With the increasing complexity of Cyber-Physical Systems (CPS), it is interesting to decompose a CPS into sub-systems. This provides greater modularity and flexibility so that each system can be developed independently, making it easier to maintain. Also, it can improve its fault tolerance. However, this decomposition of the system can lead to inconsistency. This article proposes an approach for early verification of CPS decomposition using SysML. We address the limitations of SysML as a semi-formal language by introducing syntax and static semantics for its structural diagrams. The aim is to verify structural consistency before defining behavioral aspects. For that, the proposed approach verifies a set of structural consistency rules within a refinement relation to ensure that sub-components offer at least the same services as the abstract block and require the same services. Furthermore, the sub-blocks must satisfy all the requirements that the abstract block is supposed to verify. We used the CyCab as a case study to demonstrate the effectiveness of this approach.

International audience

International audience

In the last few years, Wireless Sensor Networks (WSNs) have known a great boom in a lot of domains. Indeed, the design of these networks must consider several special parameters that characterize them, such as limited energy, processing, power and storage, which makes addressing energy conservation to be a significant challenge. Also, it's essential to mention that achieving total security is a real dial particularly, in distributed networks using open radio frequency and limited physical security, as in the case of WSNs. However, this accuracy inherent to these type of networks makes them vulnerable to various active attacks. On this article, we suggest a defense strategy method, which is based on group protocols in order to counter active attacks in WSNs.

Abstract Autonomic computing got an increasing attention during past years in the context of Cloud computing in order to optimize the Cloud systems performance and increase their cost‐effectiveness. In that direction, a broad range of various self‐adaptability strategies have been proposed to overcome uncertainties related to Cloud systems like workload variations, hardware failures and malicious attacks. A special attention in the literature has been paid to resource allocation for cost and performance optimization, and self‐healing for better faut‐tolerance. However, while a lot of progress has been done on these topics, there is still a lack of a standardized methodology, easily reproducible and allowing validation and comparison of a self‐adaptability strategies. This article proposes a methodology allowing to forecast the autonomic Cloud systems performances. The idea is to compare different self‐adaptability approaches at the design stage, and identify the most adequate and optimized configuration. This methodology is based on a new architecture description language and a stochastic Petri nets‐based modeling and simulation approach. We illustrate our methodology in this article through a running example and a set of experiments.

Wireless Sensor Networks (WSNs) are formed of a set of tiny autonomous entities interconnected by wireless communication links. These entities cooperate to collect and transmit measures taken from their environment. WSNs are characterized by a limitation of their battery, processing power and storage memory, which makes the consumption energy saving a real challenge. However, WSNs are deployed in open radio frequency and lack of physical security. Thus, these networks are vulnerable to several attacks: passive eavesdropping; active attacks; identity theft. In this paper, by using Stochastic Automata Networks (SAN), we propose to model our proposed method named Accordion method in order to detect and apprehend Denial of Service attacks (DoS).

Sensor networks are tiny independent devices which are characterized by limiting battery, processing power and storage memory, that makes saving consumption energy as real challenge power. Morever, there are many techniques used used to conserve energy in Wireless Sensor Networks (WSNs) the clustering technique is one of them. In terms of security, WSNs are more vulnerable to attacks than wired networks. However, radio frequencies used in WSNs are open, making the eavesdropping fairly easy. By considering energy consumption and in order to prevent from Denial of Service (DoS) attacks, present study introducing a preventing DoS attacks approach, which is based on using clustering techniques.

One of the most important advantages of Web services technology is the possibility of combining existing services to create a new composite Web process according to the given requirements. BPEL is a promising language which describes web service composition in form of business processes. However, BPEL is an XML-based language and lack of a sound formal semantic, which hinders the formal analysis and verification of business processes specified in it. In this paper, we propose an approach based RECATNet to model and verify BPEL processes. We present some transformation rules of BPEL business processes into RECATNet. Since RECATNets semantics may be defined in terms of the conditional rewriting logic, Maude tools may be used for model-checking the correctness of BPEL processes. A case study is given to show the efficiency of our approach.

Clustering algorithms play an important role in design and deployment of in wireless sensor networks (WSNs). We apply here a general clustering algorithm namely FFUCA (Fast and Flexible Unsupervised Clustering Algorithm) on WSNs. This application shows that FFUCA provides rapidly a strong organizational structure of nodes. We compare its built structures with those of the common algorithm LEACH to validate our approach. We aim to provide an optimal structure regarding energy consumption but with a low computational complexity.

International audience

WIth the facility of deployment, Wireless Sensor Networks becomes very popular but have special characteristics such as limited battery, limited processing power, and limited storage that makes the energy consumption saving a real challenge. Add to this and due to their distributed deployment, these networks are exposed to denial of service attacks such as jamming and greedy attacks. In all cases these attacks tackle the energy consumption in order to degrade the overall Quality of Service (QoS). In this paper, we propose an energy-preserving solution to detect compromised nodes in WSNs. The proposed method is based on hierarchical clustering technique which elect Controlled nodes (Cnode) that analyze the traffic inside a cluster and to send warnings to the cluster-head (CH) whenever an abnormal behavior is detected. The proposed method is dynamic as the Cnodes are periodically elected among ordinary nodes on each atomic cluster. Such a solution results in a better energy balance while maintaining good detection coverage as it is based on the distance between nodes, the output throughput and delay between packets transmission.

Clustering algorithms have been widely used in many domains so as to partition a set of elements into several subsets, each subset (or “cluster”) grouping elements which share some similarities. These algorithms are particularly useful in wireless sensor networks (WSNs), where they allow data aggregation and energy cuts. By forming clusters and electing cluster heads responsible for forwarding their packets, the small devices that compose WSNs have not to reach directly the base station (BS) of the network. They spare energy and they can lead further in time their measuring task, so as to detect forest fires or water pollution for example. In this paper, we will apply a new and general clustering algorithm, based on classificability and ultrametric properties, to a WSN. Our goal is to get clusters with a low computational complexity, but with an optimal structure regarding energy consumption.