A context-aware framework for dynamic composition of process fragments in the internet of services

Abstract In the last decade, many approaches to automated service composition have been proposed. However, most of them do not fully exploit the opportunities offered by the Internet of Services (IoS). In this article, we focus on the dynamicity of the execution environment, that is, any change occurring at run-time that might affect the system, such as changes in service availability, service behavior, or characteristics of the execution context. We indicate that any IoS-based application strongly requires a composition framework that supports for the automation of all the phases of the composition life cycle, from requirements derivation, to synthesis, deployment and execution. Our solution to this ambitious problem is an AI planning-based composition framework that features abstract composition requirements and context-awareness. In the proposed approach most human-dependent tasks can be accomplished at design time and the few human intervention required at run time do not affect the system execution. To demonstrate our approach in action and evaluate it, we exploit the ASTRO-CAptEvo framework, simulating the operation of a fully automated IoS-based car logistics scenario in the Bremerhaven harbor

Service Composition in Dynamic Environments: From Theory to Practice

In recent years, service-oriented architecture (SOA) has become one of the leading paradigms in software design. Among the key advantages behind SOA is service composition, the ability to create new services by reusing the functionality of pre-existing ones. Despite the availability of standard languages and related design and development tools, ``manual'' service composition remains to be an extremely error-prone and time-consuming task. No surprise, the automation of service composition process has been and still is a hot topic in the area of service computing. In addition to high complexity, modern service-based systems tend to be dynamic. The most common examples of dynamic factors are constantly evolving set of available services, volatile execution context, frequent revision of business policies, regulations and goals, etc. Since dynamic changes of the execution environment can invalidate service compositions predefined within a service-based system, the cost of software maintenance in this case may increase dramatically. Unfortunately, the existing automated service composition approaches are not of much help here. Being design-time by their nature, they intensively involve IT experts, especially for analysing the changes and respecifying formal composition requirements in new conditions, which is still a considerable effort. To make service-based systems more agile, a new composition approach is needed that could automatically perform all composition-related tasks at run time, from deriving composition requirements to generating new compositions to deploying them. In this dissertation, we propose a novel service composition framework that (i) handles stateful and nondeterministic services that interact asynchronously, (ii) allows for rich control- and data-flow composition requirements that are independent from the details of service implementations (iii) exploits advanced planning techniques for automated reasoning and (iv) exploits modeling methodology that is applicable in dynamic environment. The corner stone of the framework is the explicit context model that abstracts composition requirements and constraints away from the details of service implementations. By linking services to the context model on the one side, and by expressing composition requirements and constraints in terms of the context model on the other side, we create a formal setting in which abstract requirements and constraints, though being implementation-independent, can always be grounded to available service implementations. Consequently, we show that in such framework it is possible to move most human activities to design time so that the run-time management of the composition life cycle is completely automated. To the best of our knowledge, it is the first composition approach to achieve this goal. A significant contribution of the dissertation is the investigation of the problem of dynamic adaptation of service-based business processes. Here, our solution is based on the composition approach proposed. Within the thesis, the problem of process adaptation plays the role of the key motivator and evaluation use case for our composition-related research. The most part of the ideas discussed in the thesis are implemented and evaluated to prove their practical applicability

A goal model for collective adaptive systems

Abstract—A collective adaptive system is composed of large numbers of autonomous and self-adaptive entities which are able to provide benefits for other participants and have to cooperate with each other to accomplish their individual goals. When entities adapt their own behavior due to unexpected situations, this may result in breaking the overall collaboration if these are not executed simultaneously and do not respect some collective constraints. The objective of this paper is to present a goal model that allows to express requirements for collective adaptability. It includes (i) how to specify the behavior of the entities that encodes cooperation with other entities, (ii) how to link collaborative goals and individual goals, and (iii) how to specify constraints that are imposed on different entities to preserve some form of collective consistency while they are adapted

Collective adaptation in process-based systems

A collective adaptive system is composed of a set of heterogeneous, autonomous and self-adaptive entities that come into a collaboration with one another in order to improve the effectiveness with which they can accomplish their individual goals. In this paper, we offer a characterization of ensembles, as the main concept around which systems that exhibit collective adaptability can be built. Our conceptualization of ensembles enables to define a collective adaptive system as an emergent aggregation of autonomous and self-adaptive process-based elements. To elucidate our approach to ensembles and collective adaptation, we draw an example from a scenario in the urban mobility domain, we describe an architecture that enables that approach, and we show how our approach can address the problems posed by the motivating scenario

Continuous Orchestration of Web Services via Planning

The service-oriented paradigm is rapidly emerging as the key approach to develop distributed business applications, and its enactment requires the ability to automatically coordinate existing services to realize novel and powerful desired functionalities. Planning-based solutions have proved to be strong candidates for this hard task. However, no current approach can satisfactorily coordinate stateful services that evolve continuously and indefinitely in an asynchronous way, such as e.g. notification services made increasingly available by business entities. This severely limits the practical applicability of current solutions. In this paper, we provide for the first time a full-fledged planning-based solution to the problem of continuously orchestrating stateful asynchronous services. To do so, we adopt a simple yet expressive requirement language, and we devise a novel planning algorithm that solves preference-ordered maintenability goals in the presence of exogenous events. Our approach is correct and complete, and our tests on a symbolic BDD-based implementation witness its ability and effectiveness in dealing with significant and realistic scenarios which no other current approach can tackle

Control Flow Requirements for Automated Service Composition

Automated composition of services is a key functionality for the adoption of the service-oriented development paradigm. Solving this problem in practice requires the ability to consider asynchronous stateful services and to express complex composition requirements which may span different phases of the life-cycle of component services. In this paper we present a novel automated service composition approach which addresses these challenges by associating so-called objects to services, and by introducing a simple yet powerful notation to express composition requirements on them. We recast this view of the problem as a specific form of planning; our experiments on a prototype implementation witness the ability of our approach to deal with realistic scenarios and requirements that cannot be tackled by other current approaches

An Approach for Collective Adaptation in Socio-Technical Systems

Socio-technical systems are systems where autonomous humans and computational entities collectively collaborate with each other to satisfy their goals in a dynamic environment. To be resilient, such systems need to adapt to unexpected human behaviours and exogenous changes in the environment. In this paper, we describe a framework for the development of social-technical systems where adaptation is itself a collective process driven by the awareness of capabilities, goals, constraints and preferences of humans and entities, and knowledge of the environment. The adaptation is controlled by a multi-criteria decision making function combined with an analytic hierarchic process (AHP). We present our approach, the collective adaptation algorithm, and its application to a smart mobility scenario