Collaborative Traffic Offloading for Mobile Systems

Due to the popularity of smartphones and mobile streaming services, the growth of traffic volume in mobile networks is phenomenal. This leads to huge investment pressure on mobile operators' wireless access and core infrastructure, while the profits do not necessarily grow at the same pace. As a result, it is urgent to find a cost-effective solution that can scale to the ever increasing traffic volume generated by mobile systems. Among many visions, mobile traffic offloading is regarded as a promising mechanism by using complementary wireless communication technologies, such as WiFi, to offload data traffic away from the overloaded mobile networks. The current trend to equip mobile devices with an additional WiFi interface also supports this vision. This dissertation presents a novel collaborative architecture for mobile traffic offloading that can efficiently utilize the context and resources from networks and end systems. The main contributions include a network-assisted offloading framework, a collaborative system design for energy-aware offloading, and a software-defined networking (SDN) based offloading platform. Our work is the first in this domain to integrate energy and context awareness into mobile traffic offloading from an architectural perspective. We have conducted extensive measurements on mobile systems to identify hidden issues of traffic offloading in the operational networks. We implement the offloading protocol in the Linux kernel and develop our energy-aware offloading framework in C++ and Java on commodity machines and smartphones. Our prototype systems for mobile traffic offloading have been tested in a live environment. The experimental results suggest that our collaborative architecture is feasible and provides reasonable improvement in terms of energy saving and offloading efficiency. We further adopt the programmable paradigm of SDN to enhance the extensibility and deployability of our proposals. We release the SDN-based platform under open-source licenses to encourage future collaboration with research community and standards developing organizations. As one of the pioneering work, our research stresses the importance of collaboration in mobile traffic offloading. The lessons learned from our protocol design, system development, and network experiments shed light on future research and development in this domain.Yksi mobiiliverkkojen suurimmista haasteista liittyy liikennemäärien eksponentiaaliseen kasvuun. Tämä verkkoliikenteen kasvu johtuu pitkälti suosituista videopalveluista, kuten YouTube ja Netflix, jotka lähettävät liikkuvaa kuvaa verkon yli. Verkon lisääntynyt kuormitus vaatii investointeja verkon laajentamiseksi. On tärkeää löytää kustannustehokkaita tapoja välittää suuressa mittakaavassa sisältöä ilman mittavia infrastruktuuri-investointeja. Erilaisia liikennekuormien ohjausmenetelmiä on ehdotettu ratkaisuksi sisällönvälityksen tehostamiseen mobiiliverkoissa. Näissä ratkaisuissa hyödynnetään toisiaan tukevia langattomia teknologioita tiedonvälityksen tehostamiseen, esimerkiksi LTE-verkosta voidaan delegoida tiedonvälitystä WiFi-verkoille. Useimmissa kannettavissa laitteissa on tuki useammalle langattomalle tekniikalle, joten on luonnollista hyödyntää näiden tarjoamia mahdollisuuksia tiedonvälityksen tehostamisessa. Tässä väitöskirjassa tutkitaan liikennekuormien ohjauksen toimintaa ja mahdollisuuksia mobiiliverkoissa. Työssä esitetään uusi yhteistyöpohjainen liikennekuormien ohjausjärjestelmä, joka hyödyntää päätelaitteiden ja verkon tilannetietoa liikennekuormien optimoinnissa. Esitetty järjestelmä ja arkkitehtuuri on ensimmäinen, joka yhdistää energiankulutuksen ja kontekstitiedon liikennekuormien ohjaukseen. Väitöskirjan keskeisiä tuloksia ovat verkon tukema liikennekuormien ohjauskehikko, yhteistyöpohjainen energiatietoinen optimointiratkaisu sekä avoimen lähdekoodin SoftOffload-ratkaisu, joka mahdollistaa ohjelmistopohjaisen liikennekuormien ohjauksen. Esitettyjä järjestelmiä arvioidaan kokeellisesti kaupunkiympäristöissä älypuhelimia käyttäen. Työn tulokset mahdollistavat entistä energiatehokkaammat liikennekuormien ohjausratkaisut ja tarjoavat ideoita ja lähtökohtia tulevaan 5G kehitystyöhön

Experimental analysis of connectivity management in mobile operating systems

We are immerse in a world that becomes more and more mobile every day, with ubiquitous connectivity and increasing demand for mobile services. Current mobile terminals support several access technologies, enabling users to gain connectivity in a plethora of scenarios and favoring their mobility. However, the management of network connectivity using multiple interfaces is still starting to be deployed. The lack of smart connectivity management in multi interface devices forces applications to be explicitly aware of the variations in the connectivity state (changes in active interface, simultaneous access from several interfaces, etc.). In this paper, we analyze the present state of the connection management and handover capabilities in the three major mobile operating systems (OSes): Android, iOS and Windows. To this aim, we conduct a thorough experimental study on the connectivity management of each operating system, including several versions of the OS on different mobile terminals, analyzing the differences and similarities between them. Moreover, in order to assess how mobility is handled and how this can affect the final user, we perform an exhaustive experimental analysis on application behavior in intra- and inter-technology handover. Based on this experience, we identify open issues in the smartphone connectivity management policies and implementations, highlighting easy to deploy yet unimplemented improvements, as well as potential integration of mobility protocols.This work has been partially supported by the European Community through the CROWD project, FP7-ICT-318115.Publicad

스마트폰에서의 다속성 기반 다중 네트워크 운용 최적화 기법 연구

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2015. 2. 최성현.Todays smartphones integrate multiple radio access technologies (multi-RAT), e.g., 3G, 4G, WiFi, and Bluetooth, etc. Moreover, state-of-the-art smartphones can activate multiple RAT interfaces simultaneously for the parallel transmission. Therefore, it is becoming more important to select the best RAT set among the available RATs, and determine how much data to transfer via each selected RAT network. We propose Energy, Service charge, and Performance Aware (ESPA), an adaptive multi-RAT operation policies for smartphone with supporting system design and multi-attribute cost function for smartphones Internet services including multimedia file transfer and video streaming services. ESPAs cost function incorporates battery energy, data usage quota, and service specific performance, simultaneously. These attributes are motivated by the growing sensitivity of todays smartphone users to these attributes. Each time the individual attributes are calculated and updated, ESPA selects the optimal RAT set that minimizes the overall cost. It can activate only the best one RAT interface or exploit multiple RATs simultaneously. The primary benefit of the ESPA is that it enables the smartphone to always operate in the best mode without the need for users manual controlthe energy saving mode if the remaining battery energy is becoming nearly depletedthe cost-saving mode if the remaining data quota is almost running outor, the performance-oriented mode if remaining data quota and battery energy are both sufficient. From Chapter 2 to Chapter 4, we cope with file transfer, video streaming, and standby mode for our proposed algorithms. The proposed algorithms are based on the service specific cost or utility models, which also take into account practical issues related to user satisfaction metrics. First, for file transfer mode, we apply the transfer completion time as the performance metric, and the energy consumption and service charge for downloading a specific size of file are simultaneously considered. Furthermore, we especially take into account a problem that the computational complexity exponentially increases as the number of available RATs increases. We propose a heuristic linear search algorithm to find the optimal RAT set without significant performance degradation. Secondly, for video streaming mode, we consider the HTTP-based video streaming model exploiting multipath with LTE and WiFi networks. Based on analysis of the energy consumption and data usage for the video streaming services, we propose a multi-RAT based video streaming algorithm that balances between the video quality, i.e., the performance metric, and the total playback time with currently given battery energy and data quota. Finally, we cope with the battery energy leakage issue of the smartphone in the standby mode due to intermittent traffic generated by some applications running on background. We analyze the energy-consuming factors in the standby mode and smartphone usage patterns of multiple users, and then, propose a usage pattern-aware deep sleep operation algorithm to save the battery energy in the standby mode. Simulation results based on real measurement data of the smartphone show that the ESPA algorithms indeed choose the best operational mode by maintaining dynamic balance among the performance, energy consumption, and service charge considering the currently provided services and the remaining resources.Abstract i Contents iv List of Tables vii List of Figures viii 1 Introduction 1 1.1 Energy, Service Charge, and Performance aware Multi-RAT Operation Policies for Smartphone 1.2 Overview of Existing Approaches 1.2.1 Multi-attribute based network selection 1.2.2 Energy and quota-aware video streaming services 1.2.3 Multi-path based approaches 1.3 Main Contributions 1.3.1 File transfer mode 1.3.2 Video streaming mode 1.3.3 Standby mode 1.4 Organization of the Dissertation 2 File Transfer Mode 2.1 Introduction 2.2 System Model 2.3 Problem Formulation 2.3.1 T-E-Q cost modeling 2.3.2 Optimization problem 2.4 Numerical Analysis 2.5 Proposed Algorithm 2.5.1 Bi-directional linear search algorithm 2.5.2 Dynamic update algorithm 2.6 Performance Evaluation 2.7 Summary 3 Video Streaming Mode 3.1 Introduction 3.2 System Model 3.2.1 HTTP-based playback model 3.2.2 LTE/WiFi-based multipath video streaming model 3.3 Chunk Download Cycle based Analysis 3.3.1 Data and energy consumption rate 3.3.2 Expected waste of data and energy 3.4 Proposed Scheme 3.4.1 Problem formulation 3.4.2 Subproblem I: Playback time maximization 3.4.3 Subproblem II: Balancing between encoding rate and total playback time 3.5 Performance Evaluation 3.5.1 Maximization of playback time with a single path 3.5.2 Balancing between video quality and playback time with LTE/WiFi multiple networks 3.6 Summary 4 Standby Mode 4.1 Introduction 4.2 Standby Mode Power Anatomy of Smartphones 4.2.1 Low power mode operation 4.2.2 Power consumption for background traffic 4.2.3 WiFi MAC overhead issue 4.3 Usage Log-based Idle Duration Analysis 4.3.1 User-specific daily distribution of idle duration 4.3.2 All-day distribution 4.3.3 Activity/inactivity time separation 4.4 Proposed Algorithm 4.4.1 Learning phase 4.4.2 Deep Sleep Mode (DSM) operation 4.5 Performance Evaluation 4.5.1 Performance comparison 4.5.2 Effect of Tonoff 4.6 Summary 5 Conclusion 5.1 Concluding Remarks Abstract (In Korean)Docto

On Leveraging Multi-Path Transport in Mobile Networks

Multi-Path TCP (MPTCP) is a new transport protocol that enables mobile devices to simultaneously use several physical paths through multiple network interfaces. MPTCP is particularly useful for mobile devices, which usually have multiple wireless interfaces such as IEEE 802.11 (WiFi), cellular (3G/LTE), and Bluetooth. However, applying MPTCP to mobile devices introduces new concerns since they operate in harsh environments with resource constraints due to intermittent path availability and limited power supply. The goal of this thesis is to resolve these problems so as to be able to practically deploy MPTCP in mobile devices. The first part of the thesis develops a cross-layer path management approach that exploits information from the physical and medium access control layers to deal with intermittent path availability in mobile environment while increasing path utilization of MPTCP over lossy links. Experimental results show that this approach efficiently utilizes intermittently available WiFi paths, with throughput improvements of up to 72%. In addition to the need to manage intermittent path availability, MPTCP must deal with the increased energy consumption due to simultaneous operation of multiple network interfaces. Hence, it is important to understand the energy consumption behavior to deploy MPTCP in mobile devices. We develop an energy model for MPTCP power consumption derived from experimental measurements. Experimental results show that the model accurately estimates the MPTCP energy consumption. Based on the MPTCP energy model, we further explore conditions under which MPTCP is more energy-efficient than either standard TCP or MPTCP. Informed by this finding, we design and implement an energy-aware MPTCP variant for mobile devices. Experimental results show that our approach reduces power consumption compared to standard MPTCP by up to 80% for small file downloads and up to 15% for large file downloads, while preserving the availability and robustness benefits of MPTCP. Finally, we study the impact of path asymmetry on MPTCP performance. Since path asymmetries frequently appear in mobile networks, it is crucial to design a MPTCP path scheduler that properly distributes traffic across available paths, which has different network characteristics such as round-trip time and bandwidth. We propose and implement a new MPTCP path scheduler, ECF (Earliest Completion First), that utilizes all relevant information about a path. Experimental results show that in the presence of path asymmetries ECF consistently utilizes all available paths more efficiently while mitigating out-of-order delay compared to the default scheduler

Context awareness and related challenges: A comprehensive evaluation study for a context-based RAT selection scheme towards 5G networks

Ο αποτελεσματικός σχεδιασμός των δικτύων είναι απαραίτητος για να αντιμετωπιστεί ο αυξανόμενος αριθμός των συνδρομητών κινητού διαδικτύου και των απαιτητικών υπηρεσιών δεδομένων, που ανταγωνίζονται για περιορισμένους ασύρματους πόρους. Επιπλέον, οι βασικές προκλήσεις για τα συνεχώς αναπτυσσόμενα δίκτυα LTE είναι η αύξηση των δυνατοτήτων των υφιστάμενων μηχανισμών, η μείωση της υπερβολικής σηματοδότησης (signaling) και η αξιοποίηση ενός αποτελεσματικού μηχανισμού επιλογής τεχνολογίας ασύρματης πρόσβασης (RAT). Υπάρχουν ποικίλες προτάσεις στην βιβλιογραφία σχετικά με αυτές τις προκλήσεις, μερικές από τις οποίες παρουσιάζονται εδώ. Ο σκοπός της εργασίας αυτής είναι να ερευνήσει τις τρέχουσες εξελίξεις στα δίκτυα LTE σχετικά με την ενσωμάτωση EPC και WiFi και την επίγνωση πλαισίου (context awareness) στην διαχείριση κινητικότητας, και να προτείνει τον αλγόριθμο COmpAsS, έναν μηχανισμό που χρησιμοποιεί ασαφή λογική (fuzzy logic) για να επιλέξει την πιο κατάλληλη τεχνολογία ασύρματης πρόσβασης για τα κινητά. Επιπλέον, έχουμε ποσοτικοποιήσει το κόστος σηματοδότησης του προτεινόμενου μηχανισμού σε σύνδεση με τις σημερινές προδιαγραφές του 3GPP και εκτελέσαμε μια ολοκληρωμένη ανάλυση. Τέλος, αξιολογήσαμε τον αλγόριθμο μέσω εκτεταμένων προσομοιώσεων σε ένα πολύπλοκο και ρεαλιστικό σενάριο χρήσης 5G, που απεικονίζονται τα σαφή πλεονεκτήματα της προσέγγισής μας όσον αφορά τη συχνότητα μεταπομπών (handover) και τις μετρήσεις βασικών QoS τιμών, όπως ρυθμός μετάδοσης και καθυστέρηση.Effective network planning is essential to cope with the increasing number of mobile internet subscribers and bandwidth-intensive services competing for limited wireless resources. Additionally, key challenges for the constantly growing LTE networks is increasing capabilities of current mechanisms, reduction of signaling overhead and the utilization of an effective Radio Access Technology (RAT) selection scheme. There have been various proposals in literature regarding these challenges, some of which are discussed here. The purpose of this work is to research the current advances in LTE networks regarding EPC - WiFi integration and context awareness in mobility management, and propose the COmpAsS algorithm, a mechanism using fuzzy logic to select the most suitable Radio Access Technology. Furthermore, we quantify the signaling overhead of the proposed mechanism by linking it to the current 3GPP specifications and performing a comprehensive analysis. Finally, we evaluate the novel scheme via extensive simulations in a complex and realistic 5G use case, illustrating the clear advantages of our approach in terms of handover frequency and key QoS metrics, i.e. the user-experienced throughput and delay

Improved planning and resource management in next generation green mobile communication networks

In upcoming years, mobile communication networks will experience a disruptive reinventing process through the deployment of post 5th Generation (5G) mobile networks. Profound impacts are expected on network planning processes, maintenance and operations, on mobile services, subscribers with major changes in their data consumption and generation behaviours, as well as on devices itself, with a myriad of different equipment communicating over such networks. Post 5G will be characterized by a profound transformation of several aspects: processes, technology, economic, social, but also environmental aspects, with energy efficiency and carbon neutrality playing an important role. It will represent a network of networks: where different types of access networks will coexist, an increasing diversity of devices of different nature, massive cloud computing utilization and subscribers with unprecedented data-consuming behaviours. All at greater throughput and quality of service, as unseen in previous generations. The present research work uses 5G new radio (NR) latest release as baseline for developing the research activities, with future networks post 5G NR in focus. Two approaches were followed: i) method re-engineering, to propose new mechanisms and overcome existing or predictably existing limitations and ii) concept design and innovation, to propose and present innovative methods or mechanisms to enhance and improve the design, planning, operation, maintenance and optimization of 5G networks. Four main research areas were addressed, focusing on optimization and enhancement of 5G NR future networks, the usage of edge virtualized functions, subscriber’s behavior towards the generation of data and a carbon sequestering model aiming to achieve carbon neutrality. Several contributions have been made and demonstrated, either through models of methodologies that will, on each of the research areas, provide significant improvements and enhancements from the planning phase to the operational phase, always focusing on optimizing resource management. All the contributions are retro compatible with 5G NR and can also be applied to what starts being foreseen as future mobile networks. From the subscriber’s perspective and the ultimate goal of providing the best quality of experience possible, still considering the mobile network operator’s (MNO) perspective, the different proposed or developed approaches resulted in optimization methods for the numerous problems identified throughout the work. Overall, all of such contributed individually but aggregately as a whole to improve and enhance globally future mobile networks. Therefore, an answer to the main question was provided: how to further optimize a next-generation network - developed with optimization in mind - making it even more efficient while, simultaneously, becoming neutral concerning carbon emissions. The developed model for MNOs which aimed to achieve carbon neutrality through CO2 sequestration together with the subscriber’s behaviour model - topics still not deeply focused nowadays – are two of the main contributions of this thesis and of utmost importance for post-5G networks.Nos próximos anos espera-se que as redes de comunicações móveis se reinventem para lá da 5ª Geração (5G), com impactos profundos ao nível da forma como são planeadas, mantidas e operacionalizadas, ao nível do comportamento dos subscritores de serviços móveis, e através de uma miríade de dispositivos a comunicar através das mesmas. Estas redes serão profundamente transformadoras em termos tecnológicos, económicos, sociais, mas também ambientais, sendo a eficiência energética e a neutralidade carbónica aspetos que sofrem uma profunda melhoria. Paradoxalmente, numa rede em que coexistirão diferentes tipos de redes de acesso, mais dispositivos, utilização massiva de sistema de computação em nuvem, e subscritores com comportamentos de consumo de serviços inéditos nas gerações anteriores. O trabalho desenvolvido utiliza como base a release mais recente das redes 5G NR (New Radio), sendo o principal focus as redes pós-5G. Foi adotada uma abordagem de "reengenharia de métodos” (com o objetivo de propor mecanismos para resolver limitações existentes ou previsíveis) e de “inovação e design de conceitos”, em que são apresentadas técnicas e metodologias inovadoras, com o principal objetivo de contribuir para um desenho e operação otimizadas desta geração de redes celulares. Quatro grandes áreas de investigação foram endereçadas, contribuindo individualmente para um todo: melhorias e otimização generalizada de redes pós-5G, a utilização de virtualização de funções de rede, a análise comportamental dos subscritores no respeitante à geração e consumo de tráfego e finalmente, um modelo de sequestro de carbono com o objetivo de compensar as emissões produzidas por esse tipo de redes que se prevê ser massiva, almejando atingir a neutralidade carbónica. Como resultado deste trabalho, foram feitas e demonstradas várias contribuições, através de modelos ou metodologias, representando em cada área de investigação melhorias e otimizações, que, todas contribuindo para o mesmo objetivo, tiveram em consideração a retro compatibilidade e aplicabilidade ao que se prevê que sejam as futuras redes pós 5G. Focando sempre na perspetiva do subscritor da melhor experiência possível, mas também no lado do operador de serviço móvel – que pretende otimizar as suas redes, reduzir custos e maximizar o nível de qualidade de serviço prestado - as diferentes abordagens que foram desenvolvidas ou propostas, tiveram como resultado a resolução ou otimização dos diferentes problemas identificados, contribuindo de forma agregada para a melhoria do sistema no seu todo, respondendo à questão principal de como otimizar ainda mais uma rede desenvolvida para ser extremamente eficiente, tornando-a, simultaneamente, neutra em termos de emissões de carbono. Das principais contribuições deste trabalho relevam-se precisamente o modelo de compensação das emissões de CO2, com vista à neutralidade carbónica e um modelo de análise comportamental dos subscritores, dois temas ainda pouco explorados e extremamente importantes em contexto de redes futuras pós-5G

IP Flow Mobility based Offload in LTE Wi-Fi Interworking Scenario

Mobile data traffic has seen an exponential growth in the past few years with the trend expected to continue. LTE as a standalone cellular network is unable to keep pace with the increasing traffic demands. In the meanwhile, wireless LAN has proven itself as an economical wireless access technology. 3GPP has thus been encouraged to standardize the integration of Wi-Fi networks with LTE. This opens up numerous opportunities to study data offloading and mobility management protocols. One of the newer offloading technique is known as IP Flow Mobility, where individual IP flows are migrated from one network to the other without affecting other flows belonging to the same IP session. In this thesis work, a framework has been developed on ns-3 which supports flow mobility between LTE and Wi-Fi. This framework is based on PMIPv6. This flow mobility framework provides an opportunity to implement various algorithms to decide which network is used to serve which flows while trying maintain a balance between bandwidth utilization and user satisfaction. One such algorithm has been proposed here for a network consisting of LTE and Wi-Fi. This algorithm calculates a quality value for each flow on the network using parameters like flow type, SNR, velocity of the user, etc and tries to offload these flows onto either network based on the flow’s quality value. A simple simulation is carried out which validates the implementation of the framework, where a TCP flow is migrated to a Wi-Fi network from the LTE network based on the SNR of the Wi-Fi network. It also shows how the velocity of a UE affects the percentage of offload which can be achieved and how the flow’s performance is affected by the offload

System Abstractions for Scalable Application Development at the Edge

Recent years have witnessed an explosive growth of Internet of Things (IoT) devices, which collect or generate huge amounts of data. Given diverse device capabilities and application requirements, data processing takes place across a range of settings, from on-device to a nearby edge server/cloud and remote cloud. Consequently, edge-cloud coordination has been studied extensively from the perspectives of job placement, scheduling and joint optimization. Typical approaches focus on performance optimization for individual applications. This often requires domain knowledge of the applications, but also leads to application-specific solutions. Application development and deployment over diverse scenarios thus incur repetitive manual efforts. There are two overarching challenges to provide system-level support for application development at the edge. First, there is inherent heterogeneity at the device hardware level. The execution settings may range from a small cluster as an edge cloud to on-device inference on embedded devices, differing in hardware capability and programming environments. Further, application performance requirements vary significantly, making it even more difficult to map different applications to already heterogeneous hardware. Second, there are trends towards incorporating edge and cloud and multi-modal data. Together, these add further dimensions to the design space and increase the complexity significantly. In this thesis, we propose a novel framework to simplify application development and deployment over a continuum of edge to cloud. Our framework provides key connections between different dimensions of design considerations, corresponding to the application abstraction, data abstraction and resource management abstraction respectively. First, our framework masks hardware heterogeneity with abstract resource types through containerization, and abstracts away the application processing pipelines into generic flow graphs. Further, our framework further supports a notion of degradable computing for application scenarios at the edge that are driven by multimodal sensory input. Next, as video analytics is the killer app of edge computing, we include a generic data management service between video query systems and a video store to organize video data at the edge. We propose a video data unit abstraction based on a notion of distance between objects in the video, quantifying the semantic similarity among video data. Last, considering concurrent application execution, our framework supports multi-application offloading with device-centric control, with a userspace scheduler service that wraps over the operating system scheduler