Enhancing Mobile Capacity through Generic and Efficient Resource Sharing

Mobile computing devices are becoming indispensable in every aspect of human life, but diverse hardware limits make current mobile devices far from ideal for satisfying the performance requirements of modern mobile applications and being used anytime, anywhere. Mobile Cloud Computing (MCC) could be a viable solution to bypass these limits which enhances the mobile capacity through cooperative resource sharing, but is challenging due to the heterogeneity of mobile devices in both hardware and software aspects. Traditional schemes either restrict to share a specific type of hardware resource within individual applications, which requires tremendous reprogramming efforts; or disregard the runtime execution pattern and transmit too much unnecessary data, resulting in bandwidth and energy waste.To address the aforementioned challenges, we present three novel designs of resource sharing frameworks which utilize the various system resources from a remote or personal cloud to enhance the mobile capacity in a generic and efficient manner. First, we propose a novel method-level offloading methodology to run the mobile computational workload on the remote cloud CPU. Minimized data transmission is achieved during such offloading by identifying and selectively migrating the memory contexts which are necessary to the method execution. Second, we present a systematic framework to maximize the mobile performance of graphics rendering with the remote cloud GPU, during which the redundant pixels across consecutive frames are reused to reduce the transmitted frame data. Last, we propose to exploit the unified mobile OS services and generically interconnect heterogeneous mobile devices towards a personal mobile cloud, which complement and flexibly share mobile peripherals (e.g., sensors, camera) with each other

Um framework para computação aproximada sensível ao contexto

Orientador: Lucas Francisco WannerDissertação (mestrado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Computação aproximada pode melhorar consideravelmente a eficiência energética em aplicações onde um resultado aproximado é suficiente. Neste trabalho, construímos bibliotecas de funções padrão que incluem uma série de funções com diferentes implementações, onde cada implementação tem um resultado de precisão diferente. Desenvolvemos ainda um serviço de sistema que monitora o contexto do computador, incluindo o consumo de energia e, de acordo com esse contexto (usando regras especificadas), altera as implementações de biblioteca usadas pelos aplicativos em tempo real. Dessa forma, o aplicativo produz resultados aproximados, mas aceitáveis, ao mesmo tempo que limita o consumo de energia. O sistema desenvolvido foi testado com aplicativos que são adequados para aproximações. Para cada uma das aplicações, medimos o consumo de energia do computador quando elas são executadas usando as implementações de maior precisão da biblioteca (as implementações mais consumidoras de energia). Conhecendo esse valor, conseguimos fixar um valor de consumo de energia de meta (uma porcentagem do valor calculado anteriormente) e desenvolvemos regras em torno desse valor, aumentando ou diminuindo a precisão das implementações usadas por um aplicativo. Os resultados mostram que, em nossos estudos de caso, podemos limitar a degradação máxima de 4% na qualidade de resultados das aplicações para obter até 62% de economia no consumo de energia. Além disso, fixamos uma meta de consumo de energia para cada aplicativo, e os aplicativos foram capazes de se adaptar em tempo de execução a essa metaAbstract: Approximate computing can considerably improve energy efficiency in applications where an approximate result is enough or by relaxing the need for fully precise operations. However, approximate computing applications typically aren't able to take advantage of the computer context dynamically. By improving the computer's access to context in real-time, approximate applications can get information about the current computer power consumption, take decisions according to previously fixed rules, and use this information to produce a more suitable approximation for the current context. We built a library that includes a series of functions with different implementations wherein each implementation has a different precision result, and a system service that monitors the computer context, including energy consumption, and according to this context (using specified rules), changes the library implementations used by applications in real-time. Applications using the library can therefore save energy when necessary, without compromising quality of results. We evaluate our context-aware approximate computing library with applications that are suitable for approximations. For each of these applications, we measured the energy consumption of the computer when they are run using the highest precision implementations of the library (that most energy intensive implementations). Knowing this value, we were able to fix an goal energy consumption value (a percentage of the value previously calculated), and using rules around this value, increase or decrease the precision of the implementations used by an application. Our results show that in our case studies we are able to trade-off at most of 4% degradation in application quality for up to 62% savings in energy consumption. Furthermore, we fix an energy consumption goal for each application, and the applications were able to adapt at run-time to this goal very closelyMestradoCiência da ComputaçãoMestre em Ciência da Computaçã

A Framework for Energy-efficient Mobile Cloud Offloading

Esilekerkivad nutitelefonide tehnoloogiad on kogenud geomeetrilist kasvu ja on praegu veel tõusuteel. Inimesed kasutavad nutitelefone oma igapäevastes tegevustes nagu e-maili saatmine, fotode ja videode jagamine läbi erinevate peer-to-peersotsiaalvõrgustiku jaoturite ja nii edasi. Viimastel aastatel on nutitelefonid kogenud suuri tehnoloogilisi edusamme ja innovatsiooni seoses töötlusvõimekusega ja saab nüüd kasutada keerukate ja ressursimahukate ülesannete täitmiseks rakendustes, näiteks videode monteerimine ja töötlemine ning objekti äratundmine. Kuigi enamus nutitelefone on oluliselt täiustatud, et hakkama saada suurendatud rakendustega, millel on keerukad arvutusvajadused, piiravad neid ikkagi nende energiavarud, näiteks aku kestvus. Akutehnoloogia ei ole arenenud nii kiirelt kui teised nutitelefoni valdkonnad ja seega arvutusintensiivsete ülesannete läbiviimine põhjustaks selle kiire kahanemise; tõestuseks vajadus pidevalt laadida seadme akut. Mitmeid meetodeid on pakutud välja energiasäästu maksimeerimiseks mobiilsetel seadmetel. Mõned neist aeglustavad keskprotsessor või lülitavad ekraani välja, kui on tegevusetud. Nende hulgast kõige märkimisväärsem tehnika nutitelefoni energia säästmiseks on arvutusvõimsuse koormuse jaotamine. See hõlmab teatud ülesannete töötluse üleviimist piiratud ressurssidega nutitelefonist kaugesse ressursirikkasse seadmesse hõlbustades seega nutitelefoni energia tarbimist. See on küllaltki lai uurimisvaldkond ja on hulganisti panustatud selle ala arendamiseks. Sellele vaatamata on veel palju tööd vaja teha seoses energia säästmisega läbi arvutusvõimsuse koormuse jaotamise korduva ressursimahuka töötlemise ajal. Selles teadusuuringus on me eesmärk vähendada energia tarbimist korduva energiamahuka töötlemise ajal. Me arvestame konteksti teadlikkust pakkudes välja plaanuri mudelit, mis saaks vähendada mobiilse seadme energia kiiret vähenemist seega saavutades meie eesmärgi. Pakume teenusele orienteeritud raamistikku eesmärgiga võimaldada energiatõhusa ülesande täitmist mobiilsel seadmel plaanuri käitumisalgoritmi abil. Me arendame kontseptsiooni tõestuse prototüüpi Android seadmel, et demonstreerida ja hinnata raamistiku energiasäästu võimekust.Emerging smartphone technologies has experienced a geometric increase and is currently still on the rise. People use the smartphone for their day-to-day activities such as sending emails, sharing photos and videos through various peer-to-peer social network hubs and so on. In the last few years, the smartphone has experienced massive technological advancements and innovation with respect to its processing capabilities and can now be used to perform complex, resource-intensive tasks in advanced applications like video editing and processing, and object recognition. Although most smartphones have been greatly augmented to handle advanced applications with complex computational needs, they are still limited in terms of their energy resources i.e. battery life. Battery technology has not evolved as rapidly as other areas of the smartphone and so the execution of computational-intensive tasks would cause its rapid depletion; evidenced by the need to constantly charge the device battery. Many techniques have been proffered to maximize energy conservation on mobile devices. Some of which are slowing down the CPU, or shutting off the screen when idle. Among these, the most notable technique for conserving smartphone energy is computation offloading. This basically involves the transfer of the processing of certain tasks from a resource-constrained smartphone to a remote, resource-rich device thereby facilitating energy conservation on the smartphone. This is a fairly large research area and numerous contributions have been made towards advancement in this field. However, much work is yet to be done with regards to energy conservation through offloading during recurrent resource-intensive processing. In this research study we aim to reduce energy consumption during continuous, energy-intensive processing. We consider context-awareness in proposing a scheduling model that could potentially minimize the speedy depletion of mobile device energy thus achieving our aim. We propose a service-oriented framework towards enabling energy-optimal task execution through a task scheduling offload algorithm. We develop a proof-of-concept prototype on an Android device to demonstrate and evaluate the framework’s energy conserving capabilities

Deep Learning for Mobile Multimedia: A Survey

Deep Learning (DL) has become a crucial technology for multimedia computing. It offers a powerful instrument to automatically produce high-level abstractions of complex multimedia data, which can be exploited in a number of applications, including object detection and recognition, speech-to- text, media retrieval, multimodal data analysis, and so on. The availability of affordable large-scale parallel processing architectures, and the sharing of effective open-source codes implementing the basic learning algorithms, caused a rapid diffusion of DL methodologies, bringing a number of new technologies and applications that outperform, in most cases, traditional machine learning technologies. In recent years, the possibility of implementing DL technologies on mobile devices has attracted significant attention. Thanks to this technology, portable devices may become smart objects capable of learning and acting. The path toward these exciting future scenarios, however, entangles a number of important research challenges. DL architectures and algorithms are hardly adapted to the storage and computation resources of a mobile device. Therefore, there is a need for new generations of mobile processors and chipsets, small footprint learning and inference algorithms, new models of collaborative and distributed processing, and a number of other fundamental building blocks. This survey reports the state of the art in this exciting research area, looking back to the evolution of neural networks, and arriving to the most recent results in terms of methodologies, technologies, and applications for mobile environments

Android Application Development for the Intel Platform

Computer scienc

Discovery and Push Notification Mechanisms for Mobile Cloud Services

Viimase viie aasta jooksul on mobiilsed seadmed nagu sülearvutid, pihuarvutid, nutitelefonid jmt. tunginud peaaegu kõigisse inimeste igapäevaelu tegevustesse. Samuti on põhjalik teadus- ja arendustegevus mobiilsete tehnoloogiate vallas viinud märkimisväärsete täiustusteni riistvara, tarkvara ja andmeedastuse alal. Tänapäeval on mobiilsed seadmed varustatud sisseehitatud sensorite, kaamera, puutetundliku ekraani, suurema hulga mäluga, kuid ka tõhusamate energiatarbemehhanismidega. Lisaks on iOS ja Android operatsioonisüsteemide väljalaske tõttu suurenenud nii mobiilirakenduste arv kui keerukus, pakkudes arvukamalt kõrgetasemelisi rakendusi. Sarnaselt on toimunud olulised arengud ja standardiseerimisele suunatud jõupingutused veebiteenusete valdkonnas ja elementaarsetele veebiteenuste ligipääsu kasutatakse laialdaselt nutitelefonidest. See on viinud loogilise järgmise sammuna veebiteenuste pakkumiseni nutitelefonidest. Telefonidest veebiteenuste pakkumise kontseptsioon ei ole uus ning seda on põhjalikult uurinud Srirama, kes pakkus välja Mobile Host (Mobiilne Veebiteenuse Pakkuja) kontseptsiooni. Algne realisatsioon kasutas aga aegunud tehnoloogiaid nagu JMEE, PersonalJava, SOAP arhitektuur jne. See töö uuendab Mobile Host'i kasutades uusimaid tehnoloogiad, nagu Android OS ja REST arhitektuur, ning pakub välja teenusemootori, mis põhineb Apache Felix'il - OSGi platvormi realisatsioonil piiratud ressurssidega seadmetele. Hämmastava kiirusega toimunud arengud mobiilsete arvutuste vallas võimaldavad uue põlvkonna veebirakenduste loomist valdkondades nagu keskkonnateadlikkus, sotsiaalvõrgustikud, koostöövahendid, asukohapõhised teenused jne. Sellised rakendused saavad ära kasutada Mobile Host'i võimalusi. Selle tulemusena on klientidel ligipääs väga suurele hulgale teenustele, mistõttu tekib vajadus efektiivse teenuste avastamise mehhanismi järele. See töö pakub välja kataloogipõhise avastusmehhanismi võrgu ülekatte toega suurtele, kõrge liikuvusega võrgustikele. See mehhanism toetub OWL-S'le, mis on ontoloogia veebiteenuseid pakkuvate ressursside avastamiseks, väljakutseks, koostamiseks ja jälgimiseks. Töö kirjeldab ka Srirama välja pakutud algupärast teenuste avastamise mehhanismi, mis toetub peer-to-peer võrkudele ja Apache Lucene võtmesõna otsingumootorile. Uurimuse käigus uuendatakse teenuseotsing kasutama Apache Solr'i, Apache Lucene'i viimast versiooni. Teenuste avastust testiti põhjalikult ja tulemused on töös kokkuvõtvalt välja toodud. Mobiilsete tehnoloogiate vallas uuritakse ka võimalust kasutada pilvetehnolologiat laiendamaks mobiilseadmete salvestusmahtu ja töökoormust edastades pilve andme- ja arvutusmahukad ülesanded. See soodustab keerulisemate ja võimalusrohkemate mobiilirakenduste arendust. Pilve delegeeritavate toimingute aeganõudva iseloomu tõttu aga on vajalik asünkroonne mehhanism teavitamaks kasutajat, millal töömahukad tegevused on lõpetatud. Mobiilsete pilveteenuste pakkujad ja vahevara lahendused võivad kasu saada Mobile Host'ist ja selle asünkroonsete teavituste võimekusest. Uurimus esitleb nelja teavitusmehhanismi: AC2DM, APNS, IBM MQTT ja Mobile Host'i põhine teavitus. Töö võtab kokku kvantitatiivse analüüsi tulemused ja toob välja nelja teavitamise lähenemise tugevused ja nõrkused. Lisaks kirjeldatakse CroudSTag rakenduse realisatsiooni - CroudSTag on mobiilirakendus, mille eesmärgiks on sotsiaalsete gruppide moodustamine kasutades näotuvastustehnoloogiat. CroudSTag-i realisatsioon kasutab mobiilseid pilveteenuseid ja Mobile Host'i, et pakkuda oma funktsionaalsust kasutajale.In the last lustrum the mobile devices such as laptops, PDAs, smart phones, tablets, etc. have pervaded almost all the environments where people perform their day-to-day activities. Further, the extensive Research and Development in mobile technologies has led to significant improvements in hardware, software and transmission. Similarly, there are significant developments and standardization efforts in web services domain and basic web services have been widely accessed from smart phones. This has lead to the logical next step of providing web services from the smart phones. The concept of the web service provisioning from smart phones is not new and has been extensively explored by Srirama who proposed the concept of Mobile Host. However, the original implementation considered aged technologies such as JMEE, PersonalJava, SOAP architecture among others. This work updates the Mobile Host to the latest technologies like Android OS and REST architecture and proposes a service engine based on Apache Felix, and OSGI implementation for resource constraint devices. Moreover, the astonishing speed in developments in mobile computing enable the new generation of applications from domains such as context-awareness, social network, collaborative tools, location based services, etc., which benefit from the Mobile Host service provisioning capabilities. As a result the clients have access to a huge number of services available; therefore, an efficient and effective service discovery mechanism is required. The thesis proposes a directory-based with network overlay support discovery mechanism for large networks with high mobility. The proposed discovery mechanism relies in OWL-S, an ontology for service discovery, invocation, composition, and monitoring of web resources. The work also considers the original service discovery mechanism proposed by Srirama relying in peer-to-peer networks and Apache Lucene, a keyword search engine. The study updates the service search to Apache Solr, the latest development for Apache Lucene. The service discovery was extensively tested and the results are summarized in this work. Mobile technologies are looking into the clouds for extending their capabilities in storage and processing by offloading data and process intensive tasks. This fosters the development of more complex and rich mobile applications. However, due to the time-consuming nature of the tasks delegated to the clouds, an asynchronous mechanism is necessary for notifying the user when the intensive tasks are completed. Mobile cloud service providers and Middleware solutions might benefit from Mobile Host and its asynchronous notification capabilities. The study presents four push notification mechanisms being AC2DM, APNS, IBM MQTT and Mobile Host based push notification. The work summarizes the results of a quantitative analysis and highlights the strengths and weakness of the four notifications approaches. In addition, it explains CroudSTag realization, a mobile application that aims the social group formation by means of facial recognition that relies in mobile cloud services and Mobile Host to provide its functionality to the user