An Experimental Performance Comparison of 3G and Wi-Fi

Abstract. Mobile Internet users have two options for connectivity: pay premium fees to utilize 3G or wander around looking for open Wi-Fi access points. We perform an experimental evaluation of the amount of data that can be pushed to and pulled from the Internet on 3G and open Wi-Fi access points while on the move. This side-by-side compar-ison is carried out at both driving and walking speeds in an urban area using standard devices. We show that significant amounts of data can be transferred opportunistically without the need of always being connected to the network. We also show that Wi-Fi mostly suffers from not being able to exploit short contacts with access points but performs compa-rably well against 3G when downloading and even significantly better while uploading data.

The influences and consequences of being digitally connected and/or disconnected to travellers

© 2017, The Author(s).Technological progress and tourism have worked in tandem for many years. Connectivity is the vehicle that drove the goal of technologically enhanced tourism experiences forward. This study, through an exploratory qualitative research identifies the factors that boost and/or distract travellers from obtaining a digitally enhanced tourism experience. Four factors can boost and/or distract travellers from being connected: (1) hardware and software, (2) needs and contexts, (3) openness to usage, and (4) supply and provision of connectivity. The research also analyses the positive and/or negative consequences that arise from being connected or disconnected. A Connected/Disconnected Consequences Model illustrates five forms of positive and/or negative consequences: (1) availability, (2) communication, (3) information obtainability, (4) time consumption, and (5) supporting experiences. A better understanding of the role and consequence of connectivity during the trip can enhance traveller experience

Tracking the Evolution and Diversity in Network Usage of Smartphones

ABSTRACT We analyze the evolution of smartphone usage from a dataset obtained from three, 15-day-long, user-side, measurements with over 1500 recruited smartphone users in the Greater Tokyo area from 2013 to 2015. This dataset shows users across a diverse range of networks; cellular access (3G to LTE), WiFi access (2.4 to 5GHz), deployment of more public WiFi access points (APs), as they use diverse applications such as video, file synchronization, and major software updates. Our analysis shows that smartphone users select appropriate network interfaces taking into account the deployment of emerging technologies, their bandwidth demand, and their economic constraints. Thus, users show diversity in both how much traffic they send, as well as on what networks they send it. We show that users are gradually but steadily adopting WiFi at home, in offices, and public spaces over these three years. The majority of light users have been shifting their traffic to WiFi. Heavy hitters acquire more bandwidth via WiFi, especially at home. The percentage of users explicitly turning off their WiFi interface during the day decreases from 50% to 40%. Our results highlight that the offloading environment has been improved during the three years, with more than 40% of WiFi users connecting to multiple WiFi APs in one day. WiFi offload at offices is still limited in our dataset due to a few accessible APs, but WiFi APs in public spaces have been an alternative to cellular access for users who request not only simple connectivity but also bandwidth-consuming applications such as video streaming and software updates. Categories and Subject Descriptors General Terms Measurement Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

A New Competitive Ratio for Network Applications with Hard Performance Guarantee

Online algorithms are used to solve the problems which need to make decisions without future knowledge. Competitive ratio is used to evaluate the performance of an online algorithm. This ratio is the worst-case ratio between the performance of the online algorithm and the offline optimal algorithm. However, the competitive ratios in many current studies are relatively low and thus cannot satisfy the need of the customers in practical applications. To provide a better service, a practice for service provider is to add more redundancy to the system. Thus we have a new problem which is to quantify the relation between the amount of increased redundancy and the system performance. In this dissertation, to address the problem that the competitive ratio is not satisfactory, we ask the question: How much redundancy should be increased to fulfill certain performance guarantee? Based on this question, we will define a new competitive ratio showing the relation between the system redundancy and performance of online algorithm compared to offline algorithm. We will study three applications in network applications. We propose online algorithms to solve the problems and study the competitive ratio. To evaluate the performances, we further study the optimal online algorithms and some other commonly used algorithms as comparison. We first study the application of online scheduling for delay-constrained mobile offloading. WiFi offloading, where mobile users opportunistically obtain data through WiFi rather than through cellular networks, is a promising technique to greatly improve spectrum efficiency and reduce cellular network congestion. We consider a system where the service provider deploys multiple WiFi hotspots to offload mobile traffic with unpredictable mobile users’ movements. Then we study online job allocation with hard allocation ratio requirement. We consider that jobs of various types arrive in some unpredictable pattern and the system is required to allocate a certain ratio of jobs. We then aim to find the minimum capacity needed to meet a given allocation ratio requirement. Third, we study online routing in multi-hop network with end-to-end deadline. We propose reliable online algorithms to schedule packets with unpredictable arriving information and stringent end-to-end deadline in the network

Energy-Efficient Wireless Network Interface Selection for Mobile Devices

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2014. 2. 조유근.최근 무선 통신 기술과 모바일 컴퓨팅 환경의 발전으로 스마트 폰이나 스마트 패드 와 같이 Wi-Fi, 3G, LTE 네트워크 등을 동시에 지원하는 모바일 장치들이 다양한 분야에 널리 사용되고 있다. 대부분의 모바일 장치들은 제한된 배터리 용량을 갖고 있어 에너지의 효율성은 매우 중요한 요소이다. Wi-Fi, 3G, LTE와 같은 무선 통신 기법은 네트워크 서비스 범위, 통신 속도, 에너지 소모량과 같은 측면에서 매우 다른 특성을 보인다. 따라서 각 네트워크의 특성을 이용하여 모바일 장치의 에너지 및 데이터 전송 효율성을 증대시킬 수 있다. 본 논문에서는 3G와 Wi-Fi 네트워크 인터페이스를 가지는 모바일 장치를 가정 하여 네트워크 탐지 및 선택 주기에 따른 모바일 장치의 에너지 소모량과 데이터 전송 소요 시간을 모델링한다. 제안한 에너지 소모량 모델의 분석을 통해 에너지 소모량을 최소화할 수 있는 네트워크 탐지 및 선택 주기가 존재함을 보인다. 최적의 네트워크 탐지 및 선택 주기는 데이터 전송 요청량이나 Wi-Fi 네트워크의 가용성과 같은 다양한 네트워크 환경 요소에 따라 달라진다. 이를 기반으로 네트워크 탐지 및 선택 주기를 동적으로 조절할 수 있는 에너지 효율적인 네트워크 인터페이스 선택 기법(AWNIS, Adaptive Wireless Network Interface Selection)을 제안한다. 제안 기법은 제안한 에너지 소모 모델을 기반으로 Wi-Fi 네트워크 가용성을 근사화하여 에너지 및 데이터 전송 효율 측면에서 뛰어난 Wi-Fi 네트워크를 사용하기 위한 탐지 및 선택 주기를 동적으로 조절한다. 이를 통해 모바일 장치의 에너지 소모량과 데이터 전송 효율성을 높일 수 있다. 성능 비교 및 분석을 통해 제안 기법이 일정 수준의 데이터 전송 지연 시간을 보장하면서 모바일 장치의 에너지 소모를 감소시킬 수 있음을 보인다. 제안 기법은 3G와 Wi-Fi 네트워크의 특성과 유사한 앞으로 개발되거나 사용이 가능한 근거리와 원거리 네트워크 인터페이스를 동시에 가지는 모바일 장치의 네트워크 인터페이스 선택 기법에 적용이 가능하다.Mobile devices such as smart-phones and smart-pads are widely used not only in our everyday lives but also in various industrial fields by the development of wireless network and mobile computing technologies. Energy efficiency is very important for mobile devices because most of these mobile devices operate on limited battery power. Wireless network technologies such as Wi-Fi, 3G, and LTE have fairly different characteristics in terms of its energy consumption, service area, data transfer rate, and other factors. Efficiencies in terms of energy consumption and data transfer can be improved by leveraging the characteristics of the wireless network technologies. In this dissertation, we assume a mobile device that is equipped with 3G and Wi-Fi network interfaces. We model an energy consumption and data transfer time of the mobile device due to changes in network detection and selection interval. Based on analysis results of the proposed models, we show the existence of the optimal network detection and selection interval which minimizes the energy consumption. The optimal network detection and selection interval changes according to the network environment such as the amount of requested data or availability of Wi-Fi. Based on the above observations, we propose an energy-efficient adaptive wireless network interface-selection scheme, termed AWNIS that can adjust the detection and selection interval dynamically. AWNIS uses a dynamic network selection and detection interval in order to use Wi-Fi network that is more efficient than 3G network in terms of energy consumption and data transfer. When selecting the interval, AWNIS chooses the interval based on the proposed energy consumption model and approximated availability of Wi-Fi network. In this manner, AWNIS improves the energy and data transfer efficiencies of mobile devices. Based on the simulation results, we show that the proposed scheme effectively improves the energy efficiency while guaranteeing a certain level of data transfer delay. Proposed AWNIS also can be applied to mobile devices equipped with future short and long range network interfaces which have similar characteristics compared to 3G and Wi-Fi network interfaces.초 록 i 목 차 ii 표 목 차 v 그 림 목 차 vi 제 1 장 서론 1 1.1 연구 배경 1 1.2 연구 목적 및 범위 3 1.3 연구 성과 요약 4 1.4 논문의 구성 4 제 2 장 관련 연구 6 2.1 TailEnder 6 2.2 CoolSpots 8 2.3 Context-For-Wireless 9 2.4 SALSA 11 2.5 기타 기법 12 제 3 장 에너지 효율적인 무선 네트워크 인터페이스 선택 기법 (AWNIS) 13 3.1 무선 네트워크 인터페이스 선택 주기에 따른 비용 모델링 13 3.1.1 가정 사항 13 3.1.2 3G와 Wi-Fi를 이용한 데이터 전송 14 3.1.3 에너지 소모량 모델링 20 3.1.4 데이터 전송 소요 시간 모델링 25 3.2 무선 네트워크 인터페이스 선택 주기에 따른 비용 분석 29 3.2.1 에너지 소모량 분석 32 3.2.2 데이터 전송 지연 시간 분석 36 3.3 에너지 효율적인 무선 네트워크 인터페이스 선택 알고리즘 38 3.3.1 무선 네트워크 인터페이스 선택 및 탐지 단계 40 3.3.2 3G에서 Wi-Fi로의 네트워크 연결 전환 단계 41 3.3.3 Wi-Fi에서 3G로의 네트워크 연결 전환 단계 42 3.3.4 AWNIS 의 동작의 예 43 3.4 에너지 효율적인 무선 네트워크 인터페이스 선택 알고리즘 분석 44 3.4.1 에너지 소모량 측면 분석 44 3.4.2 데이터 전송 지연 시간 측면 분석 45 제 4 장 성능 분석 및 비교 48 4.1 시뮬레이션 환경 48 4.2 성능 분석 및 비교에 사용된 네트워크 선택 기법 50 4.2.1 AWNIS 의 적용이 가능한 네트워크 선택 기법 51 4.2.2 최적의 네트워크 선택 기법 53 4.2.3 비교 가능한 기존의 네트워크 선택 기법 54 4.3 시뮬레이션 결과 및 분석 54 4.3.1 α에 따른 에너지 소모량 및 데이터 전송 지연 분석 54 4.3.2 합성 워크로드 (Synthetic Workloads)를 이용한 성능 분석 57 4.3.3 현실적인 워크로드 (Realistic Workloads) 를 이용한 성능 분석 63 4.4 AWNIS 알고리즘 개선 및 성능 분석 67 4.4.1 개선된 AWNIS 알고리즘 67 4.4.2 개선된 AWNIS의 성능 분석을 위한 시뮬레이션 환경 71 4.4.3 개선된 AWNIS의 성능 분석 및 비교 71 제 5 장 결론 및 향후 연구 77 5.1 결론 77 5.2 향후 연구 78 참 고 문 헌 80 Abstract 86Docto

Semantic IoT for reasoning and BigData analytics

Recent developments in the IoT industries have led to an increase in data availability that is starting to weight heavily on the traditional idea of pushing data to the Cloud. This study focuses on identifying tasks that can be pulled from the Cloud in a semantic stream processing context

A New Competitive Ratio for Network Applications with Hard Performance Guarantee

Online algorithms are used to solve the problems which need to make decisions without future knowledge. Competitive ratio is used to evaluate the performance of an online algorithm. This ratio is the worst-case ratio between the performance of the online algorithm and the offline optimal algorithm. However, the competitive ratios in many current studies are relatively low and thus cannot satisfy the need of the customers in practical applications. To provide a better service, a practice for service provider is to add more redundancy to the system. Thus we have a new problem which is to quantify the relation between the amount of increased redundancy and the system performance. In this dissertation, to address the problem that the competitive ratio is not satisfactory, we ask the question: How much redundancy should be increased to fulfill certain performance guarantee? Based on this question, we will define a new competitive ratio showing the relation between the system redundancy and performance of online algorithm compared to offline algorithm. We will study three applications in network applications. We propose online algorithms to solve the problems and study the competitive ratio. To evaluate the performances, we further study the optimal online algorithms and some other commonly used algorithms as comparison. We first study the application of online scheduling for delay-constrained mobile offloading. WiFi offloading, where mobile users opportunistically obtain data through WiFi rather than through cellular networks, is a promising technique to greatly improve spectrum efficiency and reduce cellular network congestion. We consider a system where the service provider deploys multiple WiFi hotspots to offload mobile traffic with unpredictable mobile users’ movements. Then we study online job allocation with hard allocation ratio requirement. We consider that jobs of various types arrive in some unpredictable pattern and the system is required to allocate a certain ratio of jobs. We then aim to find the minimum capacity needed to meet a given allocation ratio requirement. Third, we study online routing in multi-hop network with end-to-end deadline. We propose reliable online algorithms to schedule packets with unpredictable arriving information and stringent end-to-end deadline in the network

Social dimensions of public large-scale wi-fi networks: the cases of a municipal and a community wireless network

Wireless networks play an increasingly important role in today’s mobile and interconnected society. People use mobile devices such as smartphones, tablets or portable game consoles on a regular basis to interact, retrieve and share information, and to orient and entertain themselves. However, in order to be fully performant these devices need to be connected to the Internet. Thanks to very good broadband penetration in Switzerland, this is not so much an issue in private homes and offices where local Wi-Fi networks allow mobile devices to connect to the Internet. Nonetheless, in public spaces, good working wireless networks, even though increasing, are still not very frequent and generally cover only limited areas. Alternative, provider- centered mobile data (3G/4G/LTE) is still expensive especially for visitors because of high roaming rates but also for Swiss people, whose majority still did not have unlimited data contracts in 2016. Public large-scale wireless networks can thus play an important role in providing Internet connectivity to people on the go. This dissertation studies two different approaches to the provision of Wi-Fi broadband connectivity in public spaces: on the one hand, municipalities providing Wi-Fi access in some areas of the city through so-called Municipal Wireless Networks (MWN), and on the other hand, communities with members sharing part of their home broadband connection with other community members, building so-called Community Wireless Networks (CWN). Wireless communities can either be purely self-organized (pure wireless communities) or have a for-profit company managing the community (hybrid communities). While existing studies have analyzed business and ownership models, technical solutions and policy implications of public wireless networks, this research is interested in their social dimensions, focusing on the role of individuals using and contributing to these networks. To do so, two main research goals are addressed: 1) understanding what motivates people to join and actively participate in a hybrid CWN and what hinders them from doing so, and 2) understanding who the users of a MWN are and how they use the network in order to identify various user types and usage practices, which will in turn help municipalities design networks that address the needs of various users. In order to study users’ motivations and concerns for joining and actively participating in a hybrid wireless community, the Fon community (Fon, 2018b) has been analyzed, which at the time of this study was the largest worldwide hybrid CWN. A mixed research approach has been applied. First, an existing model on motivations in pure communities (Bina & Giaglis, 2006a) has been adapted with the help of semi-structured exploratory interviews of 40 Swiss Fon members and then refined through a quantitative online survey addressed to Swiss and foreign Fon members. The resulting model shows which motivations attract members to the community, and which concerns have a dissuasive function. In a second step, 268 valid survey answers have been used for structural equation modeling (SEM) in order to assess which motivations actually result in a higher level of active participation. In order to analyze usage and users of a MWN, the “WiFi Lugano” MWN of the city of Lugano has been chosen. Lugano is located in the Italian-speaking southern part of Switzerland, is a popular tourist destination and the region’s economic capital. In collaboration with the electricity company in charge of implementing the Wi-Fi network (Aziende Industriali Luganesi – AIL), technical network data (log-data) and user-provided information – users were asked to fill-in a short survey after they logged-in to the network – have been collected and analyzed in combination (the two data sets have been merged). In a first step, usage profiles of leisure tourists, business travelers and residents have been created and described applying descriptive statistics to data of three summer months (June – August 2013). In a second step, cluster analysis has been applied to one-year data (June 2013 – May 2014), in order to identify relevant groups of users. Outcomes suggest that in a hybrid CWN, members are motivated to join the community mainly by a mix of utilitarian (e.g. getting free Internet access) and idealistic motivations (reciprocity and altruism), while intrinsic and social motivations are less important. This confirms that motivations are similar to those in pure CWNs but have different weights. In fact, in pure CWNs, intrinsic and social motivations seem to be stronger while in hybrid CWNs, utilitarian motivations prevail. Two types of active participation have been identified in the Fon community, each one driven by a different mix of motivations: “participation by sharing” – putting effort into actively sharing one’s own Internet connectivity – is mainly driven by idealistic motivations related to community values and reciprocity, while “social participation” – being socially involved in the community by interacting with and helping other community members – is driven by social (communicating, learning from each other) and technical reasons (experimenting with technologies). Surprisingly, utilitarian motivations do not have a significant effect on either of the two participation types, even though they are the most relevant ones in attracting new members. With regard to the MWN “WiFi Lugano”, five different usage practices have been identified: two business-oriented ones (“E-mailer” and “Mobile-worker”), two tourism-oriented ones (“Tourism information seeker” and “Always-on traveler”), and one corresponding to the practices of locals (“Local social networker”), each one having different characteristics. The “WiFi Lugano” network thus acts as a business, tourism, and social inclusion enabler, actively favoring various eGovernment relationships: government to business (G2B), government to visitors (G2V), and government to citizens (G2C). Based on these outcomes it has been possible to define a series of suggestions to help cities take advantage of their MWNs and improving them accordingly. Cities could for example provide different landing pages to different publics in order to promote the city in a targeted way, ensure a high quality service of their MWNs, use the Wi-Fi networks to promote tourist attractions and vice-versa (e.g. mark Wi-Fi areas on city maps, build Wi-Fi areas near to tourist attractions, and provide a description of the attraction on the Wi-Fi network’s landing page), share the network with small businesses in the area and extend the reach of the network to relevant areas