Distributed Systems, Software Engineering and Middleware - DiSSEM group

Computer Science Department of Telecom SudParis

New paper “Towards higher-level description of SLA-aware reconfiguration strategies based on state-machine” at ICEBE’2021

Authors: Jeremy Mechouche, Roua Touihri, Mohamed Sellami and Walid Gaaloul


High number of European projects and international initiatives show an increased interest in the multi-cloud paradigm. One key need identified in these studies is an SLA-driven service model for multi-cloud environment. While offering a multi-cloud application, cloud consumer define reconfiguration strategies to avoid violating SLAs established with their customers. In this context, this paper presents an approach for enriching multi-cloud SLA representations with reconfiguration strategies. Advantages of this approach are twofold: (i) simplify SLA administration and (ii) limit SLA violations caused by reconfiguration strategies. We represent reconfiguration strategies based on state-machine formalism. Furthermore, we define thresholds to guarantee their compliance with multi-cloud SLAs and anticipate SLA violations. An implementation of the approach is presented in the paper and illustrates how these thresholds are computed.

New paper “Runtime models and evolution graphs for the version management of microservice architectures” at APSEC 2021

Authors: Yuwei Wang, Denis Conan, Sophie Chabridon, Kavoos Bojnourdi, Jingxuan Ma.

APSEC 2021, https://hal.archives-ouvertes.fr/hal-03419462

Microservice architectures focus on developing modular and independent functional units, which can be automatically deployed, enabling agile DevOps. One major challenge is to manage the rapid evolutionary changes in microservices and perform continuous redeployment without interrupting the application execution. The existing solutions provide limited capacities to help software architects model, plan, and perform version management activities. The architects lack a representation of a microservice architecture with versions tracking. In this paper, we propose runtime models that distinguishes the type model from the instance model, and we build up an evolution graph of configuration snapshots of types and instances to allow the traceability of microservice versions and their deployment. We demonstrate our solution with an illustrative application that involves synchronous (RPC calls) and asynchronous (publish-subscribe) interaction within information systems.

New paper “Automating user-feedback driven requirements prioritization” in Elsevier Information and Software Technology

Authors: Fitsum Meshesha Kifetew, Anna Perini, Angelo Susi, Aberto Siena, Denisse Muñante and Itzel Morales-Ramirez

Information and Software Technology, Elsevier, 2021, 138, https://hal.archives-ouvertes.fr/hal-03277970


Context: Feedback from end users of software applications is a valuable resource in understanding what users request, what they value, and what they dislike. Information derived from user-feedback can support software evolution activities, such as requirements prioritization. User-feedback analysis is still mostly performed manually by practitioners, despite growing research in automated analysis. Objective: We address two issues in automated user-feedback analysis: (i) most of the existing automated analysis approaches that exploit linguistic analysis assume that the vocabulary adopted by users (when expressing feedback) and developers (when formulating requirements) are the same; and (ii) user-feedback analysis techniques are usually experimentally evaluated only on some user-feedback dataset, not involving assessment by potential software developers. Method: We propose an approach, ReFeed, that computes, for each requirement, the set of related user-feedback, and from such user-feedback extracts quantifiable properties which are relevant for prioritizing the requirement. The extracted properties are propagated to the related requirements, based on which ranks are computed for each requirement. ReFeed relies on domain knowledge, in the form of an ontology, helping mitigate the gap in the vocabulary of end users and developers. The effectiveness of ReFeed is evaluated on a realistic requirements prioritization scenario in two experiments involving graduate students from two different universities. Results: ReFeed is able to synthesize reasonable priorities for a given set of requirements based on properties derived from user-feedback. The implementation of ReFeed and related resources are publicly available. Conclusion: The results from our studies are encouraging in that using only three properties of user-feedback, ReFeed is able to prioritize requirements with reasonable accuracy. Such automatically determined prioritization could serve as a good starting point for requirements experts involved in the task of prioritizing requirements Future studies could explore additional user-feedback properties to improve the effectiveness of computed priorities.

New paper “PrioDeX: a Data Exchange middleware for efficient event prioritization in SDN-based IoT systems” in ACM TOIT

Authors: Georgios Bouloukakis, Kyle Benson, Luca Scalzotto, Paolo Bellavista, Casey Grant, Valérie Issarny, Sharad Mehrotra,Ioannis Moscholios, Nalini Venkatasubramanian

ACM Transactions on Internet of Things, In press, https://hal.archives-ouvertes.fr/hal-03171358


Real-time event detection and targeted decision making for emerging mission-critical applications require systems that extract and process relevant data from IoT sources in smart spaces. Oftentimes, this data is heterogeneous in size, relevance, and urgency, which creates a challenge when considering that different groups of stakeholders (e.g., first responders, medical staff, government officials, etc) require such data to be delivered in a reliable and timely manner. Furthermore, in mission-critical settings, networks can become constrained due to lossy channels and failed components, which ultimately add to the complexity of the problem. In this paper, we propose PrioDeX, a cross-layer middleware system that enables timely and reliable delivery of mission-critical data from IoT sources to relevant consumers through the prioritization of messages. It integrates parameters at the application, network, and middleware layers into a data exchange service that accurately estimates end-to-end performance metrics through a queueing analytical model. PrioDeX proposes novel algorithms that utilize the results of this analysis to tune data exchange configurations (event priorities and dropping policies), which is necessary for satisfying situational awareness requirements and resource constraints. PrioDeX leverages Software-Defined Networking (SDN) methodologies to enforce these configurations in the IoT network infrastructure. We evaluate our approach using both simulated and prototype-based experiments in a smart building fire response scenario. Our application-aware prioritization algorithm improves the value of exchanged information by 36% when compared with no prioritization; the addition of our network-aware drop rate policies improves this performance by 42% over priorities only and by 94% over no prioritization.

New paper “IoT data qualification for a logistic chain traceability smart contract” in Sensors journal

Authors: Mohamed Ahmed, Chantal Taconet, Mohamed Ould, Sophie Chabridon, Amel Bouzeghoub

MDPI Sensors, 21 (6), 2021. https://hal.archives-ouvertes.fr/hal-03219609


In the logistic chain domain, the traceability of shipments in their entire delivery process from the shipper to the consignee involves many stakeholders. From the traceability data, contractual decisions may be taken such as incident detection, validation of the delivery or billing. The stakeholders require transparency in the whole process. The combination of the Internet of Things (IoT) and the blockchain paradigms helps in the development of automated and trusted systems. In this context, ensuring the quality of the IoT data is an absolute requirement for the adoption of those technologies. In this article, we propose an approach to assess the data quality (DQ) of IoT data sources using a logistic traceability smart contract developed on top of a blockchain. We select the quality dimensions relevant to our context, namely accuracy, completeness, consistency and currentness, with a proposition of their corresponding measurement methods. We also propose a data quality model specific to the logistic chain domain and a distributed traceability architecture. The evaluation of the proposal shows the capacity of the proposed method to assess the IoT data quality and ensure the user agreement on the data qualification rules. The proposed solution opens new opportunities in the development of automated logistic traceability systems.

New paper “A Transactional Approach to Enforce Resource Availabilities – Application to the Cloud” at RCIS’2021

Authors: Zakaria Maamar, Mohamed Sellami and Fatma Masmoudi


This paper looks into the availability of resources, exemplified with the cloud, in an open and dynamic environment like the Internet. A growing number of users consume resources to complete their operations requiring a better way to manage these resources in order to avoid conflicts, for example. Resource availability is defined using a set of consumption properties (limited, limited-but-renewable, and non-shareable) and is enforced at run-time using a set of transactional properties (pivot, retriable, and compensatable). In this paper, a CloudSim-based system simulates how mixing consumption and transactional properties allows to capture users’ needs and requirements in terms of what cloud resources they need, for how long, and to what extent they tolerate the unavailability of these resources.

New paper “Privacy-Preserving Content-Based Publish/Subscribe with Encrypted Matching and Data Splitting” at SECRYPT’2020

Privacy-Preserving Content-Based Publish/Subscribe with Encrypted Matching and Data Splitting by N. Denis, P. Chaffardon, D. Conan, M. Laurent, S. Chabridon and J. Leneutre

Abstract The content-based publish/subscribe paradigm enables a loosely-coupled and expressive form of communication. However, privacy preservation remains a challenge for distributed event-based middleware especially since encrypted matching incurs significant computing overhead. This paper adapts an existing attribute-based encryption scheme and combines it with data splitting, a non-cryptographic method called for alleviating the cost of encrypted matching. Data splitting enables to form groups of attributes that are sent apart over several independent broker networks so that it prevents the identification of an end-user; and, only identifying attributes are encrypted to prevent data leakage. The goal is to achieve an acceptable privacy level at an affordable computing price by encrypting only the necessary attributes, whose selection is determined through a Privacy Impact Assessment.

New article “Real-Time Tracking and Mining of Users’ Actions over Social Media ” at Computer Science and Information Systems

Ejub Kajan, Noura Faci, Zakaria Maamar, Mohamed Sellami, Emir Ugljanin, et al.. Real-time tracking and mining of users’ actions over social media. Computer Science and Information Systems, ComSIS Consortium, In press, pp.2-2. ⟨10.2298/CSIS190822002K⟩⟨hal-02514060⟩

Abstract. With the advent of Web 2.0 technologies and social media, companiesare actively looking for ways to know and understand what users think and say about their products and services. Indeed, it has become the practice that users go online using social media like Facebook to raise concerns, make comments, and share recommendations. All these actions can be tracked in real-time and then mined using advanced techniques like data analytics and sentiment analysis. This paper discusses such tracking and mining through a system called Social Miner that allows companies to make decisions about what, when, and how to respond to users’ actions over social media. Questions that Social Miner allows to answer include what actions were frequently executed and why certain actions were executed more than others.

New paper “Towards an Approach for Validating the Internet-of-Transactional-Things” at AINA’2020

Z. Maamar, M. Sellami, N.C. Narendra, I. Guidara, E. Ugljanin, and B. Banihashemi. Towards an Approach for Validating the Internet-of-Transactional-Things. In the 34-th International Conference on Advanced Information Networking and Applications (AINA-2020)


Abstract. This paper examines the impact of transactional properties, known as pivot, retriable, and compensatable, on Internet-of-Things (IoT). Despite the ever-growing number of things in today’s cyber-physical world, a limited number of studies examine this impact while considering things’ particularities in terms of reduced size, restricted connectivity, continuous mobility, limited energy, and constrained storage. To address this gap, this paper proceeds first, with exposing things’ duties, namely sensing, actuating, and communicating. Then, it examines the appropriateness of each transactional property for each duty. During the performance of transactional things, (semi)-atomicity criterion is adopted allowing to approve when these things’ duties could be either canceled or compensated. A system that runs a set of what-if experiments is presented in the paper allowing to demonstrate the technical doability of transactional things.

New paper “A Model based Toolchain for the Cosimulation of Cyber-physical Systems with FMI” at MODELSWARD’2020

A Model based Toolchain for the Cosimulation of Cyber-physical Systems with FMI by D. Oudart, J. Cantenot, F. Boulanger and S. Chabridon

Abstract Smart Grids are cyber-physical systems that interface power grids with information and communication technologies in order to monitor them, automate decision making and balance production and consumption. Cosimulation with the Functional Mock-up Interface standard allows the exploration of the behavior of such complex systems by coordinating simulation units that correspond to the grid part, the communication network and the information system. However, FMI has limitations when it comes to cyber-physical system simulation, particularly because discrete-event signals exchanged by cyber components are not well supported. In addition, industrial projects involve several teams with different skills and methods that work in parallel to produce all the models required by the simulation, which increases the risk of inconsistency between models. This article presents a way to exchange discrete-event signals between FMI artifacts, which complies with the current 2.0 version of the standard. We developed a DSL and a model-based toolchain to generate the artifacts that are necessary to run the cosimulation of the whole system, and to
detect potential inconsistencies between models. The approach is illustrated by the use case of an islanded grid implementing diesel and renewable sources, battery storage and intelligent control of the production.