Self-Adaptive Communication for Collaborative Mobile Entities in ERCMS

International audienceAdaptation of communication is required for maintaining the connectivity and the quality of communication in group-wide collaborative activities. This becomes challenging to handle when considering mobile entities in a wireless environment, requiring responsiveness and availability of the communication system. We address these challenges in the context of the ROSACE project where mobile ground and flying robots have to collaborate with each other and with remote human and artificial actors to save and rescue in case of disasters such as forest fires. This paper aims to expose a communication component architecture allowing to manage a cooperative adaptation which is aware of the activity and resource context into pervasive environment. This allows to provide the appropriate adaptation of the activity in response to evolutions of the activity requirements and the changes in relation with the communication resource constraints. In this paper, we present a simulation of a ROSACE use case. The results show how ROSACE entities collaborate to maintain the connectivity and to enhance the quality of communications

Scenarios for an autonomic micro smart grid

Autonomic computing is a bio-inspired vision elaborated to manage the increasing complexity of contemporary heterogeneous, large scale, dynamic computer systems. This paper presents a series of scenarios relative to micro smart grids – district-size “smart” electricity networks. These scenarios involve situations where autonomic management approaches could provide promising solutions. They therefore appear as short stories of a possible autonomic micro smart grid, that illustrate the concepts of autonomic computing as well as the potential behind this vision. At the same time, these scenarios reveal open issues as well as novel perspectives on the future of micro smart grids

Toward Open Science at the European Scale: Geospatial Semantic Array Programming for Integrated Environmental Modelling

[Excerpt] Interfacing science and policy raises challenging issues when large spatial-scale (regional, continental, global) environmental problems need transdisciplinary integration within a context of modelling complexity and multiple sources of uncertainty. This is characteristic of science-based support for environmental policy at European scale, and key aspects have also long been investigated by European Commission transnational research. Approaches (either of computational science or of policy-making) suitable at a given domain-specific scale may not be appropriate for wide-scale transdisciplinary modelling for environment (WSTMe) and corresponding policy-making. In WSTMe, the characteristic heterogeneity of available spatial information and complexity of the required data-transformation modelling (D-TM) appeal for a paradigm shift in how computational science supports such peculiarly extensive integration processes. In particular, emerging wide-scale integration requirements of typical currently available domain-specific modelling strategies may include increased robustness and scalability along with enhanced transparency and reproducibility. This challenging shift toward open data and reproducible research (open science) is also strongly suggested by the potential - sometimes neglected - huge impact of cascading effects of errors within the impressively growing interconnection among domain-specific computational models and frameworks. Concise array-based mathematical formulation and implementation (with array programming tools) have proved helpful in supporting and mitigating the complexity of WSTMe when complemented with generalized modularization and terse array-oriented semantic constraints. This defines the paradigm of Semantic Array Programming (SemAP) where semantic transparency also implies free software use (although black-boxes - e.g. legacy code - might easily be semantically interfaced). A new approach for WSTMe has emerged by formalizing unorganized best practices and experience-driven informal patterns. The approach introduces a lightweight (non-intrusive) integration of SemAP and geospatial tools - called Geospatial Semantic Array Programming (GeoSemAP). GeoSemAP exploits the joint semantics provided by SemAP and geospatial tools to split a complex D-TM into logical blocks which are easier to check by means of mathematical array-based and geospatial constraints. Those constraints take the form of precondition, invariant and postcondition semantic checks. This way, even complex WSTMe may be described as the composition of simpler GeoSemAP blocks. GeoSemAP allows intermediate data and information layers to be more easily and formally semantically described so as to increase fault-tolerance, transparency and reproducibility of WSTMe. This might also help to better communicate part of the policy-relevant knowledge, often diffcult to transfer from technical WSTMe to the science-policy interface. [...

On-demand service architecture for wireless vehicular networks

Vehicular Networks (VN) or VANETS has become a cutting-edge topic in the development of innovative solutions for the automotive industry and of special interest to transit management authorities. Well known examples of the potential benefits of enabling communications in vehicles is fostering a better driving by reducing the risk of accidents on the road. Besides the transmission of safety messages among vehicles in the vicinity, the development of non-safety applications will allow the delivery of information services to potential users willing to request them in on-demand basis. To provide such type of services, major challenges need to be tackled to offer secure and reliable communication in anonymous and sometimes hostile communication environments on the roads. These challenges cover security, billing and accounting issues to provide a secure access to services. The objective of this thesis work is to propose a service architecture for on-demand services in vehicular environments. A key point to keep a robust information service supply, stands in the capacity to provide and manage security mechanisms which comprise authentication and authorization of subscribers following a temporary subscription model. These features, along with privacy mechanisms, will offer to the communicating peers a secure way to mutually access and exchange information even if no previous knowledge of each other is available. Policies of service providers can regulate the supply of information services according to the subscribers' profiles. Providers can also define the implementation of accountability models in the form of metering and billing schemes appropriate for VANETS. This will result in the implementation of incentive and collaborative mechanisms to foster service delivery among vehicles

Towards a Distributed Systems Model based on Multi-Agent Systems for Reproducing Self-properties

271-288 p. :ilustraciones, libro electrónicoEn este capítulo, presentamos un modelo preliminar de un sistema distribuido (algunos los algoritmos y principios están modelados) que ha sido inspirado por sistemas multi-agentes. Los agentes pueden comunicarse de manera local y establecer una cooperación.Capítulo 11In this chapter, we introduce a preliminary model of a distributed system (some algorithms and principles are modelled) which has been inspired by multi-agent systems. Agents can communicate in a local fashion and establish a cooperation process in order to compute some desired functions as a traditional distributed system, producing an output that is transparent to an end user. Each agent can sense new information, and acts following certain information in a decentralized way. As a result, the output of the implemented functions achieves the same result as a traditional distributed system by using local behaviours. Finally, we show that it is possible to define crashes in the proposed model in a local, natural and easy way. The purpose of doing this is to use this simulated model to introduce behaviours to agents that allow the system to recover from failures by itself, in turn, achieving self-* properties.ISBN: 978958580477

6G wireless systems : a vision, architectural elements, and future directions

Internet of everything (IoE)-based smart services are expected to gain immense popularity in the future, which raises the need for next-generation wireless networks. Although fifth-generation (5G) networks can support various IoE services, they might not be able to completely fulfill the requirements of novel applications. Sixth-generation (6G) wireless systems are envisioned to overcome 5G network limitations. In this article, we explore recent advances made toward enabling 6G systems. We devise a taxonomy based on key enabling technologies, use cases, emerging machine learning schemes, communication technologies, networking technologies, and computing technologies. Furthermore, we identify and discuss open research challenges, such as artificial-intelligence-based adaptive transceivers, intelligent wireless energy harvesting, decentralized and secure business models, intelligent cell-less architecture, and distributed security models. We propose practical guidelines including deep Q-learning and federated learning-based transceivers, blockchain-based secure business models, homomorphic encryption, and distributed-ledger-based authentication schemes to cope with these challenges. Finally, we outline and recommend several future directions. © 2013 IEEE

Self-management of machine-to-machine communications: a multi-models approach

International audienceMachine-to-Machine (M2M) paradigm apply to systems composed by numerous devices sharing information and making cooperative decisions with little or no human intervention. The M2M standard defined by the European Telecommunications Standards Institute (ETSI) is the only one providing an end-to-end view of the global M2M architecture. Noticeably, it furnishes a standardised framework for inter-operable M2M services that satisfies most of M2M modelling requirements. However, and even though M2M systems usually operate in highly evolving contexts, this standard does not address the issue of system adaptations. It is furthermore unsuitable for building self-managed systems. This paper introduces a multi-model approach for modelling manageable M2M systems. Said approach consists in a formal graph-based model on top of the ETSI M2M standard, alongside bi-directional updates that ensure layer coherency. Its fitness for enforcing self-management properties is demonstrated by designing high-level reconfiguration rules. Finally, its applicability is illustrated and evaluated using a smart-metering application

Efficient radio resource allocation scheme for 5G networks with device-to-device communication

A vital technology in the next-generation cellular network is device-to-device (D2D) communication. Cellular user enabled with D2D communication provides high spectral efficiency and further increases the coverage area of the cell, especially for the end-cell users and blind spot areas. However, the implementation of D2D communication increases interference among the cellular and D2D users. In this paper, we proposed a radio resource allocation (RRA) algorithm to manage the interference using fractional frequency reuse (FFR) scheme and Hungarian algorithm. The proposed algorithm is divided into three parts. First, the FFR scheme allocates different frequency bands among the cell (inner and outer region) for both the cellular and the D2D users to reduce the interference. Second, the Hungarian weighted bipartite matching algorithm is used to allocate the resources to D2D users with the minimum total system interference, while maintaining the total system sum rate. The cellular users share the resources with more than one D2D pair. Lastly, the local search technique of swapping is used for further allocation to minimize the interference. We implemented two types of assignments, fair multiple assignment, and restricted multiple assignment. We compared our results with existing algorithms which verified that our proposed algorithm provides outstanding results in aspects like interference reduction and system sum rate. For restricted multiple assignment, 60-70% of the D2D users are allocated in average cases