UNDERSEA : An Exemplar for Engineering Self-Adaptive Unmanned Underwater Vehicles

Recent advances in embedded systems and underwater communications raised the autonomy levels in unmanned underwater vehicles (UUVs) from human-driven and scripted to adaptive and self-managing. UUVs can execute longer and more challenging missions, and include functionality that enables adaptation to unexpected oceanic or vehicle changes. As such, the simulated UUV exemplar UNDERSEA introduced in our paper facilitates the development, evaluation and comparison of self-adaptation solutions in a new and important application domain. UNDERSEA comes with predefined oceanic surveillance UUV missions, adaptation scenarios, and a reference controller implementation, all of which can easily be extended or replaced

Interval Change-Point Detection for Runtime Probabilistic Model Checking

Recent probabilistic model checking techniques can verify reliability and performance properties of software systems affected by parametric uncertainty. This involves modelling the system behaviour using interval Markov chains, i.e., Markov models with transition probabilities or rates specified as intervals. These intervals can be updated continually using Bayesian estimators with imprecise priors, enabling the verification of the system properties of interest at runtime. However, Bayesian estimators are slow to react to sudden changes in the actual value of the estimated parameters, yielding inaccurate intervals and leading to poor verification results after such changes. To address this limitation, we introduce an efficient interval change-point detection method, and we integrate it with a state-of-the-art Bayesian estimator with imprecise priors. Our experimental results show that the resulting end-to-end Bayesian approach to change-point detection and estimation of interval Markov chain parameters handles effectively a wide range of sudden changes in parameter values, and supports runtime probabilistic model checking under parametric uncertainty

Developing a recommender mechanism for supporting mobile content reuse

Nowadays people got used to short text answers, likes and shares. Anyone can feel it by entering popular forums or social networks. Modern platforms such as Twitter or Facebook contribute to this situation with their symbols per message limitations. The quality of content produced in such conditions is not high. According to Knight and Burn (2005): “The rapid growth of the Internet and the lack of enforceable standards regarding the information it contains has led to numerous information quality problems.” The possible solution to this problem is called mobile digital storytelling. It replaces traditional communication mechanisms (text, photos) with a digital narrative, thus making a stronger impact on user. Besides, it allows creating interesting content at any location with the help of mobile phone. However, it is hard to make a high quality story from scratch without prior experience. Viewing through previously created high quality content provides such experience. At the same time, reusing this content would allow creating story by combining and rearranging instead of producing from scratch. But state of the art mobile digital storytelling applications don’t provide any possibilities for content reuse. In addition, the influence of content reuse on the story creation process was not studied. Hence, in this work the researcher will explore and try to develop alternative ways to support content reuse in mobile digital storytelling (mDS). For this purpose a mechanism called RecSM (a recommendation system using content from Social Media) is introduced. The main goal of development is to create RecSM for mobile digital storytelling application. The influence of RecSM on mobile content reuse as well as the influence of reuse on storytelling process is the main study goals. The thesis is based on research conducted in Linnaeus University, Sweden. The research is divided into two main parts: gathering requirements for RecSM and the case study. 10 users are involved in both activities. Initial requirements for RecSM are defined after conducting research in the topic but final requirements are determined with the help of users. Based on them the RecSM is developed and added to a mobile digital storytelling application. A case study in Teleborg Castle (Vaxjo, Sweden) follows afterwards. Participants create stories about their castle experience with the help of mDS or mDS-RecSM application. The data for further research is retrieved through field notes, personal interviews and a survey. Then stories and answers of people that used mDS with and without recommender are compared and analyzed. Based on the study outcomes it is concluded that developed RecSM supports content reuse in mobile digital storytelling

A Control-theoretic Approach to Realize Self-adaptive Software Systems with Guarantees

Engineering modern software systems is a challenging task as these systems are subject to different types of uncertainties. Examples of such uncertainties are disturbances in the environment that are difficult to predict and goals that may change during operation. The idea of self-adaptation is to handle these uncertainties at runtime, when the knowledge becomes available to resolve them. As more software systems with strict requirements are designed to be self-adaptive, the need for adaptation guarantees is becoming a high-priority concern. Providing such guarantees with traditional architecture-based approaches has shown to be challenging, calling for new approaches to engineer self-adaptive systems. To tackle this challenge, this thesis studies control-based software adaptation (CBSA). CBSA applies principles from control theory to design self-adaptive software systems. More specifically, we address the following research problem using CBSA: how to realize self-adaptive software systems that satisfy multiple stakeholder requirements with guarantees in the presence of uncertainties. The thesis addresses the research problem in two subsequent stages. The first stage focuses on satisfying multiple stakeholder requirements of different types, and providing adaptation guarantees. This stage starts with a systematic literature review of CBSA, which provides a comprehensive overview of the field, including existing CBSA approaches, applied models and controllers, and analyzed guarantees. From the review, we identify a number of gaps in the existing research and concrete challenges in addressing the research problem. Then, we devise SimCA, a control-theoretic approach to realize self-adaptive software systems that satisfy multiple requirements with guarantees. SimCA combines mathematical models of software system, a control-based adaptation mechanism, and formal analysis of the required guarantees. SimCA is also reusable, meaning that it can be applied to a family of cooperative software systems with strict requirements. The second research stage focuses on handling different types of uncertainty.We first discuss the types of uncertainty and study whether existing CBSA approaches try to deal with these types. We then introduce an enhanced approach called SimCA* that includes components to deal with uncertainty in software parameters, addition or removal of requirements at runtime and software component interactions. In order to obtain evidence about the applicability and reusability of SimCA and SimCA*, we apply informal exploratory case studies with three software systems with strict requirements from different domains

Keep it SIMPLEX: Satisfying Multiple Goals with Guarantees in Control-Based Self-Adaptive Systems

© 2016 ACM. An increasingly important concern of software engineers is handling uncertainties at design time, such as environment dynamics that may be dificult to predict or requirements that may change during operation. The idea of self-Adaptation is to handle such uncertainties at runtime, when the knowledge becomes available. As more systems with strict requirements require self-Adaptation, providing guarantees for adaptation has become a high-priority. Providing such guarantees with traditional architecture-based approaches has shown to be chal-lenging. In response, researchers have studied the application of control theory to realize self-Adaptation. However, existing control-Theoretic approaches applied to adapt software systems have primarily focused on satisfying only a single adaptation goal at a time, which is often too restrictive for real applica-tions. In this paper, we present Simplex Control Adaptation, SimCA, a new approach to self-Adaptation that satisfies mul-tiple goals, while being optimal with respect to an additional goal. SimCA oers robustness to measurement inaccuracy and environmental disturbances, and provides guarantees. We evaluate SimCA for two systems with strict requirements that have to deal with uncertainties: An underwater vehicle system used for oceanic surveillance, and a tele-Assistance system for health care support.status: publishe

Self-adaptation of software using automatically generated control-theoretical solutions

Control theory has contributed a set of foundational techniques to handle “change” at runtime in software applications. These techniques however pose a number of challenges as well: (i) they require the development and understanding of mathematical models; (ii) synthesizing solutions is often done on a per-problem basis, discouraging flexibility and generality. Software engineering, as a discipline, has always aimed at finding reusable and modular solutions. The combination of the desire to apply formally grounded control-theoretical principles and reuse existing solutions has motivated research on the topic of automatically generated control solutions. This research aims at designing control strategies in an automated way from data that qualifies the given problem at hand. This chapter provides an overview of the research topic of automatically generated control-theoretical solutions, explaining the key research contributions and paving the way for future research.status: accepte

Handling New and Changing Requirements with Guarantees in Self-Adaptive Systems using SimCA

Self-adaptation provides a principled way to deal with change during operation. As more systems with strict goals require self-adaptation, the need for guarantees in self-adaptive systems is becoming a high-priority concern. Designing adaptive software using principles from control theory has been identified as one of the approaches to provide guarantees. However, current solutions can only handle pre-specified requirements either in the form of setpoint values (S-reqs) or values to be optimized (O-reqs). This paper presents SimCA∗ that makes two contributions to control-based self-adaptation: (a) it allows the user to specify a third type of requirement that keeps a value above/below a threshold (T-reqs), and (b) it can deal with requirement sets that change at runtime (i.e., requirements can be adjusted, activated, and deactivated on the fly). SimCA∗ offers robustness to disturbances and provides adaptation guarantees. We evaluate SimCA∗ for two systems with strict goals from different domains: an underwater vehicle system used for oceanic surveillance, and a tele-assistance system for health care support. The test results demonstrate that SimCA∗ can deal with the three types of requirements (STO-reqs) operating under various types of dynamics and the set of requirements can be changed on the fly

SimCA*: A Control-theoretic Approach to Handle Uncertainty in Self-adaptive Systems with Guarantees

status: publishe

Handling New and Changing Requirements with Guarantees in Self-Adaptive Systems using SimCA*

© 2017 IEEE. Self-adaptation provides a principled way to deal with change during operation. As more systems with strict goals require self-adaptation, the need for guarantees in self-adaptive systems is becoming a high-priority concern. Designing adaptive software using principles from control theory has been identified as one of the approaches to provide guarantees. However, current solutions can only handle pre-specified requirements either in the form of setpoint values (S-reqs) or values to be optimized (O-reqs). This paper presents SimCA∗ that makes two contributions to control-based self-adaptation: (a) it allows the user to specify a third type of requirement that keeps a value above/below a threshold (T-reqs), and (b) it can deal with requirement sets that change at runtime (i.e., requirements can be adjusted, activated, and deactivated on the fly). SimCA∗ offers robustness to disturbances and provides adaptation guarantees. We evaluate SimCA∗ for two systems with strict goals from different domains: an underwater vehicle system used for oceanic surveillance, and a tele-assistance system for health care support. The test results demonstrate that SimCA∗ can deal with the three types of requirements (STO-reqs) operating under various types of dynamics and the set of requirements can be changed on the fly.status: accepte