Adaptive Rule-Driven Devices - General Formulation and Case Study

The paper describes an adaptive intelligent controller architecture (GRAVA) for an image understanding system. The controller architecture is based on the concept of selfadaptive software, an approach that has seen significant effort in the past few years. Self-adaptive software involves synthesizing code that monitors, diagnoses and repairs behavioral deviations from explicitly stored and managed goal and method information. There have been several self-adaptive systems produced in recent years, but none of them has yet seriously addressed the issue of behavioral guarantees (including GRAVA). In addition to describing GRAVA, this paper proposes a new mechanism for providing assurance of stability in self-adaptive architectures. That mechanism is a process reflection layer to reason about the behavior of the program correction parts of the self-adaptive system. This mechanism will limit the scope in time and severity of deviations from nominal behavior, reduce or eliminate unstable corrections, and provide design time assurance of these behavioral characteristics.

SOQUA'07: Fourth International Workshop on Software Quality Assurance - In conjunction with the 6th ESEC/FSE Joint Meeting, 2007

The impossibility of statically determining the behavior of complex systems that interact at runtime with heterogeneous devices and remote entities, may lead to unexpected system failures and performance degradation. Recently, selfadaptive applications have been recognized as viable solutions for dealing with systems where size and complexity increase beyond the ability of humans. However, selfadaptive solutions have been always studied in isolation, only involving single layers of the system (e.g. operative system, middleware, firmware, hardware). In this paper we discuss our novel idea of multi-layers deep adaptability of complex systems. We present an integrated approach for designing and coordinating applications with three-layers of self-adaptation. The solution proposed is based on specialized sense-plan-act control loops that interact each others to monitor both specific parts and also the global behavior of the system. These control loops sense unexpected behaviors that can compromise the system, then diagnose the system layer that needs an adaptation action, and finally act the proper adaptation strategy to overcome the revealed problems without user intervention. We validate the approach with a SOA-based application, the Virtual Tour Guide, designed with three-layers self-adaptive abilities in order to overcome functional/non-functional problems that can derive from the integration of heterogeneous and remote third-party services.

Proceedings of the Seventh Integrated Data …, 2000

Proc. of CSEDU 2009, 2009

Some complex problems can be modeled using more than one type of device thus having some interaction between them to represent their behavior. From this perspective, we do not have a common formulation to represent both the formalism and its interaction. The purpose of this paper is to fill in this gap by proposing a formulation that represents, for a group of devices, their behavior and interactions. We call this formalism as "Cooperating Adaptive Devices". For illustration purposes, we presented an application where its behavior can be modeled using this formalism.

arXiv (Cornell University), 2014

Journal of Reliable Intelligent Environments, 2015

This paper describes existing work related to the development of adaptive systems and approaches in ubiquitous and pervasive environments and sheds more light on how features from natural and biological systems could be exploited for engineering adaptive systems. Ubiquitous and pervasive systems are composed of different heterogeneous parts or entities that interact and perform actions favoring the emergence of global desired behavior. Furthermore, in this type of systems entities might join or leave without disturbing the collective, and the system should self-organize and continue performing their goals. Therefore, entities must self-evolve and self-improve by learning from their interactions with the environment. In this paper, the main challenges for engineering these systems are presented by putting more emphasis on the design and the development of distributed and adaptive algorithms that allow system entities to select the best suitable strategy/action in order to drive the system to the best suitable behavior according to the current state of the system and environment changes. We also highlight specific aspects being investigated via illustrative examples in order to show the usefulness of natural and biological system principles for developing adaptive approaches. Keywords Pervasive and ubiquitous computing • Adaptive systems • Self-CHOP • Natural and biological systems • Bio-inspired algorithms B Mohamed Bakhouya

2006

The paper presents the use of Evolving Logic Programming to model adaptive controllers. The advantage of using well-defined, self-evolving logic-based controllers is that it is possible to model dynamic environments, and to formally prove systems' requirements.

Advances in Intelligent Systems and Computing, 2016

One of the most important challenges of this decade is the Internet of Things (IoT) that pursues the integration of real-world objects in Internet. One of the key areas of the IoT is the Ambient Assisted Living (AAL) systems, which should be able to react to variable and continuous changes while ensuring their acceptance and adoption by users. This means that AAL systems need to work as self-adaptive systems. The autonomy property inherent to software agents, makes them a suitable choice for developing self-adaptive systems. However, agents lack the mechanisms to deal with the variability present in the IoT domain with regard to devices and network technologies. To overcome this limitation we have already proposed a Software Product Line (SPL) process for the development of self-adaptive agents in the IoT. Here we analyze the challenges that poses the development of self-adaptive AAL systems based on agents. To do so, we focus on the domain and application engineering of the self-adaptation concern of our SPL process. In addition, we provide a validation of our development process for AAL systems.

ACM Transactions on Embedded Computing Systems, 2011

This article presents our methodology for implementing self-adaptivness within an OS-based and reconfigurable embedded system according to objectives such as quality of service, performance, or power consumption. We detail our approach to separate application-specific decisions and hardware/softwareimplementation decisions at system level. The former are related to the efficiency control of applications and based on the knowledge of application engineers. The latter are generic and address the choice between various hardware and software implementations according to user objectives. The decision management is implemented as an adaptive closed-loop model. We describe how each design step may be implemented and especially how we solved the issue of stability. Finally, we present a video-tracking application implemented on a FPGA to demonstrate the effectiveness of our solution, results are given for a system built around a NIOS soft-core with μCOS II RTOS and new services for managing hardware and software tasks transparently.