Star-rating evaluation model for rating the energy-efficiency level of android google play apps

The tremendous increase in smartphone usage is 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 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 do not indicate the energy behavior of the apps they offer, which causes users to randomly choose apps without understanding their energy-consumption behavior. A review of the relevant literature was provided covering various energy-saving techniques. The results gave an initial impression about the popularity of the usage of two power-saving modes where the average usage of these modes did not exceed 31% among the total 443 Android users. To address this issue, we propose a star-rating evaluation model (SREM), an approach that generates a tentative energy rating label for each app. The model was tested on 7 open-source apps to act as a primary evaluation sample. 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. As per our results, SREM helped in saving 35% of smartphone energy

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

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The advancement and popularity of smartphones have made it an essential and all-purpose device. But lack of advancement in battery technology has held back its optimum potential. Therefore, considering its scarcity, optimal use and efficient management of energy are crucial in a smartphone. For that, a fair understanding of a smartphone's energy consumption factors is necessary for both users and device manufacturers, along with other stakeholders in the smartphone ecosystem. It is important to assess how much of the device's energy is consumed by which components and under what circumstances. This paper provides a generalized, but detailed analysis of the power consumption causes (internal and external) of a smartphone and also offers suggestive measures to minimize the consumption for each factor. The main contribution of this paper is four comprehensive literature reviews on: 1) smartphone's power consumption assessment and estimation (including power consumption analysis and modelling); 2) power consumption management for smartphones (including energy-saving methods and techniques); 3) state-of-the-art of the research and commercial developments of smartphone batteries (including alternative power sources); and 4) mitigating the hazardous issues of smartphones' batteries (with a details explanation of the issues). The research works are further subcategorized based on different research and solution approaches. A good number of recent empirical research works are considered for this comprehensive review, and each of them is succinctly analysed and discussed

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