A language for self-adaptive system requirements

Self-adaptive systems have the capability to autonomously modify their behaviour at run-time in response to changes in their environment. Such systems are now commonly built in domains as diverse as enterprise computing, automotive control systems, and environmental monitoring systems. To date, however, there has been limited attention paid to how to engineer requirements for such systems. As a result, selfadaptivity is often constructed in an ad-hoc manner. In this paper, we argue that a more rigorous treatment of requirements relating to self-adaptivity is needed and that, in particular, requirements languages for self-adaptive systems should include explicit constructs for specifying and dealing with the uncertainty inherent in self-adaptive systems. We present some initial thoughts on a new requirements language for selfadaptive systems and illustrate it using examples from the services domain. © 2008 IEEE.

Software engineering for self-adaptive systems:a research roadmap

The goal of this roadmap paper is to summarize the state-of-the-art and to identify critical challenges for the systematic software engineering of self-adaptive systems. The paper is partitioned into four parts, one for each of the identified essential views of self-adaptation: modelling dimensions, requirements, engineering, and assurances. For each view, we present the state-of-the-art and the challenges that our community must address. This roadmap paper is a result of the Dagstuhl Seminar 08031 on "Software Engineering for Self-Adaptive Systems," which took place in January 2008. © 2009 Springer Berlin Heidelberg.

RELAX:incorporating uncertainty into the specification of self-adaptive systems

Self-adaptive systems have the capability to autonomously modify their behaviour at run-time in response to changes in their environment. Self-adaptation is particularly necessary for applications that must run continuously, even under adverse conditions and changing requirements; sample domains include automotive systems, telecommunications, and environmental monitoring systems. While a few techniques have been developed to support the monitoring and analysis of requirements for adaptive systems, limited attention has been paid to the actual creation and specification of requirements of self-adaptive systems. As a result, self-adaptivity is often constructed in an ad-hoc manner. In this paper, we argue that a more rigorous treatment of requirements explicitly relating to self-adaptivity is needed and that, in particular, requirements languages for self-adaptive systems should include explicit constructs for specifying and dealing with the uncertainty inherent in self-adaptive systems. We present RELAX, a new requirements language for selfadaptive systems and illustrate it using examples from the smart home domain. © 2009 IEEE.

Dynamic decision networks for decision-making in self-adaptive systems:a case study

Bayesian decision theory is increasingly applied to support decision-making processes under environmental variability and uncertainty. Researchers from application areas like psychology and biomedicine have applied these techniques successfully. However, in the area of software engineering and speci?cally in the area of self-adaptive systems (SASs), little progress has been made in the application of Bayesian decision theory. We believe that techniques based on Bayesian Networks (BNs) are useful for systems that dynamically adapt themselves at runtime to a changing environment, which is usually uncertain. In this paper, we discuss the case for the use of BNs, speci?cally Dynamic Decision Networks (DDNs), to support the decision-making of self-adaptive systems. We present how such a probabilistic model can be used to support the decision making in SASs and justify its applicability. We have applied our DDN-based approach to the case of an adaptive remote data mirroring system. We discuss results, implications and potential bene?ts of the DDN to enhance the development and operation of self-adaptive systems, by providing mechanisms to cope with uncertainty and automatically make the best decision.

Self-adaptive probabilistic roadmap generation for intelligent virtual agents

Agents inhabiting large scale environments are faced with the problem of generating maps by which they can navigate. One solution to this problem is to use probabilistic roadmaps which rely on selecting and connecting a set of points that describe the interconnectivity of free space. However, the time required to generate these maps can be prohibitive, and agents do not typically know the environment in advance. In this paper we show that the optimal combination of different point selection methods used to create the map is dependent on the environment, no point selection method dominates. This motivates a novel self-adaptive approach for an agent to combine several point selection methods. The success rate of our approach is comparable to the state of the art and the generation cost is substantially reduced. Self-adaptation therefore enables a more efficient use of the agent's resources. Results are presented for both a set of archetypal scenarios and large scale virtual environments based in Second Life, representing real locations in London.

Self-adaptive volunteered services composition through stimulus-and time-awareness

Volunteered Service Composition (VSC) refers to the process of composing volunteered services and resources. These services are typically published to a pool of voluntary resources. Selection and composition decisions tend to encounter numerous uncertainties: service consumers and applications have little control of these services and tend to be uncertain about their level of support for the desired functionalities and non-functionalities. In this paper, we contribute to a self-awareness framework that implements two levels of awareness, Stimulus-awareness and Time-awareness. The former responds to basic changes in the environment while the latter takes into consideration the historical performance of the services. We have used volunteer service computing as an example to demonstrate the benefits that self-awareness can introduce to self-adaptation. We have compared the Stimulus-and Time-awareness approaches with a recent Ranking approach from the literature. The results show that the Time-awareness level has the advantage of satisfying higher number of requests with lower time cost.

Confirmatory feedback in teacher education:an instigator of student teacher learning

This book examines the intricacies of the discourse of post-observation feedback that student teachers receive following group teaching practice. In particular, the author explores confirmatory feedback as an instigator of student teacher learning, and examines the potential links between feedback and change. The book will be of specific interest to researchers, teacher educators and other professionals involved in feedback-giving settings.

Investigation of PHY, MAC and APP layers for adaptive and cross-layer optimization in IEEE802.11 WLAN

Due to huge popularity of portable terminals based on Wireless LANs and increasing demand for multimedia services from these terminals, the earlier structures and protocols are insufficient to cover the requirements of emerging networks and communications. Most research in this field is tailored to find more efficient ways to optimize the quality of wireless LAN regarding the requirements of multimedia services. Our work is to investigate the effects of modulation modes at the physical layer, retry limits at the MAC layer and packet sizes at the application layer over the quality of media packet transmission. Interrelation among these parameters to extract a cross-layer idea will be discussed as well. We will show how these parameters from different layers jointly contribute to the performance of service delivery by the network. The results obtained could form a basis to suggest independent optimization in each layer (an adaptive approach) or optimization of a set of parameters from different layers (a cross-layer approach). Our simulation model is implemented in the NS-2 simulator. Throughput and delay (latency) of packet transmission are the quantities of our assessments. © 2010 IEEE.

Writing self-assembled monolayers with Cs: Optimization of atomic nanolithography imaging using self-assembled monolayers on gold substrates

We report the results of a study into the factors controlling the quality of nanolithographic imaging. Self-assembled monolayer (SAM) coverage, subsequent postetch pattern definition, and minimum feature size all depend on the quality of the Au substrate used in material mask atomic nanolithographic experiments. We find that sputtered Au substrates yield much smoother surfaces and a higher density of {111}-oriented grains than evaporated Au surfaces. Phase imaging with an atomic force microscope shows that the quality and percentage coverage of SAM adsorption are much greater for sputtered Au surfaces. Exposure of the self-assembled monolayer to an optically cooled atomic Cs beam traversing a two-dimensional array of submicron material masks mounted a few microns above the self-assembled monolayer surface allowed determination of the minimum average Cs dose (2 Cs atoms per self-assembled monolayer molecule) to write the monolayer. Suitable wet etching, with etch rates of 2.2 nm min-1, results in optimized pattern definition. Utilizing these optimizations, material mask features as small as 230 nm in diameter with a fractional depth gradient of 0.820 nm were realized.

Using SPL to Develop AAL Systems Based on Self-adaptive Agents

Abstract 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.

The Role of Motivational Strategies in the Upper Elementary Classroom : A systematic literature review about teacher strategies that promote self-confidence, motivation and a conducive learning environment

The aim of this literature review is to investigate which strategies teachers use to motivate pupils to communicate orally in English. The literature review also investigates how these teacher strategies affect pupils. The methodology used for this investigation is a systematic literature review. Various databases have been used when searching for literature. Scientific articles and theses have been searched for. They have also been read and analyzed before they have become a part of this review. The results indicate that some teachers feel insecure when speaking English. Therefore Swedish is spoken in many language classrooms. Teachers speaking in front of the class is the traditional way of teaching, and it does not seem to be a strategy who influences pupils positively. If teachers speak the target language among pupils they often get more motivated and focused pupils who feel comfortable speaking English. Young pupils are fast learners. By exposing them to the English language in early ages they receive great opportunities to learn a foreign language and strengthen their self-confidence. Drama, songs and rhymes are preferable strategies to use when teaching young learners. What position teachers decide to take in the classroom is also a significant element when teaching foreign languages.

The influences of conceptions of learning and learner self-concept on high school students' approaches to learning

This study investigated the mediating effect of learner selfconcept between conceptions of learning and students' approaches to learning using structural equation modelling. Data were collected using a modified version of Biggs' Learning Process Questionnaire, together with the recently developed 'What is Learning Survey' and 'Learner Self-Concept Scale'. A sample of 355 high school students participated in the study. Results indicate that learner self-concept does mediate between conceptions of meaning and approaches to learning. Students who adopted a deep approach liked learning new things and indirectly viewed learning as experiential, involving social interaction and directly viewed learning as personal development. Implications for teachers are discussed, with consideration given to appropriate classroom practice.

Perceptions of online learning in an Australian university : Malaysian students' perspectives

Several researchers have reported that cultural and language differences can affect online interactions and communications between students from different cultural backgrounds. Other researchers have asserted that online learning is a tool that can improve teaching and learning skills, but, its effectiveness depends on how the tool is used. Therefore, this study aims to investigate the kinds of challenges encountered by the international students and how they actually cope with online learning. To date little research exists on the perceptions of online learning environments by international Asian students, in particular Malaysian students who study in Australian Universities; hence this study aims to fill this gap. A mixed-method approach was used to collect quantitative and qualitative data using a modified Online Learning Environment Survey (OLES) instrument and focus group interviews. The sample comprised 76 international students from a university in Brisbane. Thirty-five domestic Australian students were included for comparison. Contrary to assumptions from previous research, the findings revealed that there were few differences between the international Asian students from Malaysia and Australian students with regard to their perceptions of online learning. Another cogent finding that emerged was that online learning was most effective when included within blended learning environments. The students clearly indicated that when learning in a blended environment, it was imperative that appropriate features are blended in and customised to suit the particular needs of international students. The study results indicated that the university could improve the quality of the blended online learning environment by: 1) establishing and maintaining a sense of learning community; 2) enhancing the self motivation of students; and 3) professional development of lecturers/tutors, unit coordinators and learning support personnel. Feedback from focus group interviews, highlighted the students‘ frustration with a lack of cooperative learning, strategies and skills which were expected of them by their lecturers/tutors in order to work productively in groups. They indicated a strong desire for lecturers/tutors to provide them prior training in these strategies and skills. The students identified four ways to optimise learning opportunities in cross-cultural spaces. These were: 1) providing preparatory and ongoing workshops focusing on the dispositions and roles of students within student-centred online learning environments; 2) providing preparatory and ongoing workshops on collaborative group learning strategies and skills; 3) providing workshops familiarising students with Australian culture and language; and 4) providing workshops on strategies for addressing technical problems. Students also indicated a strong desire for professional development of lecturers/tutors focused on: 1) teacher attributes, 2) ways to culturally sensitive curricula, and 3) collaborative learning and cooperative working strategies and skills, and 4) designing flexible program structures. Recommendations from this study will be useful to Australian universities where Asian international students from Malaysia study in blended learning environments. An induction program (online skills, collaborative and teamwork skills, study expectations plus familiarisation with Australian culture) for overseas students at the commencement of their studies; a cultural awareness program for lecturers (cultural sensitivity, ways to communicate and a better understanding of Asian educational systems), upskilling of lecturers‘ ability to structure their teaching online and to apply strong theoretical underpinnings when designing learning activities such as discussion forums, and consistency with regards to how content is located and displayed in a learning management system like Blackboard. Through addressing the research questions in this study, the researcher hopes to contribute to and advance the domain of knowledge related to online learning, and to better understand how international Malaysian students‘ perceive online learning environments. These findings have theoretical and pragmatic significance.

A multi-objective adaptive immune algorithm for multi-application NoC mapping

Current SoC design trends are characterized by the integration of larger amount of IPs targeting a wide range of application fields. Such multi-application systems are constrained by a set of requirements. In such scenario network-on-chips (NoC) are becoming more important as the on-chip communication structure. Designing an optimal NoC for satisfying the requirements of each individual application requires the specification of a large set of configuration parameters leading to a wide solution space. It has been shown that IP mapping is one of the most critical parameters in NoC design, strongly influencing the SoC performance. IP mapping has been solved for single application systems using single and multi-objective optimization algorithms. In this paper we propose the use of a multi-objective adaptive immune algorithm (M(2)AIA), an evolutionary approach to solve the multi-application NoC mapping problem. Latency and power consumption were adopted as the target multi-objective functions. To compare the efficiency of our approach, our results are compared with those of the genetic and branch and bound multi-objective mapping algorithms. We tested 11 well-known benchmarks, including random and real applications, and combines up to 8 applications at the same SoC. The experimental results showed that the M(2)AIA decreases in average the power consumption and the latency 27.3 and 42.1 % compared to the branch and bound approach and 29.3 and 36.1 % over the genetic approach.