11 research outputs found
Dynamic Choreographies: Theory And Implementation
Programming distributed applications free from communication deadlocks and
race conditions is complex. Preserving these properties when applications are
updated at runtime is even harder. We present a choreographic approach for
programming updatable, distributed applications. We define a choreography
language, called Dynamic Interaction-Oriented Choreography (AIOC), that allows
the programmer to specify, from a global viewpoint, which parts of the
application can be updated. At runtime, these parts may be replaced by new AIOC
fragments from outside the application. AIOC programs are compiled, generating
code for each participant in a process-level language called Dynamic
Process-Oriented Choreographies (APOC). We prove that APOC distributed
applications generated from AIOC specifications are deadlock free and race free
and that these properties hold also after any runtime update. We instantiate
the theoretical model above into a programming framework called Adaptable
Interaction-Oriented Choreographies in Jolie (AIOCJ) that comprises an
integrated development environment, a compiler from an extension of AIOCs to
distributed Jolie programs, and a runtime environment to support their
execution.Comment: arXiv admin note: text overlap with arXiv:1407.097
Extending the battery life of mobile device by computation offloading
Doctor of PhilosophyComputing and Information SciencesDaniel A. AndresenThe need for increased performance of mobile device directly conflicts with the desire for longer battery life. Offloading computation to resourceful servers is an effective method to reduce energy consumption and enhance performance for mobile applications. Today, most mobile devices have fast wireless link such as 4G and Wi-Fi, making computation offloading a reasonable solution to extend battery life of mobile device. Android provides mechanisms for creating mobile applications but lacks a native scheduling system for determining where code should be executed. We present Jade, a system that adds sophisticated energy-aware computation offloading capabilities to Android applications. Jade monitors device and application status and automatically decides where code should be executed. Jade dynamically adjusts offloading strategy by adapting to workload variation, communication costs, and device status. Jade minimizes the burden on developers to build applications with computation offloading ability by providing easy-to-use Jade API. Evaluation shows that Jade can effectively reduce up to 37% of average power consumption for mobile device while improving application performance