Formal composition of partial system behaviors

Modeling the behavior of a system under development has shown to be a very effective way to ensure that it will have better chance to be constructed correctly. With the growing complexity of systems, building this model has become a major task that requires a significant time investment and a high level of expertise. Incremental approaches that help construct a system model from partial behavioral descriptions have been widely adopted. The challenge in such approaches lies in finding both the adequate behavioral formalism that fits the needs of the analyst as well as the formal composition mechanism that facilitates the generation of the expected behavioral model and produces a verifiable model. Within this framework, use case approaches have been accepted in the industry because they make the process of requirements engineering simpler. In the first stage of their development, use cases have been associated with requirements gathering and domain analysis since they allow the partial description of system behavior in a more intuitive manner. During the last decade, their use has been expanded to include all phases of the lifecycle. Consequently, the model representing use cases has an increasing importance. Although use case approaches present benefits in terms of improving the communication among stakeholders, permitting incremental construction of the system specification, and improving the requirements traceability, such approaches have some drawbacks in relation to their lack of formality. In fact, it is difficult to validate and verify use cases for completeness and consistency. This thesis addresses the problem of modeling use cases and their composition based on formal models in order to generate a system specification that can be used for validation and verification. We tackled the problem of both composing overlapping use cases that share partial similar behaviors, and composing non overlapping use cases according to additional criteria. We experimented with different formal models of use cases having different levels of expressivenesses to develop an approach for use case composition. All use case models we tackled are state-based models. We first started by proposing an approach for composing use cases expressed as extended finite state machines with variables that characterize their states. The use case model allows the definition of explicit loops. The state characterization is used as the criterion of composition. It allows the detection of common states between use cases that have to be merged in the overall system model. When composing, we proposed an approach that protects the user-defined loops from unexpected scenarios that may threaten their behavior. As a second step, we proposed to compose use cases based on the interactions they are making between each other. In this context, an interaction is defined as an invocation of a use case by another. Unlike the first approach, use cases are no more considered overlapping. When composing, we developed an approach that avoids unexpected scenarios. Finally, we proposed a general approach for composing system behaviors where partial system behaviors are defined as state based model using imperative expressions. Each use case describes a certain system concern. The imperative expression represents the composition criterion. In fact, it defines the semantics of the composition to perform. Our approach is fully automated and provides the advantage of generating a state based model that meets the intended behavior without allowing unexpected scenarios. The approach is formalized in the case of finite state machines and extended finite state machines

An Elastic Hybrid Sensing Platform: Architecture and Research Challenges

© 2016 Published by Elsevier B.V. The dynamic provisioning of hybrid sensing services that integrates both WSN and MPS is a promising, yet challenging concept. It does not only widen the spatial sensing coverage, but it also enables different types of sensing nodes to collaboratively perform sensing tasks and complement each other. Furthermore, it allows for the provisioning of a new category of services that was not possible to implement in pure WSN or MPS networks. Offering a hybrid sensing platform as a service results in several benefits including, but no limited to, efficient sharing and dynamic management of sensing nodes, diversification and reuse of sensing services, as well as combination of many sensing paradigms to enable data to be collected from different sources. However, many challenges need to be resolved before such architecture can be feasible. Currently, the deployment of sensing applications and services is a costly and complex process, which also lacks automation. This paper motivates the need for hybrid sensing, sketches an early architecture, and identifies the research issues with few hints on how to solve them. We argue that a sensing platform that reuses the virtualization and cloud computing concepts will help in addressing many of these challenges, and overcome the limitations of today\u27s deployment practices

Hybrid verification integrating HOL theorem proving with MDG model checking

In this paper, we describe a hybrid tool for hardware formal verification that links the HOL (higher-order logic) theorem prover and the MDG (multiway decision graphs) model checker. Our tool supports abstract datatypes and uninterpreted function symbols available in MDG, allowing the verification of high-level specifications. The hybrid tool, HOL-MDG, is based on an embedding in HOL of the grammar of the hardware modeling language, MDG-HDL, as well as an embedding of the first-order temporal logic L"m"d"g used to express properties for the MDG model checker. Verification with the hybrid tool is faster and more tractable than using either tools separately. We hence obtain the advantages of both verification paradigms

Monetizing Personal Data: A Two-Sided Market Approach

© 2016 The Authors. Mobile phone-based sensing is a new paradigm that aims at using smartpohnes to answer sensing requests and collect useful data. Nowadays, a wide variety of domains ranging from health-care applications to pollution monitoring are benefiting from such collected data. However, despite its increasing popularity and the huge amount of data provided by users, there is no platform where mobile phone owners can effectively sell their data. In this paper, we propose the idea of a data monetization platform using two-sided market theory. In this platform, the data is viewed as an economic good and the data sharing activity is considered as an economic transaction. The proposed platform considers the case of abundant data. An experimental analysis is conducted to compare our approach against the peer-to-peer model using a real case study from the health care domain. We show that our proposed platform has the potential to generate higher profit for both data providers and data consumers

Remote Robotic Surgery: Joint Placement and Scheduling of VNF-FGs

Remote robotic surgery is one of the most interesting Tactile Internet (TI) applications. It has a huge potential to deliver healthcare services to remote locations. Moreover, it provides better precision and accuracy to diagnose and operate on patients. Remote robotic surgery requires ultra-low latency and ultra-high reliability. The aforementioned stringent requirements do not apply for all the multimodal data traffic (i.e., audio, video, and haptic) triggered during a surgery session. Hence, customizing resource allocation policies according to the different quality-of-service (QoS) requirements is crucial in order to achieve a cost-effective deployment of such system. In this paper, we focus on resource allocation in a softwarized 5G-enabled TI remote robotic surgery system through the use of Network Functions Virtualization (NFV). Specifically, this work is devoted to the joint placement and scheduling of application components in an NFV-based remote robotic surgery system, while considering haptic and video data. The problem is formulated as an integer linear program (ILP). Due to its complexity, we propose a greedy algorithm to solve the developed ILP in a computationally efficient manner. The simulation results show that our proposed algorithm is close to optimal and outperforms the benchmark solutions in terms of cost and admission rate. Furthermore, our results demonstrate that splitting application traffic to multiple VNF-forwarding graphs (VNF-FGs) with different QoS requirements achieves a significant gain in terms of cost and admission rate compared to modeling the whole application traffic with one VNF-FG having the most stringent requirements

The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions

The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual reality (VR) technology. Many disciplines can benefit from the advancement of the Metaverse when accurately developed, including the fields of technology, gaming, education, art, and culture. Nevertheless, developing the Metaverse environment to its full potential is an ambiguous task that needs proper guidance and directions. Existing surveys on the Metaverse focus only on a specific aspect and discipline of the Metaverse and lack a holistic view of the entire process. To this end, a more holistic, multi-disciplinary, in-depth, and academic and industry-oriented review is required to provide a thorough study of the Metaverse development pipeline. To address these issues, we present in this survey a novel multi-layered pipeline ecosystem composed of (1) the Metaverse computing, networking, communications and hardware infrastructure, (2) environment digitization, and (3) user interactions. For every layer, we discuss the components that detail the steps of its development. Also, for each of these components, we examine the impact of a set of enabling technologies and empowering domains (e.g., Artificial Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on its advancement. In addition, we explain the importance of these technologies to support decentralization, interoperability, user experiences, interactions, and monetization. Our presented study highlights the existing challenges for each component, followed by research directions and potential solutions. To the best of our knowledge, this survey is the most comprehensive and allows users, scholars, and entrepreneurs to get an in-depth understanding of the Metaverse ecosystem to find their opportunities and potentials for contribution

On the Embedding of the MDG Specification Languages in HOL

In this paper, we propose an embedding of the MDG input languages in HOL. The MDG (Multiway Decision Graph) system is a tool for equivalence and model checking. It is based on multiway decision graphs that extend Reduced-Ordered Binary Decision Diagrams with abstract sorts and uninterpreted functions, prime feature of the MDG. The HOL system is a higher-order logic theorem prover. It has an open user-extensible architecture, giving the possibility of adding expressiveness power to the theorem prover by embedding new theories. We have embedded in HOL the grammar of the MDG hardware description language, MDG-HDL, and the first-order temporal logic, LMDO, used to specify properties for the MDG model checker. A Hybrid tool for verification, linking HOL with the MDG model checker, is proposed as an application of the developed embeddings

A Hybrid Tool for Linking HOL Theorem Proving with MDG Model Checking

MDG Model Checking and submitted in partial fulfilment of the requirements for the degree of Master of Applied Science complies with the regulations of this University and meets the accepted standards with respect to originality and quality. Signed by the final examining committee: Dr. M. Reza Soleymani Dr. Otmane Ait Mohamed Dr. Patrice Chalin Dr. Sofi`ene Tahar Approved by Chair of the ECE Departmen