Best paper “SmartSPEC: Customizable Smart Space Datasets via Event-Driven Simulations” at PERCOM 2022
Authors: Andrew Chio, Daokun Jiang, Peeyush Gupta, Georgios Bouloukakis, Roberto Yus, Sharad Mehrotra and Nalini Venkatasubramanian
This paper presents SmartSPEC, an approach to generate customizable smart space datasets using sensorized spaces in which people and events are embedded. Smart space datasets are critical to design, deploy and evaluate robust systems and applications to ensure cost-effective operation and safety/comfort/convenience of the space occupants. Often, real-world data is difficult to obtain due to the lack of fine-grained sensing; privacy/security concerns prevent the release and sharing of individual and spatial data. SmartSPEC is a smart space simulator and data generator that can create a digital representation (twin) of a smart space and its activities. SmartSPEC uses a semantic model and ML-based approaches to characterize and learn attributes in a sensorized space, and applies an event-driven simulation strategy to generate realistic simulated data about the space (events, trajectories, sensor datasets, etc). To evaluate the realism of the data generated by SmartSPEC, we develop a structured methodology and metrics to assess various aspects of smart space datasets, including trajectories of people and occupancy of spaces. Our experimental study looks at two real-world settings/datasets: an instrumented smart campus building and a city-wide GPS dataset. Our results show that the trajectories produced by SmartSPEC are 1.4x to 4.4x more realistic than the best synthetic data baseline when compared to real-world data, depending on the scenario and configuration.
Keywords: smart space, sensor, simulation, trajectory
New paper “Analysis of the Impact of Interaction Patterns and IoT Protocols on Energy Consumption of IoT Consumer Applications” at DAIS 2022
Authors: Rodrigo Canek, Pedro Borges, and Chantal Taconet
Nowadays, it is estimated that half the connected devices are related to the Internet of Things (IoT). The IoT paradigm contributes to the increase of the Information Technology energy demand. The energy demand is due on one side to the huge number of IoT devices, and on the other side to the plethora of IoT end user applications consuming
data produced by those devices. However, taking into account energy consumption in the development of such applications, consuming data produced by IoT devices is still challenging. There is a lack of knowledge on what are the best practises to develop green IoT applications. The work presented in this paper aims to raise the awareness of application designers concerning the impact of the choice of IoT protocols and interaction patterns on the energy consumption of the applications. For this purpose, we have experimentally analysed the energy consumption of HTTP and MQTT, which are two of the most popular, mature and stable protocols for IoT consumer applications. For the HTTP protocol, we have studied both the publish-subscribe and the request-reply interaction patterns. For MQTT, we have studied the publish-subscribe interaction pattern with the three available Quality of Services. We also examine the impact of message payload on energy consumption. The results show that the publish/subscribe interaction pattern has lower energy consumption (around 92% less) than the synchronous interaction pattern and HTTP consumes 20% more energy than the MQTT protocol for the publish/subscribe interaction pattern. Finally, we have shown that the payload has a low impact on energy consumption having a 9% overhead on payloads ranging from 24 to 3120 bytes
Keywords: Middleware, Internet of Things applications, IoT protocols Interaction patterns, IoT Platforms, Energy Consumption, Green IT
New paper “Conformance checking for autonomous multi-cloud SLA management and adaptation” at Journal of Supercomputing
Authors: Jeremy Mechouche, Roua Touihri, Mohamed Sellami and Walid Gaaloul
Satisfying cloud customers’ requirements, i.e., respecting an agreed-on service level agreement (SLA), is not a trivial task in a multi-cloud context. This is mainly due to divergent SLA objectives among the involved cloud service providers and hence divergent reconfiguration strategies to enforce them. In this paper, we propose a hierarchical representation of multi-cloud SLAs: sub-SLAs associated with a system’s components deployed on distinct cloud service providers and global-SLA associated with the whole system. We also enrich these SLA representations with state machines reflecting reconfiguration strategies defined by cloud customers. Then, we propose an autonomous multi-cloud resource orchestrator based on the MAPE-K adaptation control loop to enforce them and to avoid SLA violations. Finally, in order to check the conformity of this enforcement with defined multi-cloud SLA, we propose an approach for multi-cloud SLA reporting inspired by conformance checking techniques. An implementation of the approach is presented in the paper and illustrates the approach feasibility.
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.