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2017 | Book

Decentralized Dynamic Adaptation for Service-Based Collective Adaptive Systems Read chapter Read first chapter

Service-Oriented Computing – ICSOC 2016 Workshops

ASOCA, ISyCC, BSCI, and Satellite Events, Banff, AB, Canada, October 10–13, 2016, Revised Selected Papers

Editors: Khalil Drira, Hongbing Wang, Qi Yu, Yan Wang, Yuhong Yan, François Charoy, Jan Mendling, Mohamed Mohamed, Zhongjie Wang, Sami Bhiri

Publisher: Springer International Publishing

Book Series : Lecture Notes in Computer Science

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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About this book

This book constitutes the revised selected papers of the scientific satellite events that were held in conjunction with the 14th International Conference on Service-Oriented Computing, ICSOC 2016, held in Banff, AB, Canada, in October 2016.
The ICSOC 2016 workshop track consisted of three workshops on a wide range of topics that fall into the general area of service computing:ASOCA 2016: The rst Workshop on Adaptive Service-oriented and Cloud Applications
ISyCC 2016: The rst Workshop on IoT Systems Provisioning & Management in Cloud Computing
BSCI 2016: The Second International Workshop on Big Data Services and Computational Intelligence

Table of Contents

Frontmatter

Adaptive Service-Oriented and Cloud Applications

Frontmatter
Decentralized Dynamic Adaptation for Service-Based Collective Adaptive Systems
Abstract
Modern service-based systems are progressively becoming more heterogeneous. They form a socio-technical system, composed of distributed entities, software and human participants, interacting with and within the environment. These systems operate under constant perturbations that are due to unexpected changes in the environment and to the unpredictable behavior of the participants. We argue that for a service-based system to be resilient, adaptation must be collective. Multiple participants must adapt their behavior in concert to respond to critical runtime impediments. In this work, we present a framework for the modeling and execution of large-scale service-based Collective Adaptive Systems, where adaptation needs are solved in a decentralized and collective manner.
Antonio Bucchiarone, Martina De Sanctis, Annapaola Marconi
A Generic Framework for Quality-Based Autonomic Adaptation Within Sensor-Based Systems
Abstract
With the growth of the Internet of Things (IoT), sensor-based systems deal with heterogeneous sources, which produce heterogeneous observations of disparate quality. Since network QoS is rarely sufficient to expertise Quality of Observation (QoO), managing such diversity at the application level is a very complex task and requires high levels of experience from application developers. Given this statement, this paper proposes a generic framework for QoO-based autonomic adaptation within sensor-based systems. An abstract architecture is first introduced, intended to bridge the gap between sensors capabilities and application needs thanks to the Autonomic Computing paradigm. Then, the framework is instantiated and practical considerations when implementing an autonomous sensor-based system are given. We illustrate this instantiation with concrete examples of sensor middlewares and IoT platforms.
Antoine Auger, Ernesto Exposito, Emmanuel Lochin
Using Formal Model for Evaluation of Business Processes Elasticity in the Cloud
Abstract
As it has been the case with other technologies, the availability of Service-based Business Processes (SBPs) in the Cloud allows imagining new usage scenarios. Typically, these scenarios include the execution of thousands of processes during a very short period of time requiring temporarily a very important amount of resources. Novel and innovative approaches for modeling of business processes should be developed to allow supporting these scenarios and others in a safer and cost-effective way. For instance, it is necessary to define strategies to scale resource consumed by business processes up and down to ensure their adaptation to the workload changes. In this paper, we focus on how to model and evaluate SBPs elasticity strategies. We propose an analytical model based on queuing model with variable number of servers to represent SBPs adaptation to demands’ variation. We consider a queuing model as Markov chain to evaluate elasticity strategies in the steady state, and to calculate the indices of performance. Our analytical model allows Cloud providers to evaluate and decide about the elasticity strategy to consider before implementing it in real environments.
Lydia Yataghene, Malika Ioualalen, Mourad Amziani, Samir Tata
A Brokerage Architecture: Cloud Service Selection
Abstract
Due to the various benefits of cloud computing such as flexibility and ease of management, several organizations decided to adopt its services. However, with the large number of available cloud services, the selection of services which meets the specific requirements of the user becomes a complex task. This paper proposes a cloud brokerage architecture which allows selecting cloud services based on functional and non-functional requirements identified by the user. Before selecting the best cloud service which satisfies the user, it is important to know the significance of each parameter that characterizes the cloud service. For this reason, we will use the objective ranking of attributes approach based on rough set theory. In this paper, the selection of cloud service by the broker is done using a developed version of the CM-factory algorithm which takes into account the organization cross-cutting concerns.
Hela Malouche, Youssef Ben Halima, Henda Ben Ghezala
Service Virtualization for Self-adaptation in Mobile Cyber-Physical Systems
Abstract
Mobile Cyber-Physical Systems (mCPS) consist of cooperating units that often operate in an unpredictably changing environment. Thus, they need to adapt quickly to varying spatial and temporal conditions during operation, e.g., to avoid collisions. The control software of the mobile units has to reflect this complex dynamics, and traditional device-level adaptation models are usually not efficient enough to engineer them smoothly. We address this challenge by proposing a Virtual Adaptation Services Framework (VASF). It provides a virtualized application-level view to adaptation requirements, enabling adaptation coordination between cooperative mCPS devices. In particular, VASF allows us to describe the contextual conditions of mCPS by abstract rules that are analyzed at runtime by the tool-set BeSpaceD. Based on this analysis, the control systems of the involved mCPS units are automatically reconfigured using the OSGi framework. The approach is demonstrated with DiddyBorg robots that are operated by Raspberry Pi boards.
Amir Taherkordi, Peter Herrmann, Jan Olaf Blech, Álvaro Férnandez

IoT Systems Provisioning and Management in Cloud Computing

Frontmatter
EQL: Event Query Language for the Sharing of Internet-of-Things Infrastructure and Collaborative Applications Development
Abstract
A user-friendly and functional query language for complex events in an IoT environment, along with the query processing techniques involved therein, are introduced in this paper. In an IoT environment which smart services provide a uniform Boolean abstraction to handle massive device heterogeneity, the proposed query language, EQL (Event Query Language), allows application developers to access event streams from smart services. Our approach allows application developers without domain knowledge to more intuitively formulate queries using temporal and logical operators. The processing of EQL queries takes into account the soft real-time event response requirement of the IoT environment.
Kutalmış Akpınar, Kien A. Hua
Trust-Based IoT Participatory Sensing for Hazard Detection and Response
Abstract
The physical world can be monitored by ubiquitous Internet of Things (IoT) devices through participatory sensing by which a huge amount of data is collected and analyzed in the cloud for hazard detection and response. In this paper, we propose a Trust as a Service (TaaS) cloud utility leveraging a cloud hierarchy for assessing service trustworthiness of IoT devices so as filter out untrustworthy sensing data before hazard detection and response are taken. We demonstrate that our TaaS utility achieves accuracy, convergence, and resiliency compared with contemporary IoT/P2P distributed trust protocols while achieving scalability to cope with a huge number of IoT devices. We demonstrate the feasibility with an air pollution detection and response application.
Jia Guo, Ing-Ray Chen, Jeffrey J. P. Tsai, Hamid Al-Hamadi
Data Provenance Model for Internet of Things (IoT) Systems
Abstract
Internet of Things (IoT) systems and applications are increasingly deployed for critical use cases and therefore exhibit an increasing need for dependability. Data provenance deals with the recording, management and retrieval of information about the origin and history of data. We propose that the introduction of data provenance concepts into the IoT domain can help create dependable and trustworthy IoT systems by recording the lineage of data from basic sensor readings up to complex derived information created by software agents. In this paper, we present a data provenance model for IoT systems that is geared towards providing a generic mechanism for assuring the correctness and integrity of IoT applications and thereby reinforcing their trustworthiness and dependability for critical use cases.
Habeeb Olufowobi, Robert Engel, Nathalie Baracaldo, Luis Angel D. Bathen, Samir Tata, Heiko Ludwig
Securing Data Provenance in Internet of Things (IoT) Systems
Abstract
The Internet of Things (IoT) promises to yield a plethora of new innovative applications based on highly interconnected devices. In order to enable IoT applications for critical and/or sensitive use cases, it is important to (i) foster their dependability by assuring and verifying the integrity and correctness of data processed in such applications, and (ii) adequately account for privacy and confidentiality concerns. For addressing these requirements, IoT systems can be equipped with data provenance mechanisms for maintaining information on the lineage and ownership of data. However, in order to provide secure and dependable IoT systems, provenance data needs to be sufficiently protected against tampering and unauthorized access. In this paper, we present a novel framework for cryptographic provenance data protection and access control based on blockchain technology and confidentiality policies.
Nathalie Baracaldo, Luis Angel D. Bathen, Roqeeb O. Ozugha, Robert Engel, Samir Tata, Heiko Ludwig

Big Data Services and Computational Intelligence

Frontmatter
Enhancing UML Class Diagram Abstraction with Page Rank Algorithm and Relationship Abstraction Rules
Abstract
Model-Driven Engineering (MDE) alleviates the cognitive complexity and effort through the refinement and abstraction of consecutive models. In MDE, models should accurately and completely accommodate the expected data, information and knowledge in requirement specification following a series of refinement and abstraction. Proper abstraction starting from Class Diagrams lays the foundation for effective reuse and efficient manipulation of contained data, information and knowledge. Most current model abstraction approaches assume the scenarios with interaction of stakeholders for providing the key entities and thereafter focus on the relationship abstraction. However few work is done on unguided abstraction where stakeholders don’t know the key entities. Towards resolving the abstraction covering both automatic locating of representative entities and abstracting of link among these entities in Class Diagrams, we proposed a combination of class rank algorithm which prioritizes classes and relationship abstraction rules which heuristically determine the representative semantics of relationships towards improving the efficiency and effectiveness of class abstraction.
Liang Huang, Yucong Duan, Zhangbing Zhou, Lixu Shao, Xiaobing Sun, Patrick C. K. Hung
Energy-Aware Composition for Service-Oriented Wireless Sensor Networks
Abstract
This article proposes a service-oriented wireless sensor networks (WSNs) framework. Sensor nodes are encapsulated and represented as WSN services, which are energy-limited, and typically spatial- and temporal-aware. Service classes chains are generated with respect to the requirement of domain applications, and the composition of WSN services is constructed through selecting appropriate WSN services as the instantiation of service classes contained in chains. This WSN services composition is reduced to a multi-objective and multi-constrained optimization problem, which can be solved through adopting particle swarm optimization (PSO) algorithm and genetic algorithm (GA).
Deng Zhao, Zhangbing Zhou, Yucong Duan, Patrick C. K. Hung

PhD Symposium

Frontmatter
Searching the Web of Things: Resolving a Real Library of Babel
Abstract
The advancement on embedded computing and low-power communication technologies allows more physical entities to participate in the Web of Things (WoT) and provide a massive range of resources, covering everything from information to interaction with the physical world. These resources are rapidly turning WoT into a real “Library of Babel” - an infinite library that holds all available information. My PhD research project focuses on making sense of this “infinite library” through developing services that provide the capability to discover and search for WoT resources. I propose to architect the WoT search engine as a Web service, which is composed from a set of interchangeable component services for maximal flexibility. I also present my research questions and three planned evaluation methods.
Nguyen Khoi Tran
A Migration Approach for Cloud Service Composition
Abstract
Service-oriented computing offers an attractive platform for the provisioning of existing resources without investing in new infrastructure. Providers who expect to benefit from the web may bring explosive number of web services. As a result, time and space required to find a solution may be insufferable. To alleviate this problem, we propose to solve service composition problem with a database. In our previous work, we have proposed a relational database-based approach for automated service composition. We want to utilize existing resources on clouds. NoSQL databases are suitable for using as cloud data management systems. However, it is challenging to migrate relational databases to highly scalable NoSQL databases on clouds. The objective of this research project is to extend our work to cloud service composition.
Jing Li
Towards Quality Guided Data Integration on Multi-cloud Settings
Abstract
This PhD project addresses data integration considering data quality (freshness, provenance, cost, availability) properties in a multi-cloud context. In fact, in a multi-cloud context, data is made available through a huge offer of services deployed on different clouds with heterogeneous quality of service features. By users who thank to their contracts with the clouds expressed by traditional SLA according to their rights. Consequently, data integration in this context needs to take into account these new constraints. The aim of our work is to revisit previously proposed data integration solutions in order to adapt them to the multi-cloud context. Our solution consists in defining over the clouds a layer that provides a reasoning on the best services combination that meets services and user constraints and willings, the best way to deploy the integration process. This layer should let further data integration easier thank to the definition of a new kind of SLA called Integration SLA. This paper gives a model-oriented vision of our proposal.
Daniel A. S. Carvalho
Revenue-Driven Service Provision for Mobile Hosts
Abstract
The development of modern technologies has greatly improved the capability of mobile devices. Along with this, mobile devices can provide their idle resources such as apps, sensors and network to others via service computing. However, mobile service hosts cannot satisfy excessive service requests due to relatively limited capabilities and resources. Therefore, how to select service requests and schedule them to an efficient utilization has become a critical problem. To deal with this problem, we propose a novel approach named RDSP4MH (revenue-drive service provision for mobile hosts) towards request selection, request scheduling and resource allocation for mobile service hosts. The experiments have demonstrated the high performance and efficiency of the algorithm.
Hongyue Wu, Shuiguang Deng, Jianwei Yin
Context-Aware Automated Workflow Composition for Interactive Data Exploration
Abstract
Nowadays, the Web of Data contains a myriad of structured information sources on a large number of domains. Nevertheless, most of the information is available through Web APIs that act as isolated silos of data that cannot interoperate automatically with other resources and services on the Web. My dissertation aims at synthesizing semantic web technologies over Web APIs, in order to combine the easy data integration techniques offered by semantic web, with the flexibility and availability of web services. This paper discusses the two main aspects of the envisioned thesis: (a) a description language to semantically describe functional and non-functional components of web services, and the relationships among those components, and (b) a middleware that plans composition chains, based on user’s specifications, optimizing their trade-offs.
Diego Serrano
Towards Rules-Based Mapping Framework for RESTful Web Services
Abstract
Integrating web services is usually time-consuming and requires a lot of programming efforts and experiences due to documentation burden and coding style convention overhead provided by external parties. Fortunately, RESTful web services simplify the integration task compared to the traditional web service WSDL as coding convention is significantly reduced. However, the documentation burden is still evident and developers usually rely on running examples to gain better knowledge and use web service documentation efficiently. The subject of my PhD thesis is to propose a novel rules-based mapping method for mapping a desired web service to potential candidates from a predefined web service repository. In this research, the assumption is that web services are made of RESTful APIs specified in Javascript Object Notation (JSON) format. My significant thesis contributions are: (1) a hybrid model for web service similarity, (2) a rules-based mapping approach for identifying and classifying the most related and similar services against a given desired web service, and lastly (3) a concrete and detailed evaluation to show the effectiveness of the proposed approach and framework.
Khanh Duc Hoang Le

Demonstration

Frontmatter
Demand-Driven SOA Simulation Platform Based on GIPSY for Context-Based Brokerage
Abstract
This demo complements our main research contribution to illustrate a demand-driven SOA extension of the GIPSY’s multi-tier architecture as a simulation scenario testbed for scalable context aware brokerage testing and data integration.
Touraj Laleh, Esteban Garro, Jashanjot Singh, Gurpreet Raju, Muhammad Usman, Serguei Mokhov, Joey Paquet
DeMOCAS: Domain Objects for Service-Based Collective Adaptive Systems
Abstract
DeMOCAS is a framework for the modeling and execution of service-based collective adaptive systems operating in dynamic environments. In this framework, we apply the Domain Object model and a Collective Adaptation algorithm to a case study from the mobility domain and we show its advantages in handling large-scale, decentralized and adaptive applications.
Antonio Bucchiarone, Martina De Sanctis, Annapaola Marconi, Alberto Martinelli
Anuvaad Pranaali: A RESTful API for Machine Translation
Abstract
The current web APIs are end-user centric as they mostly focus on the end results. In this paper, we break this paradigm for one class of scientific workflow problems —machine translation, by designing an API that caters not only to the end users but also allows researchers to find bugs in their systems by exposing the ability to programmatically manipulate the results. Moreover, it follows an easy to replicate workflow based mechanism, which is built on the concept of microservices.
Nehal J. Wani, Sharada Prasanna Mohanty, Suresh Purini, Dipti Misra Sharma
Integration of Heterogeneous Services and Things into Choreographies
Abstract
Internet-of-Things (IoT) protocols are constantly increasing in the research and industrial landscape. However, the current standardization efforts limit the incorporation of Things as first-class entities into choreographies. To tackle this interoperability barrier, we propose and demonstrate the eVolution Service Bus (VSB), a middleware solution targeted to enable the interaction between Things-based and business-oriented services. Particularly, we demonstrate the incorporation of a service/Thing into the following choreographies: (i) temperature sensors interacting with a business-oriented service, and (ii) business-oriented services interacting with a route planner service.
Georgios Bouloukakis, Nikolaos Georgantas, Siddhartha Dutta, Valérie Issarny
Testing Processes with Service Invocation: Advanced Logging in CPEE
Abstract
Business process analysis is one of the major concerns for companies: before processes are enacted and executed, flaws and bottlenecks should be removed. Process simulation has been traditionally used to simulate process paths based on stochastic information. However, the obtained results are often not consistent with the behavior that can be observed later during process execution as the functioning and reaction of the orchestrated web services cannot be considered. To provide more realistic results, a process testing environment is presented that equips the Cloud Process Execution Engine (CPEE) with a newly developed logging component. The contribution of the logging component is that it incorporates simulated data from invoked services and thus allows for the generation of more realistic log files.
Florian Stertz, Stefanie Rinderle-Ma, Tobias Hildebrandt, Juergen Mangler
COOL: A Model-Driven and Automated System for Guided and Verifiable Cloud Solution Design
Abstract
In this paper, we present COOL (ClOud sOlution design tooL), which is a model-driven cloud solution design tool for automatic solution generation, and solution verification. It offers a guided solutioning and customization method starting from complex client business and IT requirements, and enables verification of solution correctness by leveraging constraint satisfaction solvers.
Hamid R. Motahari Nezhad, Karen Yorov, Peifeng Yin, Taiga Nakamura, Scott Trent, Gil Shurek, Takayuki Kushida, Uma Subramanian
A Service-Based System for Sentiment Analysis and Visualization of Twitter Data in Realtime
Abstract
The existing solutions for sentiment analysis suffer from serious shortcomings to effectively deal with Twitter data as they can merely exploit hashtags. In this demo, we present SANA: a reusable, service-based architecture for dealing with streaming data, analysing this data on the fly taking into account more comprehensive semantics of Tweets, and dynamically monitoring and visualising trends in sentiments through dasbboarding and query facilities.
Yehia Taher, Rafiqul Haque, Mohammed AlShaer, Willem Jan v. d. Heuvel, Karine Zeitouni, Renata Araujo, Mohand-Saïd Hacid, Mohamed Dbouk
XDAI-A: Framework for Enabling Cross-Device Integration of Android Apps
Abstract
A lot of people are managing multiple computing devices suited for different purposes, like private and work devices. Integrating applications running on different devices is often a problem, because the services provided by those applications are not meant to be integrated. In this demonstration, we present our XDAI-A framework which enables cross-device integration of services provided by Android apps. The framework uses adapters to convert Android-internal service interfaces of existing apps into external services with a platform-independent interface that can be accessed from applications on other devices and even other platforms. Our ready-to-use framework does not require to alter existing Android apps, since the adapters are installed separately. For the convenient specification of adapters, our framework comes with a domain-specific language (DSL). Additionally, we provide an infrastructure to find and integrate devices and their applications’ services.
Dennis Wolters, Jonas Kirchhoff, Christian Gerth, Gregor Engels
Desire: Deep Semantic Understanding and Retrieval for Technical Support Services
Abstract
Technical support services involve enterprises providing after-sales support to users of technology products. The current support structure is labor intensive with practitioners manually consulting support documentation to troubleshoot users’ problems. We propose a cognitive technical support system as one that: (a) can understand technical problems expressed by users, (b) can automatically provide relevant resolution information and (c) can learn and improve its understanding and resolution over time. A typical technical problem description contains a combination of symptoms experienced by the user, explanation of attempts already made to resolve the problem, and sometimes, a clear expression of the requirement to solve the problem. Handling such intricate descriptions is outside the scope of current retrieval based systems and requires a deep understanding of the problem, combined with reasoning over a knowledge graph.
Abhirut Gupta, Arjun Akula, Gargi Dasgupta, Pooja Aggarwal, Prateeti Mohapatra
BlueSight: Automated Discovery Service for Cloud Migration of Enterprises
Abstract
Migrating legacy enterprise infrastructures to the cloud is highly desirable due to greater versatility, lower management costs, as well as improved scalability. However, the large scale of these systems makes transforming the current architecture a long and difficult process that involves weeks or even months of manual collection and analysis of data. BlueSight serves to expedite and simplify this process by collecting the data through an agentless process and analyzing the collected data to determine which and how applications should migrate.
Dannver Wu, Jinho Hwang, Maja Vukovic, Nikos Anerousis
A Configurator Component for End-User Defined Mobile Data Collection Processes
Abstract
The widespread dissemination of smart mobile devices offers promising perspectives for collecting huge amounts of data. When realizing mobile data collection applications (e.g., to support clinical trials), challenging issues arise. For example, many real-world projects require support for heterogeneous mobile operating systems. Usually, existing data collection approaches are based on specifically tailored mobile applications. As a drawback, changes of a data collection procedure require costly code adaptations. To remedy this drawback, we implemented a model-driven approach that enables end-users to realize mobile data collection applications themselves. This paper demonstrates the developed configurator component, which enables domain experts to implement digital questionnaires. Altogether, the configurator component allows for the fast development of questionnaires and hence for collecting data in large-scale scenarios using smart mobile devices.
Johannes Schobel, Rüdiger Pryss, Marc Schickler, Manfred Reichert
Backmatter
Metadata
Title
Service-Oriented Computing – ICSOC 2016 Workshops
Editors
Khalil Drira
Hongbing Wang
Qi Yu
Yan Wang
Yuhong Yan
François Charoy
Jan Mendling
Mohamed Mohamed
Zhongjie Wang
Sami Bhiri
Copyright Year
2017
Electronic ISBN
978-3-319-68136-8
Print ISBN
978-3-319-68135-1
DOI
https://doi.org/10.1007/978-3-319-68136-8

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