Service recommendation and selection in centralized and decentralized environments.

With the increasing use of web services in everyday tasks we are entering an era of Internet of Services (IoS). Service discovery and selection in both centralized and decentralized environments have become a critical issue in the area of web services, in particular when services having similar functionality but different Quality of Service (QoS). As a result, selecting a high quality service that best suits consumer requirements from a large list of functionally equivalent services is a challenging task. In response to increasing numbers of services in the discovery and selection process, there is a corresponding increase of service consumers and a consequent diversity in Quality of Service (QoS) available. Increases in both sides leads to a diversity in the demand and supply of services, which would result in the partial match of the requirements and offers. Furthermore, it is challenging for customers to select suitable services from a large number of services that satisfy consumer functional requirements. Therefore, web service recommendation becomes an attractive solution to provide recommended services to consumers which can satisfy their requirements.In this thesis, first a service ranking and selection algorithm is proposed by considering multiple QoS requirements and allowing partially matched services to be counted as a candidate for the selection process. With the initial list of available services the approach considers those services with a partial match of consumer requirements and ranks them based on the QoS parameters, this allows the consumer to select suitable service. In addition, providing weight value for QoS parameters might not be an easy and understandable task for consumers, as a result an automatic weight calculation method has been included for consumer requirements by utilizing distance correlation between QoS parameters. The second aspect of the work in the thesis is the process of QoS based web service recommendation. With an increasing number of web services having similar functionality, it is challenging for service consumers to find out suitable web services that meet their requirements. We propose a personalised service recommendation method using the LDA topic model, which extracts latent interests of consumers and latent topics of services in the form of probability distribution. In addition, the proposed method is able to improve the accuracy of prediction of QoS properties by considering the correlation between neighbouring services and return a list of recommended services that best satisfy consumer requirements. The third part of the thesis concerns providing service discovery and selection in a decentralized environment. Service discovery approaches are often supported by centralized repositories that could suffer from single point failure, performance bottleneck, and scalability issues in large scale systems. To address these issues, we propose a context-aware service discovery and selection approach in a decentralized peer-to-peer environment. In the approach homophily similarity was used for bootstrapping and distribution of nodes. The discovery process is based on the similarity of nodes and previous interaction and behaviour of the nodes, which will help the discovery process in a dynamic environment. Our approach is not only considering service discovery, but also the selection of suitable web service by taking into account the QoS properties of the web services. The major contribution of the thesis is providing a comprehensive QoS based service recommendation and selection in centralized and decentralized environments. With the proposed approach consumers will be able to select suitable service based on their requirements. Experimental results on real world service datasets showed that proposed approaches achieved better performance and efficiency in recommendation and selection process.N/

Exploiting cloud utility models for profit and ruin

A key characteristic that has led to the early adoption of public cloud computing is the utility pricing model that governs the cost of compute resources consumed. Similar to public utilities like gas and electricity, cloud consumers only pay for the resources they consume and only for the time they are utilized. As a result and pursuant to a Cloud Service Provider\u27s (CSP) Terms of Agreement, cloud consumers are responsible for all computational costs incurred within and in support of their rented computing environments whether these resources were consumed in good faith or not. While initial threat modeling and security research on the public cloud model has primarily focused on the confidentiality and integrity of data transferred, processed, and stored in the cloud, little attention has been paid to the external threat sources that have the capability to affect the financial viability of cloud-hosted services. Bounded by a utility pricing model, Internet-facing web resources hosted in the cloud are vulnerable to Fraudulent Resource Consumption (FRC) attacks. Unlike an application-layer DDoS attack that consumes resources with the goal of disrupting short-term availability, a FRC attack is a considerably more subtle attack that instead targets the utility model over an extended time period. By fraudulently consuming web resources in sufficient volume (i.e. data transferred out of the cloud), an attacker is able to inflict significant fraudulent charges to the victim. This work introduces and thoroughly describes the FRC attack and discusses why current application-layer DDoS mitigation schemes are not applicable to a more subtle attack. The work goes on to propose three detection metrics that together form the criteria for detecting a FRC attack from that of normal web activity and an attribution methodology capable of accurately identifying FRC attack clients. Experimental results based on plausible and challenging attack scenarios show that an attacker, without knowledge of the training web log, has a difficult time mimicking the self-similar and consistent request semantics of normal web activity necessary to carryout a successful FRC attack

A formal architecture-centric and model driven approach for the engineering of science gateways

From n-Tier client/server applications, to more complex academic Grids, or even the most recent and promising industrial Clouds, the last decade has witnessed significant developments in distributed computing. In spite of this conceptual heterogeneity, Service-Oriented Architecture (SOA) seems to have emerged as the common and underlying abstraction paradigm, even though different standards and technologies are applied across application domains. Suitable access to data and algorithms resident in SOAs via so-called ‘Science Gateways’ has thus become a pressing need in order to realize the benefits of distributed computing infrastructures.In an attempt to inform service-oriented systems design and developments in Grid-based biomedical research infrastructures, the applicant has consolidated work from three complementary experiences in European projects, which have developed and deployed large-scale production quality infrastructures and more recently Science Gateways to support research in breast cancer, pediatric diseases and neurodegenerative pathologies respectively. In analyzing the requirements from these biomedical applications the applicant was able to elaborate on commonly faced issues in Grid development and deployment, while proposing an adapted and extensible engineering framework. Grids implement a number of protocols, applications, standards and attempt to virtualize and harmonize accesses to them. Most Grid implementations therefore are instantiated as superposed software layers, often resulting in a low quality of services and quality of applications, thus making design and development increasingly complex, and rendering classical software engineering approaches unsuitable for Grid developments.The applicant proposes the application of a formal Model-Driven Engineering (MDE) approach to service-oriented developments, making it possible to define Grid-based architectures and Science Gateways that satisfy quality of service requirements, execution platform and distribution criteria at design time. An novel investigation is thus presented on the applicability of the resulting grid MDE (gMDE) to specific examples and conclusions are drawn on the benefits of this approach and its possible application to other areas, in particular that of Distributed Computing Infrastructures (DCI) interoperability, Science Gateways and Cloud architectures developments

Flexible Automation and Intelligent Manufacturing: The Human-Data-Technology Nexus

This is an open access book. It gathers the first volume of the proceedings of the 31st edition of the International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2022, held on June 19 – 23, 2022, in Detroit, Michigan, USA. Covering four thematic areas including Manufacturing Processes, Machine Tools, Manufacturing Systems, and Enabling Technologies, it reports on advanced manufacturing processes, and innovative materials for 3D printing, applications of machine learning, artificial intelligence and mixed reality in various production sectors, as well as important issues in human-robot collaboration, including methods for improving safety. Contributions also cover strategies to improve quality control, supply chain management and training in the manufacturing industry, and methods supporting circular supply chain and sustainable manufacturing. All in all, this book provides academicians, engineers and professionals with extensive information on both scientific and industrial advances in the converging fields of manufacturing, production, and automation

Analysis and design of security mechanisms in the context of Advanced Persistent Threats against critical infrastructures

Industry 4.0 can be defined as the digitization of all components within the industry, by combining productive processes with leading information and communication technologies. Whereas this integration has several benefits, it has also facilitated the emergence of several attack vectors. These can be leveraged to perpetrate sophisticated attacks such as an Advanced Persistent Threat (APT), that ultimately disrupts and damages critical infrastructural operations with a severe impact. This doctoral thesis aims to study and design security mechanisms capable of detecting and tracing APTs to ensure the continuity of the production line. Although the basic tools to detect individual attack vectors of an APT have already been developed, it is important to integrate holistic defense solutions in existing critical infrastructures that are capable of addressing all potential threats. Additionally, it is necessary to prospectively analyze the requirements that these systems have to satisfy after the integration of novel services in the upcoming years. To fulfill these goals, we define a framework for the detection and traceability of APTs in Industry 4.0, which is aimed to fill the gap between classic security mechanisms and APTs. The premise is to retrieve data about the production chain at all levels to correlate events in a distributed way, enabling the traceability of an APT throughout its entire life cycle. Ultimately, these mechanisms make it possible to holistically detect and anticipate attacks in a timely and autonomous way, to deter the propagation and minimize their impact. As a means to validate this framework, we propose some correlation algorithms that implement it (such as the Opinion Dynamics solution) and carry out different experiments that compare the accuracy of response techniques that take advantage of these traceability features. Similarly, we conduct a study on the feasibility of these detection systems in various Industry 4.0 scenarios

Rise of the Planet of Serverless Computing: A Systematic Review

Serverless computing is an emerging cloud computing paradigm, being adopted to develop a wide range of software applications. It allows developers to focus on the application logic in the granularity of function, thereby freeing developers from tedious and error-prone infrastructure management. Meanwhile, its unique characteristic poses new challenges to the development and deployment of serverless-based applications. To tackle these challenges, enormous research efforts have been devoted. This paper provides a comprehensive literature review to characterize the current research state of serverless computing. Specifically, this paper covers 164 papers on 17 research directions of serverless computing, including performance optimization, programming framework, application migration, multi-cloud development, testing and debugging, etc. It also derives research trends, focus, and commonly-used platforms for serverless computing, as well as promising research opportunities

Applications of Internet of Things

This book introduces the Special Issue entitled “Applications of Internet of Things”, of ISPRS International Journal of Geo-Information. Topics covered in this issue include three main parts: (I) intelligent transportation systems (ITSs), (II) location-based services (LBSs), and (III) sensing techniques and applications. Three papers on ITSs are as follows: (1) “Vehicle positioning and speed estimation based on cellular network signals for urban roads,” by Lai and Kuo; (2) “A method for traffic congestion clustering judgment based on grey relational analysis,” by Zhang et al.; and (3) “Smartphone-based pedestrian’s avoidance behavior recognition towards opportunistic road anomaly detection,” by Ishikawa and Fujinami. Three papers on LBSs are as follows: (1) “A high-efficiency method of mobile positioning based on commercial vehicle operation data,” by Chen et al.; (2) “Efficient location privacy-preserving k-anonymity method based on the credible chain,” by Wang et al.; and (3) “Proximity-based asynchronous messaging platform for location-based Internet of things service,” by Gon Jo et al. Two papers on sensing techniques and applications are as follows: (1) “Detection of electronic anklet wearers’ groupings throughout telematics monitoring,” by Machado et al.; and (2) “Camera coverage estimation based on multistage grid subdivision,” by Wang et al