Describing Dynamism in Service Dependencies: Industrial Experience and Feedbacks

Talavera

2015 International Conference on Distributed Computing in Sensor Systems

et al. 2015

The current ubiquity of smart phones with mobile Internet and several short-range wireless interfaces (NFC, Bluetooth, Bluetooth Smart) and the fact that these devices are carried almost anytime and anywhere by users, enables potentially new pervasive sensing applications where smartphones can act as universal hubs for interaction with sensors (or sensor networks) that have only short-range wireless connectivity. Thus, in next years we can expect an increasing number of long-term and large-scale deployments for various crowd-sourced monitoring applications, such as environment monitoring, domestic utility meter reading, urban monitoring, etc. In this paper, we present the implementation and initial performance results with our mobile-cloud middleware that enables such opportunistic mobile sensing. One of the singular features of our middleware is the capability to discover, dynamically download and install sensor-specific transcoding modules on the mobile phone according to the encountered sensor type and make.

Section: Fig 3 Mobile Application Architecturementioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

An Adaptive Middleware for Opportunistic Mobile Sensing

Talavera

2015 International Conference on Distributed Computing in Sensor Systems

et al. 2015

“…When we update a component A, we have to update all previous instances of component A. For such, we need a mechanism able to transparently update the component instances and to keep their references for the application [4]. Thus, we have developed the wrapper, which is a container for component instances, that manages the dynamism related to the process of update component instances.…”

Section: Implementation Detailsmentioning

confidence: 99%

“…The authors present an architectural model addressing flexible and adaptive composition of services in Very Large Scale (VLS) IoT systems by exploiting the concepts of service orchestration (i.e., centralized approach) and choreography (i.e., decentralized approach). While the authors follow a service orchestration/choreography model, which seems to be more adequate for web applications, we chose following the serviceoriented component approach [4] [5]. Although the authors address VLS IoT systems, there is no information about how the architecture achieves scalability, and how the adaptation engineer defines the service composition.…”

Section: Related Workmentioning

confidence: 99%

“…The coordination of decentralized dynamic adaptation of software components in distributed systems has always been a challenge, because of problems such as management of dynamism, service discovery, disruption of remote services, and transient situations where part of the system is updated [4] [16]. With the ongoing trend towards networked and mobile embedded systems, adaptation become even more necessary as the applications must be capable of discovering the computing resources in their near environment and the corresp onding capabilities of sensors and actuators.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A middleware for managing dynamic software adaptation

Proceedings of the 13th Workshop on Adaptive and Reflective Middleware

Endler

2014

The design and development of adaptive systems brings new challenges since the dynamism of such systems is a multifaceted concern that range from mechanisms to enable the adaptation on the software level to the (self-) management of the entire system using adaptation plans or system administrator, for instance. Networked and mobile embedded systems are examples of systems where dynamic adaptation become even more necessary as the applications must be capable of discovering the computing resources in their near environment. While most of the current research is concerned with low-level adaptation techniques (i.e., how to dynamically deploy new components or change parameters), we are focused in providing management of distributed dynamic adaptation and facilitating the development of adaptation plans. In this paper, we present a middleware tailored for mobile embedded systems that supports distributed dynamic software adaptation, in transactional and non-transactional fashion, among mobile devices. We also present results of initial evaluation.

A robust reconfiguration protocol for the dynamic update of component‐based software systems

2017

This paper focuses on the dynamic reconfiguration of component-based software systems. From a structural point of view, such systems are made of components linked together through their provided and required services, the code of components being defined by modules (e.g., jar files). Today, the ability to reconfigure component-based systems at runtime faces limitations. Some component frameworks allow to dynamically reconfigure components -starting or stopping them, or changing how they are wired together for instancebut forbid any dynamic evolution of the modules defining their code. Other frameworks allow to dynamically update modules but at the cost of loosing control on component wires, preventing software architects or tools alike to decide how components are wired together. In this paper, we propose a component framework that addresses these limitations through a unified approach for the management of components and modules. Our approach uniquely enables to reconfigure both components and modules at runtime, without restrictions. We prototyped the proposed framework in Java and exercised various dynamic reconfigurations of componentbased systems. Furthermore, we formalized this framework and proved the correctness of its reconfiguration protocol with the Coq proof assistant.files defined in M 1 by those defined in M 2 . Such reconfigurations are complementary to components reconfigurations that allow to manipulate components without changing their code (e.g., starting or stopping components, replacing a component by a newly started one instanciated from the same module). Module reconfigurations are useful to upgrade components to new versions or to adapt the code of components, for load management reasons, for instance. However, existing component frameworks do not fully support module reconfigurations at runtime.Several Java-based component frameworks [7][8][9] imply to shutdown and restart the entire system to manage module reconfigurations, mainly because modules are simply managed through setting up the classpath of the Java Runtime Environment. With the recent Tapestry industrial Java-based component framework [10], some component classes may be dynamically updated but only at the condition component interfaces do not evolve.Alternate approaches [11, 12] propose to use dynamic software updating (DSU) techniques [13] to allow updating the code of a component without any shutdown-restart. Despite being useful, such techniques face restrictions and are not guaranteed to succeed, which makes them suited to use at debug time but unreliable to use at production time.Other component frameworks, either industrial [2][3][4]14] or academic [15,16], leverage a module platform such as OSGi [17] or the NetBean Platform Module System [18] to manage the dynamic update of Java modules. Module platforms manage module updates through micro-rebooting the necessary components only, avoiding the global downtime imposed by a global shutdown-restart approach. However, such platforms autonomously decide how modules are link...