Teenustele orienteeritud ja tõendite-teadlik mobiilne pilvearvutus

Arvutiteaduses on kaks kõige suuremat jõudu: mobiili- ja pilvearvutus. Kui pilvetehnoloogia pakub kasutajale keerukate ülesannete lahendamiseks salvestus- ning arvutusplatvormi, siis nutitelefon võimaldab lihtsamate ülesannete lahendamist mistahes asukohas ja mistahes ajal. Täpsemalt on mobiilseadmetel võimalik pilve võimalusi ära kasutades energiat säästa ning jagu saada kasvavast jõudluse ja ruumi vajadusest. Sellest tulenevalt on käesoleva töö peamiseks küsimuseks kuidas tuua pilveinfrastruktuur mobiilikasutajale lähemale? Antud töös uurisime kuidas mobiiltelefoni pilveteenust saab mobiilirakendustesse integreerida. Saime teada, et töö delegeerimine pilve eeldab mitmete pilve aspektide kaalumist ja integreerimist, nagu näiteks ressursimahukas töötlemine, asünkroonne suhtlus kliendiga, programmaatiline ressursside varustamine (Web APIs) ja pilvedevaheline kommunikatsioon. Nende puuduste ületamiseks lõime Mobiilse pilve vahevara Mobile Cloud Middleware (Mobile Cloud Middleware - MCM) raamistiku, mis kasutab deklaratiivset teenuste komponeerimist, et delegeerida töid mobiililt mitmetele pilvedele kasutades minimaalset andmeedastust. Teisest küljest on näidatud, et koodi teisaldamine on peamisi strateegiaid seadme energiatarbimise vähendamiseks ning jõudluse suurendamiseks. Sellegipoolest on koodi teisaldamisel miinuseid, mis takistavad selle laialdast kasutuselevõttu. Selles töös uurime lisaks, mis takistab koodi mahalaadimise kasutuselevõttu ja pakume lahendusena välja raamistiku EMCO, mis kogub seadmetelt infot koodi jooksutamise kohta erinevates kontekstides. Neid andmeid analüüsides teeb EMCO kindlaks, mis on sobivad tingimused koodi maha laadimiseks. Võrreldes kogutud andmeid, suudab EMCO järeldada, millal tuleks mahalaadimine teostada. EMCO modelleerib kogutud andmeid jaotuse määra järgi lokaalsete- ning pilvejuhtude korral. Neid jaotusi võrreldes tuletab EMCO täpsed atribuudid, mille korral mobiilirakendus peaks koodi maha laadima. Võrreldes EMCO-t teiste nüüdisaegsete mahalaadimisraamistikega, tõuseb EMCO efektiivsuse poolest esile. Lõpuks uurisime kuidas arvutuste maha laadimist ära kasutada, et täiustada kasutaja kogemust pideval mobiilirakenduse kasutamisel. Meie peamiseks motivatsiooniks, et sellist adaptiivset tööde täitmise kiirendamist pakkuda, on tagada kasutuskvaliteet (QoE), mis muutub vastavalt kasutajale, aidates seeläbi suurendada mobiilirakenduse eluiga.Mobile and cloud computing are two of the biggest forces in computer science. While the cloud provides to the user the ubiquitous computational and storage platform to process any complex tasks, the smartphone grants to the user the mobility features to process simple tasks, anytime and anywhere. Smartphones, driven by their need for processing power, storage space and energy saving are looking towards remote cloud infrastructure in order to solve these problems. As a result, the main research question of this work is how to bring the cloud infrastructure closer to the mobile user? In this thesis, we investigated how mobile cloud services can be integrated within the mobile apps. We found out that outsourcing a task to cloud requires to integrate and consider multiple aspects of the clouds, such as resource-intensive processing, asynchronous communication with the client, programmatically provisioning of resources (Web APIs) and cloud intercommunication. Hence, we proposed a Mobile Cloud Middleware (MCM) framework that uses declarative service composition to outsource tasks from the mobile to multiple clouds with minimal data transfer. On the other hand, it has been demonstrated that computational offloading is a key strategy to extend the battery life of the device and improves the performance of the mobile apps. We also investigated the issues that prevent the adoption of computational offloading, and proposed a framework, namely Evidence-aware Mobile Computational Offloading (EMCO), which uses a community of devices to capture all the possible context of code execution as evidence. By analyzing the evidence, EMCO aims to determine the suitable conditions to offload. EMCO models the evidence in terms of distributions rates for both local and remote cases. By comparing those distributions, EMCO infers the right properties to offload. EMCO shows to be more effective in comparison with other computational offloading frameworks explored in the state of the art. Finally, we investigated how computational offloading can be utilized to enhance the perception that the user has towards an app. Our main motivation behind accelerating the perception at multiple response time levels is to provide adaptive quality-of-experience (QoE), which can be used as mean of engagement strategy that increases the lifetime of a mobile app

Context Sensor Data on Demand for Mobile Users Supported by XMPP

Tänapäeval võimaldavad tehnoloogilised edusammud kasutaja käitumise seiremeetodites automatiseerida teatud arvutusülesandeid, mis täidetakse kasutaja kavatsust prognoosides. Nutitelefonid rikastavad mobiilseid rakendusi prognoosiva käitumisega kasutatavuses, mis võimaldab käitumismustritega sammu pidada. Üldiselt on sellist käitumist võimalik saavutada nutitelefoni enda vahenditega, kasutades telefoni sisse ehitatud mikromehaanilisi seadmeid, mis võimaldavad keskkonda tajuda. Lisaks võivad mobiilsed rakendused kasutaja mobiilse kogemuse rikastamiseks lõigata kasu keskkonda integreeritud hajuslausteenustest, nagu näiteks ümbrustundlike mängude, kodu automatiseerimise tarkvara jms puhul. Ent mobiilikasutajatele suunatud lausteenuseid pakkuvatel elektroonilistel seadmetel, mis koguvad sensorite abi keskkonnast informatsiooni, on teatavad riistvaralised piirangud (arvutusjõudlus, mälu, salvestusmeedia, energiatarbimine jne). Seega, lausüsteemid ei ole võimelised nõudluse suurenemisel skaleeruma ega rakendama suurt arvutusjõudlust. Töö eesmärgiks on pakkuda lahendus ületamaks skaleeruvuse, andmete terviklikkuse säilitamise ja vähese arvutusjõudluse probleeme ning rikastada nutitelefoni rakendusi detailsete kasutajapõhiste andmetega. Eesmärgi saavutamiseks transporditakse sensoritelt kogutud informatsioon optimiseeritud XMPP protokolli abiga Arduino mikrokontrollerist pilvesüsteemi. Süsteemi ehitamiseks kasutatakse Arduino poolt pakutavat odavat riistvara, samas kui pilvesüsteemi usaldusväärset ja kõrge kättesaadavusega vahendeid kasutatakse mikrokontrollerist saadetud andmete salvestamiseks ja edaspidiseks töötlemiseks. Töö käigus testiti mikrokontrolleri energia nõudlust, kasutades 9V patareid, nii juhtme kui ka juhtmevaba liidesega. Tulemused tõestasid eeldustele vastupidiselt, et juhtmevaba süsteemi energia nõudlus on suurem. Lisaks testiti vabavara XMPP serveri jõudlust pilvesüsteemi keskkonnas ning tulemused näitasid, et XMPP võimaldab üheaegselt serveerida suure hulga kasutajaid

POLICY-BASED MIDDLEWARE FOR MOBILE CLOUD COMPUTING

Mobile devices are the dominant interface for interacting with online services as well as an efficient platform for cloud data consumption. Cloud computing allows the delivery of applications/functionalities as services over the internet and provides the software/hardware infrastructure to host these services in a scalable manner. In mobile cloud computing, the apps running on the mobile device use cloud hosted services to overcome resource constraints of the host device. This approach allows mobile devices to outsource the resource-consuming tasks. Furthermore, as the number of devices owned by a single user increases, there is the growing demand for cross-platform application deployment to ensure a consistent user experience. However, the mobile devices communicate through unstable wireless networks, to access the data and services hosted in the cloud. The major challenges that mobile clients face when accessing services hosted in the cloud, are network latency and synchronization of data. To address the above mentioned challenges, this research proposed an architecture which introduced a policy-based middleware that supports user to access cloud hosted digital assets and services via an application across multiple mobile devices in a seamless manner. The major contribution of this thesis is identifying different information, used to configure the behavior of the middleware towards reliable and consistent communication among mobile clients and the cloud hosted services. Finally, the advantages of the using policy-based middleware architecture are illustrated by experiments conducted on a proof-of-concept prototype

Developing a Mobile Game Environment to Support Disadvantaged Learners

Schmitz, B., Hoffmann, M., Klamma, R., Klemke, R., & Specht, M. (2012). Developing a Mobile Game Environment to Support Disadvantaged Learners. Proceedings of 12th IEEE International Conference on Advanced Learning Technologies (ICALT 2012) (pp. 223-227). July, 4-6, 2012, Rome, Italy: IEEE Computer Society CPS.This paper reports on the development of WeBuild, a mobile learning game designed to engage learners difficult to reach with IT learning. The development is based on a mobile game engine for the Android smart phone that was devised to support the required multiplayer and location based services. We played and tested the mobile learning game in a training facility of the building industry. The results indicate that the learners accepted the game for the low entry barriers and were motivated to use the game in an educational context. This paper describes the WeBuild prototype and the underlying game engine. Eventually, it presents results from the game session that was carried to assess interface and gameplay usability, technical functionality and motivational aspects of the game design

Multi-Access Edge Computing: Open issues, Challenges and Future Perspective

Latency minimization is a pivotal aspect in provision of real time services while adhering to Quality of Experience (QoE) parameters for assuring spectral efficiency. Edge Cloud Computing, being a potential research dimension in the realm of 5G networks, targets to enhance the network efficiency by harnessing activeness of both cloud computing and mobile devices in user's proximity. Keeping in view the far ranging impact of Edge Cloud Computing in future mobile generations, a comprehensive review of the prevalent Edge Cloud Computing frameworks and approaches is presented with a detailed comparison of its classifications through various QoS metrics (pertinent to network performance and overheads associated with deployment/migration). Considering the knowledge accumulated, procedures analysed and theories discussed, the paper provides a comprehensive overview on sate-of-the-art and future research directions for multi-access mobile edge computing

Semantic reasoning on the edge of internet of things

Abstract. The Internet of Things (IoT) is a paradigm where physical objects are connected with each other with identifying, sensing, networking and processing capabilities over the Internet. Millions of new devices will be added into IoT network thus generating huge amount of data. How to represent, store, interconnect, search, and organize information generated by IoT devices become a challenge. Semantic technologies could play an important role by encoding meaning into data to enable a computer system to possess knowledge and reasoning. The vast amount of devices and data are also challenges. Edge Computing reduces both network latency and resource consumptions by deploying services and distributing computing tasks from the core network to the edge. We recognize four challenges from IoT systems. First the centralized server may generate long latency because of physical distances. Second concern is that the resource-constrained IoT devices have limited computing ability in processing heavy tasks. Third, the data generated by heterogeneous devices can hardly be understood and utilized by other devices or systems. Our research focuses on these challenges and provide a solution based on Edge computing and semantic technologies. We utilize Edge computing and semantic reasoning into IoT. Edge computing distributes tasks to the reasoning devices, which we call the Edge nodes. They are close to the terminal devices and provide services. The newly added resources could balance the workload of the systems and improve the computing capability. We annotate meaning into the data with Resource Description Framework thus providing an approach for heterogeneous machines to understand and utilize the data. We use semantic reasoning as a general purpose intelligent processing method. The thesis work focuses on studying semantic reasoning performance in IoT system with Edge computing paradigm. We develop an Edge based IoT system with semantic technologies. The system deploys semantic reasoning services on Edge nodes. Based on IoT system, we design five experiments to evaluate the performance of the integrated IoT system. We demonstrate how could the Edge computing paradigm facilitate IoT in terms of data transforming, semantic reasoning and service experience. We analyze how to improve the performance by properly distributing the task for Cloud and Edge nodes. The thesis work result shows that the Edge computing could improve the performance of the semantic reasoning in IoT

On Programmable Interactions: Principles, Concepts and Challenges of Co-Located and Social Interplay

Computing machines and humans interacting has long followed similar principles – A human gives an input command to a machine, which the machine then executes, gives an output, and waits for the next human input. Thus the interactions are user-initiated, requiring constant active participation, and much attention. Despite this, the number of such interactions has kept increasing since computing has now pervaded all areas of human life. Take mobile devices as an example: they are now considered as magic remote controllers that enable interaction with the whole world. Hence, people are now glued to their mobiles, which makes them more detached from their surroundings and other people nearby. Consequently, there is no need nor desire to socialize with other people in close proximity. Presently, the physical world and the cyber world are melting into each other, and new cyber-physical devices are rapidly emerging. This means that an ever-increasing number of computers are awaiting user input.This wide array of computing devices and heterogeneous networking capabilities have great potential for improving the ways human interactions with computing can work. The problem is that the current ways of implementing software are not well-suited for implementing interactions where multiple co-located people and devices participate. The tools mainly support implementing apps where a sole user interacts with the device, and possibly, remotely with another person. Vendor-neutrality also causes many challenges as some manufacturers only focus on improving interoperability within ecosystems.This thesis approaches computing with a novel concept of programmable interactions. The idea is to consider the interactions as first class citizens in software development. Instead of focusing on how a human interacts with a machine, the focus is on how the machines in the same space can share resources and jointly interact with each other, serving the humans – the programmable interactions are based on principles that put humans into a central role in the interactions. For developing such interactions, the thesis presents an Action-Oriented Programming model and its runtime environment. Human and social aspects are considered with a concept of companion devices. These companions carry personal profiles about their owners, and represent them for other devices that are nearby. The devices socialize and interact with each other as well as with their owners proactively, meaning that they are also allowed to initiate interactions.The approaches and concepts that are presented form the basis for developing software where interactions play a key role. These programmable interactions are based on a set of human-centric principles, and the task of enabling them is highly demanding. Therefore, enabling programmable interactions should rather be considered as a continuous process that improves over time. The most crucial challenges have been identified in this thesis together with a view on how the current technology can be used to respond to them