this goal, the return on investment in Tehran Stock Exchange index is evaluated and the performance of Radial Base Neural Network and Feed-Forward Perceptron Neural Network are compared. Neural networks performance test is applied based on the least square error in two approaches of in-sample and out-of-sample. The research results show the superiority of the radial base neural network in the in-sample approach and the superiority of perceptron neural network in the out-of-sample approach.

Keywords: exchange index, forecasting, perceptron neural network, Tehran stock exchange

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4674 Mapping Network Connection of Personality Traits and Psychiatric Symptoms in Chinese Adolescents

Authors: Yichao Lv, Minmin Cai, Yanqiang Tao, Xinyuan Zou, Chao Zhang, Xiangping Liu

Abstract:

Objective: This study aims to explore the network structure of personality traits and mental health and identify key factors for effective intervention strategies. Methods: All participants (N = 6,067; 3,368 females) underwent the Eysenck Personality Scale (EPQ) to measure personality traits and the Symptom Self-rating Scale (SCL-90) to measure psychiatric symptoms. Using the mean value of the SCL-90 total score plus one standard deviation as the cutoff, 854 participants (14.08%; 528 females) were categorized as individuals exhibiting potential psychological symptoms and were included in the follow-up network analysis. The structure and bridge centrality of the network for dimensions of EPQ and SCL-90 were estimated. Results: Between the EPQ and SCL-90, psychoticism (P), extraversion (E), and neuroticism (N) showed the strongest positive correlations with somatization (Som), interpersonal sensitivity (IS), and hostility (Hos), respectively. Extraversion (E), somatization (Som), and anxiety (Anx) were identified as the most important bridge factors influencing the overall network. Conclusions: This study explored the network structure and complex connections between mental health and personality traits from a network perspective, providing potential targets for intervening in adolescent personality traits and mental health.

Keywords: EPQ, SCL-90, Chinese adolescents, network analysis

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4673 NSBS: Design of a Network Storage Backup System

Authors: Xinyan Zhang, Zhipeng Tan, Shan Fan

Abstract:

The first layer of defense against data loss is the backup data. This paper implements an agent-based network backup system used the backup, server-storage and server-backup agent these tripartite construction, and we realize the snapshot and hierarchical index in the NSBS. It realizes the control command and data flow separation, balances the system load, thereby improving the efficiency of the system backup and recovery. The test results show the agent-based network backup system can effectively improve the task-based concurrency, reasonably allocate network bandwidth, the system backup performance loss costs smaller and improves data recovery efficiency by 20%.

Keywords: agent, network backup system, three architecture model, NSBS

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4672 Intelligent Grading System of Apple Using Neural Network Arbitration

Authors: Ebenezer Obaloluwa Olaniyi

Abstract:

In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

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4671 Suggestion for Malware Detection Agent Considering Network Environment

Authors: Ji-Hoon Hong, Dong-Hee Kim, Nam-Uk Kim, Tai-Myoung Chung

Abstract:

Smartphone users are increasing rapidly. Accordingly, many companies are running BYOD (Bring Your Own Device: Policies to bring private-smartphones to the company) policy to increase work efficiency. However, smartphones are always under the threat of malware, thus the company network that is connected smartphone is exposed to serious risks. Most smartphone malware detection techniques are to perform an independent detection (perform the detection of a single target application). In this paper, we analyzed a variety of intrusion detection techniques. Based on the results of analysis propose an agent using the network IDS.

Keywords: android malware detection, software-defined network, interaction environment, android malware detection, software-defined network, interaction environment

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4670 Reliability Improvement of Power System Networks Using Adaptive Genetic Algorithm

Authors: Alireza Alesaadi

Abstract:

Reliability analysis is a powerful method for determining the weak points of the electrical networks. In designing of electrical network, it is tried to design the most reliable network with minimal system shutting down, but it is usually associated with increasing the cost. In this paper, using adaptive genetic algorithm, a method was presented that provides the most reliable system with a certain economical cost. Finally, the proposed method is applied to a sample network and results will be analyzed.

Keywords: reliability, adaptive genetic algorithm, electrical network, communication engineering

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4669 GIS-Based Topographical Network for Minimum “Exertion” Routing

Authors: Katherine Carl Payne, Moshe Dror

Abstract:

The problem of minimum cost routing has been extensively explored in a variety of contexts. While there is a prevalence of routing applications based on least distance, time, and related attributes, exertion-based routing has remained relatively unexplored. In particular, the network structures traditionally used to construct minimum cost paths are not suited to representing exertion or finding paths of least exertion based on road gradient. In this paper, we introduce a topographical network or “topograph” that enables minimum cost routing based on the exertion metric on each arc in a given road network as it is related to changes in road gradient. We describe an algorithm for topograph construction and present the implementation of the topograph on a road network of the state of California with ~22 million nodes.

Keywords: topograph, RPE, routing, GIS

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4668 Design an Intelligent Fire Detection System Based on Neural Network and Particle Swarm Optimization

Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

Abstract:

In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

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4667 Network Word Discovery Framework Based on Sentence Semantic Vector Similarity

Authors: Ganfeng Yu, Yuefeng Ma, Shanliang Yang

Abstract:

The word discovery is a key problem in text information retrieval technology. Methods in new word discovery tend to be closely related to words because they generally obtain new word results by analyzing words. With the popularity of social networks, individual netizens and online self-media have generated various network texts for the convenience of online life, including network words that are far from standard Chinese expression. How detect network words is one of the important goals in the field of text information retrieval today. In this paper, we integrate the word embedding model and clustering methods to propose a network word discovery framework based on sentence semantic similarity (S³-NWD) to detect network words effectively from the corpus. This framework constructs sentence semantic vectors through a distributed representation model, uses the similarity of sentence semantic vectors to determine the semantic relationship between sentences, and finally realizes network word discovery by the meaning of semantic replacement between sentences. The experiment verifies that the framework not only completes the rapid discovery of network words but also realizes the standard word meaning of the discovery of network words, which reflects the effectiveness of our work.

Keywords: text information retrieval, natural language processing, new word discovery, information extraction

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4666 Personal Exposure to Respirable Particles and Other Selected Gases among Cyclists near and Away from Busy Roads of Perth Metropolitan Area

Authors: Anu Shrestha, Krassi Rumchev, Ben Mullins, Yun Zhao, Linda Selvey

Abstract:

Cycling is often promoted as a means of reducing vehicular congestion, noise and greenhouse gas and air pollutant emissions in urban areas. It is also indorsed as a healthy means of transportation in terms of reducing the risk of developing a range of physical and psychological conditions. However, people who cycle regularly may not be aware that they can become exposed to high levels of Vehicular Air Pollutants (VAP) emitted by nearby traffics and therefore experience adverse health effects as a result. The study will highlight the present scenario of ambient air pollution level in different cycling routes in Perth and also highlight significant contribution to the understanding of health risks that cyclist may face from exposure to particulate air pollution. Methodology: This research was conducted in Perth, Western Austral and consisted of two groups of cyclists cycling near high (2 routes) and low (two routes) vehicular traffic roads, at high and low levels of exertion, during the cold and warm seasons. A sample size of 123 regular cyclists who cycled at least 80 km/week, aged 20-55, and non-smoker were selected for this study. There were altogether 100 male and 23 female who were asked to choose one or more routes among four different routes, and each participant cycled the route for warm or cold or both seasons. Cyclist who reported cardiovascular and other chronic health conditions (excluding asthma) were not invited into the study. Exposures to selected air pollutants were assessed by undertaking background and personal measurements alone with the measurement of heart and breathe rate of each participant. Finding: According to the preliminary study findings, the cyclists who used cycling route close to high traffic route were exposed to higher levels of measured air pollutants Nitrogen Oxide (NO₂) =0.12 ppm, sulfur dioxide (SO₂)=0.06 ppm and carbon monoxide (CO)=0.25 PPM compared to those who cycled away from busy roads. However, we measured high concentrations of particulate air pollution near one of the low traffic route which we associate with the close proximity to ferry station. Concluding Statement: As a conclusion, we recommend that cycling routes should be selected away from high traffic routes. If possible, we should also consider that if the cycling route is surrounded by the dense populated infrastructures, it can trap the pollutants and always facilitate in increasing inhalation of particle count among the cyclists.

Keywords: air pollution, carbon monoxide, cyclists' health, nitrogen dioxide, nitrogen oxide, respirable particulate matters

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4665 Optimization of Reliability and Communicability of a Random Two-Dimensional Point Patterns Using Delaunay Triangulation

Authors: Sopheak Sorn, Kwok Yip Szeto

Abstract:

Reliability is one of the important measures of how well the system meets its design objective, and mathematically is the probability that a complex system will perform satisfactorily. When the system is described by a network of N components (nodes) and their L connection (links), the reliability of the system becomes a network design problem that is an NP-hard combinatorial optimization problem. In this paper, we address the network design problem for a random point set’s pattern in two dimensions. We make use of a Voronoi construction with each cell containing exactly one point in the point pattern and compute the reliability of the Voronoi’s dual, i.e. the Delaunay graph. We further investigate the communicability of the Delaunay network. We find that there is a positive correlation and a negative correlation between the homogeneity of a Delaunay's degree distribution with its reliability and its communicability respectively. Based on the correlations, we alter the communicability and the reliability by performing random edge flips, which preserve the number of links and nodes in the network but can increase the communicability in a Delaunay network at the cost of its reliability. This transformation is later used to optimize a Delaunay network with the optimum geometric mean between communicability and reliability. We also discuss the importance of the edge flips in the evolution of real soap froth in two dimensions.

Keywords: Communicability, Delaunay triangulation, Edge Flip, Reliability, Two dimensional network, Voronio

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4664 A New Method to Reduce 5G Application Layer Payload Size

Authors: Gui Yang Wu, Bo Wang, Xin Wang

Abstract:

Nowadays, 5G service-based interface architecture uses text-based payload like JSON to transfer business data between network functions, which has obvious advantages as internet services but causes unnecessarily larger traffic. In this paper, a new 5G application payload size reduction method is presented to provides the mechanism to negotiate about new capability between network functions when network communication starts up and how 5G application data are reduced according to negotiated information with peer network function. Without losing the advantages of 5G text-based payload, this method demonstrates an excellent result on application payload size reduction and does not increase the usage quota of computing resource. Implementation of this method does not impact any standards or specifications and not change any encoding or decoding functionality too. In a real 5G network, this method will contribute to network efficiency and eventually save considerable computing resources.

Keywords: 5G, JSON, payload size, service-based interface

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4663 Thermal Network Model for a Large Scale AC Induction Motor

Authors: Sushil Kumar, M. Dakshina Murty

Abstract:

Thermal network modelling has proven to be important tool for thermal analysis of electrical machine. This article investigates numerical thermal network model and experimental performance of a large-scale AC motor. Experimental temperatures were measured using RTD in the stator which have been compared with the numerical data. Thermal network modelling fairly predicts the temperature of various components inside the large-scale AC motor. Results of stator winding temperature is compared with experimental results which are in close agreement with accuracy of 6-10%. This method of predicting hot spots within AC motors can be readily used by the motor designers for estimating the thermal hot spots of the machine.

Keywords: AC motor, thermal network, heat transfer, modelling

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4662 A Two-Step Framework for Unsupervised Speaker Segmentation Using BIC and Artificial Neural Network

Authors: Ahmad Alwosheel, Ahmed Alqaraawi

Abstract:

This work proposes a new speaker segmentation approach for two speakers. It is an online approach that does not require a prior information about speaker models. It has two phases, a conventional approach such as unsupervised BIC-based is utilized in the first phase to detect speaker changes and train a Neural Network, while in the second phase, the output trained parameters from the Neural Network are used to predict next incoming audio stream. Using this approach, a comparable accuracy to similar BIC-based approaches is achieved with a significant improvement in terms of computation time.

Keywords: artificial neural network, diarization, speaker indexing, speaker segmentation

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4661 Identification of Soft Faults in Branched Wire Networks by Distributed Reflectometry and Multi-Objective Genetic Algorithm

Authors: Soumaya Sallem, Marc Olivas

Abstract:

This contribution presents a method for detecting, locating, and characterizing soft faults in a complex wired network. The proposed method is based on multi-carrier reflectometry MCTDR (Multi-Carrier Time Domain Reflectometry) combined with a multi-objective genetic algorithm. In order to ensure complete network coverage and eliminate diagnosis ambiguities, the MCTDR test signal is injected at several points on the network, and the data is merged between different reflectometers (sensors) distributed on the network. An adapted multi-objective genetic algorithm is used to merge data in order to obtain more accurate faults location and characterization. The proposed method performances are evaluated from numerical and experimental results.

Keywords: wired network, reflectometry, network distributed diagnosis, multi-objective genetic algorithm

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4660 Implementation and Demonstration of Software-Defined Traffic Grooming

Authors: Lei Guo, Xu Zhang, Weigang Hou

Abstract:

Since the traditional network is closed and it has no architecture to create applications, it has been unable to evolve with changing demands under the rapid innovation in services. Additionally, due to the lack of the whole network profile, the quality of service cannot be well guaranteed in the traditional network. The Software Defined Network (SDN) utilizes global resources to support on-demand applications/services via open, standardized and programmable interfaces. In this paper, we implement the traffic grooming application under a real SDN environment, and the corresponding analysis is made. In our SDN: 1) we use OpenFlow protocol to control the entire network by using software applications running on the network operating system; 2) several virtual switches are combined into the data forwarding plane through Open vSwitch; 3) An OpenFlow controller, NOX, is involved as a logically centralized control plane that dynamically configures the data forwarding plane; 4) The traffic grooming based on SDN is demonstrated through dynamically modifying the idle time of flow entries. The experimental results demonstrate that the SDN-based traffic grooming effectively reduces the end-to-end delay, and the improvement ratio arrives to 99%.

Keywords: NOX, OpenFlow, Software Defined Network (SDN), traffic grooming

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4659 Impact of Network Workload between Virtualization Solutions on a Testbed Environment for Cybersecurity Learning

Authors: Kevin Fernagut, Olivier Flauzac, Erick M. G. Robledo, Florent Nolot

Abstract:

The adoption of modern lightweight virtualization often comes with new threats and network vulnerabilities. This paper seeks to assess this with a different approach studying the behavior of a testbed built with tools such as Kernel-Based Virtual Machine (KVM), Linux Containers (LXC) and Docker, by performing stress tests within a platform where students experiment simultaneously with cyber-attacks, and thus observe the impact on the campus network and also find the best solution for cyber-security learning. Interesting outcomes can be found in the literature comparing these technologies. It is, however, difficult to find results of the effects on the global network where experiments are carried out. Our work shows that other physical hosts and the faculty network were impacted while performing these trials. The problems found are discussed, as well as security solutions and the adoption of new network policies.

Keywords: containerization, containers, cybersecurity, cyberattacks, isolation, performance, virtualization, virtual machines

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4658 Minimizing Vehicular Traffic via Integrated Land Use Development: A Heuristic Optimization Approach

Authors: Babu Veeregowda, Rongfang Liu

Abstract:

The current traffic impact assessment methodology and environmental quality review process for approval of land development project are conventional, stagnant, and one-dimensional. The environmental review policy and procedure lacks in providing the direction to regulate or seek alternative land uses and sizes that exploits the existing or surrounding elements of built environment (‘4 D’s’ of development – Density, Diversity, Design, and Distance to Transit) or smart growth principles which influence the travel behavior and have a significant effect in reducing vehicular traffic. Additionally, environmental review policy does not give directions on how to incorporate urban planning into the development in ways such as incorporating non-motorized roadway elements such as sidewalks, bus shelters, and access to community facilities. This research developed a methodology to optimize the mix of land uses and sizes using the heuristic optimization process to minimize the auto dependency development and to meet the interests of key stakeholders. A case study of Willets Point Mixed Use Development in Queens, New York, was used to assess the benefits of the methodology. The approved Willets Point Mixed Use project was based on maximum envelop of size and land use type allowed by current conventional urban renewal plans. This paper will also evaluate the parking accumulation for various land uses to explore the potential for shared parking to further optimize the mix of land uses and sizes. This research is very timely and useful to many stakeholders interested in understanding the benefits of integrated land uses and its development.

Keywords: traffic impact, mixed use, optimization, trip generation

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4657 Reliable Multicast Communication in Next Generation Networks

Authors: Muazzam Ali Khan Khattak

Abstract:

Next Generation Network is combination of different networks having different technologies. Due to mobile nature of nodes the movement of nodes occurs from one network to another network. Multicasting in such networks is still a hot issue of research because the user in today's world wants reliable communication wherever it lies. Due to heterogeneity of NGN it is very difficult to handle reliable multicast communication. In this paper we proposed an improved scheme for reliable multicast communication in next generation networks. Because multicast communication is very important to deliver same data packets to multiple receivers and minimize the network traffic. This new scheme will make the multicast communication in NGN more reliable and efficient.

Keywords: next generation networks, route request, IPT, NACK, ARQ, DTN

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4656 Towards Security in Virtualization of SDN

Authors: Wanqing You, Kai Qian, Xi He, Ying Qian

Abstract:

In this paper, the potential security issues brought by the virtualization of a Software Defined Networks (SDN) would be analyzed. The virtualization of SDN is achieved by FlowVisor (FV). With FV, a physical network is divided into multiple isolated logical networks while the underlying resources are still shared by different slices (isolated logical networks). However, along with the benefits brought by network virtualization, it also presents some issues regarding security. By examining security issues existing in an OpenFlow network, which uses FlowVisor to slice it into multiple virtual networks, we hope we can get some significant results and also can get further discussions among the security of SDN virtualization.

Keywords: SDN, network, virtualization, security

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4655 A Review of Literature for Online Social Network Business Continuance Intention and the Hypotheses Thereof

Authors: Akwesi Assensoh-Kodua

Abstract:

Online Social Networks (OSN) has come and gone, yet the explosion of business activities on such platforms continuous to surge high, giving advantage to the bold entrepreneurs. It is therefore a practical requirement that practitioners and researchers understand the key determinants of costumers’ online social network business activities and continuance intention. An exploratory literature research to examine OSN continuous intention of business participants on OSN revealed that the practice of doing business on social network has come to stay and the following factors are the likely drivers for this new business model: perceived trust, perceived ease of use, confirmation, habit, social norm, perceived behavioural control, expected benefit, and satisfaction are the most probable factors that can lead to online social network (OSN) continuance intention.

Keywords: online social network, continuance intention, business continuance

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