Vincenzo Grassi

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.

Software Engineering for Self-Adaptive Systems: A Second Research Roadmap

The goal of this roadmap paper is to summarize the state-of-the-art and identify research challenges when developing, deploying and managing self-adaptive software systems. Instead of dealing with a wide range of topics associated with the field, we focus on four essential topics of self-adaptation: design space for self-adaptive solutions, software engineering processes for self-adaptive systems, from centralized to decentralized control, and practical run-time verification & validation for self-adaptive systems. For each topic, we present an overview, suggest future directions, and focus on selected challenges. This paper complements and extends a previous roadmap on software engineering for self-adaptive systems published in 2009 covering a different set of topics, and reflecting in part on the previous paper. This roadmap is one of the many results of the Dagstuhl Seminar 10431 on Software Engineering for Self-Adaptive Systems, which took place in October 2010.

On Patterns for Decentralized Control in Self-Adaptive Systems

Self-adaptation is typically realized using a control loop. One prominent approach for organizing a control loop in self-adaptive systems is by means of four components that are responsible for the primary functions of self-adaptation: Monitor, Analyze, Plan, and Execute, together forming a MAPE loop. When systems are large, complex, and heterogeneous, a single MAPE loop may not be sufficient for managing all adaptation in a system, so multiple MAPE loops may be introduced. In self-adaptive systems with multiple MAPE loops, decisions about how to decentralize each of the MAPE functions must be made. These decisions involve how and whether the corresponding functions from multiple loops are to be coordinated (e.g., planning components coordinating to prepare a plan for an adaptation). To foster comprehension of self-adaptive systems with multiple MAPE loops and support reuse of known solutions, it is crucial that we document common design approaches for engineers. As such systematic knowledge is currently lacking, it is timely to reflect on these systems to: (a) consolidate the knowledge in this area, and (b) to develop a systematic approach for describing different types of control in self-adaptive systems. We contribute with a simple notation for describing interacting MAPE loops, which we believe helps in achieving (b), and we use this notation to describe a number of existing patterns of interacting MAPE loops, to begin to fulfill (a). From our study, we outline numerous remaining research challenges in this area.

Flow-Based Service Selection forWeb Service Composition Supporting Multiple QoS Classes

In the service oriented paradigm applications are created as a composition of independently developed Web services. Since the same service may be offered by different providers with different non-functional Quality of Service (QoS) attributes, a selection process is needed to identify the constituent services for a given composite service that best meet the users QoS requirements. In this paper, we consider a broker that offers a composite service with multiple QoS classes to several users each generating a flow of requests over time. We propose a service selection scheme which optimizes the end-to-end aggregated QoS of all incoming flows of requests by means of a simple linear programming problem which scales as the number of users, request volumes and/or services grows. This approach differs from most of the current proposals which may not scale well since: a) requests, even from the same user, are handled independently from one another; and b) the selection process often requires the solution of an NP-hard problem.

MOSES: A Framework for QoS Driven Runtime Adaptation of Service-Oriented Systems

Architecting software systems according to the service-oriented paradigm and designing runtime self-adaptable systems are two relevant research areas in todays software engineering. In this paper, we address issues that lie at the intersection of these two important fields. First, we present a characterization of the problem space of self-adaptation for service-oriented systems, thus providing a frame of reference where our and other approaches can be classified. Then, we present MOSES, a methodology and a software tool implementing it to support QoS-driven adaptation of a service-oriented system. It works in a specific region of the identified problem space, corresponding to the scenario where a service-oriented system architected as a composite service needs to sustain a traffic of requests generated by several users. MOSES integrates within a unified framework different adaptation mechanisms. In this way it achieves greater flexibility in facing various operating environments and the possibly conflicting QoS requirements of several concurrent users. Experimental results obtained with a prototype implementation of MOSES show the effectiveness of the proposed approach.

Qos-driven runtime adaptation of service oriented architectures

Runtime adaptation is recognized as a viable way for a service-oriented system to meet QoS requirements in its volatile operating environment. In this paper we propose a methodology to drive the adaptation of such a system, that integrates within a unified framework different adaptation mechanisms, to achieve a greater flexibility in facing different operating environments and the possibly conflicting QoS requirements of several concurrent users. To determine the most suitable adaptation action(s), the methodology is based on the formulation and solution of a linear programming problem, which is derived from a behavioral model of the system updated at runtime by a monitoring activity. Numerical experiments show the effectiveness of our approach. Besides the methodology, we also present a prototype tool that implements it.

On the optimal checkpointing of critical tasks and transaction-oriented systems

The probability distribution of the overhead caused by the use of the checkpointing rollback recovery technique is evaluated in both cases of a single critical task and of an overall transaction-oriented system. This distribution is obtained in Laplace-Stieltjes transform form, from which all the moments can be easily calculated. Alternatively, inversion methods can be used to evaluate the distribution. The authors propose checkpointing strategies based on the above distribution in order to optimize performance criteria motivated, in the case of critical tasks, by real time constraints, and in the case of transaction-oriented systems, by the need of guaranteeing the users about the maximum system unavailability. >

Reliability analysis of component-based systems with multiple failure modes

This paper presents a novel approach to the reliability modeling and analysis of a component-based system that allows dealing with multiple failure modes and studying the error propagation among components. The proposed model permits to specify the components attitude to produce, propagate, transform or mask different failure modes. These component-level reliability specifications together with information about systems global structure allow precise estimation of reliability properties by means of analytical closed formulas, probabilistic model-checking or simulation methods. To support the rapid identification of components that could heavily affect systems reliability, we also show how our modeling approach easily support the automated estimation of the system sensitivity to variations in the reliability properties of its components. The results of this analysis allow system designers and developers to identify critical components where it is worth spending additional improvement efforts.

Towards model driven design of service-based context-aware applications

Context-aware adaptation is an important feature for pervasive computing applications. In our approach, we intend to support the viewpoint of context-aware adaptation as a crosscutting concern with respect to the core business logic of an application. In this way, the design of the application core can be decoupled from the design of the adaptation logic. This facilitate the plugging of different adaptation strategies within the same basic application, tailoring it for different contexts. To this end, we leverage ideas from the domains of model-driven development and aspect-oriented design. We assume that the applications to be adapted are designed according to the service-oriented paradigm. Hence, our adaptation mechanisms only assume the knowledge of information accessible in this kind of applications.

Distributed QoS-aware scheduling in storm

Storm is a distributed stream processing system that has recently gained increasing interest. We extend Storm to make it suitable to operate in a geographically distributed and highly variable environment such as that envisioned by the convergence of Fog computing, Cloud computing, and Internet of Things.