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This paper studies the economic utilities and the quality of service (QoS) in a two-sided non-neutral market where Internet service providers (ISPs) charge content providers (CPs) for the content delivery. We propose new models on a two-sided market which involves a CP, an ISP, end users and advertisers. The CP may have either the subscription revenue model (charging end users) or the advertisement revenue model (charging advertisers). We formulate the interactions between the ISP and the CP as a noncooperative game problem for the former and an optimization problem for the latter. Our analysis shows that the revenue model of the CP plays a significant role in a non-neutral Internet. With the subscription model, both the ISP and the CP receive better (or worse) utilities as well as QoS in the presence of side payment at the same time. However, with the advertisement model, the side payment impedes the CP from investing on its contents., Comment: 15 pages, 10 figures

Part 4: Machine Learning for Systems; International audience; The mobile ecosystem is witnessing an unprecedented increase in the number of malware in the wild. To fight this threat, actors from both research and industry are constantly innovating to bring concrete solutions to improve security and malware protection. Traditional solutions such as signature-based anti viruses have shown their limits in front of massive proliferation of new malware, which are most often only variants specifically designed to bypass signature-based detection. Accordingly, it paves the way to the emergence of new approaches based on Machine Learning (ML) technics to boost the detection of unknown malware variants. Unfortunately, these solutions are most often underexploited due to the time and resource costs required to adequately fine tune machine learning algorithms. In reality, in the Android community, state-of-the-art studies do not focus on model training, and most often go through an empirical study with a manual process to choose the learning strategy, and/or use default values as parameters to configure ML algorithms. However, in the ML domain, it is well known admitted that to solve efficiently a ML problem, the tunability of hyper-parameters is of the utmost importance. Nevertheless, as soon as the targeted ML problem involves a massive amount of data, there is a strong tension between feasibility of exploring all combinations and accuracy. This tension imposes to automate the search for optimal hyper-parameters applied to ML algorithms, that is not anymore possible to achieve manually. To this end, we propose a generic and scalable solution to automatically both configure and evaluate ML algorithms to efficiently detect Android malware detection systems. Our approach is based on devOps principles and a microservice architecture deployed over a set of nodes to scale and exhaustively test a large number of ML algorithms and hyper-parameters combinations. With our approach, we are able to systematically find the best fit to increase up to 11% the accuracy of two state-of-the-art Android malware detection systems.

Part 1: Full Papers; International audience; Neural networks (NN) are taking over ever more decisions thus far taken by humans, even though verifiable system-level guarantees are far out of reach. Neither is the verification technology available, nor is it even understood what a formal, meaningful, extensible, and scalable testbed might look like for such a technology. The present paper is a modest attempt to improve on both the above aspects. We present a family of formal models that contain basic features of automated decision making contexts and which can be extended with further orthogonal features, ultimately encompassing the scope of autonomous driving. Due to the possibility to model random noise in the decision actuation, each model instance induces a Markov decision process (MDP) as verification object. The NN in this context has the duty to actuate (near-optimal) decisions. From the verification perspective, the externally learnt NN serves as a determinizer of the MDP, the result being a Markov chain which as such is amenable to statistical model checking. The combination of a MDP and a NN encoding the action policy is central to what we call “deep statistical model checking” (DSMC). While being a straightforward extension of statistical model checking, it enables to gain deep insight into questions like “how high is the NN-induced safety risk?”, “how good is the NN compared to the optimal policy?” (obtained by model checking the MDP), or “does further training improve the NN?”. We report on an implementation of DSMC inside The Modest Toolset in combination with externally learnt NNs, demonstrating the potential of DSMC on various instances of the model family.

Part 3: Message-Based Communication; International audience; We propose a model-driven approach based on formal data-driven choreographies to model message-passing applications. We apply our approach to the threat intelligence exchange (TIE) services provided by McAfee through the OpenDXL industrial platform. We advocate a chain of model transformations that (i) devises a visual presentation of communication protocols, (ii) formalises a global specification from the visual presentation that captures the data flow among services, (iii) enables the automatic derivation of specifications for the single components, and (iv) enables the analysis of software implementations.

Part 3: eBusiness; International audience; This study aims to identify the conceptual structure and the thematic progress in e-Business, e-Services and e-Society and to elaborate on backbone/emerging topics in the field from 2001 to 2019. To address this objective, this paper employs hierarchical clustering, strategic diagrams and network analysis to construct the intellectual map of the I3E community and to visualize the thematic landscape in this field, using co-word analysis. Overall, a total of 835 papers from the proceedings of the e-Business, e-Services and e-Society (I3E) conference, and the respective 2574 author-assigned keywords, were included in the analyses. The results indicate that the community has significantly focused in areas like technology adoption models, Social Media, e-Government and business models; sentiment analysis and m-payments are peripheral themes, yet topics like cloud computing and Open Data are emerging. The analysis highlights the shift of the research interest throughout the past decades, and the rise of new topics, comprising evidence that the field is expanding and evolving. Limitations of the approach and future work plans conclude the paper.

Part 3: eBusiness; International audience; Sustainable food security (Sfs) desires not only that people always have passage to ample and nutritious food, but also that this food be formed with minimum environmental impact. This research is aimed at developing a mobile application for marketing organic farm products with the functionality of automated geo-location services, preferred goods delivery services, easy access to different organic farm produce. The mobile user platform consists of the Presentation, Business, Data and Data storage which is a slight variation of the Model-View-Controller architecture. It also takes into deep awareness the configuration, security and communications aspect as these are the underlying factors for the robustness of mobile application. The Presentation Tier consists of the user interface and the logic used to navigate around the user interface meaningfully. It modifies and shows information into a human distinct pattern. The Business Logic tier is essentially efficient for information transfer between the user interface and the database of the project. The last layer of the three-tiered architecture is the Data Access tier, which is made up of the Database servers. The application was implemented in Java, SQLite (local) and PHP for the backend server and Amazon Web Services for cloud infrastructure. Farmers were engaged in cursory testing. Users find the application concept very interesting.

Part 2: Fourth Industrial Revolution; International audience; Smart manufacturing, Industry 4.0 and Smart Factory are phenomena regarded as a key necessity for Small, Medium and Micro Businesses (SMMEs) worldwide. Even though these 4th Industrial Revolution (4IR) phenomena are generally used interchangeably, this paper sought to identify how SMME readiness for smart manufacturing has been investigated through a systematic review. The systematic review was conducted through the lens of Nooteboom, and Tornatzky and Klein’s research on technological innovation in SMMEs based on Rogers’ diffusion of innovations theory. The findings reveal that there is little to no research on smart manufacturing in relation to SMMEs in low-income countries particularly the African continent. The results also show that smart manufacturing is still an emergent phenomenon with disparate definitional challenges. These definitional challenges make the adoption of smart manufacturing innovations a challenge in resource-constrained contexts; but similarly present an opportunity for new definitions and theories in such contexts. The little research often treats SMMEs homogenously and as such misses their important heterogeneous (sector or industry specific) nature. Few research studies investigate SMME awareness (adequate knowledge) or make explicit the benefits (relative advantage) of smart manufacturing. Even fewer studies are explicit on the smart manufacturing technologies that are relevant for different SMME sectors. Smart manufacturing is identified as incompatible with SMME characteristics, that is SMMEs lack expertise/skills to comprehend the complexity of smart manufacturing, and also lack financial and human resources to implement smart manufacturing. Given that awareness, relative advantage, complexity and compatibility are critical barriers for SMME smart manufacturing readiness/adoption, there is a critical need for research to focus on these factors in particular for the context of resource constrained low-income country environments.

Part 2: Fourth Industrial Revolution; International audience; Inter-organisational relationships have been receiving increased attention in the context of the fourth industrial revolution. Technological advances in connectivity and digitisation are enabling vertically and horizontally integrated networks. The highly technical and dynamic environment in which various types of relationships exist requires a high level of cooperation and transparency between partners. The importance for Small and Medium Sized Organisations (SMEs) to develop and improve their relational capabilities is widely acknowledged. This research paper thus presents a tool and methodology that will enable SMEs to assess and improve these capabilities within the organisation. This paper aims to identify those requirements and practices described in the literature as conducive to sustainable relationship formation and development. A Relational Capability Maturity Model (RCMM) is proposed as a tool that will be able to address the requirements across the various functions of the organisation.

Part 4: Business Processes; International audience; Finding and comparing appropriate cloud services that best fit cloud service consumer requirements can be a complex, time-consuming and cost-intensive process, especially for small and medium-sized enterprises. Since there is no “one-fits-all” cloud service provider, companies face the challenge of selecting and combining services from different vendors to meet all their requirements. Therefore, this paper calls for the design of a cloud brokering framework that would enable faster and easier selection of cloud services by recommending appropriate services through a matchmaking system. Drawing on previously conducted studies and considering current issues and practical experiences both from provider and user perspectives, we propose a framework that would identify, rank and recommend cloud services from multiple modules and components to individual consumers. Furthermore, we contribute an early-stage design of a cloud broker framework that considers cloud-service consumers’ sourcing preferences while making new cloud-sourcing decisions and that can be used in the selection and adoption phase of implementing cloud services and/or as part of a multicloud strategy.

Part 2: Fault Tolerance and Big Data; International audience; To process big data, applications have been utilizing data processing libraries over the last years, which are however not optimized to work together for efficient processing. Intermediate Representations (IR) have been introduced for unifying essential functions into an abstract interface that supports cross-optimization between applications. Still, the efficiency of an IR depends on the architecture and the tools required for compilation and execution. In this paper, we present a first glance at a framework that provides an IR by creating containers with executable code from structures of data analytics functions, described in an input grammar. These containers process data in query lists and they can be executed either standalone or integrated with other big data analytics applications without the need to compile the entire framework.

Part 4: Modelling: Structures and Implementations; International audience; The Contract Automata Tool is an open-source tool for the specification, composition and synthesis of coordination of service contracts, including functionalities to deal with modalities and configurations. We discuss an implementation of the abstract parametric synthesis algorithm firstly introduced in our COORDINATION 2019 paper, comprehending most permissive controller, orchestration and choreography synthesis. The tool’s source code has been redesigned and refactored in Java 8, and we show the resulting gain in computational efficiency.

A k-anonymous broadcast can be implemented using a small group of dining cryptographers to first share the message, followed by a flooding phase started by group members. Members have little incentive to forward the message in a timely manner, as forwarding incurs costs, or they may even profit from keeping the message. In worst case, this leaves the true originator as the only sender, rendering the dining-cryptographers phase useless and compromising their privacy. We present a novel approach using a modified dining-cryptographers protocol to distributed shares of an (n,k)-Shamir's secret sharing scheme. Finally, all group members broadcast their received share through the network, allowing any recipient of k shares to reconstruct the message, enforcing anonymity. If less than k group members broadcast their shares, the message cannot be decoded thus preventing privacy breaches for the originator. Our system provides (n-|attackers|)-anonymity for up to k-1 attackers and has little performance impact on dissemination. We show these results in a security analysis and performance evaluation based on a proof-of-concept prototype. Throughput rates between 10 and 100 kB/s are enough for many real applications with high privacy requirements, e.g., financial blockchain system., 16 pages, 5 figures

Part 3: Distributed Algorithms; International audience; Federated learning is a novel research area of AI technology that focus on distributed training and privacy preservation. Current federated optimization algorithms face serious challenge in the aspects of speed and accuracy, especially in non-i.i.d scenario. In this work, we propose UCBFed, a federated optimization algorithm that uses the Upper Confidence Bound (UCB) method to heuristically select participating clients in each round’s optimization process. We evaluate our algorithm in multiple federated distributed datasets. Comparing to most widely-used FedAvg and FedOpt, the UCBFed we proposed is superior in both the final accuracy and communication efficiency.

Docker images are used to distribute and deploy cloud-native applications in containerised form. A container engine runs them with separated privileges according to namespaces. Recent studies have investigated security vulnerabilities and runtime characteristics of Docker images. In contrast, little is known about the extent of hardware-dependent features in them such as processor-specific trusted execution environments, graphics acceleration or extension boards. This problem can be generalised to missing knowledge about the extent of any hardware-bound instructions within the images that may require elevated privileges. We first conduct a systematic one-year evolution analysis of a sample of Docker images concerning their use of hardware-specific features. To improve the state of technology, we contribute novel tools to manage such images. Our heuristic hardware dependency detector and a hardware-aware Docker executor give early warnings upon missing dependencies instead of leading to silent or untimely failures. Our dataset and tools are released to the research community., 21st International Conference on Distributed Applications and Interoperable Systems

Part 2: Communications: Types and Implemenations; International audience; Rust is a popular systems language focused on performance and reliability, with an emphasis on providing “fearless concurrency”. Message passing has become a widely-used pattern by Rust developers although the potential for communication errors leaves developing safe and concurrent applications an unsolved challenge. In this ongoing work, we use multiparty session types to provide safety guarantees such as deadlock-freedom by coordinating message-passing processes. In contrast to previous contributions [20–22], our implementation targets asynchronous applications using / code in Rust. Specifically, we incorporate asynchronous subtyping theory, which allows program optimisation through reordering input and output actions. We evaluate our ideas by developing several representative use cases from the literature and by taking microbenchmarks. We discuss our plans to support full API generation integrating asynchronous optimisations.

Session types denote message protocols between concurrent processes, allowing a type-safe expression of inter-process communication. Although previous work demonstrate a well-defined notion of subtyping where processes have different perceptions of the protocol, these formulations were limited to linear session types where each channel of communication has a unique provider and client. In this paper, we extend subtyping to shared session types where channels can now have multiple clients instead of a single client. We demonstrate that this generalization can statically capture protocol requirements that span multiple phases of interactions of a client with a shared service provider, something not possible in prior proposals. Moreover, the phases are manifest in the type of the client., Extended and revised version of a paper presented at COORDINATION 2021

Part 5: Microservices; International audience; Field-based coordination is a model for expressing the coordination logic of large-scale adaptive systems, composing functional blocks from a global perspective. As for any coordination model, a proper toolchain must be developed to support its adoption across all development phases. Under this point of view, the ScaFi toolkit provides a coordination language (field calculus) as a DSL internal in the Scala language, a library of reusable building blocks, and an infrastructure for simulation of distributed deployments. In this work, we enrich such a toolchain by introducing ScaFi-Web, a web-based application allowing in-browser editing, execution, and visualisation of ScaFi programs. ScaFi-Web facilitates access to the ScaFi coordination technology by flattening the learning curve and simplifying configuration and requirements, thus promoting agile prototyping of field-based coordination specifications. In turn, this opens the door to easier demonstrations and experimentation, and also constitutes a stepping stone towards monitoring and control of simulated/deployed systems.

Part 1: Tutorial; International audience; Actor languages decouple communication from synchronization, which makes them suitable for distributed and scalable applications with flexible synchronization patterns, but also facilitates analysis. ABS is a timed actor-based modeling language which supports cooperative scheduling and the specification of timing- and resource-sensitive behavior. Cooperative scheduling allows a process which is executing in an actor to be suspended while it is waiting for an event to occur, such that another process in the same actor can execute. Timed semantics allows the specification of the temporal behavior of the modeled system. Resource-sensitive behavior takes a supply and demand perspective of execution, relating cost centers which provision resources to processes which require them. These modeling concepts have been used in ABS to model cloud computing, e.g., data-processing applications running on the Hadoop platform and micro-services running on containers orchestrated by Kubernetes. In this tutorial, we present ABS and its execution environment, and discuss the use of cooperative scheduling and resources in modeling cyber-physical systems and applications deployed on virtualized infrastructure.

Part 2: Communications: Types and Implemenations; International audience; Detecting programming errors and vulnerabilities in software is increasingly important, and building tools that help developers with this task is a crucial area of investigation on which the industry depends. In object-oriented languages, one naturally defines stateful objects where the safe use of methods depends on their internal state; the correct use of objects according to their protocols is then enforced at compile-time by an analysis based on behavioral types.We present Java Typestate Checker (JATYC), a tool based on the Checker Framework that verifies Java programs with respect to typestates. These define the object’s states, the methods that can be called in each state, and the states resulting from the calls. The tool offers the following strong guarantees: sequences of method calls obey to object’s protocols; completion of objects’ protocols; detection of null-pointer exceptions; and control of the sharing of resources through access permissions.To the best of our knowledge, there are no research or industrial tools that offer all these features. In particular, the implementation of sharing control in a typestate-based tool seems to be novel, and has an important impact on programming flexibility, since, for most programs, the linear discipline imposed by behavioral types is too strict.Sharing of objects is enabled by means of an assertion language incorporating fractional permissions; to lift from programmers the burden of writing the assertions, JATYC infers all of these by building a constraint system and solving it with Z3, producing general assertions sufficient to accept the code, if these exist.

Part 1: Cloud and Fog Computing; International audience; Multi-tenancy enables cost-effective SaaS through resource consolidation. Multiple customers, or tenants, are served by a single application instance, and isolation is enforced at the application level. Service load for different tenants can vary over time, requiring applications to scale in and out. A large class of SaaS providers operates legacy applications structured around a relational (SQL) database. These applications achieve tenant isolation through dedicated fields in their relational schema and are not designed to support scaling operations. We present a novel solution for scaling in or out such applications through the migration of a tenant’s data to new application and database instances. Our solution requires no change to the application and incurs no service downtime for non-migrated tenants. It leverages external tables and foreign data wrappers, as supported by major relational databases. We evaluate the approach using two multi-tenant applications: Iomad, an extension of the Moodle Learning Management System, and Camunda, a business process management platform. Our results show the usability of the method, minimally impacting performance for other tenants during migration and leading to increased service capacity after migration.

Part 5: Short Contributions; International audience; Highly configurable systems (HCSs), such as software product lines, have complex configuration spaces. Combinatorial Testing and Random Testing are the main approaches to testing of HCSs. In this paper, we empirically compare their strengths with respect to scalability and diversity of sampled configurations (i.e., tests). We choose Icpl and QuickSampler to respectively represent Combinatorial Testing and Random Testing. Experiments are conducted to evaluate the t-way coverage criterion of generated test suites for HCS benchmarks.

Part 3: Testing Methods and Applications; International audience; There is a large need for effective and efficient testing processes and tools for mobile applications, due to their continuous evolution and to the sensitivity of their users to failures. Industries and researchers focus their effort to the realization of effective fully automatic testing techniques for mobile applications. Many of the proposed testing techniques lack in efficiency because their algorithms cannot be executed in parallel. In particular, Active Learning testing techniques usually relay on sequential algorithms.In this paper we propose a Active Learning technique for the fully automatic exploration and testing of Android applications, that parallelizes and improves a general algorithm proposed in the literature. The novel parallel algorithm has been implemented in the context of a prototype tool exploiting a component-based architecture, and has been experimentally evaluated on 3 open source Android applications by varying different deployment configurations.The measured results have shown the feasibility of the proposed technique and an average saving in testing time between 33% (deploying two testing resources) and about 80% (deploying 12 testing resources).

Part 2: Security Testing; International audience; Denial of Service (DoS) attacks represent an ever evolving landscape, which ranges from bruteforce flooding approaches to more sophisticated low-bandwidth slow techniques. DoS has become a major threat to the availability of modern web servers because of the large number of attack tools across the Internet. In spite of the increasing number of security modules that can be usefully deployed in production servers, there is not a one-fits-all defense solution against DoS.This paper proposes a measurement-based analysis of a well-established defense module for the Apache web server. The module is tested against both flooding and slow DoS attacks in order to quantify its capability at assuring correct service to legitimate clients. Results indicate that the module can mitigate flooding DoS attacks while causing some performance loss of the server; however, it is ineffective against slow attacks. The findings of our analysis are useful to support the deployment of proper defense mechanisms.

Part 3: Testing Methods and Applications; International audience; In this paper, we present a new design and proof of concept of a smart Near Field Communication (NFC) sniffer, including special trigger features for high-precision measurements during NFC interoperability testing. Even though interoperability testing is not mandatory for successful NFC-device certification, the fast increasing amount of electronic consumer devices providing NFC functionality strongly increases the need for interoperability testing. Nowadays, used automated interoperability test systems require time-consuming and expensive manual debug sessions in case of a communication error, to compensate missing test data for analyzing the failure root cause. To highly decrease costs and time required to perform these manual measurements, we developed a proof of concept of a sniffer tool providing intelligent trigger functionalities. It supports the test engineer during manual debug session and can be integrated into a fully automated interoperability test and analysis system. Hence, we drive the development of automated interoperability test systems and want to encourage standardization bodies to include interoperability testing to the certification procedure.

Part 3: Testing Methods and Applications; International audience; Service providers use cloud to reduce the cost of their services and speed up their time to market. There is a huge gap between the environment where the services are developed and first tested, and the environment where they operate. Live testing is defined as testing a service in its production environment without causing any intolerable disruption to its usage. It is considered as one of the solutions to overcome the impact of the difference between the development environment and the production environment on the reliability of the test results. Test interferences are a major challenge for live testing as they may lead to the system mishandling the production traffic. Existing solutions to alleviate the risk of interferences have limited applicability. In this paper we propose a set of test methods, applicable in different situations, for live testing to improve the reliability of test results without causing any intolerable disturbance to the cloud services. To reduce the complexity of these test methods we define the concept of boundary environments and a set of coverage criteria to aim at during live testing.

Part 2: Cloud and Systems; International audience; Virtual machine introspection (VMI) is the process of external monitoring of virtual machines. Previous work has demonstrated that VMI can contribute to the security of cloud environments and distributed systems, as it enables, for example, stealthy intrusion detection. One of the biggest challenges for applying VMI in production environments is the performance overhead that certain tracing operations impose on the monitored virtual machine. In this paper, we show how this performance overhead can be significantly minimized by incorporating minor extensions for VMI operations into the hypervisor. In a proof-of-concept implementation, we demonstrate that the pre-processing of VMI events in the Xen hypervisor reduces the monitoring overhead for the use case of VMI-based process-bound monitoring by a factor of 18.

Part 4: Communications: Types and Implementations; International audience; There are two approaches to defining subtyping relations: the syntactic and the semantic approach. In semantic subtyping, one defines a model of the language and an interpretation of types as subsets of this model. Subtyping is defined as inclusion of subsets denoting types.An orthogonal subtyping question, typical of object-oriented languages, is the nominal versus the structural subtyping. Dardha et al. [11, 12] defined boolean types and semantic subtyping for Featherweight Java (FJ) and integrated both nominal and structural subtyping, thus exploiting the benefits of both approaches. However, these benefits were illustrated only at a theoretical level, but not exploited practically.We present SFJ—Semantic Featherweight Java, an implementation of FJ which features boolean types, semantic subtyping and integrates nominal as well as structural subtyping. The benefits of SFJ, illustrated in the paper and the accompanying video (with audio/subtitles) [27], show how static type-checking of boolean types and semantic subtyping gives higher guarantees of program correctness, more flexibility and compactness of program writing.

Part 1: Privacy and Security; International audience; Cloud Computing services for data analytics are increasingly being sought by companies to extract value from large quantities of information. However, processing data from individuals and companies in third-party infrastructures raises several privacy concerns. To this end, different secure analytics techniques and systems have recently emerged. These initial proposals leverage specific cryptographic primitives lacking generality and thus having their application restricted to particular application scenarios. In this work, we contribute to this thriving body of knowledge by combining two complementary approaches to process sensitive data.We present SafeSpark, a secure data analytics framework that enables the combination of different cryptographic processing techniques with hardware-based protected environments for privacy-preserving data storage and processing. SafeSpark is modular and extensible therefore adapting to data analytics applications with different performance, security and functionality requirements.We have implemented a SafeSpark’s prototype based on Spark SQL and Intel SGX hardware. It has been evaluated with the TPC-DS Benchmark under three scenarios using different cryptographic primitives and secure hardware configurations. These scenarios provide a particular set of security guarantees and yield distinct performance impact, with overheads ranging from as low as 10% to an acceptable 300% when compared to an insecure vanilla deployment of Apache Spark.

Part 6: Large-Scale Decentralised Systems; International audience; Emerging application scenarios, such as cyber-physical systems (CPSs), the Internet of Things (IoT), and edge computing, call for coordination approaches addressing openness, self-adaptation, heterogeneity, and deployment agnosticism. Field-based coordination is one such approach, promoting the idea of programming system coordination declaratively from a global perspective, in terms of functional manipulation and evolution in “space and time” of distributed data structures, called fields. More specifically, regarding time, in field-based coordination it is assumed that local activities in each device, called computational rounds, are regulated by a fixed clock, typically, a fair and unsynchronized distributed scheduler. In this work, we challenge this assumption, and propose an alternative approach where the round execution scheduling is naturally programmed along with the usual coordination specification, namely, in terms of a field of causal relations dictating what is the notion of causality (why and when a round has to be locally scheduled) and how it should change across time and space. This abstraction over the traditional view on global time allows us to express what we call “time-fluid” coordination, where causality can be finely tuned to select the event triggers to react to, up to to achieve improved balance between performance (system reactivity) and cost (usage of computational resources). We propose an implementation in the aggregate computing framework, and evaluate via simulation on a case study.

Part 9: Verification and Analysis; International audience; Among dozens of decentralized computing platforms, Ethereum attracts widespread attention for its native support of smart contracts by means of a virtual machine called Ethereum Virtual Machine (EVM). Programs can be developed in various front-end languages. For example, Solidity can be deployed to the blockchain in the form of compiled EVM opcodes. However, such flexibility leads to critical safety challenges. In this paper, we formally define the behavior of EVM in Why3, a platform for deductive program verification, which facilitates the verification of different properties. The extracted implementation in OCaml can be directly integrated into the production environment and tested against the standard test suite. The combination of proofs and testing in our framework serves as a powerful analysis basis for EVM and smart contracts.

Part 4: Business Processes; International audience; Enterprise Architecture (EA) has had an interesting and often controversial history since its inception in the late 80’s by pioneers such as John Zachman. Zachman proposed the Zachman Framework for Enterprise Architecture (ZFEA), a descriptive, holistic representation of an enterprise for the purposes of providing insights and understanding. Some scholars claim that EA is an imperative to ensure successful business structures or business-IT alignment, or more recently with Enterprise Architecture Management (EAM), to manage required organizational transformation. However, EA initiatives within companies are often costly and the expected return on investment is not realized. In fact, Gartner recently indicated in their 2018 Enterprise Architecture Hype Cycle that EA is slowly emerging from the trough of disillusionment after nearly a decade. In this paper we argue that the role and value of EA is often misunderstood, and that EA, specifically the ZFEA for the purpose of this paper, could be considered as a theory given the view of theory within Information Systems (IS). The purpose of IS theories is to analyse, predict, explain and/or prescribe and it could be argued that EA often conform to these purposes. Using the taxonomy of theories as well as the structural components of theory within IS as proposed by Gregor, we motivate that the ZFEA could be regarded as an explanatory theory. Positioning ZFEA as IS explanatory theory provides insight into the role and purpose of the ZFEA (and by extension EA), and could assist researchers and practitioners with mediating the challenges experienced when instituting EA and EAM initiatives within organizations.

Part 5: Big Data and Machine Learning; International audience; Big data analytics tools have many functions that are common or similar to one another. This is a problem for many organisations that are either interested or have deployed some of the tools. The problem arises because there is no mechanism on how to determine appropriateness of the tools within context in an environment. Some of the implications of the problem are that it is difficult to assess appropriateness of the tools in an environment, which sometimes result to duplication; and the value of the tools. The aim of this project was to propose a solution through a model that can be used to evaluate big data analytics tools for organisations’ benefits. The qualitative method, case study approach and semi-structured interview technique were applied in the study. From the analysis, the role of criteria, business and IT alignment, governance, and skill-sets were revealed as critical factors. Based on the factors, a model was developed, which can be used as a building block through which evaluation of big data analytics tools in an organisation is carried out.

Part 6: ICT and Education; International audience; During the years there has been an increasing number of one-to-one programs around the world. In such programs all students are equipped with portable devices, such as laptops, tablets, smartphones for learning purposes. Even if these initiatives are increasing, our knowledge of the impact of such digital transformation of education is still little studied. Based on data from a three years longitudinal study on a large-scale implementation of Chromebooks in a municipality, this paper highlights teachers’ experiences. Key findings suggest that this initiative has been successful when it comes to the administrative and technical implementation of the Chromebooks, but there is still a way to go to transform pedagogical practices to enhance student-active learning supported by the Chromebooks.

Part 2: Fourth Industrial Revolution; International audience; There is a growing emphasis on digitalization in research and business practice. The rapid progress in digital technologies compel firms to innovate and transform their businesses. One way to improve the capacity to innovate and transform is to cooperate with others. However, there is a general lack of research on how co-creation among businesses can facilitate digitalization. This qualitative study explores how co-creation among businesses can stimulate and facilitate digitalization.We have investigated co-creation activities involving companies in business clusters. This paper reports from a study of three business clusters in Norway. We conducted an inductive qualitative study comprising semi-structured interviews as the primary empirical data source. 12 interviews were carried out with informants from three clusters. We found that the co-creation arenas and activities in the business clusters stimulate and facilitate digitalization among the cluster companies. We also addressed the most significant drivers and barriers to co-creation to get a deeper understanding of the co-creation phenomenon.

Part 6: ICT and Education; International audience; Digital course designs such as the Flipped Classroom (FC) are increasingly enriching university education. However, before implementing such an FC, teachers face the challenge of creating content in the form of materials and activities and finding a suitable development method. This is very time-consuming, which is why circumstances such as lack of time and personnel can make implementation difficult. In other areas, agile approaches have already proven to be effective in enabling flexible and efficient development. We use this opportunity to overcome different barriers in the context of FC development by creating an agile model for FC development. To achieve this, we first examined the previous research on agile development approaches concerning the implementation of an FC by a systematic literature review, concluding that no appropriate model exists yet. Building upon this, we designed an AgileFC Development Model, which can be used by teachers to create their FC. This model is very generally designed so that it can be easily adopted. On the other hand, it can be adjusted to a particular situation without effort. We also illustrate the application of the model using a small case study.

Part 2: Fourth Industrial Revolution; International audience; The Industrial Internet of Things (IIoT) is a new concept that has the potential to add value to any industrial organisation that wants to embark on the implementation thereof. Due to this newness of IoT in industrial operations, an increase in cost and maturity in terms of data handling, together with only a few implementations. There was a gap in available practical IIoT frameworks that could aid interested parties in the understanding of the constructs of IIoT and the practical implications of implementation. Within this study, we propose an Industrial Internet of Things framework intended to aid academic, technical and management persons in understanding the different considerations of the Industrial Internet of Things. This framework could also apply as a basis for implementation considerations.

Part 6: ICT and Gender Equality and Development; International audience; Inequalities exist and persist in society in different forms and are often areas of prime concern for governments and policy makers around the globe. One such inequality that plagues societies is the rural-urban divide. Several social entrepreneurs are attempting to leverage technology to bridge this divide. In our research-in-progress paper, we describe the case of an Indian company, which is leveraging technology to create knowledge-based jobs for the rural Indian population. The approach adopted by the company in initiating and sustaining such an effort was an inside-out approach in contrast to the usual approach of focusing only on the internal resources within the company. Specifically, our research aims at abstracting the process mechanisms that enabled such an initiative. The unearthed mechanisms would inform future research on the modalities for orchestrating such an initiative. The findings would also help practitioners, especially social entrepreneurs, to think of innovative business models that would create value not only for the company but also for society as a whole. The delineated learnings would also help enthused social entrepreneurs to transplant such initiatives to other regions of the world.

Part 6: ICT and Education; International audience; The usage of digital media to provide learning content is becoming increasingly popular. One form of e-learning is the Flipped Classroom (FC). FC courses, however, are still heavily dependent on the commitment of individual teachers. Repeatable descriptions of approaches or institutionalized support are rare. The high amount of work involved discourages many teachers from using FCs. Strategic course development should therefore be conducted collaboratively by several stakeholders. Change management approaches offer a solution to deal with the integration of strategies for change and consider all stakeholder groups. This paper aims to combine an FC process model and a change management approach to include all stakeholders. Based on a literature review, we develop an integrative approach and summarize the necessary aspects of change. Our results show that for the successful integration and development of FC courses, we need new roles that support the process and assure the stakeholder’s acceptance.

Part 5: Big Data and Machine Learning; International audience; The continual growth of big data necessitates efficient ways of analysing these large datasets. Data visualisation and visual analytics has been identified as a key tool in big data analysis because they draw on the human visual and cognitive capabilities to analyse data quickly, intuitively and interactively. However, current visualisation tools and visual analytical systems fall short of providing a seamless user experience and several improvements could be made to current commercially available visualisation tools. By conducting a systematic literature review, requirements of visualisation tools were identified and categorised into six groups: dimensionality reduction, data reduction, scalability and readability, interactivity, fast retrieval of results, and user assistance. The most common themes found in the literature were dimensionality reduction and interactive data exploration.

Part 3: eBusiness; International audience; It has been shown that serious games are useful in the military, healthcare, and education sectors. Meanwhile corporate interest in serious gaming in business has rapidly grown internationally. However the level of awareness and adoption of serious gaming among South African corporates in business is still unclear.This interpretive study explores South African corporate awareness of serious gaming in business and the barriers to its adoption. Semi-structured interviews were used to collect qualitative data from managers in Johannesburg Stock Exchange-listed companies. Eight participants were interviewed across four different industries. Data analysis was guided by the general inductive approach.The absence of serious gaming adopters among the participants, and the general lack of awareness of serious gaming in business were identified as the most salient features. The analysis suggests that corporates currently use technologies related to serious games (e-learning, collaborative tools, and simulation tools), and that there is a demand for the greater promotion and use of serious gaming.While the findings provide new insights into the level of serious gaming awareness, caution should be exercised when attempting to generalize these findings due to the small sample and the scarcity of prior research.

Part 2: Fourth Industrial Revolution; International audience; This paper explores an overly optimistic and tenacious claim in the literature that robotic process automation (RPA) will only free knowledge workers from mundane tasks and introduce more interesting work. We explore this claim and other consequences for knowledge workers using data from a sequential quantitative-qualitative, mixed-method study in Norway. 88 RPA users from different sectors and industries where first surveyed to identify differences in utilization and effects from RPA. Then, differences were explored in 24 in-depth interviews in the public and private sectors, including financial industry, manufacturing, and oil and gas. Results indicate that RPA is used to either layoff or not reemploy knowledge workers, but also to empower knowledge workers with more interesting tasks. Private sector was different from public sector in that private, financial companies have experienced the strongest reduction in the need for employment. RPA often lead to layoffs indirectly, and to reduced need for consultants, especially in financial companies. In contrast, public companies use RPA more for innovations in their service production from increased quality in data registration, handling of invoices, and data migration between systems. We conclude that RPA is maturing as a management tool motivated by cost reductions from reduced employment, and we suggest propositions for further research.

Part 4: Business Processes; International audience; Obtaining and maintaining a competitive advantage is vital for profit-driven organizations. Business Process Management (BPM) and the governance thereof offer such organizations a framework of management practices within which to achieve this goal. The objectives of this study were to identify and describe the BPM governance challenges that constrain BPM in large South African corporates as BPM in South Africa had not previously received any comprehensive BPM governance focus. Additionally, the BPM and BPM governance bodies of knowledge lack literature on studies focused on BPM governance challenges. Qualitative research methods were utilized to collect useful and descriptive data through secondary document collection and interviews in a single case study. The study confirmed eight of the literature-identified governance challenge themes that constrain BPM and contributed eleven new BPM governance challenge themes to the BPM and BPM governance body of research.

Part 1: Block Chain; International audience; Patient-centred care allows patients to have complete autonomy in managing their health information and encourages patients to be proactive. Unfortunately, most patients do not have access to their complete health information as they are stored across the various institutions that they have visited over their lifetime. The purpose of this paper is to report on an investigation into developing a mobile system for patient-centered healthcare using blockchain technology. A design science research approach was used to design, develop and evaluate a prototype that implemented a three-tier architecture using blockchain. Formative evaluations of the prototype revealed that the system could successfully support patient-managed healthcare. The implications of this project would be changing the way patients and healthcare practitioners interact with each other by improving the quality of clinical encounters by allowing patients access to their health information, sharing the information with healthcare practitioners and both parties collaborating in the development of a treatment plan.

Part 4: Business Processes; International audience; This paper considers the dichotomy inherent in Information Systems where its introduction, for the purposes of creating new or sustaining existing business value, subsequently also inadvertently or deliberately dissipates value. We investigate root people-induced causes, delineated within a rudimentary Conceptual Technology Value Framework. To support a qualitative investigation, the framework is forthwith applied as the basis for a series of interviews within a major South African financial institution operating within the disciplines of information technology, business operations and organisational development. The constructs identified are discussed and find gestalt in an Adjusted Technology Value Model which can be used to safeguard business value against destructive HCI behaviors.

Part 4: Business Processes; International audience; Corporate governance has been severely condemned, as a result of company failures around the world. Regulatory and legislative measure have been introduced in response to these failures. However, arguments by sceptics advocate that it is time consuming and costly to comply these legislative measures that cause overregulation. These measures further do not always add value to business initiatives and adherence to these measures cannot be enforced or guaranteed. This paper argues for the use of business process management systems (BPMSs) to improve corporate governance. The “dynamics capabilities theory model of IT-enabled organisational performance” [1] is applied in this study as theoretical underpinning. A theoretical framework is proposed for IT-enabled and IT-enforced corporate governance compliance using a BPMS, after collecting data from seven BPMS user companies and a BPMS vendor company in South Africa.

Part 2: Cloud and Systems; International audience; Coping with failures in modern distributed storage systems that handle massive volumes of heterogeneous and potentially rapidly changing data, has become a very important challenge. A common practice is to utilize fault tolerance methods like Replication and Erasure Coding for maximizing data availability. However, while erasure codes provide better fault tolerance compared to replication with a more affordable storage overhead, they frequently suffer from high reconstruction cost as they require to access all available nodes when a data block needs to be repaired, and also can repair up to a limited number of unavailable data blocks, depending on the number of the code’s parity block capabilities. Furthermore, storing and placing the encoded data in the federated storage system also remains a challenge. In this paper we present Fed-DIC, a framework which combines Diagonally Interleaved Coding on client devices at the edge of the network with organized storage of encoded data in a federated cloud system comprised of multiple independent storage clusters. The erasure coding operations are performed on client devices at the edge while they interact with the federated cloud to store the encoded data. We describe how our solution integrates the functionality of federated clouds alongside erasure coding implemented on edge devices for maximizing data availability and we evaluate the working and benefits of our approach in terms of read access cost, data availability, storage overhead, load balancing and network bandwidth rate compared to popular Replication and Erasure Coding schemes.

Part 5: Big Data and Machine Learning; International audience; Researchers have been experimenting with various drivers of the diffusion rate like sentiment analysis which only considers the presence of certain words in a tweet. We theorize that the diffusion of particular content on Twitter can be driven by a sequence of nouns, adjectives, adverbs forming a sentence. We exhibit that the proposed approach is coherent with the intrinsic disposition of tweets to a common choice of words while constructing a sentence to express an opinion or sentiment. Through this paper, we propose a Custom Weighted Word Embedding (CWWE) to study the degree of diffusion of content (retweet on Twitter). Our framework first extracts the words, create a matrix of these words using the sequences in the tweet text. To this sequence matrix we further multiply custom weights basis the presence index in a sentence wherein higher weights are given if the impactful class of tokens/words like nouns, adjectives are used at the beginning of the sentence than at last. We then try to predict the possibility of diffusion of information using Long-Short Term Memory Deep Neural Network architecture, which in turn is further optimized on the accuracy and training execution time by a Convolutional Neural Network architecture. The results of the proposed CWWE are compared to a pre-trained glove word embedding. For experimentation, we created a corpus of size 230,000 tweets posted by more than 45,000 users in 6 months. Research experimentations reveal that using the proposed framework of Custom Weighted Word Embedding (CWWE) from the tweet there is a significant improvement in the overall accuracy of Deep Learning framework model in predicting information diffusion through tweets.

Part 1: Regular Papers; International audience; Next generation networks – spanning from wide area networks to intra-datacenters – are expected to encompass devices and sub-devices from different vendors. Inter operability and vendor neutrality are now key topics for researchers and companies as a way to reduce costs avoiding to be tied to a single vendor. Also the management system is expected to be disaggregated from the hardware and possibly developed by a different company. An example is the white box, which disaggregates the software from the hardware and can be composed of modules from different vendors. Currently, NETCONF – based on YANG – is the protocol considered for the (re)configuration of white boxes. Discussions are being carried on to identify commonly agreed information models to guarantee vendor-neutral configuration and management of next generation networks.In addition, emerging services (e.g., 5G) will impose the involvement of a variety of technologies (e.g., networks, datacenters) and resources (e.g., compute, storage, radio). Such heterogeneity will imply the cooperation of several business actors to bring services to the users. In such a scenario, the management of resources will require their abstraction in order to satisfy confidentiality as well as to increase scalability and, again, to provide information that is neutral with respect to the related vendor and technology.In this paper, we propose to use NETCONF also for the exchange of resource information among different business actors considering the several network segments (wide area network, data centers, radio segment) involved in a 5G vertical. To this purpose, resource abstraction is proposed based on a YANG data model. An experiment will involve the (re)configuration of a wide area network composed of white boxes. Moreover, resource information (virtual links) will be exchanged through NETCONF with the objective of orchestrating resources.

International audience; As ubiquitous computer and sensor systems become abundant, the potential for automatic identification and tracking of human behaviours becomes all the more evident. Annotating complex human behaviour datasets to achieve ground truth for supervised training can however be extremely labour-intensive, and error prone. One possible solution to this problem is activity discovery: the identification of activities in an unlabelled dataset by means of an unsupervised algorithm. This paper presents a novel approach to activity discovery that utilises deep learning based language production models to construct a hierarchical, tree-like structure over a sequential vector of sensor events. Our approach differs from previous work in that it explicitly aims to deal with interleaving (switching back and forth between activities) in a principled manner, by utilising the long-term memory capabilities of a recurrent neural network cell. We present our approach and test it on a realistic dataset to evaluate its performance. Our results show the viability of the approach and that it shows promise for further investigation. We believe this is a useful direction to consider in accounting for the continually changing nature of behaviours.

International audience; Deep autoencoding Gaussian mixture model (DAGMM) employs dimensionality reduction and density estimation and jointly optimizes them for unsupervised anomaly detection tasks. However, the absence of large amount of training data greatly compromises DAGMM’s performance. Due to rising concerns for privacy, a worse situation can be expected. By aggregating only parameters from local training on clients for obtaining knowledge from more private data, federated learning is proposed to enhance model performance. Meanwhile, privacy is properly protected. Inspired by the aforementioned, this paper presents a federated deep autoencoding Gaussian mixture model (FDAGMM) to improve the disappointing performance of DAGMM caused by limited data amount. The superiority of our proposed FDAGMM is empirically demonstrated with extensive experiments.