The security testing of Ethereum smart contracts has become increasingly important with the rise of decentralized applications (DApps) and blockchain technology. This systematic literature review (SLR) aims to provide a comprehensive overview of the state-of-the-art techniques, methodologies, tools, and challenges in the security testing of Ethereum smart contracts. By synthesizing and analyzing existing research articles, conference papers, and other relevant sources, this SLR identifies common trends, gaps, and areas for future research in this domain. The review covers various aspects of security testing, including vulnerability detection, testing frameworks, automated analysis tools, and best practices. In addition, it explores the impact of security vulnerabilities on smart contract ecosystems and proposes recommendations to improve the effectiveness and efficiency of security testing processes. This SLR serves as a valuable resource for researchers, practitioners, and developers interested in improving the security and reliability of Ethereum smart contracts.

The evolution of 5G and Beyond (B5G) networks requires innovative solutions to address the growing complexity of network management and enhance Energy Efficiency (EE). Sleep Mode (SM) has emerged as an essential strategy for minimizing energy consumption in densely deployed networks, particularly in Base Stations (BS), significantly improving Energy Saving (ES) in 5G/B5G network. By dynamically deactivating underutilized BS components, SM can be effectively applied across various 5G infrastructures. In addition, the application of Artificial Intelligence (AI) and Self Organizing Networks (SON) provides advanced tools for automatic and intelligent system reconfiguration, further enhancing ES in B5G networks. This paper explores ES approaches centered on SM, providing an overview of their application in 5G architectures and the role of AI algorithms and the SON paradigm in improving ES. Finally, we discuss potential ES advancements for future networks, including the transition to 6G, highlighting the importance of intelligent and adaptive energy management in next-generation networks.

The proliferation of fraudulent certificates not only erodes trust but also deceives employers and academic organizations, making it harder to verify the qualifications of applicants and employees. Our blockchain-based web application, enhanced with self-sovereign identity (SSI), addresses these challenges by ensuring the authenticity and integrity of academic credentials. Graduates gain full control over their credentials through SSI, allowing them to securely manage, share, and verify their qualifications independently. Educational institutions, in turn, benefit from streamlined processes such as bulk certificate generation and QR code-enabled verification, all within a decentralized and tamper-proof framework enabled by SSI. Additionally, we provide an off-chain cache to further enhance system efficiency by alleviating the blockchain’s load and achieving optimal response times for frequently accessed credentials.

ABSTRACT Elasticity is an essential treatment in Cloud environment employed in academic and industrial contexts. The main purpose of elasticity is to reduce the deployment cost while optimizing computing resources. Multiple studies were conducted to tackle classic applications using monolithic architecture deployed with virtual machines (VMs). However, with the spread of microservice pattern, recent studies have been investigating this new trend using containers. This paper classifies and discusses existing approaches dealing with cloud elasticity. It provides a novel taxonomy for elastic approaches while focusing on microservices‐based solutions. We additionally specify the strength and the shortcomings of each class of works. As a conclusion, we report the challenges for microservices‐based applications elasticity and provide requirements for future investigations.

The technological progress of miniaturized sensors has led to the invasion of IoT in our lives through multiple applications, specifically in the healthcare domain where security and privacy are paramount concerns. This evolution has given rise to the Internet of Medical Things (IoMT). Despite the promising role of Blockchain technology in ensuring traceability and privacy for IoT systems, integrating it into IoMT poses challenges due to the IoMT devices resource shortage that cannot bear the blockchain heavy tasks. To bridge this integration gap, numerous Blockchain-based solutions have been proposed, either by modifying core Blockchain properties which reduces its efficiency and security level or by relying on intermediary parties. This paper introduces a novel lightweight solution, allowing IoMT devices to directly interact with the Blockchain network. Specifically, we advocate for the development of a lightweight Web3 interface embedded within IoMT devices. This interface facilitates secure authentication, efficient resource utilization, and efficient interaction with decentralized applications powered by blockchain technology. We provide all technical choices and implementation details of the proposed solution, leveraging the ESP32 microcontroller platform. Furthermore, we provide rigorous security and performance evaluations to demonstrate the credibility and efficiency of our solution.

Within cardiovascular diseases detection using deep learning applied to ECG signals, the complexities of handling physiological signals have a sparked growing interest in leveraging deep generative models for effective data augmentation. In this paper, we introduce a novel versatile approach based on denoising diffusion probabilistic models for ECG synthesis, addressing three scenarios: (i) heartbeat generation, (ii) partial signal imputation, and (iii) full heartbeat forecasting. Our approach presents the first generalized conditional approach for ECG synthesis, and our experimental results demonstrate its effectiveness for various ECG-related tasks. Moreover, we show that our approach outperforms other state-of-the-art ECG generative models and can enhance the performance of state-of-the-art classifiers.

Abstract Security faces huge challenges in Internet of Things (IoT) environments. In particular, conventional access control standards and models tend to be less tailored for IoT due to the constrained nature of smart objects. Usually, a powerful third party is used to handle the access control logic. However, this third party is lacking in transparency and could harm user privacy. Therefore, providing a distributed access control solution, while considering transparency and privacy-preserving awareness in IoT smart systems, is of paramount importance. The described issue can be addressed using the emergent Blockchain technology that provides a promising choice to build a new generation of decentralized and transparent access control solutions. This paper proposes a smart contract-based access control framework for IoT smart healthcare systems, which is based on smart contracts to provide a distributed and trustworthy access control, combined with the GTRBAC model to express fine-grained access control policies while considering temporal authorization constraints. To prove the feasibility and validity of the proposed framework, this paper also provides a detailed technical description and an initial implementation and execution. An experimental evaluation shows that security properties’ analyses on smart contracts achieved the best possible evaluation with no vulnerabilities found, and the cost of access control operations increases linearly as the number of policy constraints increases. Besides, a comparative analysis reveals that the proposed approach can achieve good results with low gas costs and latency.

Blockchain-based applications are basically built on smart contracts, which are widely different in regards of the encoded logic and the used standards. When talking about Ethereum standards, ERC-721 is a well-known standard interface developed for Non-Fungible Tokens. Even though it is standard-based contracts that are more and more exploited, prior work on smart contracts verification mostly investigates efforts in regards of specific vulnerabilities. To address this gap, this paper introduces a formal modeling and verification approach for Ethereum smart contracts including the standard-based ones. We propose a model checking framework that, according to a Solidity smart contract provided as an input, uses ERC guidelines as a standard template to extract the related security properties. Another added benefit of our proposal consists on modeling ERC contracts using the extended finite state machine formalism. As a proof of concept, we illustrate our model checking approach through an NFT contract.

This research paper elaborates an overview of auto scaling solutions for microservices-based applications deployed with containers. Two main features may characterize the efficiency of an autoscaler: analysis strategy launched to identify the root cause of resource saturation, and resource allocation strategy which selects the eligible components for scaling and calculates the required amount of resources. However, existing solutions do not consider the specificity of microservice architecture in their analysis and resource allocation strategies, which may lead to wrong root cause identification and unnecessary resource allocation. In this paper, we investigate and classify existing autoscalers dealing with containers in microservice context. We additionally specify the strength and the shortcomings of each category. As a conclusion, we report the challenges of such solutions and provide recommendations for future works enabling the development of microservices-aware autoscalers.

Focusing on important features in blockchain applications, smart contracts are one of the most studied in the literature. Despite the trusted implementations that smart contracts offer, different security problems and vulnerabilities are rising during their development and execution. Trying to deal with such issues, different researches are proposed to give eventual solutions. Such studies focus on the verification of smart contracts and adopt different techniques. While various formal methods are considered significant effective to ensure the trustworthiness and correctness of smart contracts, this work deals with formal verification of smart contracts using model checking. In this survey, we conduct an overview on smart contracts verification using model checking. We analyze and classify each study according to four main aspects; the adopted formalism, the verified properties, the system under verification and to which blockchain platform the contribution is dedicated. Finally, we suggest some promising future directions to stir research efforts into this area.

Abstract Service providers provision more and more Internet-of-Things (IoT) services in the cloud for dynamicity and cost-effectiveness purposes. This is made possible thanks to the introduction of edge computing that brings additional computing and resources for analytics close to the data sources and thus enables meeting the low latency requirement. Edge nodes should support (i) the heterogeneity of IoT devices (e.g., sensor, actuator) and (ii) characteristics (e.g., mobility, location awareness). IoT is already integrated to the hybrid cloud/edge environment. However, the ecosystem lacks of automation due to the previously mentioned characteristics. Indeed, edge nodes are often manually selected during deployment time, and most of the regular quality-of-service (QoS) management procedures remain difficult to implement. This paper introduces a comprehensive semantic model called EdgeOnto. It encompasses all concepts related to IoT applied in the context of edge computing. The ultimate goal of EdgeOnto is to automate the several steps that make up the IoT services lifecycle in hybrid cloud/edge environment. On the one hand, semantics enable an automatic discovery of the relevant edge nodes that are suitable to host and execute IoT services considering their requirements. On the other hand, it allows supporting the specific QoS procedures that are related to such setting (e.g., low latency, mobility, jitter). The core ontology was designed with the Protégé open-source tool. A smart strawberry farming use case was implemented and evaluated for illustration purposes. The results validate the accuracy and the precision of the designed semantic matchmaker.

We present a novel smart trap for counting olive moths using Internet of Things principles and deep learning algorithms. The smart trap takes a picture of the captured insects once per day and processes it using a deep convolutional neural network to detect “Prays oleae” insects and count their number. Then, the results are transferred via a wireless connection to a backend cloud server. The proposed smart trap is designed to reduce power consumption as much as possible. Two deep neural network models (i.e., YOLO V5 and YOLO V7) are employed to detect and count Prays oleae insects, using our newly created Prays oleae dataset, PraysDB. Our experimental results demonstrate the detection quality, energy efficiency, and computational performance of our smart trap.

Smart contracts' vulnerabilities are widely dependent on developed code. Due to blockchain immutability, once this code is deployed it cannot be reversed. In this context, formal verification techniques are widely used to check smart contracts' correctness with respect to a given specification. In light of this, we introduce a model checking-based approach for solidity smart contracts and their blockchain environment using the nuXmv model checker. Our model-based approach considers the transaction pricing mechanism set by the Ethereum proposal EIP-1559 [1] and consists of three main steps, respectively, representing a smart contract with its blockchain behavior into an Extended Finite State Machine (EFSM) meanwhile, providing an over-approximation of the contract gas usage following the EIP-1559 proposal, then, encoding the modeled EFSM into nuXmv input language and, finally, specifying safety and liveness properties that will be checked against the model. Our contributions reason about modelling and checking gas usage consumption which makes it failure-aware. We illustrate this approach through a voting case study.

Blockchain presents a promising and revolutionary technology for organizations' collaboration, particularly for Inter-Organizational Business Processes (IOBP).It addresses the lack-of-trust problem thanks to its transparency and decentralized features.However, while the adoption of Blockchain technology can alleviate some of IOBP's challenges, it does so at the expense of significant privacy issues.In fact, some process execution data, such as customers' data or business secrets, cannot be shared across the collaborating organizations owing to regulatory restrictions such as the General Data Protection Regulation (GDPR).To address trust and privacy issues in IOBP, this paper presents a Blockchain-based Self-Sovereign Identity (SSI) approach.The SSI concept is combined with a registry proof smart contract to provide an efficient privacy-preserving solution.The proposed approach is applied to the pharmaceutical supply chain case study and implemented on the Ethereum Blockchain.

The COVID-19 pandemic has emerged as a highly transmissible disease which has caused a disastrous impact worldwide by adversely affecting the global economy, health, and human lives. This sudden explosion and uncontrolled worldwide spread of COVID-19 has revealed the limitations of existing healthcare systems regarding handling public health emergencies. As governments seek to effectively re-establish their economies, open workplaces, ensure safe travels and progressively return to normal life, there is an urgent need for technologies that may alleviate the severity of the losses. This article explores a promising solution for secure Digital Health Certificate, called NovidChain, a Blockchain-based privacy-preserving platform for COVID-19 test/vaccine certificates issuing and verifying. More precisely, NovidChain incorporates several emergent concepts: (i) Blockchain technology to ensure data integrity and immutability, (ii) self-sovereign identity to allow users to have complete control over their data, (iii) encryption of Personally Identifiable Information to enhance privacy, (iv) W3C verifiable credentials standard to facilitate instant verification of COVID-19 proof, and (v) selective disclosure concept to permit user to share selected pieces of information with trusted parties. Therefore, NovidChain is designed to meet a high level of protection of personal data, in compliant with the GDPR and KYC requirements, and guarantees the user's self-sovereignty, while ensuring both the safety of populations and the user's right to privacy. To prove the security and efficiency of the proposed NovidChain platform, this article also provides a detailed technical description, a proof-of-concept implementation, different experiments, and a comparative evaluation. The evaluation shows that NovidChain provides better financial cost and scalability results compared to other solutions. More precisely, we note a high difference in time between operations (i.e., between 46% and 56%). Furthermore, the evaluation confirms that NovidChain ensures security properties, particularly data integrity, forge, binding, uniqueness, peer-indistinguishability, and revocation.

In several countries, the connected systems and especially the Internet of Medical Things (IoMT) based systems has been deployed with other advanced technologies to counter and to mitigate the spread of the coronavirus disease 2019 known as (COVID-19) and to smooth the severity of the pandemic. Accordingly, many IoMT-based systems merged with the use of blockchain, artificial intelligence and big data analytics proposed and adopted by diverse countries and governments to counter COVID-19 pandemic. In this context, this paper highlights the needs, the architecture, the design guidelines and the provided services related to our proposed system named (CMK-COVID: Connected Medical Kiosks to Counter COVID-19). Besides that, this paper offers useful insights into the literature related IoMT-based solutions countering COVID-19.

This paper presents an overview of autoscaling solutions for microservices-based applications during elastic treatment. Actually, most of existing work propose solutions dealing with elasticity at the VM level. These solutions launch elasticity when VM overload is detected or predicted. Few solutions treat this issue at the container level and deal with elasticity of microservices- based applications. In addition, these latter use ideas employed at the VM level without considering the specificity of microservice architecture. In this paper, we study and classify existing autoscalers dealing with containers and deploying microservices-based applications. We explain the strength and the shortcomings of each category. As a conclusion, we describe the challenges of autoscaling treatment and we give recommendations for future solutions.

Abstract This paper focuses on the problem of the hierarchical multi‐label classification of research papers, which is the task of assigning the set of relevant labels for a paper from a hierarchy, using reduced amounts of labelled training data. Specifically, we study leveraging unlabelled data, which are usually plentiful and easy to collect, in addition to the few available labelled ones in a semi‐supervised learning framework for achieving better performance results. Thus, in this paper, we propose a semi‐supervised approach for the hierarchical multi‐label classification task of research papers based on the well‐known Co‐training algorithm, which exploit content and bibliographic coupling information as two distinct papers' views. In our approach, two hierarchical multi‐label classifiers, are learnt on different views of the labelled data, and iteratively select their most confident unlabelled samples, which are further added to the labelled set. The success of our suggested Co‐training‐based approach lies in two main components. The first is the use of two suggested selection criteria (i.e., Maximum Agreement and Labels Cardinality Consistency) that enforce selecting confident unlabelled samples. The second is the appliance of an oversampling method that rebalances the labels distribution of the initial labelled set, which reduces the reinforcement of the label imbalance issue during the Co‐training learning. The proposed approach is evaluated using a collection of scientific papers extracted from the ACM digital library. Performed experiments show the effectiveness of our approach with regards to several baseline methods.

The Internet of Medical Things (IoMT) represents a network of implantable or wearable medical devices that continuously collect medical data about the patient’s health status. These data are heavy, sensitive and require high level of security. With the emergence of blockchain technology, researchers are focusing on using blockchain strategies to bring security to healthcare applications. However, such integration is very difficult and challenging due to the different requirements in these two technologies. We present in this paper a technical review of existing solutions applying blockchain technology on IoMT. We analyze these studies, discuss the proposed architectures and how they managed the integration challenges. The open issues regarding the application of blockchain over IoMT are also specified.

In response to the researchers need in the bio-medical domain, we opted for automating the bibliographic research stage. In this context, several classification models of supervised machine learning are used. Namely the SVM, Random Forest, Decision Tree, KNN, and Gradient Boosting. In this paper, we conduct a comparative study between experimental results of full article classification and abstract classification approaches. Furthermore, we evaluate our results by using evaluation metrics such as accuracy, precision, recall and F1-score. We observe that the abstract approach outperforms the full article approach in terms of learning time and efficiency.

The COVID-19 pandemic is sweeping across the world and causing widespread death and disruption. To this effect, nations have struggled to use technologies to detect and to monitor COVID-19 cases and related information. Unfortunately, both inconsistent and inaccurate information from "trustless" sources, and "mistrust" in effectively monitoring and reporting patients symptoms and condition have highlighted the failure of existing infrastructures to preserve human healthcare while maintaining patient's privacy and to slow down the widespread of the pandemic. This paper provides an insight of the perceived benefits of Blockchain to expectations of the COVID-19 pandemic in terms of providing "trust" in addressing information sharing in health systems while maintaining privacy. This paper exhibits a Blockchain-based COVID-19 Smart Healthcare approach that embraces Blockchain's benefits in healthcare systems.

Smart Systems are composed of interconnected nodes (devices, services, components, etc.) that can be intelligent, mobile, embedded, cloud-based, or/and adaptive. These nodes interact together through new communication protocols. Architectures of such system needs to adapt its behavior and deals with change in the environment. An adaptive and reconfigurable architecture can repair itself if any execution problems occur, in order to successfully complete its own execution. In the design of an adaptive and reconfigurable software system, several aspects have to be considered. Also other emerging areas such as Big data can also be used to solve traditional problems of Smart Systems, like scalability and performance. This special issue addresses these issues and is composed of seven papers. The paper of1 entitled “Efficient monitoring for intrusion detection in wireless sensor networks” addresses the design of a reliable and energy-efficient monitoring system that resists internal security attacks based on a distributed smart monitoring protocol. The paper of2 entitled “Cloud SLA negotiation and re-negotiation: An ontology-based context-aware approach” defines a context-aware system that automates the negotiation of dynamically generated and adapted SLAs using reasoning techniques and semantic mapping between client requests and provider offers. The paper of3 entitled “Cloud service composition using minimal unsatisfiability and genetic algorithm” targets the run-time phase of adaptive systems. It addresses the dynamic properties of service-oriented adaptive systems by provide a hybrid approach for automatic WS composition based on formal methods and genetic algorithms. The paper of4 entitled “A knowledge-based approach to manage configurable business processes” targets both run-time and design-time as well as structural and behavioral properties of enterprise systems modelled and enacted as Business Processes (BP). It proposes a knowledge-based approach for capturing the different versions of a BP into a single configurable BP and splitting this process into fragments as an alternative of handling multiple BP versions. The paper of5 entitled “Avoiding resource misallocations in business processes” presents an approach for avoiding resource misallocations, considered as an improper combination of resources, in Business Processes (BPs). The paper of6 entitled “Simulating systems of systems using situation/reaction paradigm” targets the designs-time phase of adaptive systems. It considers the paradigm of Systems of Systems that can be applied to different smart and adaptive systems. The paper sees these systems from the mission point of view to characterise their evolving rules with formal modelling and simulation. The paper of7 entitled “A comprehensive survey on modeling of cyber-physical systems” provides a survey of existing approaches to modeling CPS. It aims to study and to classify the CPS properties and to discuss their importance in different application domains. We would like to thank CCPE Editor-in-Chief Dr. Geoffrey C. Fox for his strong support. A special thank goes to all authors for their valuable contributions to this special issue. Special thanks go to all the guest eidtorial board members for their comments that helped in enhancing the quality of the papers.

Abstract Mobile health care systems highly depend on collected physiological data through medical sensors to provide high‐quality care services. However, inaccurate physiological data from sensors pose a major challenge for health care providers when making decisions, whereas an erroneous decision can affect the user's life. We propose, in this paper, an anomalous data detection and isolation approach for mobile health care systems. Our approach, called AUDIT, detects inaccurate measurements in real time and distinguishes between faults or errors and health events. To do so, we propose reduced time and space complexities algorithms based on dimension reduction within the context of resource constraints. Furthermore, a decision algorithm is proposed while exploring the spatio‐temporal correlation between physiological attributes. First, we describe our approach. Then, we give its implementation details. Finally, to demonstrate the effectiveness of our approach, we show different experiments related to its detection performances and its time and space complexities.

In personalized medicine, a challenging task is to identify the most effective treatment for a patient. In oncology, several computational models have been developed to predict the response of drugs to therapy. However, the performance of these models depends on multiple factors. This paper presents a new approach, called Q-Rank, to predict the sensitivity of cell lines to anti-cancer drugs. Q-Rank integrates different prediction algorithms and identifies a suitable algorithm for a given application. Q-Rank is based on reinforcement learning methods to rank prediction algorithms on the basis of relevant features (e.g., omics characterization). The best-ranked algorithm is recommended and used to predict the response of drugs to therapy. Our experimental results indicate that Q-Rank outperforms the integrated models in predicting the sensitivity of cell lines to different drugs.

In this paper, we present a convolutional gated recurrent neural network (CGRNN) to predict epileptic seizures based on features extracted from EEG data that represent the temporal aspect and the frequency aspect of the signal. Using a dataset collected in the Children’s Hospital of Boston, CGRNN can predict epileptic seizures between 35 min and 5 min in advance. Our experimental results indicate that the performance of CGRNN varies between patients. We achieve an average sensitivity of 89% and a mean accuracy of 75.6% for the patients in the data set, with a mean False Positive Rate (FPR) of 1.6 per hour.

This paper presents a deep learning approach for depressive episode detection on mobile devices, called DL4DED. It is based on a convolutional neural network and a long short-term memory network to identify the status of a patient’s voice extracted from spontaneous phone calls. To run DL4DED on mobile devices, two neural network model compression techniques are used: quantization and pruning. DL4DED protects data privacy, since it can be executed on a patient’s smartphone. Our proposal is validated on the DAIC-WOZ database. The obtained results show that the accuracy of DL4DED with model compression is only slightly lower than the accuracy of DL4DED without model compression. Furthermore, our experiments indicate that the power consumption of DL4DED is reasonably low.

This article deals with anomaly detection for microservices-based applications during elastic treatment. In elastic treatment, scaling-up resources is based on threshold. Many studies consider that threshold exceeding is caused by the increase in requests number. However, this exceeding may be caused by many problems such as specific requests requiring a lot of resources or issues related to VMs and containers. That's why, when thresholds are exceeded we propose to apply an analysis treatment that detects and identifies the root cause of the threshold exceeding, either it's caused by a problem such as specific request, VM issue, container issue or it's caused by a normal increase in request's number. This paper presents "DOCKERANALYZER" a software module that detects and identifies execution problems in microservices context. Experimental measurements have been conducted on an IOT platform as a real use-case presenting realistic problems and demonstrating the effectiveness of our proposed solution.

Wireless Sensor Networks (WSNs) have been recognized as a promising communication technology for the Internet of Things (IoT). In particular, smart grid applications rely on WSNs for enabling pervasive monitoring and control of the electric grid. However, these applications are commonly deployed in harsh environments that adversely impact the reliability of low-power wireless links in WSNs. Efficient link quality estimation has been shown as a prerequisite to overcome link unreliability. Several WSN Link Quality Estimators (LQEs) have been proposed in the literature. However, there is a lack of real world experimentations that investigate their adequacy to assess low-power links in smart grid environments. To fill this gap, this paper presents a thorough experimental study of representative LQEs in a smart grid distribution substation. Both single and composite LQEs are evaluated in terms of reliability, stability and reactivity, by analyzing their statistical behavior. This study would help system designers choose the most appropriate estimators for smart grid environments. Especially, it shows that composite LQEs, such as Opt-FLQE, F-LQE, and four-bit, are more reliable than single LQEs, including PRR, WMEWMA, and RNP. Further, experimental results show that Opt-FLQE is found to be the most reliable estimator, F-LQE, PRR, and WMEWMA are the most stable estimators, while Opt-FLQE, RNP, and four-bit are the most reactive LQEs.

Mobile healthcare applications highly depend on healthcare data, which is collected from wearable or implantable sensors. However, sensor readings may be inaccurate due to resource-constrained devices, sensor misplacement, patient with smearing, and other environmental related causes. Analyzing healthcare data is of paramount importance to provide high quality-care services and reduce false medical diagnosis. In this paper, we propose an online approach to detect inaccurate measurements and to raise alerts only when patients seem to be in emergency situations. The proposed approach is based on robust principal component analysis and adaptive threshold for multivariate anomaly detection, and on contribution plots for univariate anomaly diagnosis. We apply our proposed approach on real medical dataset. Our experimental results prove the effectiveness of our approach in detecting and diagnosing anomalous physiological measurements. The reduced time and space complexities of our approach make it useful and efficient for real time mobile health applications.

Cloud environments offer an interesting infrastructure for any modern enterprise information systems due to their high performance and low operating cost. Cloud resources are offered in various pricing strategies based on temporal properties. In general, enterprises looking towards minimizing their spending on IT infrastructure find such pricing strategies very attractive to deploy and run their business processes. Nevertheless, due to the lack of explicit and formal description of (Cloud) resources in existing business processes modeling languages, such as BPMN, Cloud resources can not be correctly allocated. Therefore, we elaborate an extension to BPMN 2.0 to fully integrate (Cloud) resource perspective, especially the temporal properties of Cloud pricing strategies in business process model. In order to help the designer to allocate correctly the required Cloud resources, we propose an automatic generation of timed automata from this BPMN extensions to check the matching between both temporal constraints: activities and Cloud resources. To show its feasibility, our approach has been implemented and tested using a real use case from an industrial partner.

Constructing Linguistic Web Services (LingWS for short) is a difficult task that requires expertise in both linguistic and software engineering. The challenge is to manage the various and richness linguistic knowledge and the heterogeneous Natural Language Processing (NLP for short) using the web service technology. In this paper, we propose a semantic approach to improve the composition of LingWS. First, we provide a rich NLP domain ontology that covers the data and processing concepts in a fine granularity and richness relationships between these concepts. Second, we proceed with the generation of an ontological view from the rich proposed NLP domain ontology using a set of selection criteria. A view delimits the linguistic ontology to the user’s needs. Starting from this view, the user will be assisted in selecting a valid processing scenario, assimilated to a scenario of linguistic services, with respect to the coherence, completeness and redundancy properties. In order to prove the feasibility of the proposed approach, we carried out an experiment on the morphological level.

The goal of this track is to bring together researchers and practitioners both from the Academia and from the Industry working in the areas of the adaptation and reconfiguration of distributed systems. Different investigation topics are involved, such as: CBSE, Web service, cloud applications, mobile applications, Functional and Non-Functional requirements (QoS, performance, resilience), monitoring, diagnosis, decision and execution of adaptation and reconfiguration. Different research areas are covered: concepts, methods, techniques, and tools to design, develop, deploy and manage adaptive and reconfigurable software systems.

AADL (Architecture Analysis & Design Language) is a modelling language enabling the design of embedded realtime systems. This language has proven its power in several domains like aeronautics and space. The AADL core language describe both software and hardware components and it can be extensible by properties to provide information about these components or annexes to enable a designer to extend and customize the AADL core specification with other concepts specified in a language other than AADL. In particular, the AADL Error Model Annex (EMA) was proposed to model such requirements separately from the core model since dependability requirements is of major importance in real-time embedded systems. This annex can not only model different kinds of errors but also error propagation, error detection and error recovery. In this paper, we ensure a comparative study of existing tools and compilers of the AADL language and its error model annex. We present, then, our work aiming at integrating a new compiler of the EMA annex into the Ocarina tool suite to support dependability requirements.

Self-adaptation is an important capability for applications, especially those running in pervasive environments. Self-adaptive applications need a dynamic adaptation of their architecture to cope with the changes of their environments. A decision within the architectural adaptation must be taken to select the architectural configuration of the application that fits more the contextual situation. Many approaches for adaptation decisions are proposed in the literature. The utility-oriented approach is an efficient decision approach which arouses the interest of researchers. However, while different utility functions can be used, there is a lack of comparisons and recommendations for the choice of the utility functions. In this paper, we present an overview of the utility functions. Moreover, we present guidelines that support the choice of the most suitable utility function for the applications' designers.

System of Systems (SoS) is a new class of complex software systems resulting from the integration of several independent systems working together. Within a SoS, many participant systems may be integrated and deleted operationally over the time. Each system has an Architecture Model modeled at design time. Thus, the SoS' software architecture description is represented by an aggregated Architecture Model. This aggregated Architecture Model represents participant systems but not necessarily their interactions and communications over the time. In literature, several research studies addressed issues related to SoS. However, we noticed a lack of studies that address the problem of how to describe the whole SoS' software architecture for each change of a participant system over the time. Moreover, studies dealing with checking conformity between the whole SoS' software architecture description and the aggregated Architecture Model, are still lacking. This paper presents an approach for the discovery of SoS' software architecture description from execution traces. For this purpose, the proposed approach records execution traces of all participant systems belonging to the SoS, their interactions and communications in a data base. Then, our approach relies on mining techniques to extract software architecture from the data base and describes it via a model called Architecture Model. In addition, this paper offers a solution for checking conformity between the aggregated Architecture Model and the Discovered Model. The diagnosis results may suggest new rules/constraints to enhance the aggregated Architecture Model.

Research in the development of context-aware applications has gained significant attention, in which context awareness should be taken into account to adapt these applications to the requirements of the environments and the users. The development of context-aware applications is based on a control loop with four phases. Collecting context information (phase 1), analyzing context information to detect changes (phase 2), deciding adaptation actions (phase 3) and executing the corresponding adaptation actions (phase 4) to deal with the changes. In this paper, we discuss the analysis phase (phase 2) and we propose an analysis approach. The proposed analysis approach is illustrated by an analysis procedure that aims to offer a support for application designers allowing them to design easily context-aware applications. The analysis procedure is achieved by a sequence of steps performed by the designers. We have also implemented an analysis module that aims at guiding the programmers when developing context-aware applications. To motivate the use of our approach, we present a case study related to smart buildings. Finally, we show the effectiveness of our analysis approach through experiments related to the processing time of our analysis module as well as the memory and the CPU overhead.

Epidemiology is a rapidly evolving science with many hopes. It focuses on the study and analysis of the patterns, causes, and effects of health and disease conditions in defined populations, which justifies its complexity. Over time, many computer-based technical tools are born with the major aim of facilitating the study of new phenomena, the collection of masses of enormous data, the analysis of its data, etc. In this survey, we are interested in the creation of the epidemiological research protocol which represents the initial phase of epidemiological research. An epidemiological research protocol requires, at each stage of its creation, well-defined computer tools relating to the particular medical field of application, to a precise writing phase, etc. In this article, we propose a survey about the tools for creating the epidemiological research protocol. First, we outline the research challenges in conducting a scientific research. Then, we emphasize the importance of the research protocol in the case of epidemiological studies. We further detail the several components of the epidemiological research protocol. After that, we discuss several related works before reporting our contribution in the epidemiological research process. Then, we highlight the several aspects of research in epidemiology and related needed tools. We present some perspectives and innovations in the software tools for creating the epidemiological research protocol in an easy, safe and simple way.

Real time mobile Health applications highly depend on sensor readings to provide high-quality health services. However, real-time sensor readings may be inaccurate and cause abnormal physiological measurements due to internal and external factors. Thus, abnormal readings have a significant impact on the reliability of such applications and consequently affect the patient's life. This paper addresses the following issue by proposing a robust approach for online detection of abnormal medical measurements. The proposed approach is based on robust Principal Component Analysis (PCA) to analyze collected physiological measurements from sensors and detect the occurrence of multivariate anomalies based on squared prediction error at runtime. We apply our proposed approach on real medical dataset. Our simulation results prove the effectiveness of our approach in achieving good recall with a low false alarm rate. The reduced time and space complexity of our approach make it useful and efficient for real time settings.

Autonomic computing has received great attention as a solution for the increasing complexity of today’s self-adaptive systems. In this kind of systems, the decision to ensure the most suitable autonomic application’s adaptation according to context is very important. In the literature, several research activities propose decision approaches and frameworks within the MAPE-K autonomic loop for adaptation. However, there is a lack of guidelines to design adaptation decisions. Such guidelines are required to assist the designers of autonomic applications and unify existing decision approaches. In this work, we propose a design guideline for adaptation decisions and an instantiation of this guideline in the case study Smart Building.

Current communication systems restrict user affordances in terms of expressiveness and interaction. Complex Event Processing (CEP) have gained much importance to overcome these shortcomings. It allows users to interact with powerful expressiveness when defining logical and temporal patterns of exchanged events. This expressiveness allows cleaning network traffic by eliminating the routing of useless events and consequently reducing the overall consumed energy. However, handling the expressiveness of desired events, filtering coming events still challenging features, especially with the growth of data size encapsulated as events in the network. In this work, we rely on Publish/Subscribe system based on Distributed Hash Tables (DHT), which offers intrinsically flexible event routing, scalability and load balancing in order to manage distributed composite events routing. For efficient event filtering, we propose a three dimensional indexing hash space named CECube as a smart data structure for rapid CEP over DHT. The CECube indexes firstly composite subscriptions, then basing on a simple binary search, it serves as publications filter and helps making the right decision for what events should be aggregated and forwarded to the adequate subscribers. The performance of our solution is evaluated using Free Pastry simulator. The results demonstrate firstly that our approach is efficient in terms of filtering process and that the average number of routing nodes is decreased. Secondly, we prove the superiority of our approach as compared to another existing work.

In this paper, we introduce the IaaS "PriArmor" (Privacy Armor) solution for privacy preservation in the cloud. This approach allows the data owner (tenant and/or end users) to define his privacy requirements and to include regulations policy based on a privacy ontology model that captures all privacy concepts related to the data access and usage in the cloud. The PriArmor approach allows the enforcement of usage control requirements at a low level using a System Call Interception (SCI) technique that enables detecting the intention for policy breaching and inhibiting it. Moreover, the PriArmor approach introduces a data flow model that tracks private data and reflects the existence of derived data through the system to maintain a strong enforcement level. The performed evaluation proves the efficiency of our approach for ensuring policy enforcement in the cloud environment.

Scientific research teams have immense valuable knowledge that need to be managed. Organizing scientific contributions of team members constitutes a major challenge for the monitoring of knowledge evolution, team member’s competences discovery, and facilitating information retrieval processes. However, performing manual annotations is often time consuming and labor-intensive task, especially in case of complex annotation schemas. Currently, existing knowledge management systems focus on ensuring the scientific knowledge creation, sharing, organization and evaluation but don’t provide a way for helping researchers in the classification task. In this paper, we introduce a knowledge management system that offers an annotation service for researchers’ contributions by including some natural language processing techniques. The provided service process comprises four phases: (1) the semantic enrichment of domain ontology based on the extraction of background data from Babelnet knowledge base, (2) the automatic generation of candidate categories using the enriched domain ontology, (3) the forwarding of the pre-annotated papers to our web-based system to interact with researchers, and finally (4) the human revision of the generated annotations. Evaluation results show its advantage not only in reducing human effort and time consumption during the annotation task but also in improving annotations quality.

Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceedings record.

Aspect-Oriented Programming (AOP) supports the separation of concerns cutting across the implementation of a software application in order to avoid scattering and tangling. We focus on the integration of this paradigm into the development of real-time systems. AOP is based on the weaving process to automatically integrate separately-created segments of code (specified by aspects), into the application by replacing them in the final implementation code. In the context of real-time systems, this can harm determinism by including constructs that may violate real-time constraints beyond the control of the developer such as dynamic allocation. We both studied and tested the AspectAda language, an existing aspect mechanism, in order to adapt its implementation to respect real-time constraints. We studied this language's grammar, runtime and especially weaving operation. In this paper, we briefly discuss both the limitations of the existing language and the proposed solutions. Then, we present a new architecture of the compiler/weaver to overcome the problems of the existing one and we detail the implementation of its different parts based on tree manipulation. Finally, we illustrate our contribution using a case study.

Medical data are crucial for providing reliable mobile health services. However, its reliability may be degraded due to internal factors related to performance variations of mobile technologies used in the application and other external ones such as the environmental ones. This paper addresses this problem by proposing an ontology-based approach to deal with data and reliability management in mobile health applications. To this end, the proposed ontology model is inspired from the IBM autonomic paradigm which encompasses four concepts namely Monitor, Analyzer, Planner and Executor. The monitor concept includes the major reusable concepts that provide the basic infrastructure to build an ontology model for mobile health applications and the major reusable concepts to build an ontology model for data reliability management procedure. Besides, we defines analysis rules using SWRL (Semantic Web Rule Language) in order to analyze the reliability of each incoming medical datum et generate alerts regarding abnormal behaviors. We implement the proposed ontology model using Protg as an ontology editor.

Opportunistic real time mobile crowdsensing pertains to the instantaneous monitoring of large scale phenomena by leveraging human mobility and smartphones' sensors. However, while urban applications concern more about coverage quality and timeliness of detected data, mobile users should care about their consumed energy for performing a sensing task. In this paper, we introduce the Real time OPportunistic Scheduler Framework for Energy aware mobile Crowdsensing (Re-OPSEC). Especially, we present in deep the off-line tasks allocation approach operating on top of energy saving model. The methodology consists of two main processes. Re-OPSEC builds firstly connectivity patterns called online episodes and extracts mobility information jointly with those patterns. Secondly, it allocates, in an off-line mode, online episodes to send jointly sensing tasks in real time. Allocated patterns should increase the total expected sensing revenue and protect volunteers from embarassed situations such as their smartphones turning off. The performance of the approach is evaluated using realistic mobility datasets. The results demonstrate firstly the superiority of our approach as compared to an other existing work. Secondly, they prove that coverage rate can achieve a high level in spite of energy saving mechanisms restriction.

Embedded and invisible computing resources are paving the way to a new paradigm known as ubiquitous computing. In this paradigm, more attention needs to be paid to the development of context aware applications. Several proposals for the development of these applications are based on a context awareness loop with four phases. First, monitoring context information (Collect). Second, analyzing the collected context information to detect changes (Analysis), third, deciding adaptation actions relative to the changes (Decide). Finally, executing the corresponding adaptation actions to deal accordingly with the changes (Act). In this paper, we discuss the Analysis phase. We propose an analysis approach that aims at detecting the context changes and raising notifications when changes occur. The analysis approach is based on thresholds and formalized through an analysis procedure that aims to facilitate the design of the analysis phase to develop context aware applications in ubiquitous environments. The analysis procedure is described by a set of steps used by the application designers to design context aware applications. In order to demonstrate the usefulness of our approach, we present a Smart Building case study and we illustrate the use of our analysis procedure through a Smart Building application scenario.

Wireless Sensor Networks (WSNs) have been recognized as a promising communication technology for smart grid monitoring and control applications. Unfortunately, environmental conditions in smart grids are complex and harsh (electromagnetic interference, obstructions, fading, etc.), which turns radio links extremely unreliable. Routing protocols play a crucial role to overcome low-power link unreliability in smart grid environments. Especially, RPL (IPv6 Routing Protocol for Low Power and Lossy Networks) is an IETF standard that is supposed to meet the requirements of WSN-based smart grid communications. RPL routing metric relies on link quality estimation through ETX (Expected Transmission Count) assessment, to identify high quality links for data delivery. However, ETX is not sufficiently accurate as it assesses a particular link aspect, number of packet retransmissions over the link, and ignores other important aspects such as channel quality. Consequently, as confirmed by recent experimental studies, RPL can fail to identify routing paths with high quality links leading to high packet loss rates. In this paper, we propose an alternative routing metric for RPL based on holistic link quality estimation, where several link metrics are combined. Based on COOJA simulations, we demonstrate that our proposed routing metric improves RPL performance over traditional routing metrics, including the RPL default metric, mainly in terms of packet loss ratio, end-to-end delay, energy efficiency, and topology stability.

Real-time embedded systems may be composed of a large number of time constrained functions. During software architecture design, these functions must be assigned to tasks that will run the functions on the top of a real-time operating systems (RTOS). This is a challenging work due to the large number of valid candidate functions to tasks assignment solutions. Moreover, the impact of the assignment on the system performance criteria (often conflicting) should be taken into account in the architecture exploration. The automation of the design exploration by the use of metaheuristics such as multi-objective evolutionary algorithm (MOEA) is a suitable way to help the designers. MOEAs approximate near-optimal alternatives at a reasonable time when compared to an exact search method. However, for large-scale systems even a MOEA method is impractical due to the increased time required to solve a problem instance. To tackle this problem, we present in this article a parallel implementation of the Pareto Archived Evolution Strategy (PAES) algorithm used as a MOEA for the design exploration. The proposed parallelization method is based on the well-known Master-Slave paradigm. Additionally, it involves a new selection scheme in the PAES algorithm. Results of experimentations provide evidence that, on one hand, the parallel approach can considerably speed up the design exploration and the optimization processes. On the other hand, the proposed selection strategy improves the quality of obtained solutions as compared to the original PAES selection schema.

Fault tolerance, one of the means of dependability, is defined as the capability of a system to continue providing offered services even in the presence of errors. Modelling fault tolerant systems is becoming a serious challenge due to emerging requirements suh as dynamism, distribution and system evolution. In this context, AADL is extended by the Error Model Annex to design architectural error model even for critical systems for analysis and assessment purposes. In this paper, we define a model driven approach to generate fault tolerant application code using aspect oriented programming. First, we integrate fault tolerance elements since the modelling step of a system using AADL and its annex Error Model Annex. Second, we define a set of transformation rules from the EMA annex to the AO4AADL annex, an extension of the AADL language by architectural aspects. The model transformation is generic and not specific to a language. AO4AADL is transformed into aspect code using the same target language as the functional code. Therefore, we ensure separation of concerns at the model level as well as the application level. To validate our approach, we apply it to an infant incubator system.

AROSA Track Report

This Editorial [1] was originally published bearing the title “Towards the optimal synchronization granularity for dynamic scheduling of pipelined computations on heterogeneous computing systems” which was taken from another article's title [2] due to a production error. The title is now corrected above, and in the Editorial itself. We apologize for this error.

Service-Oriented Architecture is a cornerstone for the realization of the user's needs through the automatic composition of services from service descriptions and user tasks. Yet, automatic service composition processes commonly assume that Linguistic Web Service descriptions and user requests share the same abstraction level, and that services have been pre-designed to integrate. In this paper, we identify several composition patterns that assist the users with the composition of appropriate services. Moreover, we use our previous proposal to ensure the compatibility between Linguistic Web services using different exchange formats. This proposal is based on the Lexical Markup Framework which is the ISO standard for lexicons.

Fine-grained Web service security policies contain protection assertions that include XPath expressions pointing to the message data to be secured. However, existing security policy (SP) matching approaches don't take into account the structural heterogeneities that may exist between the requestor and provider data. In this paper, we show how this can lead to wrong SP matching results and propose an XPath translation approach that makes the XPath expressions in a requestor and provider SPs refer to the same XML schema so that they may be correctly compared. We also implement our XPath translator, integrate it into our previous SP matcher, and validate the correctness of matching fine-grained protection assertions through several tests and a real-world use case.

This article deals with real-time embedded system design and verification. Real-time embedded systems are frequently designed according to multi-tasking architectures that have timing constraints to meet. The design of real-time embedded systems expressed as a set of tasks raises a major challenge since designers have to decide how functions of the system must be assigned to tasks. Assigning each function to a different task will result in a high number of tasks, and then in higher preemption overhead. In contrast, mapping many functions on a limited number of tasks leads to a less flexible design which is more expensive to change when the functions of the system evolve. This article presents a method based on an optimization technique to investigate the assignment of functions to tasks. We propose a multi-objective evolution strategy formulation which both minimizes the number of preemptions and maximizes task laxities. Our method allows designers to explore the search space of all possible function to task assignments and to find good tradeoffs between the two optimization objectives among schedulable solutions. After explaining our mapping approach, we present a set of experiments which demonstrates its effectiveness for different system sizes.

QoS-based service selection is one of the important requirements in Service Oriented Computing (SOC). A challenging task towards this purpose is the selection of the best combination of services that fulfils user's requirements while meeting quality of service (QoS) constraints. This challenge becomes more complex when dealing with time-dependent QoS values and temporal properties. Indeed, during the selection, mutual dependencies between the different temporal constraints may arise so that the selection of each service may influence or be influenced by the selection of other services. On other side, to find the best solution, all potential combinations must be compared. However, the number of these combinations may be very high, which can present a barrier for enabling effective service selection. In this paper, we present a heuristic based time-aware service selection approach to efficiently select a close-to-optimal combination of services. First, pruning techniques are adopted to reduce the search space. Second, a novel heuristic approach is proposed based on service clustering, constraints decomposition and local selection while considering both QoS and temporal constraints. Finally, experiments which confirm the feasibility and effectiveness of the proposed approach in terms of its timeliness and optimality, are conducted.

Smart Buildings have been the subject of research for more than two decades. The different perspectives range from monitoring and controlling energy consumption. Indeed, energy efficiency is considered as one of the promising fields of applications of the Internet of Things. Since Smart Buildings are an important part of the smart grid, their energy efficiency is vital for the environment and global sustainability. In ubiquitous computing systems, designing Smart Building applications is a challenge since these applications must ensure a trade-off between energy consumption and occupants comfort especially in ubiquitous environments. In this paper, we focus on the design of a Smart Building application in ubiquitous computing systems. The Smart Building application is able to manage energy consumption while keeping the occupants comfort. We elaborate an illustrative scenario to demonstrate the usefulness of our work.

This paper is interested in the assisted interrogation of lexical databases designed according to the LMF standard (Lexical Markup Framework) ISO-24613. The proposed solution is based on a requirement-based lexical web service generation approach that makes easier the task of engineers when developing NLP (Natural Language Processing) systems. Using this approach, the developer will not deal with the database content or its structure. Also, he will not use any language query. For each lexical requirement, we generate through a lexical web service for interrogating LMF databases. Also we generate with it its enhanced WSDL description file that we have enriched by semantic data describing data categories used in the requirement specification.

Several Link Quality Estimators (LQEs) have been proposed for Wireless Sensor Networks. However, their adequacy to smart grid environments has not been properly investigated. This paper addresses the problem of efficient low-power link quality estimation for smart grid environments. The first part of this paper presents a performance study of representative LQEs, namely ETX, four-bit and F-LQE, in three typical smart grid environments. These LQEs are evaluated in terms of reliability, stability and reactivity, by analyzing their statistical behavior. This study shows that F-LQE is more reliable and more stable than ETX and four-bit. However, it is not the most efficient for smart grid due to the lack of reactivity and also its higher complexity. Hence, the second part of this paper introduces Opt-FLQE, an optimized version of F-LQE that overcomes its limitations. The performance analysis of Opt-FLQE shows that it is more reactive than F-LQE while still being more reliable.

The focal concerns are Service-oriented software systems, applications and architectures addressing adaptation and reconfiguration issues. Different investigation topics are involved, such as: SOA, requirements (QoS, performance), monitoring, diagnosis, decision and execution of adaptation and reconfiguration. Different research axes are covered: concepts, methods, techniques, and tools to design, develop, deploy and manage adaptive and reconfigurable software systems.

Slim Kallel, Mohamed Jmaiel, Sumitra Reddy; Enabling Technologies: Infrastructure for Collaborative Enterprises, The Computer Journal, Volume 58, Issue 3, 1 Mar

Summary In this paper, we propose a model‐driven approach allowing to build reconfigurable distributed real‐time embedded (DRE) systems. The constant growth of the complexity and the required autonomy of embedded software systems management give the dynamic reconfiguration a big importance. New challenges to apply the dynamic reconfiguration at model level as well as runtime support level are required. In this direction, the development of reconfigurable DRE systems according to traditional processes is not applicable. New methods are required to build and to supply reconfigurable embedded software architectures. In this context, we propose an model‐driven engineering based approach that enables to design reconfigurable DRE systems with execution framework support. This approach leads the designer to specify step by step his/her system from a model to another one more refined until the targeted model is reached. This targeted model is related to a specific platform leading to the generation of the most part of the system implementation. We also develop a new middleware that supports reconfigurable DRE systems. Copyright © 2013 John Wiley & Sons, Ltd.

In Wireless Sensor Networks, flooding in one of the basic communication primitives. It is used to propagate informations from one node to the entire network. Every node, receiving a piece of information, has to flood it to all its neighborhood. As informations to spread are important, such as fire or intrusion alerts, communications should be secured. In this paper, we present a greedy flooding algorithm for Wireless Sensor Networks secured by a Random Key Pre-distribution model that make them redoubtable. We present two theoretical upper bounds of the time complexity of this algorithm that depend on the network structure. We then use the ViSiDiA platform to implement and simulate our algorithm to validate these theoretical results.

Control and data dependencies represent prominent information for modeling, managing, testing and optimizing service based business processes (SBPs). BPMN 2.0, as a twofold-purpose language, can be used to both mode land execute these SBPs. However, there is neither tailored support nor implemented tool for dependency ananlysis of such processes. Therefore, in this paper, we designed and implemented DAT, a dependency analysis tool for SBPs inBPMN. Then, we show the usability of this tool using a realistic case study.

Dynamic selection of the best services to execute abstract tasks of business processes is very important. Indeed, it enables to cope with complex user's requirements that require the collaboration of several more elementary services. However, with the increasing amount of candidate services of each business task that offer different QoS (Quality of Service) values, the selection of the optimal combination of services becomes a very hard task. This problem is more complex when dealing with temporal properties of business processes associated with time-dependent QoS parameters that can change according to the execution time. Unlike static QoS which have been deeply studied in the existing service selection approaches, time-dependent QoS are insufficiently taken into consideration. In this paper, we are interested in the problem of service selection to satisfy a given business process while considering temporal properties associated to time-dependent QoS. The selection approach that we propose relies on a new service pruning approach that is applied prior to our selection algorithm to reduce the number of candidate services while guaranteeing that the optimal solution still be found.

In professional or home settings, the usage of Machine-to-Machine (M2M) technology is desired and often enforced for its ability to reduce the total cost and to expose ubiquitous networks services. However, due to the unpredictability of M2M network mobility, connection and disconnection, a lot of problems can attend services availability and cause path loss or change service selection parameters, making services discovery more difficult than ever. In this paper, we present an approach based on knowledge for ensuring discovery and invocation of available services. The approach firstly leverages semantic data from user regularity of movement by extracting knowledge jointly from the mobility data and underlying geographic domain information. Then, it analyzes those data in order to prepare a pre-planned list of available services ranked not only according to their relevance but also according to their degree of availability. To illustrate the feasibility of our approach, we adopt an illustrative scenario highlighting the importance of exploiting the daily life of a mobile user for service discovery enhancements.

Temporal constraints are one cornerstone of process specification and verification in the whole process lifecycle. Nevertheless, in the existing research approaches, little consideration has been given to the subject of verification of advanced temporal constraints such as absolute temporal constraints associated with relative temporal constraints. In this paper, we handle the problem of verification while considering advanced relative and absolute temporal constraints. Firstly, a set of rules are proposed to prevent the designer to specify some faulty temporal combinations of absolute temporal constraints, early on, before the execution step. Second, to capture relative temporal constraints, we propose a mapping step whose aim is to map timed business processes into timed automata. Using the defined formal model, we finally investigate a model checking based verification approach that aims at validating business processes against their temporal constraints.

In advanced service-oriented computing, complex applications are usually specified as abstract business processes. The execution of these applications requires the selection of a set of services to invoke abstract business tasks. With the growing number of alternative services of each business task that differ in their QoS, the selection of the best combination of services that satisfies business process constraints and end-to-end users' requirements becomes a complex decision problem. Current selection approaches consider only static QoS and ignore the fact that QoS values can depend on temporal properties. In this paper, we propose a novel service selection approach considering time-dependent QoS attributes. The proposed approach introduces two search space reduction mechanisms that combine QoS and temporal constraints. The application of these mechanisms improves the performance of the selection process which is demonstrated by experimental results.

This paper presents an analytical model for monitoring and analyzing QoS of publish/subscribe systems on MANET. The proposed customizable model ensures the user a good quality of service requirements and combines both proactive and reactive statistical analysis. In fact, the reactive analysis, suitable for multimedia applications, aims to detect failures by approximating latency series with a Gumbel distribution. Besides, the proactive analysis, suitable for crisis management applications, forecasts failures occurrence relaying on the Autoregressive Integrated Moving Average Formula. Finally, a hybrid analysis was proposed by dynamically switching from reactive to predictive forms of analysis whenever QoS violations are noticed. The correlation method was also used to identify source failure causes once they were detected or predicted. The efficiency and accuracy of the proposed scheme were validated by performing simulation.

This paper presents a cross-layer self-healing approach for Cloud computing environments, based on the Complex Event Processing method. It analyzes monitored events to detect performance-related problems and performs action to fix them without human intervention. Our proposal makes use of novel analysis rules, derived from a comprehensive study of the relationships between monitored metrics across multiple Cloud layers. The results of our study are used to define and optimize the analysis rules and identify the causes of performance-related problems. The results of several experiments demonstrate the benefits of the proposed approach in terms of speeding up the analysis without affecting the quality of the diagnosis.

Cloud monitoring and analysis are challenging tasks that have recently been addressed by Complex Event Processing (CEP) techniques. CEP systems can process many incoming event streams and execute continuously running queries to analyze the behavior of a Cloud. Based on a Cloud performance monitoring and analysis use case, this paper experimentally evaluates different CEP architectures in terms of precision, recall and other performance indicators. The results of the experimental comparison are used to propose a novel dynamic CEP architecture for Cloud monitoring and analysis. The novel dynamic CEP architecture is designed to dynamically switch between different centralized and distributed CEP architectures depending on the current machine load and network traffic conditions in the observed Cloud environment.

Business-to-business (B2B) e-commerce market is expected to expand rapidly in coming years. In this context, organizations tend to rely more on business process management (BPM) to streamline their operations. The business process field is influenced by a wide range of temporal constraints which rise from legal, regulatory, and managerial rules. One of the most promising standards for business process modeling, namely the Business process Model and notation BPMN poorly addresses the time dimension so far. In this paper, we elaborate an extension to BPMN 2.0 to handle the time dimension. The aim of this BPMN extensions is to support business analysts and modellers in easily including the needed temporal constraints in their processes. We motivate and justify our proposed extensions by means of illustrative case studies. Furthermore, based on the proposed extensions, a verification approach based on the model checking technique is used to diagnose potential temporal violations of the process model. The work presented in this paper sets foundation for later automation of these constraints through process execution engines.

Correction added

We propose in this paper a new approach for conformance testing of WS-BPEL compositions under various load conditions. It is based on Timed Automata as model for testing WS-BPEL implementations, a distributed testing framework that automatically generates and executes parallel tests online, and an algorithm for online test generation and execution. We also implemented a part of our solution in the form of a prototype tool named WSCCT for WS-BPEL compositions conformance testing.

The lack of semantics in WS-SecurityPolicy (WS-SP) hampers the effectiveness of matching security policies. To resolve this problem, we present a semantic approach for specifying and matching web service security policies. The approach consists in the transformation of WS-SP into an OWL-DL ontology and the definition of a set of rules which automatically generate semantic relations that can exist between the provider and requestor security requirements. We show how these relations lead to more correct and accurate matching of security policies. At the end of this paper, we present the implementation of our approach and its validation through a real-world use case.

In the context of Publish/Subscribe systems (Pub/Sub), Peer-to-Peer (P2P) solutions based on Distributed Hash Tables (DHT) offer efficient functionalities such as event routing flexibility, scalability, load balancing and fault tolerance. For event routing, it uses event identifiers computed by event encryption. Likewise, Pub/Sub systems based on ontologies offers well adapted semantic expression capabilities allowing consumers and providers to easily describe services' requests and properties. Thanks to the ontologies, semantic reasoning allows to provide enhanced event discovering. Indeed, DHT-based systems are based on traditional matching algorithms while in ontology-based systems, users can use various literals semantically equivalent but syntactically different expressions in order to describe their requirements. However, both approaches present limitations in terms of: semantic expression restrictions for the first one and scalability issues for the second one. Our solution consists in combining the advantage of both of them, by taking advantage of the semantic capabilities of ontologies at local domain level and the scalable P2P-DHT solutions at inter-domains level. This paper proposes an approach based on a community-wide ontology in order to allow publishers and subscribers to use a common semantic space to characterize production and consumption of resources and services. Based on this ontology, a P2P network based on distributed reasoners (i.e. inference engines) will be able to evaluate if a specific content belongs to an ontology-based community topic. Thus, we use these topics to compute keys for routing events in a DHT.

This paper proposes a verification approach of reconfigurable Distributed Real-time Embedded (DRE) systems. Since dynamic reconfiguration significantly complicates the execution of such a system, it is necessary to ensure the preservation of non-functional properties after applying a such reconfiguration. The proposed approach allows thus verifying non-functional properties at design time. Using our verification approach, the designer can easily verify these properties without deep knowledge of existing verification techniques.

In this paper, we propose an analytical framework for monitoring and analyzing QoS of publish/subscribe systems on MANET. Our framework copes with intermittent connectivity frequently occurring in MANET and provides statistical methods allowing detecting QoS degradations affecting links between brokers at the middleware layer. Besides, our analytical framework identifies QoS degradation source which enables to repair the system. The proposed framework is extensively evaluated with simulation experiments. Simulations results show its efficiency.

In this paper, we propose a failure prediction methodology for quality of service (QoS) degradation prediction for publish/subscribe systems on MANET. Our propose is to use the Auto Regressive Integrated Moving Average (ARIMA) method to predict failure occurrence in the system and to provide optimal QoS provision of applications. Besides, our forecasting algorithm looks for the source behind QoS degradation using the Correlation method. Simulations results are performed to prove the efficiency of the proposed approach. A comparison is done proving that our proposal outperforms the Auto Regression (AR) based prediction approach.

In this paper, we propose a decentralized and adaptive approach for QoS aware publish/subscribe systems deployed on MANET. It provides monitoring and analysis modules acting at the middleware layer to detect QoS degradations between brokers. The paper presents a statistical method allowing for a permanent measurement of QoS parameters and an instantaneous detection of link failures. The statistical method used resorts to the Extreme Values Theory (EVT) and particularly uses the Gaussian and Gumbel distributions to approximate empirical distributions of the measured QoS parameter. Simulation results show the efficiency of the proposed approach.

Abstract This paper has two purposes. First, it shows that existing solutions employing checkpointing and mobility in distributed applications, fix, at design time, the types and the techniques of checkpointing and mobility to be employed at runtime. Second, it provides policies allowing the dynamic selection of checkpointing and mobility techniques according to the execution environment. For that, this paper presents checkpointing and mobility techniques to evaluate them in order to identify their advantages and their shortcomings, and then determine the appropriate execution conditions in which a specific mobility technique becomes beneficial. This investigation will allow in assisting adaptation plans' generation and promoting future research in the area of self‐adaptivity of distributed applications. Copyright © 2011 John Wiley & Sons, Ltd.

The discovery of suitable Web services for a given task is one of the central operations in Service-Oriented Architectures, and research on Web services (WS)s aims at automating this step. For the large amount of available WSs that can be expected in real-world settings, the efficiency of automated discovery becomes important. For this, we propose to exploit previous discovery results to reduce the search space in distributed registry environment. The architecture we adopt consists in structuring registries of WSs into communities. Then, we propose to adapt recommendation techniques to ease the services discovery process. This consists of (1) the selection of communities of registries using semantic matching and (2) the recommendation of registries within these communities using user-characterization based technique. To put our proposed distributed registry architecture in practise and to test the efficiency of recommendation-based discovery, we propose to implement a Peer-to Peer (P2P) registries environment on top of JXTA platform.

We are going to present in this document a generic approach for lingware systems reuse. This approach is based on reverse engineering technique in order to wrap up an existing lingware system with web services. This approach permits the reuse of lingware systems regardless of programming languages, development environments and the structures of linguistic resources. In order to preserve the interoperability between the reused lingware systems, the proposed approach performs the unification and the standardization of exchanged linguistic data using the Natural Language Processing (NLP) standards and consensus. Doing so, we facilitate the integration and the composition of lingware services in order to create a new application that treats several linguistic levels. In order to consolidate the given approach, we developed the LIngware Reuse Environment (LIRE). A practical experiment was carried out using LIRE environment on an automatic application summary of Arabic texts.

Abstract Web Services (WS) can be considered as the most influent enabling technology for the next generation of web applications. WS‐based application providers will face challenging features related to nonfunctional properties in general and to performance and QoS in particular. Moreover, WS‐based developers have to provide solutions to extend such applications with self‐healing (SH) mechanisms as required for autonomic computing to face the complexity of interactions and to improve availability. Such solutions should be applicable when the components implementing SH mechanisms are deployed on both or only one platform on the WS providers and requesters sides depending on the deployment constraints. Associating application‐specific performance requirements and monitoring‐specific constraints will lead to complex configurations where fine tuning is needed to provide SH solutions. To contribute to enhancing the design and the assessment of such solutions for WS technology, we designed and implemented a monitoring and measurement framework, which is part of a larger Self‐Healing Architectures (SHA) developed during the European WS‐DIAMOND project. We implemented the Conference Management System (CMS), a real WS‐based complex application. We achieved a large‐scale experimentation campaign by deploying CMS on top of SHA on the French grid Grid5000. We experienced the problem as if we were a service provider who has to tune reconfiguration strategies. Our results are available on the web in a structured database for external use by the WS community. Copyright © 2010 John Wiley & Sons, Ltd.

Improving information propagation in wide-area communication is an important concern of publish/subscribe systems especially for content-based systems. In secure domain, the dissemination of events in a large scale decreases the importance of the event. The issue of confidentiality appears when the plaintexts of events should be kept private from the infrastructure to counter against eavesdropping. Thus, the infrastructure must remain able to make correct routing decisions efficiently. Our goal is to ensure event delivery to consumers in case of malicious dispatchers without decreasing CBPS (content-based publish/subscribe) performances such as expressivity and scalability. This solution is based on smart cards as trusted devices. It uses certificate to enforce security during authentication stage. It is a generic solution applicable for all CBPS.

Service provisioning is a challenging research area for the design and implementation of autonomic service- oriented software systems. It includes automated QoS management for such systems and their applications. Monitoring and Measurement are two key features of QoS management. They are addressed in this paper as elements of a main step in provisioning of self-healing web services. In a previous work, we defined and implemented a generic architecture applicable for different services within different business activities. Our approach is based on meta-level communications defined as extensions of the SOAP envelope of the exchanged messages, and implemented within handlers provided by existing web service containers. Using the web services technology, we implemented a complete prototype of a service-oriented Conference Management System (CMS). We experienced our monitoring and measurement architecture using the implemented application and assessed successfully the scalability of our approach under the French grid5000. In this paper, experimental results are analyzed and concluding remarks are given.

We present in this paper a novel approach to non-functional safety properties, combining formal methods and Aspect-Oriented Programming (AOP). The approach supports both the formal specification and the enforcement of such properties through runtime monitoring. We apply our approach for security policies and especially Role-Based Access Control (RBAC) policies including application-specific constraints such as separation of duties and delegation. For formal specification, we introduce TemporalZ, a formal language based on Z and temporal logic, which provides domain specific predicates for expressing RBAC policies. For the enforcement, we generate automatically modular enforcement code out of the formal specification using the aspect-oriented language ALPHA.

We define in this paper, a formal conceptual model, which presents the most fundamental concepts for mobile agent systems and unifies their representation and defines the relations between them. On this base, we propose a formal security framework which consists of three basic frameworks. The specification framework proposes a generic definition of security policies for the entities of mobile agent systems. The verification framework checks the intra-policy consistency. The reconfiguration framework describes how to reconfigure security policies and to maintain their consistency. Finally, we examine this theoretical work by defining an operational framework for dynamic enforcement of security policies.

Needless to say, distributed algorithms are usually hard to design mush harder to prove and to use in real distributed systems. In these systems, local computations theory has proved its power to formalize and prove in an intuitive way distributed algorithms. This paper uses this formalism to present solutions to the election problem in several network topologies using mobile agents at the design and the implementation levels. We formalized the proposed solutions in the local computations model using transition systems [11]. This facilitates the proof of the proposed solutions using the mathematical tool-box provided by the local computation theory. Using mobile agents, the proposed solutions get rid of synchronization and do not need continuous use of all machines computational resources. Proposed solutions are also simulated within the VISIDIA [3] platform.

In this paper we propose a UML based approach for describing and checking dynamic software architectures. In fact, the UML profile enables us to model dynamic software architectures by three aspects: the first one defines the architectural style of an application, the second describes a set of reconfiguration operations and the last one specifies the coordination among the reconfiguration operations defined in the above aspect. The built models are automatically checked through a set of syntactical rules. These models are automatically transformed into formal Z specifications in order to prove architectural properties such as consistency and invariants preservation against reconfiguration.

Delegation is a powerful concept in access control systems, which allows users to assign all or part of their permissions to other users. Several types of delegation models for role-based access control have been proposed so far. However, most existing works focus on the specification of delegation policies and there is very little work on the monitoring and enforcement of such policies at runtime. In this paper, we use a security approach combining formal methods and aspect-oriented programming for specifying and enforcing delegation policies. In our approach, delegation models and their characteristics are specified formally using TemporalZ, which is a combination of Z notation and temporal logic. Then, we verify the formal specification to ensure consistency using theorem proving. Finally, we generate automatically a set of aspects in the aspect-oriented language ALPHA from the TemporalZ specifications. These aspects enforce the specified delegation policies at runtime.

Security in mobile agent systems is twofold: protection of mobile agents and protection of agent execution system. Indeed, the proposed solutions for the security of distributed systems arenpsilat sufficient. Moreover, therepsilas no solution which treats the different concerns of security in the mobile agent systems. To achieve this goal, we use formal foundations which provide a rigorous reasoning about security of mobile agent systems. We propose in this paper a formal framework for the security in mobile agent systems which consists of three basic frameworks. The specification framework proposes, explicitly, a generic definition of security policies that may be enhanced by several concepts related to one or more security models. For illustration, we present a security policy enhancement based on the concepts of the RBAC model. Inevitably, we associate to the specification framework a verification framework which checks the consistency of the proposed specifications as well as the consistency intra-policy. In response to the dynamic changes of security requirements in mobile agent systems, we propose a third framework for the reconfiguration of policies.

Maintaining the Quality of Service (QoS) is important for self-healing web service-based distributed interactive applications. It requires the ability to deal with permanently changing constraints both at the communication and the execution levels. Preventing or repairing QoS degradation also requires the capacity of identifying its possible or actual sources and the capacity of reconfiguration decision and enforcement. Dealing with these issues is especially challenging for web services since the self-healing solution has to preserve the dynamic composition property and to be seamless for the service requesters, while being always usable under the different deployment constraints. In this paper, we present a self-healing middleware framework able to provide the self-healing properties for QoS management in web service-based distributed interactive applications. The framework implementation has been achieved in the context of the WS-DIAMOND project. It covers the whole cycle of adaptation management including monitoring and analysis of QoS values, and substitution-based reconfiguration.

Architectural style constitutes a mean to put in practice design approaches based on pattern refinement, adaptation and reuse. Our objective is to support such approaches. In this work, we focus on real-life architectural styles and more particularly on the event-based style. We provide a set of basic styles and we describe a formal approach to specify them and to compose them to generate more complex patterns. In this way, we help the architect to design correct and elaborated architectural styles that can serve as a starting point for a more correct and successful refinement process.

Summary form only given. This paper proposes a formal definition of a conceptual model for mobile agent systems. This works constitute a part of a general research project aiming at defining a generic interaction model that covers the different facets of the cooperative activity among mobile agent based systems. We propose a framework for the specification of interaction mechanisms among mobile agent systems. Doing so, and using the Z notation, we bring closer the concepts describing a mobile agent systems and the cooperative activity while integrating them with the concepts related to the agent migration. The syntax and the semantic of proposed specifications have been checked using the Z-EVES tool.

Summary form only given. This paper presents a formal approach where we adopt a formal specification language which allows us to cover individual agent aspects (knowledge, goals, roles, ...) as well as collective aspects of a multiagent application in terms of coordination protocols, organization structure and planning activities. In this context, we propose a methodology based on stepwise refinements allowing to develop a design specification starting from an abstract requirements specification. We illustrate our approach by developing a multiagent solution for the pursuit problem.

This paper has two purposes. First, it suggests a formal approach for specifying and verifying lingware. This approach is based on a unified notation of the main existing formalisms for describing linguistic knowledge (i.e. Formal Grammars, Unification Grammars, HPSG, etc.) on the one hand, and the integration of data and processing on the other. Accordingly, a lingware specification includes all related aspects in a unified framework. This facilitates the development of a lingware system, since one has to follow a single development process instead of two separate ones. Secondly, it presents an environment for the formal specification of lingware, based on the suggested approach, which is neither restricted to a particular kind of application nor to a particular class of linguistic formalisms. This environment provides interfaces enabling the specification of both linguistic knowledge and functional aspects of a lingware system. Linguistic knowledge is specified with the usual grammatical formalisms, whereas functional aspects are specified with a suitable formal notation. Both descriptions will be integrated into the same framework to obtain a complete requirement specification that can be refined towards an executable program.

Proposes a multi-agent approach (MA) for genetic algorithms (GA) applied to the training of Beta basis function neural networks (BBFNN). This approach, called the multi-agent distributed genetic algorithm (MADGA) has two advantages. First, thanks to the GAs' efficiency, it allows us to design a suitable architecture for the Beta system. Second, it improves the GAs' convergence by reducing their temporal complexity thanks to distributed implementation of the MA system. Agents, which are managed dynamically, interact to provide an optimal solution in order to obtain the best neural network that is considered as a compromise between network performances and structures. For illustration and discussion, we used BBFNN training sets with two space dimensions.

Presents an environment that supports the formal specification and verification of "lingware" (applications related to natural language processing). This environment provides interfaces enabling the specification of both linguistic knowledge and the functional aspects of an application. Linguistic knowledge is specified with the usual grammatical formalisms, while the functional aspects are specified with a suitable formal notation. Both descriptions are integrated, after transformation, into the same framework in order to obtain a complete requirements specification that can be refined towards an executable program.

Agent-oriented techniques represent a promising approach for engineering complex systems where interaction is probably the most important single characteristic. Accordingly, the recent years have witnessed the emergence of different approaches for the study of intelligent agent-based systems. One such architecture views the system as a rational agent having certain mental attitudes of Belief, Desire and Intention (BDI). This paper explores a particular type of rational agent, a Belief-Goal-Role agent. Unlike most previous work, our approach has been to characterize the mental state of the agents that leads them to take part in cooperative action. Hence, beliefs, goals and roles are relevant to our study of cooperation which have lead to the identification of communication concepts (beliefs and goals) and organization concepts (roles). The model is formalized by expressing it as a theory in a first-order, multi-modal, and linear-time logic. We use labeled transition systems to deal with the truth conditions of the formulae of our theory as well as with the behavioral semantics of our agents. We illustrate our work with the well-known prey/predator game.

Provides a unified framework for the specification of communication protocols. This framework enables one to integrate different formalisms within algebraic specifications, permitting the description of the dynamic aspects of distributed systems, such as temporal logic, Petri nets and process algebra. These integrations provide different languages, allowing specifications which may include both the data aspects and the behavioral aspects of protocols. In addition, this paper gives a unified semantics for the different languages based on algebra and event structures. Finally, we illustrate our framework by specifying the Alternating Bit Protocol using the different behavioral formalisms.