Exploiting Personal Web Servers for Mobile Context-Aware Applications

There is an increasing trend in moving desktop applications to web browsers, even when the web server is running on the same desktop machine. In this paper we go further in this direction and show how to combine a web server, a web application framework (enhanced to support desktop-like Model-View-Controller interaction) and a context-aware architecture to develop web based mobile context-aware applications. By using this approach we take advantage of the well established web paradigm to design the GUIs and the inherent ability of the web to mash up applications with external components (such as Google Maps). On top of that, since the web server runs on the device itself, the application can access local resources (such as disk space or sensing devices, which are indispensable for context-aware systems) avoiding the sandbox model of the web browsers. To illustrate our approach we show how a mobile hypermedia system has been built on top of our platform.Facultad de InformáticaLaboratorio de Investigación y Formación en Informática Avanzada (LIFIA

Compositional schedulability analysis of real-time actor-based systems

We present an extension of the actor model with real-time, including deadlines associated with messages, and explicit application-level scheduling policies, e.g.,"earliest deadline first" which can be associated with individual actors. Schedulability analysis in this setting amounts to checking whether, given a scheduling policy for each actor, every task is processed within its designated deadline. To check schedulability, we introduce a compositional automata-theoretic approach, based on maximal use of model checking combined with testing. Behavioral interfaces define what an actor expects from the environment, and the deadlines for messages given these assumptions. We use model checking to verify that actors match their behavioral interfaces. We extend timed automata refinement with the notion of deadlines and use it to define compatibility of actor environments with the behavioral interfaces. Model checking of compatibility is computationally hard, so we propose a special testing process. We show that the analyses are decidable and automate the process using the Uppaal model checke

Exploiting Personal Web Servers for Mobile Context-Aware Applications

There is an increasing trend in moving desktop applications to web browsers, even when the web server is running on the same desktop machine. In this paper we go further in this direction and show how to combine a web server, a web application framework (enhanced to support desktop-like Model-View-Controller interaction) and a context-aware architecture to develop web based mobile context-aware applications. By using this approach we take advantage of the well established web paradigm to design the GUIs and the inherent ability of the web to mash up applications with external components (such as Google Maps). On top of that, since the web server runs on the device itself, the application can access local resources (such as disk space or sensing devices, which are indispensable for context-aware systems) avoiding the sandbox model of the web browsers. To illustrate our approach we show how a mobile hypermedia system has been built on top of our platform.Facultad de InformáticaLaboratorio de Investigación y Formación en Informática Avanzada (LIFIA

A flexible fine-grained adaptive framework for parallel mobile hybrid cloud applications

Mobile devices have become ubiquitous and provide ever richer content and functionality. At the same time, applications are also becoming more complex and require ever increasing amount of computational power and energy. With cloud computing providing unlimited elastic on-demand resources, supporting mobile devices with cloud allows overcoming limitations of mobile devices. This is generally known as Mobile Cloud Computing (MCC) and can be achieved through code offloading that selects computationally or data intensive parts of an application, outsources them to more-resourceful spaces and brings back the final results. While code offloading has been widely studied in the past within the context of distributed systems and grid computing, applying it to current mobile applications requires significant amount of manual changes to existing application codes. An alternative is to outsource the entire application process or the whole virtual machine in which the application is running. This solution assumes running the same code on a more-resourceful system is more efficient, but it is coarse-grained and requires significant amount of data to be transferred. Furthermore, requirements and expectations from mobile applications vary considerably by different users using wide range of mobile devices in various environmental conditions. This diversity in requirements and expectations creates wide range of target offloading goals, ranging from maximizing application performance to minimizing mobile energy consumption. The increased dynamicity and complexity of mobile cloud applications requires open systems that interact with the environment while addressing application-specific constraints, user expectations and hardware limitations. Our goal is to facilitate mobile cloud application development by masking all the complexity of mobile-to-cloud code offloading without requiring application developers to rewrite their code or perform additional manual work. Our focus is on separating the application logic, to be developed by programmers, from the application component configuration and distribution, to be adjusted transparently and dynamically at run-time. Our framework is fine-grained, supporting mobile application configuration and distribution at the granularity of individual components; it is flexible, allowing organizations, application developers, or end-users easily adjust target offloading goal or define policy-driven restrictions on offloading budget, execution quality, or privacy and move around of components without modifying the existing application codes; and it is adaptive, addressing the dynamicity in run-time conditions and end-user contexts. It further supports component distribution in a hybrid cloud environment consisting of multiple public and private cloud spaces. Finally, it provides a new code offloading model that supports fully parallel program execution, where application components located at mobile device and multiple cloud spaces are executed independently but concurrently. The proposed solution can be divided into three main parts: First, a light-weight monitoring system, called Monitor, to capture dynamic environmental parameters and end-user context, profile application resource usage and communications, as well as monitoring availability and performance of cloud resources. Profiling energy consumption per specific application components is primary of importance and requires design and development of a fine-grained automatic energy consumption model, as most mobile devices do not provide any tool for direct measurement of consumed energy and different applications with arbitrary number of components might be running at any time. Second, we design and implement two independent performance-based and energy-based models to enable transparent automatic configuration and distribution of application code and data components that address specific organization, application, and end-user requirements. These models leverage dynamic information from the Monitor on run-time parameters, energy and resource usage of different components, and application characteristics to optimize application performance or mobile energy consumption with respect to a predefined policy. Finally, we design and develop a proof-of-concept framework called IMCM, Illinois Mobile Cloud Management, that embodies the described components to enable fine-grained adaptive application component configuration and distribution, while providing flexibility in terms of adjusting desired target optimization goal or defining additional policy-driven constraints on offloading budget, quality of service per resource, and privacy. Evaluations are carried out using a suite of benchmark applications, including computationally-intensive, I/O-intensive, communication-intensive and combined multi-purpose applications. Compared to sequential execution on a mobile device, these empirical benchmarks using IMCM framework result in speedups or energy-savings factor of over 50 times

Performance evaluation and model checking of probabilistic real-time actors

This dissertation is composed of two parts. In the first part, performance evaluation and verification of safety properties are provided for real-time actors. Recently, the actor-based language, Timed Rebeca, was introduced to model distributed and asynchronous systems with timing constraints and message passing communication. A toolset was developed for automated translation of Timed Rebeca models to Erlang. The translated code can be executed using a timed extension of McErlang for model checking and simulation. In the first part of this dissertation, we induce a new toolset that provides statistical model checking of Timed Rebeca models. Using statistical model checking, we are now able to verify larger models against safety properties comparing to McErlang model checking. We examine the typical case studies of elevators and ticket service to show the efficiency of statistical model checking and applicability of our toolset. In the second part of this dissertation, we enhance our modeling ability and cover more properties by performance evaluation and model checking of probabilistic real-time actors. Distributed systems exhibit probabilistic and nondeterministic behaviors and may have time constraints. Probabilistic Timed Rebeca (PTRebeca) is introduced as a timed and probabilistic actor-based language for modeling distributed real-time systems with asynchronous message passing. The semantics of PTRebeca is a Timed Markov Decision Process (TMDP). We provide SOS rules for PTRebeca, and develop two toolsets for analyzing PTRebeca models. The first toolset automatically generates a TMDP model from a PTRebeca model in the form of the input language of the PRISM model checker. We use PRISM for performance analysis of PTRebeca models against expected reachability and probabilistic reachability properties. Additionally, we develop another toolset to automatically generate a Markov Automaton from a PTRebeca model in the form of the input language of the Interactive Markov Chain Analyzer (IMCA). The IMCA can be used as the back-end model checker for performance analysis of PTRebeca models against expected reachability and probabilistic reachability properties. We present the needed time for the analysis of different case studies using PRISM-based and IMCA-based approaches. The IMCA-based approach needs considerably less time, and so has the ability of analyzing significantly larger models. We show the applicability of both approaches and the efficiency of our tools by analyzing a few case studies and experimental results.Þessi ritgerð er tvískipt. Í fyrri hlutanum er farið í mat og sannprófun á eiginleikum öryggis í rauntímalíkönum. Fyrir stuttu síðan var leikendabyggða málið, Timed Rebeca, notað við líkana dreifingu og ósamstillt kerfi með tímastillingu og samskipti í skilaboðum. Búið var til verkfærasett fyrir sjálfvirka þýðingu á Timed Rebeca líkön yfir í Erlang. Hægt er að nota þýdda kóðann með því að nota tímastillta framlengingu af McErlang fyrir líkanaprófun og hermun. Í fyrri hluta þessarar ritgerðar, ætlum við að kynna verkfærasettið sem veitir tölfræðilega prófun á líkön á Timed Rebeca líkön. Með því að nota tölfræðileg próf á líkön er núna hægt að sannreyna stærri líkön eins og í öryggiskröfum McErlang. Við rannsökum dæmigerðar ferilsathuganir af lyftum og miðasölu til að sýna fram á skilvirkni tölfræðilegra líkana og beitingu verkfærasettsins okkar. Í seinni hluta þessarar ritgerðar aukum við við getu líkanagerðarinnar og við náum yfir fleiri eiginleika með mati á framkvæmd og prófunum á líkönum á líkinda rauntíma leikara. Dreifð kerfi sýna líkindi og brigðgenga hegðun sem kunna að hafa tímamörk. Probabilistic Timed Rebeca (PTRebeca) er kynnt sem tímastillt og líkinda leikarabyggt mál líkindadreifðra rauntímakerfa með ósamstillta sendingu skilaboða. Merkingarfræði PTRebeca er Timed Markov Decision Process (TMDP). Við verðum með SOS reglur fyrir PTRebeca, og þróum tvö verkfærasett til að greina PTRebeca líkön.The work on this dissertation was supported by the project "Timed Asynchronous Reactive Objects in Distributed Systems: TARO" (nr.110020021) of the Icelandic Research Fund

Towards Context-Aware Web Applications

Abstract. In order to guarantee certain levels of QoS, a Web application needs to adapt itself to different execution contexts. However, because of the lack of coordination support in Web platforms, service providers respond to the challenge by simply providing multiple versions of a Web application, one for each context. We argue this top-down approach is neither efficient nor scalable: developing a context-specific application requires considerable effort and expertise while the ever-changing Internet never stops generating interesting contexts which can be exploited for better deployment. As an alternative, we propose a three-layer, bottomup approach to building context-aware Web applications. At the bottom layer, we characterize a context-specific Web application with a particular component distribution plan which provides details for composing individual objects. In the middle layer, recursively defined configurations provide a bridge which relates high-level context features to low-level component distribution properties, where a configuration is a combination of configurations and/or component distribution properties. At the top level, a context management system selects desirable configurations according to the execution contexts.