Trajectory Reconstruction and Mobility Pattern Analysis Based on Call Detail Record Data

Tehnoloogiad, mis kasutavad geograafilisi andmeid, on muutunud meie igapäevaelu tähtsaks osaks. Tänu sellele on kasvanud asukoha andmetemassiliine salvestamine ja kaevandamine. Seni on GPS tehnoloogiad olnud põhiliseks geograafiliste andmete kogumismeetodiks. Sellega paralleelselt on populaarsust kogunud mobiiliandmete kasutamine positsiooni tuvastamiseks ja liikumismustrite analüüsimiseks. Mobiiliandmete (CDR) põhjal trajektooride taastamiseks on vajalik meetodite kohendamine selleks, et tulemused oleksid korrektsed. Tänu sellele, et telekommunikatsiooni ettevõtted on alustanud suuremat koostööd ja hakanud CDR-andmeid järjest rohkem avalikustama, on mobiiliandmete kasutamine mitmetel aladel suurenenud. Töödeldud mobiiliandmed aitavad anda ülevaadet rahvastiku liikumisest erinevates ulatustes. Samal ajal on trajektooride taastamine CDR-andmetest kohati raskendatud võrreldes GPS-andmetega. Suurimaks probleemiks on algus- ja lõpp-positsioonide asukoha määramine, mis on veelgi enam raskendatud juhul kui objekt liigub.Selle lõputöö eesmärgiks on trajektooride taastamine anonüümsete kasutajatepoolt genereeritud CDR-andmete põhjal. Tulemuste valideerimine GPS-andmetega, mis on loodud paralleelselt mobiiliandmetega ning on vajalik selleks, et määrata saadud trajektooride täpsust. Loodud trajektoore saab kasutada objektide, sealhulgas ka inimeste, liikumismustrite analüüsimiseks ja rahvastiku paiknemise tuvastamiseks, mis aitab linnade planeerimisel ja infrastruktuuride optimeerimisel. Lõputöö väljunditeks on trajektooride taastamine ja täpsuse analüüsimine, lisaks sellele inimese liikumismudelite tuvastamine ja tihedamini külastatavate asukohtade identifitseerimine nagu näiteks kodu, töökoht ja poed.Up until now, GPS data has been greatly used for collecting highlyprecise locational data from moving objects including humans. In contrast, mobile phone data is becoming more and more popular in the last few years. The usage of mobile phone data, that is also known as CDR data, has many benefits over the widely used GPS. This means that the methods used for example in GPS trajectory reconstruction, need to have modifications made be compatible with CDR data.The fact that telecommunication companies have started to cooperate moreand share the CDR data with the public is also a boost to the usage of CDRdata. The processed and analyzed CDR data can be used to get an overview ofcrowd movement in different scales, for example traveling inside a city as opposed to between countries. Extracting trajectories from CDR data has numerous complications.This is due to the fact that the data might not be continuous anddiscovering of the starting point of the object in motion is complicated.The goal of this thesis is to use CDR data in the reconstruction of trajectoriesmade by an anonymous user and to validate the results with GPS data generated in parallel to the CDR data. Reconstructed trajectories can be used for movement analysis and population displacement and would help city planning by optimizing the infrastructures.Outcomes of this thesis are the reconstructed trajectories based on CDR dataand the precisions of final paths. Also, the frequency of CDR events is analyzedin addition to distance distribution. After that the areas that the user visits most frequently are extracted, such as home and work locations

STOCHASTIC MODELING AND TIME-TO-EVENT ANALYSIS OF VOIP TRAFFIC

Voice over IP (VoIP) systems are gaining increased popularity due to the cost effectiveness, ease of management, and enhanced features and capabilities. Both enterprises and carriers are deploying VoIP systems to replace their TDM-based legacy voice networks. However, the lack of engineering models for VoIP systems has been realized by many researchers, especially for large-scale networks. The purpose of traffic engineering is to minimize call blocking probability and maximize resource utilization. The current traffic engineering models are inherited from the legacy PSTN world, and these models fall short from capturing the characteristics of new traffic patterns. The objective of this research is to develop a traffic engineering model for modern VoIP networks. We studied the traffic on a large-scale VoIP network and collected several billions of call information. Our analysis shows that the traditional traffic engineering approach based on the Poisson call arrival process and exponential holding time fails to capture the modern telecommunication systems accurately. We developed a new framework for modeling call arrivals as a non-homogeneous Poisson process, and we further enhanced the model by providing a Gaussian approximation for the cases of heavy traffic condition on large-scale networks. In the second phase of the research, we followed a new time-to-event survival analysis approach to model call holding time as a generalized gamma distribution and we introduced a Call Cease Rate function to model the call durations. The modeling and statistical work of the Call Arrival model and the Call Holding Time model is constructed, verified and validated using hundreds of millions of real call information collected from an operational VoIP carrier network. The traffic data is a mixture of residential, business, and wireless traffic. Therefore, our proposed models can be applied to any modern telecommunication system. We also conducted sensitivity analysis of model parameters and performed statistical tests on the robustness of the models’ assumptions. We implemented the models in a new simulation-based traffic engineering system called VoIP Traffic Engineering Simulator (VSIM). Advanced statistical and stochastic techniques were used in building VSIM system. The core of VSIM is a simulation system that consists of two different simulation engines: the NHPP parametric simulation engine and the non-parametric simulation engine. In addition, VSIM provides several subsystems for traffic data collection, processing, statistical modeling, model parameter estimation, graph generation, and traffic prediction. VSIM is capable of extracting traffic data from a live VoIP network, processing and storing the extracted information, and then feeding it into one of the simulation engines which in turn provides resource optimization and quality of service reports

Técnicas de previsão em sistemas de informação e comunicação: aplicação às redes móveis celulares

The rapid proliferation of information and communication technologies around the world has increased the need for careful planning of infrastructures. This is true in the situation like mobile telecommunication networks, data centers, web servers, etc. By developing and implementing intelligent solutions to improve the measurement and planning, telecommunication service operators can anticipate problems and minimize cost. This dissertation focuses on forecasting mobile telecommunication capacity networks to maximize existing resources and avoid problems related to performance or capacity, such as bottlenecks and latencies. In the case of mobile telecommunication networks, the data forecast can be used to predict traffic growth, contributing to better network planning. Therefore, a poorly designed forecast may lead to mobile network operators not being prepared for possible network problems, such as reaching the limit of an RNC, which may become expensive in terms of OPEX. Thus, it is fundamental to study different quantitative methods to forecast the trend and the volume of traffic in the RNCs. This paper analyzes some basic forecast methods used in scenarios where the data do not present behavioral complexity and some models such as ARIMA and Holt Winters used in data with behavioral complexity (presence of trend and seasonality). It also evaluates the accuracy of the forecasts determined from the application of these models.A rápida proliferação de tecnologias de informação e comunicação em todo o mundo aumentou a necessidade de um planeamento cuidadoso das infraestruturas. Este facto também é verdade em redes de telecomunicações móveis, data centers, servidores web, etc. Ao desenvolver e implementar soluções inteligentes para melhorar o dimensionamento e planeamento, os operadores de serviços de telecomunicações podem antecipar problemas e minimizar custos. Esta dissertação foca-se na previsão de capacidade de redes de telecomunicações móveis de forma a maximizar recursos existentes e evitar problemas relacionados ao desempenho ou capacidade, como “bottlenecks” e latências. No caso das redes de telecomunicações móveis, a previsão de dados pode ser aplicada para prever o crescimento de tráfego, contribuindo para um melhor planeamento da rede. Portanto, uma previsão mal projetada pode levar os operadores de redes móveis a não estarem preparados para possíveis problemas de rede, como alcance do limite de capacidade de um RNC, isto pode se tornar muito caro em termos de OPEX. Assim, é fundamental estudar diferentes métodos quantitativos para prever a tendência e o volume de tráfego nos RNCs. Neste trabalho são analisados alguns métodos básicos de previsão utilizados em cenários em que os dados não apresentam complexidade comportamental e alguns modelos como ARIMA e Holt Winters utilizados em dados com complexidade comportamental (presença de tendência e sazonalidade). Também se avalia a exatidão das previsões que resultam da aplicação destes modelos.Mestrado em Engenharia Informátic

Mobiiliverkkodatan käytön validointi lähtö-määränpää -matriisien luomisessa

The rapid development in telecommunication networks during last years has made it possible to study human travel behaviour effectively from mobile network data. The combination of passive and active signalling events gathered by mobile network operators allow analysing movements of people with full longitudinal and spatial coverage. Therefore, recent years have seen an increasing interest in utilizing mobile network data in transportation studies, as an alternative or a complementary data source for conventional transport data. This study validates the capability of mobile network data to produce long-distance origin-destination matrices in Finland. Features that are being validated include trip counts, seasonal trip count changes and modal split. As reference data sources of the study, the National Travel Survey 2016, HELMET-transport demand model (Transport model by HSL) and LAM-data (automated traffic census) are used. Validation is done by analysing correlations between mobile network data and the reference data sources. By being able to demonstrate the validity and reliability of mobile network data usage in producing origin-destination matrices, cost-effectiveness and more accurate methods to gather information from long-distance transportation can be provided for the field in general. The overall results of the study are in line with the few similar related studies that have been conducted. The thesis work suggests that mobile network data is capable of producing more reliable trip counts from sparsely populated areas than the National Travel Survey. In addition, it seems to be more capable of capturing the high summer peak in longdistance travelling in Finland. The results regarding modal split are promising, but more studies regarding the modal detection will be needed.Matkapuhelinverkkojen viime vuosien nopea kehitys on mahdollistanut yhä tarkemman matkapuhelinten solupaikannuksen. Teleoperaattoreiden keräämä passiivisten ja aktiivisten matkapuhelinverkon signaalihavaintojen yhdistelmä mahdollistaa ihmisten liikkumiskäyttäytymisen tutkimisen kattavasti sekä ajallisesti että alueellisesti. Viime aikoina matkapuhelinverkkodatan hyödyntäminen liikennetutkimuksissa on tästä syystä herättänyt kasvavaa kiinnostusta perinteisten tiedonkeruumenetelmien korvaajana ja täydentäjänä. Tämä tutkimus validoi mobiiliverkkodatan käyttöä lähtö-määränpää -matriisien luomisessa Suomen pitkän matkan liikenteessä. Validoitavia ominaisuuksia ovat matkamäärät, matkamäärien vuodenajoittainen vaihtelu ja matkojen kulkumuotojakauma. Referenssiaineistona työssä käytetään Suomen Henkilöliikennetutkimusta, HELMET-liikennemallia ja LAM-dataa. Validointi suoritetaan analysoimalla mobiiliverkkodatan ja referenssiaineistojen välisiä korrelaatioita. Osoittamalla mobiiliverkkodatan käytettävyys lähtö-määränpää matriisien luomisessa, liikennesuunnittelun kustannustehokkuutta ja keinoja tarkemman tiedon keräämiseen pitkämatkaisesta liikkumisesta voidaan edistää. Työn tulokset ovat linjassa aiemman tutkimuksen kanssa. Tulokset näyttävät mobiiliverkkodatan olevan kykenevä tuottamaan lähtö-määränpää -tietoa hajaasutusalueilta luotettavammin kuin Henkilöliikennetutkimus. Lisäksi, mobiiliverkkodata näyttää pystyvän observoimaan kesän lomakauden matkapiikin tarkemmin kuin Henkilöliikennetutkimus. Tulokset mobiiliverkkodatan kulkumuototunnistukseen ovat lupaavia, mutta lisää tutkimusta tarvitaan näiden havaintojen vahvistamiseen

Case Study: Comparison Among Lao PDR, Thailand, and Vietnam: Lesson Learned for Laos

학위논문(석사) -- 서울대학교대학원 : 행정대학원 글로벌행정전공, 2021.8. 다호.The inward FDI is one of the largest sources of the country's revenue after tax excising. In this regard, every country wants to find a viable strategy to move forward with FDI attraction. On this note, ASEAN members attempt to attract inward FDI to the government, specifically from the developing countries and emerging economies such as Thailand, Vietnam, and Lao PDR endeavor to attract foreign direct investment to strengthen their economic prowess in pursuit of sustainable development. Thus, this paper will seek the determinant factors of inward FDI in ASEAN, particularly Thailand and Vietnam. On the other hand, we will catch up on Lao PDR lessons for more significant inward FDI attraction. This paper criticizes to link between the levels of foreign direct investment inflow and Doing Business indicators, including the cost and time (days) starting a business, the cost to register property. The host country's specific indicators, such as trade openness, quality of infrastructure, location, regime, culture, and natural resources, were collected from several research sources from ADB, UNCTAD, and World Bank. The study found to reduce the cost and time (days) required starting a business, and the cost to register the property in the host country will help attract the inward FDI at some particular level. Then the country's specific indicators will be the second row of consideration of investors such as natural resources, culture, location of the country, debt level, trade openness, quality of human resources and quality of infrastructure, and geopolitics another layer to attract inward FDI. Especially, natural resources need innovative technology and the creative process to put more value-added. The infrastructure quality includes transportation infrastructure and communication infrastructure, which are critical for securing and circumventing the extra payment during transportation. Overall, a comparison among three countries found that the most critical factor to drive FDI into the host country is the human capital quality, more specifically skilled labor for the industries. However, the study's result is limited because it is conducted in a holistic framework of the relationship between inward FDI and the determinant factors to attract FDI. Therefore, to refine the research, the more specific on some significant indicators for inward FDI will improve particular regulation in macro policies in the host country.FDI 유입은 국가의 세입 다음으로 가장 큰 국가의 재정 수입원 중 하나이다. 이러한 점에서 모든 국가는 FDI 유치를 추진하기 위하여 실행 가능한 전략을 찾고자 한다. 아세안 회원국들도 FDI 유치를 위하여 노력하고 있으며, 개발도상국과 태국, 베트남, 라오스와 같은 신흥국은 지속 가능한 발전 및 경제력 강화를 위하여 FDI 유입을 촉진하기 위한 노력을 전개하고 있다. 따라서 본 논문은 아세안 국가 중 태국과 베트남에 초점을 맞추어 FDI 유입의 결정요인을 살펴보고자 한다. 이를 통하여 라오스의 FDI 유치를 위한 교훈을 제시하고자 한다. 본 연구는 외국인직접투자 유입 수준과 창업 비용 및 시간, 재산권 등록 비용 등을 포함한 Doing Business Indicators 등을 살펴보았다. 본 연구에서 활용되는 무역 개방도, 사회기반시설 수준, 지리적 위치, 체제, 문화, 그리고 천연 자원 등의 자료는 ADB, UNCTAD, 그리고 World Bank로부터 수집되었다. 본 연구에서는 FDI 유치국에서 사업 시작에 소요되는 비용 및 시간의 감소, 재산권 등록 비용 인하는 일정 수준의 FDI을 유치하는데 도움이 되는 것으로 나타났다. 천연자원, 문화, 국가의 지리적 위치, 부채 수준, 무역 개방도, 인적 자원 수준, 사회기반시설의 수준, 그리고 지정학적 측면 등은 투자 시 고려되는 두번째 측면이라고 볼 수 있다. 특히 천연자원은 더 많은 부가가치를 창출하기 위하여 혁신적인 기술 및 창의적인 과정이 필요하다. 사회기반시설의 질은 운송과정에서 추가적인 비용을 절감할 수 있는 교통 및 통신 인프라를 포함한다. 전반적으로 3개 국가를 비교하면 FDI의 유입을 결정하는 가장 중요한 요소는 인적 자본 수준이며 구체적으로 산업에서 숙련된 노동력이라는 점을 발견하였다. 그러나 본 연구결과는 FDI의 유입과 FDI 유치 결정요인 간의 관계에 대한 총체적인 틀 내에서 수행되었기 때문에 한계가 존재한다. 따라서 이후 연구에서 FDI 유입에 대한 몇가지 중요한 지표가 구체적으로 연구될수록 FDI 유치국의 거시정책에서 특정 규제가 개선될 것이다.CHAPTER 1: INTRODUCTION 1 1.1. THE ASSOCIATION OF SOUTHEAST ASIA (ASEAN) OVERVIEW 1 1.2. ASEAN MACROECONOMIC OVERVIEW 7 1.3. PURPOSE OF RESEARCH 11 1.4. RESEARCH METHODOLOGY AND RESEARCH STRUCTURE 14 1.5. SIGNIFICANCE OF THE STUDY 15 1.6. SCOPE AND LIMITATION 16 CHAPTER 2: THEORY FRAMEWORK 17 2.1. CONCEPTS OF FOREIGN DIRECT INVESTMENT 17 2.2. THE MOTIVATION FOR THE INFLOW OF FDI 18 2.3. THEORETICAL OF DETERMINANT FACTORS OF FDI INFLOW 20 CHAPTER 3: BACKGROUND OF ANALYSIS 29 3.1. THE ESSENTIAL OF INWARD FDI IN THE REGION 29 3.1. THE INWARD FDI ATTRACTIVENESS IN THAILAND 34 3.2. THE INWARD FDI ATTRACTIVENESS IN VIETNAM 45 3.3. THE INWARD FDI ATTRACTIVENESS IN LAO PDR 62 CHAPTER 4: RESULT AND DISCUSSION 80 4.1. APPROACH OF RESEARCH 80 4.1. CORRELATION OF VARIABLES AND INWARD FDI 80 4.2. RESEARCH ANALYSIS AND RESULT 83 4.3. POLICY IMPLICATIONS AND LESSONS LEARNED FOR LAO PDR 92 CHAPTER 5: CONCLUSION 96 5.1. CONCLUSION AND RECOMMENDATIONS 96 BIBLIOGRAPHY 99석

Large-scale Mobile Traffic Analysis: a Survey

International audienceThis article surveys the literature on analyses of mobile traffic collected by operators within their network infrastructure. This is a recently emerged research field, and, apart from a few outliers, relevant works cover the period from 2005 to date, with a sensible densification over the last three years. We provide a thorough review of the multidisciplinary activities that rely on mobile traffic datasets, identifying major categories and sub-categories in the literature, so as to outline a hierarchical classification of research lines. When detailing the works pertaining to each class, we balance a comprehensive view of state-of-the-art results with punctual focuses on the methodological aspects. Our approach provides a complete introductory guide to the research based on mobile traffic analysis. It allows summarizing the main findings of the current state-of-the-art, as well as pinpointing important open research directions