Julien Ponge

Various Extensions for the Ambient OSGi Framework

OSGi is a wrapper above the Java Virtual Machine that embraces two concepts: component approach and service-oriented programming. The component approach enables a Java run-time to host several concurrent applications, while the service-oriented programming paradigm allows the decomposition of applications into independent units that are dynamically bound at runtime. Combining component and service-oriented programming greatly simplifies the implementation of highly adaptive, constantly evolving applications. This, in turn, is an ideal match to the requirements and constraints of ambient intelligence computing, such as adaptation to changes associated with context evolution. OSGi particularly fits ambient requirements and constraints by absorbing and adapting to changes associated with context evolution. However, OSGi needs to be finely tuned in order to integrate ambient specific issues. This paper focuses on Zero-configuration architecture, Multi-provider framework, and Limited resource requirements. The authors studied many OSGi improvements that should be taken into account when building OSGi-based gateways. This paper summarizes the INRIA Amazones teamwork (http://amazones.gforge.inria.fr/) on extending OSGi specifications and implementations to cope with ambient concerns. This paper references three main concerns: management, isolation, and security.

Are Middlewares Ready for Multi-robots Systems?

Autonomous robot fleets are complex systems that require the interaction and communication between heterogeneous hardware and software. Despite many years of work in robotics, there is still a lack of established software architecture and middleware, in particular for large scale multi-robots systems. Many research teams are still writing specific hardware orientated software that is very tied to a robot. This vision makes sharing modules or extending existing code difficult. A robotic middleware should be designed to abstract the low-level hardware architecture, facilitate communication and integration of new software. In this paper, we present and compare seven existing middlewares capable of being used in multi-robot systems. We also present two dedicated cloud based multi-robots platforms. After this analysis, we discuss why a cloud of robots and not a cloud for robots is more suitable in a fleet context.

Golo, a dynamic, light and efficient language for post-invokedynamic JVM

This paper introduces Golo, a simple dynamic programming language for the Java Virtual Machine (JVM) that has been designed to leverage the capabilities of the new Java 7 invokedynamic instruction and API (JSR 292). Golo has its own language constructs being designed with invokedynamic in mind, whereas existing dynamic languages for the JVM such as Groovy, JRuby or Nashorn have to adapt language constructions which are sometimes hard to optimize. Coupled with a minimal runtime that directly uses the Java SE API, Golo is an interesting language for rapid prototyping, polyglot application embedding, research (e.g., runtime extensions, language prototyping) and teaching (e.g., programming, dynamic language runtime implementation). We show that the language design around invokedynamic allows for a very concise runtime code base with performance figures that compare favorably against Java and other dynamic JVM languages. We also discuss its future directions, either as part of Golo or through language and runtime research extensions.

ROCS: a remotely provisioned OSGi framework for ambient systems

One of the challenges of ambient systems lies in providing all the available services of the environment to the ambient devices, even if they do not physically host those services. Although this challenge has come to find a solution through cloud computing, there are still few devices and operating systems that enable applications execution by only uploading the required components into the runtime environment. The ROCS (Remote OSGi Caching Service) framework is a novel proposal which relies on a heavy-weighted standard Java/OSGi stack. It is distributed between class servers and ambient devices to provide full functionalities to resource-constrained environments. The ROCS framework provides improvements in two areas. First, it defines a minimal bootstrap environment that runs a standard Java/OSGi stack. Secondly, it provides an architecture for loading any necessary missing class from remote servers into memory at runtime. Our first results show similar performances when classes are either remotely downloaded into the main memory from a local network or from a flash drive. These results suggest a way to design minimalistic middleware that dynamically obtain their applications from the network as a first step towards cloud-aware operating systems.

Towards a Decoupled Context-Oriented Programming Language for the Internet of Things

Easily programming behaviors is one major issue of a large and reconfigurable deployment in the Internet of Things. Such kind of devices often requires to externalize part of their behavior such as the sensing, the data aggregation or the code offloading. Most existing context-oriented programming languages integrate in the same class or close layers the whole behavior. We propose to abstract and separate the context tracking from the decision process, and to use event-based handlers to interconnect them. We keep a very easy declarative and non-layered programming model. We illustrate by defining an extension to Golo - a JVM-based dynamic language.

Spontaneous Proximity Clouds: Making Mobile Devices to Collaborate for Resource and Data Sharing

The base motivation of Mobile Cloud Computing was empowering mobile devices by application offloading onto powerful cloud resources. However, this goal can’t entirely be reached because of the high offloading cost imposed by the long physical distance between the mobile device and the cloud. To address this issue, we propose an application offloading onto a nearby mobile cloud composed of the mobile devices in the vicinity - a Spontaneous Proximity Cloud. We introduce our proposed dynamic, ant-inspired, bi-objective offloading middleware - ACOMMA, and explain its extension to perform a close mobile application offloading. With the learning-based offloading decision-making process of ACOMMA, combined to the collaborative resource sharing, the mobile devices can cooperate for decision cache sharing. We evaluate the performance of ACOMMA in collaborative mode with real benchmarks - Face Recognition and Monte-Carlo algorithms - and achieve 50% execution time gain.

Automated application offloading through ant-inspired decision-making

The explosive trend of smartphone usage as the most effective and convenient communication tools of human life in recent years make developers build ever more complex smartphone applications. Gaming, navigation, video editing, augmented reality, and speech recognition applications require considerable computational power and energy. Although smartphones have a wide range of capabilities - GPS, WiFi, cameras their inherent limitations - frequent disconnections, mobility - and significant constraints - size, lower weights, longer battery life make difficult to exploiting their full potential to run complex applications. Several research works have proposed solutions in application offloading domain, but few ones concerning the highly changing properties of the environment. To address these issues, we realize an automated application offloading middleware, ACOMMA, with dynamic and re-adaptable decision-making engine. The decision engine of ACOMMA is based on an ant-inspired algorithm.

SDfR - Service Discovery for Robots

Multi-robots systems require dedicated tools and models for their design and the deployment. Our approach proposes service-oriented architecture that can simplify the development and deployment. In order to solve the problem of neighbors and service discovery in an ad-hoc network, the fleet robot needs a protocol that is able to constantly discover new robots in its coverage area. To this end we propose a robotic middleware, SDfR, that is able to provide service discovery. This protocol is an extension of the Simple Service Discovery Protocol (SSDP) used in Universal Plug and Play (UPnP) to dynamic networks generated by the mobility of the robots. Even if SDfR is platform independent, we propose a ROS (ROS, 2014) integration in order to facilitate the usage. We evaluate a series of overhead benchmarking across static and dynamic scenarios. We also present some use-cases where our proposal was successfully tested.