3.1 Introduction

Our scientific foundations are grounded on distributed collaborative systems supported by sophisticated data sharing mechanisms and on service oriented computing with an emphasis on orchestration and on non-functional properties. Distributed collaborative systems enable distributed group work supported by computer technologies. Designing such systems requires an expertise in Distributed Systems and in Computer-supported collaborative Work research area. Besides theoretical and technical aspects of distributed systems, the design of distributed collaborative systems must take into account the human factor to offer solutions suitable for users and groups. The Coast team vision is to move away from a centralized authority based collaboration toward a decentralized collaboration. Users will have full control over their data. They can store them locally and decide with whom to share them. The Coast team investigates the issues related to the management of distributed shared data and coordination between users and groups. Service oriented Computing  17 is an established domain on which the ECOO, Score and now the Coast teams have been contributing for a long time. It refers to the general discipline that studies the development of computer applications on the web. A service is an independent software program with a specific functional context and capabilities published as a service contract (or more traditionally an API). A service composition aggregates a set of services and coordinates their interactions. The scale, the autonomy of services, the heterogeneity and some design principles underlying Service Oriented Computing open new research questions that are at the basis of our research. They span the disciplines of distributed computing, software engineering and computer supported collaborative work (CSCW). Our approach to contribute to the general vision of Service Oriented Computing is to focus on the issue of the efficient and flexible construction of reliable and secure high-level services. We aim to achieve it through the coordination/orchestration/composition of other services provided by distributed organizations or people.

3.2 Consistency Models for Distributed Collaborative Systems

Collaborative systems are distributed systems that allow users to share data. One important issue is to manage consistency of shared data according to concurrent access. Traditional consistency criteria such as serializability, linearizability are not adequate for collaborative systems. Causality, Convergence and Intention preservation (CCI)  21 are more suitable for developing middleware for collaborative applications. We develop algorithms for ensuring CCI properties on collaborative distributed systems. Constraints on the algorithms are different according to the kind of distributed system and to the data structure. The distributed system can be centralized, decentralized or peer-to-peer. The type of data can include strings, growable arrays, ordered trees, semantic graphs and multimedia data.

3.3 Optimistic Replication

Replication of data among different nodes of a network promotes reliability, fault tolerance, and availability. When data are mutable, consistency among the different replicas must be ensured. Pessimistic replication is based on the principle of single-copy consistency while optimistic replication allows the replicas to diverge during a short time period. The consistency model for optimistic replication  19 is called eventual consistency, meaning that replicas are guaranteed to converge to the same value when the system is idle. Our research focuses on the two most promising families of optimistic replication algorithms for ensuring CCI:

• operational transformation (OT) algorithms  12
• algorithms based on commutative replicated data types (CRDT)  18.

Operational transformation algorithms are based on the application of a transformation function when a remote modification is integrated into the local document. Integration algorithms are generic, being parametrised by operational transformation functions which depend on replicated document types. The advantage of these algorithms is their genericity. These algorithms can be applied to any data type and they can merge heterogeneous data in a uniform manner. Commutative replicated data types is a new class of algorithms initiated by WooT 16, the first algorithm designed WithOut Operational Transformations. They ensure consistency of highly dynamic content on peer-to-peer networks. Unlike traditional optimistic replication algorithms, they can ensure consistency without concurrency control. CRDT algorithms rely on natively commutative operations defined on abstract data types such as lists or ordered trees. Thus, they do not require a merge algorithm or an integration procedure.

3.4 Process Orchestration and Management

Process Orchestration and Management is considered as a core discipline behind Service Management and Computing. It includes the analysis, the modelling, the execution, the monitoring and the continuous improvement of enterprise processes and is for us a central domain of studies. Many efforts have been devoted establishing standard business process models founded on well-grounded theories (e.g. Petri Nets) that meet the needs of business analysts, software engineers and software integrator. This led to heated debate in the Business Process Management (BPM) community as the two points of view are very difficult to reconcile. On one side, business people in general require models that are easy to use and understand and that can be quickly adapted to exceptional situations. On the other side, IT people need models with an operational semantic in order to be able transform them into executable artifacts. Part of our work has been an attempt to reconcile these points of view. This resulted in the development of the Bonita BPM system. It resulted also more recently on our work in crisis management where the same people are designing, executing and monitoring the process as it executes. More generally, and at a larger scale, we have been considering the problem of processes spanning the barriers of organizations. This leads to the more general problem of service composition as a way to coordinate inter organizational construction of applications. These applications provide value, based on the composition of lower level services  9.

3.5 Service Composition

Recently, we started a study on service composition for software architects where services are coming from different providers with different plans (capacity, degree of resilience...). The objective is to support the architects to select the most accurate services (wrt. to their requirements, both functional and non-functional) and plans for building their software. We also compute the properties that we enforce for the composition of these services.

4.1 Crisis Management

Crisis management research investigates all the dimensions regarding the management of unexpected catastrophic events like floods, earthquake, terrorist attacks or pandemics. All the phases of a crisis, from preparedness to recovery require collaboration between people from many organizations. This provides opportunities to study inter-organizational collaboration at a large scale and to propose and evaluate mechanisms that ensure secure and safe collaboration. The work of Béatrice Linot provides us with a deep understanding of the factors that encourage collaboration and help to maintain trustworthy collaboration between stakeholders. This work is continued by Clélie Amiot who studies the effects of human chat-bot collaboration in this kind of setting.

4.2 Collaborative Editing

Collaborative editing is a common application of optimistic replication in distributed settings. The goal of collaborative editors, irrespective of the kind of document, is to allow a group of users to update a document concurrently while ensuring that they eventually get all the same copy at the end. Our algorithm allows to implement collaborative editor in a peer to peer way. It avoids the need for a central server ensuring a higher level of privacy among collaborators. In this context, it requires to consider the problem of authentication and authorization of participants 8 and of trust between them 13.

5.1 New software

6.1 Time-position characterization of conflicts in collaborative editing

Participants: François Charoy, Claudia-Lavinia Ignat, Hoai Le Nguyen.

We studied collaborative editing behavior in terms of collaboration patterns users adopt and in terms of a characterisation of conflicts, i.e. edits from different users that occur close in time and position in the document 3. The process of collaborative editing can be split into several editing sessions which are performed by a single author (single-authored sessions) or several authors (co-authored sessions). This fragmentation process requires a pre-defined maximum time gap between sessions which is not yet well defined in previous studies. We analysed collaboration logs of 108 documents collaboratively edited by groups of students using Overleaf. We show how to establish a suitable maximum time gap to split collaboration activities into sessions by evaluating the distribution of the time distance between two adjacent sessions. We studied editing activities inside co-authored sessions in order to define potential conflicts in terms of time and position dimensions before they occur in the document. We also analysed how many of these potential conflicts become real conflicts. Findings show that potential conflicting cases are few. However, they are more likely to become real conflicts.

6.2 Conflict-Free Replicated Relations for multi-synchronous access to relational databases

Participants: Claudia-Lavinia Ignat.

In a cloud-edge environment, edge devices may not always be connected to the network. However, a multi-synchronous access of data on edge devices needs to be ensured. This multi-synchronous access includes an asynchronous mode where the user can always access the data on the device even when the device is off-line, and a synchronous mode where as long as the device is online the data on the device is kept synchronous with the data stored in the cloud.

We proposed augmenting existing relational database schema with a Conflict-free Replicated Relations (CRRs) layer in order to support a multi-synchronous access to relational databases in a cloud-edge environment 5. The underlying CRR layer uses CRDTs to allow immediate data access at edge and to guarantee data convergence when the edge devices are online. It also resolves violations of integrity constraints at merge by undoing offending updates. Since a relation instance is a set of tuples, the basic building block of CRR is a set CRDT, more specifically a delta-state set CRDT.

The key issue that a general-purpose set CRDT must address is how to identify the causality between the different insertion and deletion updates. CLSet, our novel set CRDT suitable for relational databases identifies causality relations by using the abstraction of causal length, which is based on two observations. First, the insertions and deletions of a given element occur in turns, one causally dependent on the other. A deletion is an inverse of the last insertion it sees. Similarly, an insertion is an inverse of the last deletion it sees (or none, if the element has never been inserted). Second, two concurrent executions of the same mutation of a set CRDT fulfill the same purpose and therefore are regarded as the same update. Seeing one means seeing both. Two concurrent inverses of the same update are also regarded as the same one.

We implemented and reported on performances of a CRR prototype on top of a data mapping library that is independent of any specific database management system..

6.3 Mitigating the Cost of Identifiers in Sequence CRDT

Participants: Matthieu Nicolas, Gérald Oster, Olivier Perrin.

To achieve high availability, large-scale distributed systems have to replicate data and to minimise coordination between nodes. The literature and industry increasingly adopt Conflict-free Replicated Data Types (CRDTs) to design such systems. CRDTs are data types which behave as traditional ones, e.g. the Set or the Sequence. However, compared to traditional data types, they are designed to support natively concurrent modifications. To this end, they embed in their specification a conflict-resolution mechanism.

To resolve conflicts in a deterministic manner, CRDTs usually attach identifiers to elements stored in the data structure. Identifiers have to comply with several constraints such as uniqueness or being densely ordered according to the kind of CRDT. These constraints may prevent the identifiers’ size from being bounded. As the number of the updates increases, the size of identifiers grows. This leads to performance issues, since the efficiency of the replicated data structure decreases over time.

To address this issue, we propose a new CRDT for Sequence which embeds a renaming mechanism. It enables nodes to reassign shorter identifiers to elements in an uncoordinated manner. Obtained experiment results demonstrate that this mechanism decreases the overhead of the replicated data structure and eventually limits it.

To validate the proposed renaming mechanism, we performed an experimental evaluation to measure its performances on several aspects: (i) the size of the data structure ; (ii) the integration time of the rename operation ; (iii) the integration time of insert and remove operations. In cases (i) and (iii), we use LogootSplit as the baseline data structure to compare results. The results we obtained are very encouraging, as the integration time is far shorter with the renaming mechanism, even with the time spent to apply the rename operation.

6.4 Social Networks as Collaboration Support

Participants: Quentin Laporte Chabasse, Gérald Oster, François Charoy.

Safe peer to peer collaborative services requires a trusted peer to peer network in order to be effective. We started to investigate how to leverage social networks underlying inter organizational collaboration to support such collaboration. To reach this goal, we need to analyze collaborative graphs. They are a relevant sources of information to understand behavioural tendencies of groups of individuals. Exponential Random Graph Models (ERGMs) are commonly used to analyze such social processes including dependencies between members of the group. Our approach considers a modified version of ERGMs, modeling the problem as an edge labelling one. The main difficulty is inference since the normalizing constant involved in classical Markov Chain Monte Carlo approaches is not available in an analytic closed form.

The main contribution is to use the recent ABC Shadow algorithm 20. This algorithm is built to sample from posterior distributions while avoiding the previously mentioned drawback. The proposed method is illustrated on real data sets provided by the HAL 3 platform and provides new insights on self-organized collaborations among researchers7. In 2020, we applied this method in a longitudinal way to identify patterns regarding the evaluation of collaboration on several years for the same teams.

6.5 Identification and Selection of Services from Cloud Providers

Participants: Anis Ahmed Nacer, François Charoy, Olivier Perrin.

We continued our work on providing a framework to compare plans for services from cloud providers in order to help architects to select the best composition given the required criteria (both functional and non-functional requirements) for a micro service architecture. This year, we have made progress in two directions: the first is the identification of the key elements to be considered when architects want to compare the different plans, and the second one is a methodology to compute the best composition of services, given partial information provided in service description.

In order to gather the key elements of the comparison that met the architects’ requirements and the relationship between these key elements of the comparison, we reviewed the service providers’ plans and previous works on benchmarks. Finally, to ensure that the list of key elements of the comparison and their relationship was complete for the service selection process, we conducted an empirical study with the architects6

Regarding the second part, we use the WOWA (Weighted Ordered Weighted Averaging) operator to solve this decision problem. This operator provides an aggregation function that uses both the simultaneous advantage of the OWA method to allow compensation between high and low values and the weighted average method to consider the importance of the suppliers who provide the information. WOWA uses two sets of weights: one corresponds to source significance, and the other corresponds to value significance.

6.6 Combining data analysis and event processing for a proactive business process management

Participants: Khalid Benali, Abir Ismaili-Alaoui.

Facing competitive and continuous changing environments, organizations, now more than ever, tend to have recourse to agile methods and continuous improvement practices such as Lean Six Sigma method, Activity Based Costing (ABC) methods and Business Process Management (BPM) in order to have a transversal view of their business, to identify opportunities for enhancement, to reduce costs and wastes, to improve customer satisfaction and overall profitability, and to overcome the problem of isolation and non-communication between the different hierarchical levels within the organization. Among all these existing approaches, Business Process Management (BPM) is still considered as the more appropriate solution that help organizations to adapt to strategic, tactical and operational changes, and also to have more visibility and control over their business processes. This approach allows companies to gain in terms of agility, efficiency and performance; it also enables an effective communication and collaboration between their different stakeholders. Recently, with this new digitized era and the rise of several new technologies such as of Big Data, Internet of Things, Cloud Computing, etc., organizations face many factors and challenges that generate real changes in the traditional BPM. Among these challenges, we have the huge amount of data and event data that are continuously gathered within the organization, especially with the ubiquity of IoT devices in all domains. These data/event data represent a real engine of growth for organizations, and must be adequately exploited to extract high added value that can assist the organization in its decision making process. However, traditional BPM systems present different limits, as they do not facilitate the use of knowledge extracted from this data by business processes, because they do not benefit from statistical functionalities and data analysis and manipulation techniques. Over the past decade and till now, a lot of efforts have been done in both academic and industrial research environments, to improve all the aspects of Business Process and Business Process Management, because Business Processes were completely isolated within the organization thus they don’t benefit from the different added values that could be created from all these tremendous data.

Learning from data and event data that are gathered from past operations and process execution is an effective approach to improve the performance of business processes, especially those that perform repetitive tasks and activities. In fact, insights that are obtained from these data represents a valuable support for decision making. The main objective of our research consists on proposing new approaches for enhancing business processes, in order to achieve a core objective that both academia and industry are striving for, which is proactivity. As a first step towards this proactivity, we have tackled the business process instances scheduling problem, based on the priority of events that trigger these instances, taking into consideration historical data gathered from previous business process instances. We proposed a clustering approach using a set of event sources, so that we can classify these sources on different clusters using a score calculated for each event source. This score is based on the frequency and the criticality of previous events. The main objective of this approach was to create clusters of priorities. These latter are used to estimate in a proactive way the criticality level of incoming events, and then the priority level of incoming process instances. However, there is always a degree of uncertainty regarding the criticality/priority level of events generated from sources that belong to the same cluster. We tried to work on this issue as a second step by using fuzzy logic. In fact, the integration of a Fuzzy Inference System (FIS) in our IoT-BPM architecture, helps us to handle uncertainties regarding the criticality level of events, especially when these events are generated by sources that may have the same characteristics.

7.1 Bilateral contracts with industry

8.1 International initiatives

9.1 Promoting scientific activities

9.2 Teaching - Supervision - Juries

9.3 Popularization

10.1 Publications of the year

10.2 Cited publications

• 8 article Mohammed RiyadhM. Abdmeziem and FrançoisF. Charoy. Securing IoT-based Groups: Efficient, Scalable and Fault-tolerant Key Management Protocol Ad Hoc & Sensor Wireless Networks October 2019
  HAL back to text
• 9 articleSamiS. Bhiri, OlivierO. Perrin, WalidW. Gaaloul and ClaudeC. Godart. An Object-Oriented Metamodel For Inter-Enterprises Cooperative Processes Based on Web ServicesJournal of Integrated Design and Process Science82004, 37--55
  HALback to text
• 10 incollectionFabioF. Casati. Promises and Failures of Research in Dynamic Service CompositionSeminal Contributions to Information Systems EngineeringSpringer Berlin Heidelberg2013, 235-239URL: http://dx.doi.org/10.1007/978-3-642-36926-1_18
  back to text
• 11 inproceedingsQuang VinhQ. Dang and Claudia-LaviniaC.-L. Ignat. Computational Trust Model for Repeated TrustGames Proceedings of the 15th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom 2016) Tianjin, ChinaAugust 2016, URL: https://hal.inria.fr/hal-01351250
  back to text
• 12 inproceedingsClarence A.C. Ellis and Simon J.S. Gibbs. Concurrency Control in Groupware SystemsProceedings of the ACM SIGMOD Conference on the Management of Data - SIGMOD 89Portland, Oregon, USAMay 1989, 399--407URL: http://doi.acm.org/10.1145/67544.66963
  back to textback to text
• 13 articleClaudia-LaviniaC.-L. Ignat, Quang-VinhQ.-V. Dang and ValerieV. Shalin. The Influence of Trust Score on Cooperative BehaviorACM Transactions on Internet Technology194September 2019, 1-22
  HALDOIback to textback to text
• 14 inproceedingsHoang-LongH.-L. Nguyen, Jean-PhilippeJ.-P. Eisenbarth, Claudia-LaviniaC.-L. Ignat and OlivierO. Perrin. Blockchain-Based Auditing of Transparent Log ServersThe 32nd Annual IFIP WG 11.3 Conference on Data and Applications Security and Privacy (DBSec 2018)Proceeding of Data and Applications Security and Privacy XXXII - 32nd Annual IFIP WG 11.3 ConferenceBergamo, ItalyJuly 2018, 21-37URL: https://hal.archives-ouvertes.fr/hal-01917636
  back to text
• 15 inproceedingsHoang-LongH.-L. Nguyen, Claudia-LaviniaC.-L. Ignat and OlivierO. Perrin. Trusternity: Auditing Transparent Log Server with BlockchainCompanion of the The Web Conference 2018Lyon, FranceApril 2018, 79-80URL: https://hal.inria.fr/hal-01883589
  DOIback to text
• 16 inproceedingsGéraldG. Oster, PascalP. Urso, PascalP. Molli and AbdessamadA. Imine. Data Consistency for P2P Collaborative EditingACM Conference on Computer-Supported Cooperative Work - CSCW 2006Banff, Alberta, CanadaACM Press11 2006, 259 - 268URL: http://hal.inria.fr/inria-00108523/en/
  back to text
• 17 articleMichael P.M. Papazoglou, PaoloP. Traverso, SchahramS. Dustdar and FrankF. Leymann. Service-Oriented Computing: State of the Art and Research ChallengesComputer402007, 38-45
  back to text
• 18 inproceedingsNunoN. Preguiça, Joan ManuelJ. Marquès, MarcM. Shapiro and MihaiM. Letia. A commutative replicated data type for cooperative editing29th IEEE International Conference on Distributed Computing Systems (ICDCS 2009)Montreal, Québec CanadaIEEE Computer Society2009, 395-403
  HALDOIback to text
• 19 articleYasushiY. Saito and MarcM. Shapiro. Optimistic ReplicationComputing Surveys371March 2005, 42--81URL: http://doi.acm.org/10.1145/1057977.1057980
  back to text
• 20 articleRadu SR. Stoica, AnneA. Philippe, PabloP. Gregori and JorgeJ. Mateu. ABC Shadow algorithm: a tool for statistical analysis of spatial patternsStatistics and computing2752017, 1225--1238
  back to text
• 21 articleChengzhengC. Sun, XiaohuaX. Jia, YanchunY. Zhang, YunY. Yang and DavidD. Chen. Achieving Convergence, Causality Preservation, and Intention Preservation in Real-Time Cooperative Editing SystemsACM Transactions on Computer-Human Interaction51March 1998, 63--108URL: http://doi.acm.org/10.1145/274444.274447
  back to text