A real-time power monitoring and energy-efficient network/interface selection tool for android smartphones

Energy efficiency in wireless and cellular networks has become one of the most important concerns for both academia and industry due to battery dependence of mobile devices. In this regard, Wireless Network Interface Cards (WNICs) of mobile devices have to be taken into account carefully as they consume an important chunk of the system's total energy. In this paper, we propose a real-time network power consumption profiler and an energy-aware network/interface selection tool for Android-based smartphones. The tool has been freely released on the Android Play Store. The proposed solution reports the power consumption levels of different network interfaces (Wi-Fi and Cellular) by making use of actual packet measurements and precise computations, and enables the devices to handover horizontally/vertically in order to improve the energy efficiency. In this context, widespread analyses have been executed to show the accuracy of the proposed tool. The results demonstrate that the proposed tool is very accurate for any type of IEEE 802.11 wireless or cellular stations, regardless of having different amount of channel utilization, transmission rates, signal strengths or traffic types

A real-time power monitoring and energy-efficient network/interface selection tool for android smartphones

Energy efficiency in wireless and cellular networks has become one of the most important concerns for both academia and industry due to battery dependence of mobile devices. In this regard, Wireless Network Interface Cards (WNICs) of mobile devices have to be taken into account carefully as they consume an important chunk of the system's total energy. In this paper, we propose a real-time network power consumption profiler and an energy-aware network/interface selection tool for Android-based smartphones. The tool has been freely released on the Android Play Store. The proposed solution reports the power consumption levels of different network interfaces (Wi-Fi and Cellular) by making use of actual packet measurements and precise computations, and enables the devices to handover horizontally/vertically in order to improve the energy efficiency. In this context, widespread analyses have been executed to show the accuracy of the proposed tool. The results demonstrate that the proposed tool is very accurate for any type of IEEE 802.11 wireless or cellular stations, regardless of having different amount of channel utilization, transmission rates, signal strengths or traffic types

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

Google Play apps ERM: (energy rating model) multi-criteria evaluation model to generate tentative energy ratings for Google Play store apps

A common issue that is shared among Android smartphones users was and still related to saving their batteries power and to avoid the need of using any recharging resources. The tremendous increase in smartphone usage is clearly accompanied by an increase in the need for more energy. This preoperational relationship between modern technology and energy generates energy-greedy apps, and therefore power-hungry end users. With many apps falling under the same category in an app store, these apps usually share similar functionality. Because developers follow different design and development schools, each app has its own energy-consumption habits. Since apps share similar features, an end-user with limited access to recharging resources would prefer an energy-friendly app rather than a popular energy-greedy app. However, app stores give no indication about the energy behaviour of the apps they offer, which causes users to randomly choose apps without understanding their energy-consumption behaviour. Furthermore, with regard to the research questions about the fact that power saving application consumes a lot of electricity, past studies clearly indicate that there is a lot of battery depletion due to several factors. This problem has become a major concern for smartphone users and manufacturers. The main contribution of our research is to design a tool that can act as an effective decision support factor for end users to have an initial indication of the energy-consumption behaviour of an application before installing it. The core idea of the “before-installation” philosophy is simplified by the contradicting concept of installing the app and then having it monitored and optimized. Since processing requires power, avoiding the consumption of some power in order to conserve a larger amount of power should be our priority. So instead, we propose a preventive strategy that requires no processing on any layer of the smartphone. To address this issue, we propose a star-rating evaluation model (SREM), an approach that generates a tentative energy rating label for each app. To that end, SREM adapts current energy-aware refactoring tools to demonstrate the level of energy consumption of an app and presents it in a star-rating schema similar to the Ecolabels used on electrical home appliances. The SREM will also inspire developers and app providers to come up with multiple energy-greedy versions of the same app in order to suit the needs of different categories of users and rate their own apps. We proposed adding SREM to Google Play store in order to generate the energy-efficiency label for each app which will act as a guide for both end users and developers without running any processes on the end-users smartphone. Our research also reviews relevant existing literature specifically those covering various energy-saving techniques and tools proposed by various authors for Android smartphones. A secondary analysis has been done by evaluating the past research papers and surveys that has been done to assess the perception of the users regarding the phone power from their battery. In addition, the research highlights an issue that the notifications regarding the power saving shown on the screen seems to exploit a lot of battery. Therefore, this study has been done to reflect the ways that could help the users to save the phone battery without using any power from the same battery in an efficient manner. The research offers an insight into new ways that could be used to more effectively conserve smartphone energy, proposing a framework that involves end users on the process.Um problema comum entre utilizadores de smartphones Android tem sido a necessidade de economizar a energia das baterias, de modo a evitar a utilização de recursos de recarga. O aumento significativo no uso de smartphones tem sido acompanhado por um aumento, também significativo, na necessidade de mais energia. Esta relação operacional entre tecnologia moderna e energia gera aplicações muito exigentes no seu consumo de energia e, portanto, perfis de utilizadores que requerem níveis de energia crescentes. Com muitos das aplicações que se enquadram numa mesma categoria da loja de aplicações (Google Store), essas aplicações geralmente também partilham funcionalidades semelhantes. Como os criadores destas aplicações seguem abordagens diferentes de diversas escolas de design e desenvolvimento, cada aplicação possui as suas próprias caraterísticas de consumo de energia. Como as aplicações partilham recursos semelhantes, um utilizador final com acesso limitado a recursos de recarga prefere uma aplicação que consome menos energia do que uma aplicação mais exigente em termos de consumo energético, ainda que seja popular. No entanto, as lojas de aplicações não fornecem uma indicação sobre o comportamento energético das aplicações oferecidas, o que faz com que os utilizadores escolham aleatoriamente as suas aplicações sem entenderem o correspondente comportamento de consumo de energia. Adicionalmente, no que diz respeito à questão de investigação, a solução de uma aplicação de economia de energia consume muita eletricidade, o que a torna limitada; estudos anteriores indicam claramente que há muita perda de bateria devido a vários fatores, não constituindo solução para muitos utilizadores e para os fabricantes de smartphones. A principal contribuição de nossa pesquisa é projetar uma ferramenta que possa atuar como um fator de suporte à decisão eficaz para que os utilizadores finais tenham uma indicação inicial do comportamento de consumo de energia de uma aplicação, antes de a instalar. A ideia central da filosofia proposta é a de atuar "antes da instalação", evitando assim a situação em se instala uma aplicação para perceber à posteriori o seu impacto no consumo energético e depois ter que o monitorizar e otimizar (talvez ainda recorrendo a uma aplicação de monitorização do consumo da bateria, o que agrava ainda mais o consumo energético). Assim, como o processamento requer energia, é nossa prioridade evitar o consumo de alguma energia para conservar uma quantidade maior de energia. Portanto, é proposta uma estratégia preventiva que não requer processamento em nenhuma camada do smartphone. Para resolver este problema, é proposto um modelo de avaliação por classificação baseado em níveis e identificado por estrelas (SREM). Esta abordagem gera uma etiqueta de classificação energética provisória para cada aplicação. Para isso, o SREM adapta as atuais ferramentas de refatoração com reconhecimento de energia para demonstrar o nível de consumo de energia de uma aplicação, apresentando o resultado num esquema de classificação por estrelas semelhante ao dos rótulos ecológicos usados em eletrodomésticos. O SREM também se propõe influenciar quem desenvolve e produz as aplicações, a criarem diferentes versões destas, com diferentes perfis de consumo energético, de modo a atender às necessidades de diferentes categorias de utilizadores e assim classificar as suas próprias aplicações. Para avaliar a eficiência do modelo como um complemento às aplicações da loja Google Play, que atuam como uma rotulagem para orientação dos utilizadores finais. A investigação também analisa a literatura existente relevante, especificamente a que abrange as várias técnicas e ferramentas de economia de energia, propostas para smartphones Android. Uma análise secundária foi ainda realizada, focando nos trabalhos de pesquisa que avaliam a perceção dos utilizadores em relação à energia do dispositivo, a partir da bateria. Em complemento, a pesquisa destaca um problema de que as notificações sobre a economia de energia mostradas na tela parecem explorar muita bateria. Este estudo permitiu refletir sobre as formas que podem auxiliar os utilizadores a economizar a bateria do telefone sem usar energia da mesma bateria e, mesmo assim, o poderem fazer de maneira eficiente. A pesquisa oferece uma visão global das alternativas que podem ser usadas para conservar com mais eficiência a energia do smartphone, propondo um modelo que envolve os utilizadores finais no processo.Un problème fréquent rencontré par les utilisateurs de smartphones Android a été, tout en l’étant toujours, d’économiser leur batterie et d’éviter la nécessité d’utiliser des ressources de recharge. La croissance considérable de l’utilisation des smartphones s’accompagne clairement d’une augmentation des besoins en énergie. Cette relation préopérationnelle entre la technologie moderne et l’énergie génère des applications gourmandes en énergie, et donc des utilisateurs finaux qui le sont tout autant. De nombreuses applications relevant de la même catégorie dans une boutique partagent généralement des fonctionnalités similaires. Étant donné que les développeurs adoptent différentes approches de conception et de développement, chaque application a ses propres caractéristiques de consommation d’énergie. Comme les applications partagent des fonctionnalités similaires, un utilisateur final disposant d’un accès limité aux ressources de recharge préférerait une application écoénergétique plutôt qu’une autre gourmande en énergie. Cependant, les boutiques d’applications ne donnent aucune indication sur le comportement énergétique des applications qu’elles proposent, ce qui incite les utilisateurs à choisir des applications au hasard sans comprendre leurs caractéristiques en ce domaine. En outre, en ce qui concerne les questions de recherche sur le fait que les applications d’économie d’énergie consomment beaucoup d’électricité, des études antérieures indiquent clairement que la décharge d’une batterie est due à plusieurs facteurs. Ce problème est devenu une préoccupation majeure pour les utilisateurs et les fabricants de smartphones. La principale contribution de notre étude est de concevoir un outil qui peut agir comme un facteur d’aide efficace à la décision pour que les utilisateurs finaux aient une indication initiale du comportement de consommation d’énergie d’une application avant de l’installer. L’idée de base de la philosophie « avant l’installation » est simplifiée par le concept contradictoire d’installer l’application pour ensuite la contrôler et l’optimiser. Puisque les opérations de traitement exigent de l’énergie, éviter la consommation d’une partie d’entre elles pour l’économiser devrait être notre priorité. Nous proposons donc une stratégie préventive qui ne nécessite aucun traitement sur une couche quelconque du smartphone. Pour résoudre ce problème, nous proposons un modèle d’évaluation au moyen d’étoiles (star-rating evaluation model ou SREM), une approche qui génère une note énergétique indicative pour chaque application. À cette fin, le SREM adapte les outils actuels de refactoring sensibles à l’énergie pour démontrer le niveau de consommation d’énergie d’une application et la présente dans un schéma de classement par étoiles similaire aux labels écologiques utilisés sur les appareils électroménagers. Le SREM incitera également les développeurs et les fournisseurs d’applications à mettre au point plusieurs versions avides d’énergie d’une même application afin de répondre aux besoins des différentes catégories d’utilisateurs et d’évaluer leurs propres applications. Nous avons proposé d’ajouter le SREM au Google Play Store afin de générer le label d’efficacité énergétique pour chaque application. Celui-ci servira de guide à la fois pour les utilisateurs finaux et les développeurs sans exécuter de processus sur le smartphone des utilisateurs finaux. Notre recherche passe également en revue la littérature existante pertinente, en particulier celle qui couvre divers outils et techniques d’économie d’énergie proposés par divers auteurs pour les smartphones Android. Une analyse secondaire a été effectuée en évaluant les documents de recherche et les enquêtes antérieurs qui ont été réalisés pour évaluer la perception des utilisateurs concernant l’alimentation téléphonique depuis leur batterie. En outre, l’étude met en évidence un problème selon lequel les notifications concernant les économies d’énergie affichées à l’écran semblent elles-mêmes soumettre les batteries à une forte utilisation. Par conséquent, cette étude a été entreprise pour refléter les façons qui pourraient aider les utilisateurs à économiser efficacement la batterie de leur téléphone sans pour autant la décharger. L’étude offre un bon aperçu des nouvelles façons d’économiser plus efficacement l’énergie des smartphones, en proposant un cadre qui implique les utilisateurs finaux dans le processus

Vehicular Networks and Outdoor Pedestrian Localization

This thesis focuses on vehicular networks and outdoor pedestrian localization. In particular, it targets secure positioning in vehicular networks and pedestrian localization for safety services in outdoor environments. The former research topic must cope with three major challenges, concerning users’ privacy, computational costs of security and the system trust on user correctness. This thesis addresses those issues by proposing a new lightweight privacy-preserving framework for continuous tracking of vehicles. The proposed solution is evaluated in both dense and sparse vehicular settings through simulation and experiments in real-world testbeds. In addition, this thesis explores the benefit given by the use of low frequency bands for the transmission of control messages in vehicular networks. The latter topic is motivated by a significant number of traffic accidents with pedestrians distracted by their smartphones. This thesis proposes two different localization solutions specifically for pedestrian safety: a GPS-based approach and a shoe-mounted inertial sensor method. The GPS-based solution is more suitable for rural and suburban areas while it is not applicable in dense urban environments, due to large positioning errors. Instead the inertial sensor approach overcomes the limitations of previous technique in urban environments. Indeed, by exploiting accelerometer data, this architecture is able to precisely detect the transitions from safe to potentially unsafe walking locations without the need of any absolute positioning systems

Towards Secure, Power-Efficient and Location-Aware Mobile Computing

In the post-PC era, mobile devices will replace desktops and become the main personal computer for many people. People rely on mobile devices such as smartphones and tablets for everything in their daily lives. A common requirement for mobile computing is wireless communication. It allows mobile devices to fetch remote resources easily. Unfortunately, the increasing demand of the mobility brings many new wireless management challenges such as security, energy-saving and location-awareness. These challenges have already impeded the advancement of mobile systems. In this dissertation we attempt to discover the guidelines of how to mitigate these problems through three general communication patterns in 802.11 wireless networks. We propose a cross-section of a few interesting and important enhancements to manage wireless connectivity. These enhancements provide useful primitives for the design of next-generation mobile systems in the future.;Specifically, we improve the association mechanism for wireless clients to defend against rogue wireless Access Points (APs) in Wireless LANs (WLANs) and vehicular networks. Real-world prototype systems confirm that our scheme can achieve high accuracy to detect even sophisticated rogue APs under various network conditions. We also develop a power-efficient system to reduce the energy consumption for mobile devices working as software-defined APs. Experimental results show that our system allows the Wi-Fi interface to sleep for up to 88% of the total time in several different applications and reduce the system energy by up to 33%. We achieve this while retaining comparable user experiences. Finally, we design a fine-grained scalable group localization algorithm to enable location-aware wireless communication. Our prototype implemented on commercial smartphones proves that our algorithm can quickly locate a group of mobile devices with centimeter-level accuracy

Delphi: A Software Controller for Mobile Network Selection

This paper presents Delphi, a mobile software controller that helps applications select the best network among available choices for their data transfers. Delphi optimizes a specified objective such as transfer completion time, or energy per byte transferred, or the monetary cost of a transfer. It has four components: a performance predictor that uses features gathered by a network monitor, and a traffic profiler to estimate transfer sizes near the start of a transfer, all fed into a network selector that uses the prediction and transfer size estimate to optimize an objective.For each transfer, Delphi either recommends the best single network to use, or recommends Multi-Path TCP (MPTCP), but crucially selects the network for MPTCP s primary subflow . The choice of primary subflow has a strong impact onthe transfer completion time, especially for short transfers.We designed and implemented Delphi in Linux. It requires no application modifications. Our evaluation shows that Delphi reduces application network transfer time by 46% for Web browsing and by 49% for video streaming, comparedwith Android s default policy of always using Wi-Fi when it is available. Delphi can also be configured to achieve high throughput while being battery-efficient: in this configuration, it achieves 1.9x the throughput of Android s default policy while only consuming 6% more energy

Network Traffic Aware Smartphone Energy Savings

In today\u27s world of ubiquitous Smartphone use, extending the battery life has become an important issue. A significant contributor to battery drain is wireless networking. Common usage patterns expect Smartphones to maintain a constant Internet connection which exacerbates the problem.;Our research entitled A Network Traffic Approach to Smartphone Energy Savings focuses on extending Smartphone battery life by investigating how network traffic impacts power management of wireless devices. We explore 1) Real-time VoIP application energy savings by exploiting silence periods in conversation. WiFi is opportunistically placed into low power mode during Silence periods. 2.) The priority of Smartphone Application network traffic is used to modifiy WiFi radio power management using machine learning assisted prioritization. High priority network traffic is optimized for performance, consuming more energy while low priority network traffic is optimized for energy conservation. 3.) A hybrid multiple PHY, MAC layer approach to saving energy is also utilized. The Bluetooth assisted WiFi approach saves energy by combining high power, high throughput WiFi with low power, lower throughput Bluetooth. The switch between Bluetooth and WiFi is done opportunistically based upon the current data rate and health of the Bluetooth connection.;Our results show that application specific methods for wireless energy savings are very effective. We have demonstrated energy savings exceeding 50% in generic cases. With real-time VoIP applications we have shown upwards of 40% energy savings while maintaining good call quality. The hybrid multiple PHY approach saves more than 25% energy over existing solutions while attaining the capability of quickly adapting to changes in network traffic