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Rising energy costs, losses in the present-day electricity grid, risks from nuclear power generation, and global environmental changes are motivating a transformation of the conventional ways of generating electricity. Globally, there is a desire to rely more on renewable energy resources (RERs) for electricity generation. RERs reduce green house gas emissions and may have economic benefits, e.g., through applying demand side management with dynamic pricing so as to shift loads from fossil fuel-based generators to RERs. The electricity grid is presently evolving towards an intelligent grid, the so-called smart grid (SG). One of the major goals of the future SG is to move towards 100% electricity generation from RERs, i.e., towards a 100% renewable grid. However, the disparate, intermittent, and typically widely geographically distributed nature of RERs complicates the integration of RERs into the SG. Moreover, individual RERs have generally lower capacity than conventional fossil-fuel plants, and these RERs are based on a wide spectrum of different technologies. In this article, we give an overview of recent efforts that aim to integrate RERs into the SG. We outline the integration of RERs into the SG along with their supporting communication networks. We also discuss ongoing projects that seek to integrate RERs into the SG around the globe. Finally, we outline future research directions on integrating RERs into the SG. Index Terms-Renewable energy resources (RERs), Distributed energy resources (DERs), Advanced metering infrastructure (AMI), Communication architecture, Smart grid (SG). I. INTRODUCTION A. Motivation: Need for Integration of Renewable Energy Resources with Smart Grid Nowadays, there is a high demand for renewable energy and this demand is increasing due to rising energy cost and global environmental changes. The existing power grid relies heavily on conventional fossil fuel-based electricity generation units. Moving electrical energy from these generation units

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To keep the services and applications of Intelligent Transportation System (ITS) stable and active, Vehicular Ad hoc Networks (VANETs) are considered as an essential building block to maintain and manage its features. A wide deployment of VANETs is possible only after addressing numerous research challenges. One of the most complicated issues consists in designing a routing strategy, taking into consideration several serious constraints, and especially in a network such as VANET. The severity of these issues would be increased significantly when a VANET is deployed over an urban area, where we distinguish the high mobility of nodes and existing obstructions (e.g., buildings, bridges, tunnels, etc.). In this paper, an efficient routing solution based on a flooding technique is conceived to make the data delivery more reliable and to guarantee robust paths. Vehicles can cooperate in ad hoc fashion with existing Unmanned Aerial Vehicles (UAVs). This kind of collaboration provides reliable routing paths and ensures alternative solutions in the case of path failures. Furthermore, a prediction technique is used to expect the expiration time of each discovered path. To limit the overhead over the network, all control packets are characterized by their static size making the originality of this work. Based on the simulation outputs, we discuss the performances of the proposed approach as compared with other dedicated previous schemes in terms of several metrics. The obtained results demonstrate that the hybrid communication between vehicles and UAVs based on the proposed flooding technique is perfectly suited to improve the data delivery process.

International audienceIn collaborative wireless networks with a low infrastructure, the presence of misbehaving nodes can have a negative impact on network performance. In particular, we are interested in dealing with this nasty presence in road safety applications, based on vehicular ad hoc networks (VANETs). In this work, we consider as harmful the presence of malicious nodes, which spread false and forged data; and selfish nodes, which cooperate only for their own benefit. To deal with this, we propose a Distributed Trust Model (DTM2), adapted from the job market signaling model. DTM2 is based on allocating credits to nodes and securely managing these credits. To motivate selfish nodes to cooperate more, our solution establishes the cost of reception to access data, forcing them to earn credits. Moreover, to detect and exclude malicious nodes, DTM2 requires the cost of sending, using signaling values inspired form economics and based on the node's behavior, so that the more a node is malicious, the higher its sending cost, thus limiting their participation in the network. Similarly, rewards are given to nodes whose sent messages are considered as truthful, and that paid a sending cost considered as correct. The latter is a guarantee for the receivers about the truthfulness of the message since, in case of message refusal, the source node is not rewarded despite its payment. We validated DTM2 via a theoretical study using Markov chains; and with a set of simulations, in both urban and highway scenarios. Both theoretical and simulation results show that DTM2 excludes from the network 100% of malicious nodes, without causing any false positive detection. Moreover, our solution guarantees a good ratio of reception even in the presence of selfish nodes

International audienceMobility has the advantage of enlarging WSN applications. However, proposing a mobility support protocol in Wireless Sensor Networks (WSNs) represents a significant challenge. In this paper, we propose a survey on the mobility management protocols in Wireless Sensor Networks based on 6LoWPAN technology. This technology enables to connect IP sensor devices to other IP networks without any need for gateways. We highlight the advantages and drawbacks with performances issues of each studied solution. Then, in order to select a typical classification of mobility management protocols in WSNs, we provide some classification criteria and approaches on which these protocols are based. Finally, we present a comparative study of the existing protocols in terms of the required performances for this network type

International audienceInternet of Things (IoT) is a world wide network of interconnected objects. IoT capable objects will be interconnected through wired and wireless communication technologies. However, cost-effectiveness issues and accessibility to remote users make wireless communication as a feasible solution. A majority of possibilities have been proposed but many of these suffer from vulnerabilities to dynamic environmental conditions, ease of access, bandwidth allocation and utilization, and cost to purchase spectrum. Thus trends are shifting to the adaptability of Cognitive Radio Networks (CRNs) into IoT. Additionally, ubiquitous objects with cognitive capabilities will be able to make intelligent decisions to achieve interference-free and on-demand services. The main goal of this paper is to discuss how CR technology can be helpful for the IoT paradigm. More precisely, in this paper, we highlight CR functionalities, specially spectrum sensing in conjunction with cloud services to serve as self-reconfigurable IoT solutions for a number of applications

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