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Abstract. Prolonging network lifetime has become a real challenge in Mobile Wireless Sensor Networks (MWSNs) as sensors have limited energy. In this paper, we propose a Cluster-based Energy-efficient Scheme (CES) for electing a cluster-head to evenly distribute energy consumption in the overall network and therefore obtain a longer network lifetime. In CES, each sensor calculates its weight based on k-density, residual energy and mobility and then broadcasts it to its 2-hop neighborhood. The sensor node with the greatest weight in its 2-hop neighborhood will become the cluster-head and its neighboring sensors will then join it. We performed simulations to illustrate the effects of sensor mobility on LEACH and LEACH-C's performance. Unfortunately, our findings showed that sensor mobility had a significant impact on both protocols' performance, but CES provided good results in terms of the amount of data packets received at the sink when compared with LEACH and LEACH-C.

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Summary The digitization of objects has given birth to the concept of the Internet of Things (IoT) which is revolutionizing traditional objects by replacing them with intelligent objects such as smart vehicles, smartphones, smart home…etc. In this context, and with the emergence of vehicle networks, is born the need to increase the vehicular resources in order to benefit from several applications facilitating driving and ensuring the drivers safety, even going to think of the automated driving. The use of cloud computing has become the key solution to the lack of resources required to run compute‐intensive applications and the lack of storage space to back up all data related to roads and applications. In addition, we are witnessing the birth of the fog computing paradigm, which brings the functionalities of cloud computing at the edge of the network, thereby solving the latency problem for some time‐sensitive applications and also saving the bandwidth of the network because vehicle requests will not need to cross the entire network to be processed at the cloud level. In this paper, we discuss the different principles of cloud/fog computing and compare the two paradigms. We present a classification of data dissemination schemes in vehicular ad hoc networks (VANETs), vehicular cloud, and vehicular fog computing with their different architectures proposed. We finally present several cloud/fog computing applications.