Search results for: distributed workplaces
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2072

Search results for: distributed workplaces

2042 A Hybrid Distributed Algorithm for Solving Job Shop Scheduling Problem

Authors: Aydin Teymourifar, Gurkan Ozturk

Abstract:

In this paper, a distributed hybrid algorithm is proposed for solving the job shop scheduling problem. The suggested method executes different artificial neural networks, heuristics and meta-heuristics simultaneously on more than one machine. The neural networks are used to control the constraints of the problem while the meta-heuristics search the global space and the heuristics are used to prevent the premature convergence. To attain an efficient distributed intelligent method for solving big and distributed job shop scheduling problems, Apache Spark and Hadoop frameworks are used. In the algorithm implementation and design steps, new approaches are applied. Comparison between the proposed algorithm and other efficient algorithms from the literature shows its efficiency, which is able to solve large size problems in short time.

Keywords: distributed algorithms, Apache Spark, Hadoop, job shop scheduling, neural network

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2041 A New Distributed Computing Environment Based On Mobile Agents for Massively Parallel Applications

Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

Abstract:

In this paper, we propose a new distributed environment for High Performance Computing (HPC) based on mobile agents. It allows us to perform parallel programs execution as distributed one over a flexible grid constituted by a cooperative mobile agent team works. The distributed program to be performed is encapsulated on team leader agent which deploys its team workers as Agent Virtual Processing Unit (AVPU). Each AVPU is asked to perform its assigned tasks and provides the computational results which make the data and team works tasks management difficult for the team leader agent and that influence the performance computing. In this work we focused on the implementation of the Mobile Provider Agent (MPA) in order to manage the distribution of data and instructions and to ensure a load balancing model. It grants also some interesting mechanisms to manage the others computing challenges thanks to the mobile agents several skills.

Keywords: image processing, distributed environment, mobile agents, parallel and distributed computing

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2040 A Study on Exploring Employees' Well-Being in Gaming Workplaces Prior to and after the Chinese Government Crackdowns on Corruption

Authors: Ying Chuan Wang, Zhang Tao

Abstract:

The aim of this article intends to explore the differences of well-being of employees in casino hotels before and after the Chinese government began to fight corruption. This researcher also attempted to find out the relationship between work pressure and well-being of employees in gambling workplaces before and after the Chinese government crackdowns the corruption. The category of well-being including life well-being, workplace well-being, and psychological well-being was included for analyzing well-being of employees in gaming workplaces. In addition, the psychological pressure classification was applied into this study and the Job Content Questionnaire (JCQ) would be adopted on investigating employees’ work pressure in terms of decision latitude, psychological demands, and workplace support. This study is a quantitative approach research and was conducted in March 2017. A purposive sampling was used in this study. A total of valid 339 responses were collected and the participants were casino hotel employees. The findings showed that decision latitude was significantly different prior to and after Chinese government crackdowns on corruption. Moreover, workplace support was strongly significantly related to employees’ well-being before Chinese government crackdowns. Decision latitude was strongly significantly related to employees’ well-being after Chinese government crackdowns. The findings suggest that employees’ work pressure affects their well being. In particular, because of workplace supports, it may alleviate employees’ work pressure and affect their perceptions of well-being but only prior to fighting the crackdowns. Importantly, decision latitude has become an essential factor affecting their well-being after the crackdown. It is finally hoped that the findings of this study provide suggestion to the managerial levels of hospitality industries. It is important to enhance employees’ decision latitude. Offering training courses to equip employees’ skills could be a possible way to reduce work pressure. In addition, establishing career path for the employees to pursuit is essential for their self-development and the improvement of well being. This would be crucial for casino hotels’ sustainable development and strengthening their competitiveness.

Keywords: well-being, work pressure, Casino hotels’ employees, gaming workplace

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2039 Distributed System Computing Resource Scheduling Algorithm Based on Deep Reinforcement Learning

Authors: Yitao Lei, Xingxiang Zhai, Burra Venkata Durga Kumar

Abstract:

As the quantity and complexity of computing in large-scale software systems increase, distributed system computing becomes increasingly important. The distributed system realizes high-performance computing by collaboration between different computing resources. If there are no efficient resource scheduling resources, the abuse of distributed computing may cause resource waste and high costs. However, resource scheduling is usually an NP-hard problem, so we cannot find a general solution. However, some optimization algorithms exist like genetic algorithm, ant colony optimization, etc. The large scale of distributed systems makes this traditional optimization algorithm challenging to work with. Heuristic and machine learning algorithms are usually applied in this situation to ease the computing load. As a result, we do a review of traditional resource scheduling optimization algorithms and try to introduce a deep reinforcement learning method that utilizes the perceptual ability of neural networks and the decision-making ability of reinforcement learning. Using the machine learning method, we try to find important factors that influence the performance of distributed system computing and help the distributed system do an efficient computing resource scheduling. This paper surveys the application of deep reinforcement learning on distributed system computing resource scheduling proposes a deep reinforcement learning method that uses a recurrent neural network to optimize the resource scheduling, and proposes the challenges and improvement directions for DRL-based resource scheduling algorithms.

Keywords: resource scheduling, deep reinforcement learning, distributed system, artificial intelligence

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2038 Application of the Discrete Rationalized Haar Transform to Distributed Parameter System

Authors: Joon-Hoon Park

Abstract:

In this paper the rationalized Haar transform is applied for distributed parameter system identification and estimation. A distributed parameter system is a dynamical and mathematical model described by a partial differential equation. And system identification concerns the problem of determining mathematical models from observed data. The Haar function has some disadvantages of calculation because it contains irrational numbers, for these reasons the rationalized Haar function that has only rational numbers. The algorithm adopted in this paper is based on the transform and operational matrix of the rationalized Haar function. This approach provides more convenient and efficient computational results.

Keywords: distributed parameter system, rationalized Haar transform, operational matrix, system identification

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2037 Parallel Querying of Distributed Ontologies with Shared Vocabulary

Authors: Sharjeel Aslam, Vassil Vassilev, Karim Ouazzane

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Ontologies and various semantic repositories became a convenient approach for implementing model-driven architectures of distributed systems on the Web. SPARQL is the standard query language for querying such. However, although SPARQL is well-established standard for querying semantic repositories in RDF and OWL format and there are commonly used APIs which supports it, like Jena for Java, its parallel option is not incorporated in them. This article presents a complete framework consisting of an object algebra for parallel RDF and an index-based implementation of the parallel query engine capable of dealing with the distributed RDF ontologies which share common vocabulary. It has been implemented in Java, and for validation of the algorithms has been applied to the problem of organizing virtual exhibitions on the Web.

Keywords: distributed ontologies, parallel querying, semantic indexing, shared vocabulary, SPARQL

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2036 An Exploratory Analysis of Brisbane's Commuter Travel Patterns Using Smart Card Data

Authors: Ming Wei

Abstract:

Over the past two decades, Location Based Service (LBS) data have been increasingly applied to urban and transportation studies due to their comprehensiveness and consistency. However, compared to other LBS data including mobile phone data, GPS and social networking platforms, smart card data collected from public transport users have arguably yet to be fully exploited in urban systems analysis. By using five weekdays of passenger travel transaction data taken from go card – Southeast Queensland’s transit smart card – this paper analyses the spatiotemporal distribution of passenger movement with regard to the land use patterns in Brisbane. Work and residential places for public transport commuters were identified after extracting journeys-to-work patterns. Our results show that the locations of the workplaces identified from the go card data and residential suburbs are largely consistent with those that were marked in the land use map. However, the intensity for some residential locations in terms of population or commuter densities do not match well between the map and those derived from the go card data. This indicates that the misalignment between residential areas and workplaces to a certain extent, shedding light on how enhancements to service management and infrastructure expansion might be undertaken.

Keywords: big data, smart card data, travel pattern, land use

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2035 Optimal Planning of Dispatchable Distributed Generators for Power Loss Reduction in Unbalanced Distribution Networks

Authors: Mahmoud M. Othman, Y. G. Hegazy, A. Y. Abdelaziz

Abstract:

This paper proposes a novel heuristic algorithm that aims to determine the best size and location of distributed generators in unbalanced distribution networks. The proposed heuristic algorithm can deal with the planning cases where power loss is to be optimized without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power factor node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37 -node feeder. The results obtained show the effectiveness of the proposed algorithm.

Keywords: distributed generation, heuristic approach, optimization, planning

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2034 Merging of Results in Distributed Information Retrieval Systems

Authors: Larbi Guezouli, Imane Azzouz

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This work is located in the domain of distributed information retrieval ‘DIR’. A simplified view of the DIR requires a multi-search in a set of collections, which forces the system to analyze results found in these collections, and merge results back before sending them to the user in a single list. Our work is to find a fusion method based on the relevance score of each result received from collections and the relevance of the local search engine of each collection.

Keywords: information retrieval, distributed IR systems, merging results, datamining

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2033 Technical and Economic Environment in the Polish Power System as the Basis for Distributed Generation and Renewable Energy Sources Development

Authors: Pawel Sowa, Joachim Bargiel, Bogdan Mol, Katarzyna Luszcz

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The article raises the issue of the development of local renewable energy sources and the production of distributed energy in context of improving the reliability of the Polish Power System and the beneficial impact on local and national energy security. The paper refers to the current problems of local governments in the process of investment in the area of distributed energy projects, and discusses the issues of the future role and cooperation within the local power plants and distributed energy. Attention is paid to the local communities the chance to raise their own resources and management of energy fuels (biomass, wind, gas mining) and improving the local energy balance. The material presented takes the issue of the development of the energy potential of municipalities and future cooperation with professional energy. As an example, practical solutions used in one of the communes in Silesia.

Keywords: distributed generation, mini centers energy, renewable energy sources, reliability of supply of rural commune

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2032 Mentor and Mentee Based Learning

Authors: Erhan Eroğlu

Abstract:

This paper presents a new method called Mentor and Mentee Based Learning. This new method is becoming more and more common especially at workplaces. This study is significant as it clearly underlines how it works well. Education has always aimed at equipping people with the necessary knowledge and information. For many decades it went on teachers’ talk and chalk methods. In the second half of the nineteenth century educators felt the need for some changes in delivery systems. Some new terms like self- discovery, learner engagement, student centered learning, hands on learning have become more and more popular for such a long time. However, some educators believe that there is much room for better learning methods in many fields as they think the learners still cannot fulfill their potential capacities. Thus, new systems and methods are still being developed and applied at education centers and work places. One of the latest methods is assigning some mentors for the newly recruited employees and training them within a mentor and mentee program which allows both parties to see their strengths and weaknesses and the areas which can be improved. This paper aims at finding out the perceptions of the mentors and mentees on the programs they are offered at their workplaces and suggests some betterment alternatives. The study has been conducted via a qualitative method whereby some interviews have been done with both mentors and mentees separately and together. Results show that it is a great way to train inexperienced one and also to refresh the older ones. Some points to be improved have also been underlined. The paper shows that education is not a one way path to follow.

Keywords: learning, mentor, mentee, training

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2031 Screen Method of Distributed Cooperative Navigation Factors for Unmanned Aerial Vehicle Swarm

Authors: Can Zhang, Qun Li, Yonglin Lei, Zhi Zhu, Dong Guo

Abstract:

Aiming at the problem of factor screen in distributed collaborative navigation of dense UAV swarm, an efficient distributed collaborative navigation factor screen method is proposed. The method considered the balance between computing load and positioning accuracy. The proposed algorithm utilized the factor graph model to implement a distributed collaborative navigation algorithm. The GNSS information of the UAV itself and the ranging information between the UAVs are used as the positioning factors. In this distributed scheme, a local factor graph is established for each UAV. The positioning factors of nodes with good geometric position distribution and small variance are selected to participate in the navigation calculation. To demonstrate and verify the proposed methods, the simulation and experiments in different scenarios are performed in this research. Simulation results show that the proposed scheme achieves a good balance between the computing load and positioning accuracy in the distributed cooperative navigation calculation of UAV swarm. This proposed algorithm has important theoretical and practical value for both industry and academic areas.

Keywords: screen method, cooperative positioning system, UAV swarm, factor graph, cooperative navigation

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2030 Creating a Profound Sense of Comfort to Stimulate Workers Innovation and Productivity: Exploring Research and Case Study Applications

Authors: Rana Bazaid, Debajyoti Pati

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Purpose: The aim of this research is to explore and discuss innovative workspaces, and how the design of the space has the potential to facilitate the work process and employees’ satisfaction which can lead to innovative results. Background: The relationship between the workforce and the work environment has a strong potential to enhance human capabilities associated with innovation outcomes. The need for innovation in workplaces can benefit employees’ satisfaction, health, and performance. To understand this complicated relationship, this research explores and comprehends innovative work environments. Methods: A review of 26 peer-reviewed articles, seven books, and 23 companies’ websites was conducted, along with analysis for five case studies on successful types of research and development fields to detect appropriate examples for the study. Results: The analysis of the five case studies showed the similarity-characteristics of innovation work environments among those five fields and observed what is unique about each field that makes them stand out in their industries. Conclusion: Understanding the psychological, cultural, physiological, and social needs of workers, physical workplaces, and issues found in the work environment may help enhance multifaceted innovation and productivity.

Keywords: innovation, productivity , work environment, workers satisfaction

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2029 MULTI-FLGANs: Multi-Distributed Adversarial Networks for Non-Independent and Identically Distributed Distribution

Authors: Akash Amalan, Rui Wang, Yanqi Qiao, Emmanouil Panaousis, Kaitai Liang

Abstract:

Federated learning is an emerging concept in the domain of distributed machine learning. This concept has enabled General Adversarial Networks (GANs) to benefit from the rich distributed training data while preserving privacy. However, in a non-IID setting, current federated GAN architectures are unstable, struggling to learn the distinct features, and vulnerable to mode collapse. In this paper, we propose an architecture MULTI-FLGAN to solve the problem of low-quality images, mode collapse, and instability for non-IID datasets. Our results show that MULTI-FLGAN is four times as stable and performant (i.e., high inception score) on average over 20 clients compared to baseline FLGAN.

Keywords: federated learning, generative adversarial network, inference attack, non-IID data distribution

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2028 ROOP: Translating Sequential Code Fragments to Distributed Code Fragments Using Deep Reinforcement Learning

Authors: Arun Sanjel, Greg Speegle

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Every second, massive amounts of data are generated, and Data Intensive Scalable Computing (DISC) frameworks have evolved into effective tools for analyzing such massive amounts of data. Since the underlying architecture of these distributed computing platforms is often new to users, building a DISC application can often be time-consuming and prone to errors. The automated conversion of a sequential program to a DISC program will consequently significantly improve productivity. However, synthesizing a user’s intended program from an input specification is complex, with several important applications, such as distributed program synthesizing and code refactoring. Existing works such as Tyro and Casper rely entirely on deductive synthesis techniques or similar program synthesis approaches. Our approach is to develop a data-driven synthesis technique to identify sequential components and translate them to equivalent distributed operations. We emphasize using reinforcement learning and unit testing as feedback mechanisms to achieve our objectives.

Keywords: program synthesis, distributed computing, reinforcement learning, unit testing, DISC

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2027 Ergonomics: Solutions for the Prevention of Injuries

Authors: Muhamad Ammar Bin Mohd Asri, Muhammad Hamizan Bin Yusof, Muhammad Haziq Bin Abdul Khalil, Esman Hanief Bin Khairul Anuar, Muhammad Fikri Bin Ishak, Amril Azim Bin Mohd Norrahim, Muhammad Danial Fakhri Bin Fakhruddin, Muhammad Khairul Nizam in Hosnodin, Muhammad Ezzat Hariz Bin Norhisam

Abstract:

Ergonomics is the science of creating and arranging workplaces, products, and systems to increase human performance, comfort, and safety. This study researched ergonomics as a solution for preventing workplace injuries, specifically musculoskeletal disorders, among employers and employees. The method will be used in this project is a literature review which means conducting a study about ergonomics with peer-reviewed journal articles and books. It focuses on employees and employers who are in one company on other departments under the protection of Occupational Safety and Health (OSHA). These solutions include ergonomic assessments, workplace design improvements, effective training and education, and the use of ergonomic tools and equipment. Employers can build workplaces that are safer and more productive by putting these solutions in place, and employees can work comfortably and prevent accidents from bad ergonomics. Overall, the paper highlights how crucial it is to take injury prevention measures and consider ergonomics at work.

Keywords: occupational safety and health, musculoskeletal disorders, ergonomic, ergonomic risk

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2026 The Impacts of Local Decision Making on Customisation Process Speed across Distributed Boundaries

Authors: Abdulrahman M. Qahtani, Gary. B. Wills, Andy. M. Gravell

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Communicating and managing customers’ requirements in software development projects play a vital role in the software development process. While it is difficult to do so locally, it is even more difficult to communicate these requirements over distributed boundaries and to convey them to multiple distribution customers. This paper discusses the communication of multiple distribution customers’ requirements in the context of customised software products. The main purpose is to understand the challenges of communicating and managing customisation requirements across distributed boundaries. We propose a model for Communicating Customisation Requirements of Multi-Clients in a Distributed Domain (CCRD). Thereafter, we evaluate that model by presenting the findings of a case study conducted with a company with customisation projects for 18 distributed customers. Then, we compare the outputs of the real case process and the outputs of the CCRD model using simulation methods. Our conjecture is that the CCRD model can reduce the challenge of communication requirements over distributed organisational boundaries, and the delay in decision making and in the entire customisation process time.

Keywords: customisation software products, global software engineering, local decision making, requirement engineering, simulation model

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2025 Distribution Network Optimization by Optimal Placement of Photovoltaic-Based Distributed Generation: A Case Study of the Nigerian Power System

Authors: Edafe Lucky Okotie, Emmanuel Osawaru Omosigho

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This paper examines the impacts of the introduction of distributed energy generation (DEG) technology into the Nigerian power system as an alternative means of energy generation at distribution ends using Otovwodo 15 MVA, 33/11kV injection substation as a case study. The overall idea is to increase the generated energy in the system, improve the voltage profile and reduce system losses. A photovoltaic-based distributed energy generator (PV-DEG) was considered and was optimally placed in the network using Genetic Algorithm (GA) in Mat. Lab/Simulink environment. The results of simulation obtained shows that the dynamic performance of the network was optimized with DEG-grid integration.

Keywords: distributed energy generation (DEG), genetic algorithm (GA), power quality, total load demand, voltage profile

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2024 The Impact of Distributed Epistemologies on Software Engineering

Authors: Thomas Smith

Abstract:

Many hackers worldwide would agree that, had it not been for linear-time theory, the refinement of Byzantine fault tolerance might never have occurred. After years of significant research into extreme programming, we validate the refinement of simulated annealing. Maw, our new framework for unstable theory, is the solution to all of these issues.

Keywords: distributed, software engineering, DNS, DHCP

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2023 Creating a Senior-Friendly Workplaces: With Respect to Empowerment

Authors: Liu Yi Hui, Lin Yu Fang, Chiu Fan Yun

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In preparation for the coming super-aged society in Taiwan, the Ministry of Labor announced the Middle-aged and Elderly Employment Promotion Act in 2019, dedicating a chapter to expressly prohibiting age discrimination. This study aimed to enhance understanding of workplace ageism by collecting data through in-depth interviews. The findings can be summarized as follows: 1. Elderly employment in Taiwan and its three underlying motivations: Mainly in economic, social, and psychological needs. Economically, elders opt to continue working beyond the traditional retirement age because of financial shocks, a lack of financial planning, and being the breadwinner of the family. Socially and psychologically, they continue working to have a more diversified retirement life and find a new purpose in life. 2. Ageism on the re-employment of elders: On the ground, senior workers may face the age-based stereotype that their work performance is inferior and a broader social environment that is ostensibly friendly but essentially hostile. 3. Possible ways to facilitate elderly employment in terms of empowerment: By developing and empowering seniors with new skills or abilities for re-employment and strengthening their problem-solving skills in the face of new things through training programs, we can not only build the confidence and substantial abilities of senior workers in the workplace but also flip the social stereotype about age.

Keywords: senior-friendly workplaces, elderly employment, empowerment, ageism

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2022 Distributed Multi-Agent Based Approach on Intelligent Transportation Network

Authors: Xiao Yihong, Yu Kexin, Burra Venkata Durga Kumar

Abstract:

With the accelerating process of urbanization, the problem of urban road congestion is becoming more and more serious. Intelligent transportation system combining distributed and artificial intelligence has become a research hotspot. As the core development direction of the intelligent transportation system, Cooperative Intelligent Transportation System (C-ITS) integrates advanced information technology and communication methods and realizes the integration of humans, vehicle, roadside infrastructure, and other elements through the multi-agent distributed system. By analyzing the system architecture and technical characteristics of C-ITS, the report proposes a distributed multi-agent C-ITS. The system consists of Roadside Sub-system, Vehicle Sub-system, and Personal Sub-system. At the same time, we explore the scalability of the C-ITS and put forward incorporating local rewards in the centralized training decentralized execution paradigm, hoping to add a scalable value decomposition method. In addition, we also suggest introducing blockchain to improve the safety of the traffic information transmission process. The system is expected to improve vehicle capacity and traffic safety.

Keywords: distributed system, artificial intelligence, multi-agent, cooperative intelligent transportation system

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2021 Implementation of Distributed Randomized Algorithms for Resilient Peer-to-Peer Networks

Authors: Richard Tanaka, Ying Zhu

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This paper studies a few randomized algorithms in application-layer peer-to-peer networks. The significant gain in scalability and resilience that peer-to-peer networks provide has made them widely used and adopted in many real-world distributed systems and applications. The unique properties of peer-to-peer networks make them particularly suitable for randomized algorithms such as random walks and gossip algorithms. Instead of simulations of peer-to-peer networks, we leverage the Docker virtual container technology to develop implementations of the peer-to-peer networks and these distributed randomized algorithms running on top of them. We can thus analyze their behaviour and performance in realistic settings. We further consider the problem of identifying high-risk bottleneck links in the network with the objective of improving the resilience and reliability of peer-to-peer networks. We propose a randomized algorithm to solve this problem and evaluate its performance by simulations.

Keywords: distributed randomized algorithms, peer-to-peer networks, virtual container technology, resilient networks

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2020 Sync Consensus Algorithm: Trying to Reach an Agreement at Full Speed

Authors: Yuri Zinchenko

Abstract:

Recently, distributed storage systems have been used more and more in various aspects of everyday life. They provide such necessary properties as Scalability, Fault Tolerance, Durability, and others. At the same time, not only reliable but also fast data storage remains one of the most pressing issues in this area. That brings us to the consensus algorithm as one of the most important components that has a great impact on the functionality of a distributed system. This paper is the result of an analysis of several well-known consensus algorithms, such as Paxos and Raft. The algorithm it offers, called Sync, promotes, but does not insist on simultaneous writing to the nodes (which positively affects the overall writing speed) and tries to minimize the system's inactive time. This allows nodes to reach agreement on the system state in a shorter period, which is a critical factor for distributed systems. Also when developing Sync, a lot of attention was paid to such criteria as simplicity and intuitiveness, the importance of which is difficult to overestimate.

Keywords: sync, consensus algorithm, distributed system, leader-based, synchronization.

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2019 DOS and DDOS Attacks

Authors: Amin Hamrahi, Niloofar Moghaddam

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Denial of Service is for denial-of-service attack, a type of attack on a network that is designed to bring the network to its knees by flooding it with useless traffic. Denial of Service (DoS) attacks have become a major threat to current computer networks. Many recent DoS attacks were launched via a large number of distributed attacking hosts in the Internet. These attacks are called distributed denial of service (DDoS) attacks. To have a better understanding on DoS attacks, this article provides an overview on existing DoS and DDoS attacks and major defense technologies in the Internet.

Keywords: denial of service, distributed denial of service, traffic, flooding

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2018 The Kindergarten as a Multicultural Workplace

Authors: Monika Haanpää

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Well-functioning workplaces are often characterized by good co-operation, adequate flow of information, open interaction between workers and a supportive work environment. The workplace is a mosaic of human personalities and the influx of people, who speak different languages and who are from different cultural backgrounds, may bring about new challenges and enrich this environment. However, this influx of people could also pose a problem as the adaptation of immigrant people to new terms of work may depend heavily on the level of language skills, the stage of culture shock, professional identity, and personality. Migration is not a rare phenomenon in Finland anymore; nobody is surprised to see people from different countries and different backgrounds in the schools, on the streets or in shops. However, this does not mean that immigration is an easy process for people coming from other countries. The experience of workers, with diverse language and backgrounds, has rarely been researched, particularly from the superior's point of view. In addition, the vast majority of researchers have paid more attention to multicultural kindergartens in terms of immigrant children and their families. Hence, there is a need to show the problem which exists in the recruitment of the increasing number of workers who come from different countries. Opinions about kindergartens, as multicultural workplaces, have been gathered through interviews with immigrant workers responsible for education. In addition, a questionnaire for native Finnish workers and superiors in kindergartens was carried out. The collected material has been analyzed qualitatively, focusing on topics such as: the kindergarten as a multicultural workplace, factors influencing career success of workers with diverse language and cultural backgrounds, the social relations in the multicultural workplaces and teachers’ changing professional identity. The results of the research provided a novel aspect of the multicultural workplace and emphasized a dependency of immigrant workers’ on language skills in Finnish; affecting professional success. In addition, they showed the good relations between other native Finnish co-workers and superiors. The results also illustrate why writing skills in Finnish are so important in kindergartens. Part of the investigation also questions some results of the research i.e. which is more important in the kindergarten as a multicultural workplace: personality, good professional skills or good language skills.

Keywords: kindergarten, multicultural workplace, social relations at work, work satisfaction

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2017 Model-Free Distributed Control of Dynamical Systems

Authors: Javad Khazaei, Rick Blum

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Distributed control is an efficient and flexible approach for coordination of multi-agent systems. One of the main challenges in designing a distributed controller is identifying the governing dynamics of the dynamical systems. Data-driven system identification is currently undergoing a revolution. With the availability of high-fidelity measurements and historical data, model-free identification of dynamical systems can facilitate the control design without tedious modeling of high-dimensional and/or nonlinear systems. This paper develops a distributed control design using consensus theory for linear and nonlinear dynamical systems using sparse identification of system dynamics. Compared with existing consensus designs that heavily rely on knowing the detailed system dynamics, the proposed model-free design can accurately capture the dynamics of the system with available measurements and input data and provide guaranteed performance in consensus and tracking problems. Heterogeneous damped oscillators are chosen as examples of dynamical system for validation purposes.

Keywords: consensus tracking, distributed control, model-free control, sparse identification of dynamical systems

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2016 Considering the Reliability of Measurements Issue in Distributed Adaptive Estimation Algorithms

Authors: Wael M. Bazzi, Amir Rastegarnia, Azam Khalili

Abstract:

In this paper we consider the issue of reliability of measurements in distributed adaptive estimation problem. To this aim, we assume a sensor network with different observation noise variance among the sensors and propose new estimation method based on incremental distributed least mean-square (IDLMS) algorithm. The proposed method contains two phases: I) Estimation of each sensors observation noise variance, and II) Estimation of the desired parameter using the estimated observation variances. To deal with the reliability of measurements, in the second phase of the proposed algorithm, the step-size parameter is adjusted for each sensor according to its observation noise variance. As our simulation results show, the proposed algorithm considerably improves the performance of the IDLMS algorithm in the same condition.

Keywords: adaptive filter, distributed estimation, sensor network, IDLMS algorithm

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2015 Changes in When and Where People Are Spending Time in Response to COVID-19

Authors: Nicholas Reinicke, Brennan Borlaug, Matthew Moniot

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The COVID-19 pandemic has resulted in a significant change in driving behavior as people respond to the new environment. However, existing methods for analyzing driver behavior, such as travel surveys and travel demand models, are not suited for incorporating abrupt environmental disruptions. To address this, we analyze a set of high-resolution trip data and introduce two new metrics for quantifying driving behavioral shifts as a function of time, allowing us to compare the time periods before and after the pandemic began. We apply these metrics to the Denver, Colorado metropolitan statistical area (MSA) to demonstrate the utility of the metrics. Then, we present a case study for comparing two distinct MSAs, Louisville, Kentucky, and Des Moines, Iowa, which exhibit significant differences in the makeup of their labor markets. The results indicate that although the regions of study exhibit certain unique driving behavioral shifts, emerging trends can be seen when comparing between seemingly distinct regions. For instance, drivers in all three MSAs are generally shown to have spent more time at residential locations and less time in workplaces in the time period after the pandemic started. In addition, workplaces that may be incompatible with remote working, such as hospitals and certain retail locations, generally retained much of their pre-pandemic travel activity.

Keywords: COVID-19, driver behavior, GPS data, signal analysis, telework

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2014 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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2013 Analysis of Importance of Culture in Distributed Design Based on the Case Study at the University of Strathclyde

Authors: Zixuan Yang

Abstract:

This paper presents an analysis of the necessary consideration culture in distributed design through a thorough literature review and case study. The literature review has identified that the need for understanding cultural differences in product design and user evaluations is highlighted by analyzing cross-cultural influences; culture plays a significant role in distributed work, particularly in establishing team cohesion, trust, and credibility early in the project. By applying approaches of Geert Hofstede's dimensions and Fukuyama's trust analysis, a case study of a global design project, i.e., multicultural distributed teamwork solving the problem in terms of reducing the risk of deep vein thrombosis, showcases cultural dynamics, emphasizing trust-building and decision-making. The lessons learned emphasized the importance of cultural awareness, adaptability, and the utilization of scientific theories to enable effective cross-cultural collaborations in global design, providing valuable insights into navigating cultural diversity within design practices.

Keywords: culture, distributed design, global design, Geert Hofstede's dimensions, Fukuyama's trust analysis

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