Over the last few years, a lot of applications have been developed for Vehicular Ad Hoc NETworks (VANETs) to exchange information between vehicles. However, VANET is basically a Delay Tolerant Network (DTN) characterized by intermittent connectivity, long delays and message losses especially in low density regions [1]. Thus, VANET requires the use of an infrastructure such as Roadside Units (RSUs) that permits to enhance the network connectivity. Nevertheless, due to their deployment cost, RSUs need to be optimally deployed. Hence, the main objective of this work is to provide an optimized RSUs placement for delay-sensitive applications in vehicular networks that improves the end-to-end application delay and reduces the deployment cost. In this paper, we first mathematically model the placement problem as an optimization problem. Then, we propose our novel solution called ODEL. ODEL is a two-steps technique that places RSUs only in useful locations and allows both vehicle-to-vehicle and vehicle-toinfrastructure communication: (i) the first step is comprehensive study that looks for the RSUs candidates locations based on connectivity information, and (ii) the second step uses genetic algorithm and Dijkstra algorithm to reduce the number of RSUs based on the deliverance time requirement and the deployment cost. We show the effectiveness of our solution for different scenarios in terms of applications delay (reduced by up to 84%) and algorithm efficiency (computation performance reduced by up to 79% and deployment cost reduced at least by up to 23%).

In this paper we present a full performance analysis of an energy conserving routing protocol in mobile ad hoc network, named EM-AODV (Energy Multi-path Ad-hoc On-demand Distance Vector routing). EM-AODV is a reactive routing protocol which combines two mechanisms used in the basic AODV protocol. AODV and most of the on demand ad hoc routing protocols use single route reply along reverse path. Rapid change of topology causes that the route reply could not arrive to the source node, i.e. after a source node sends several route request messages, the node obtains a reply message, and this increases in power consumption. To avoid these problems, we propose a mechanism which tries multiple route replies. The second mechanism proposes a new adaptive approach which seeks to incorporate the metric "residual energy " in the process route selection, Indeed the residual energy of mobile nodes were considered when making routing decisions. The results of simulation show that protocol EM-AODV answers better energy conservation

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Scheduling is one of the most important issues in the operating system, such as the tasks must be affected to the appropriate virtual machines, considering different factors at the same time to ensure better use of resources. A lot of research has been carried out to propose more efficient task scheduling algorithms. Round robin is one of the most powerful algorithms in this field but its main challenge is the choice of time quantum. The effectiveness of Round Robin depends on the choice of this parameter. In this paper, we aimed to overcome these challenge by proposing an improved Round Robin scheduling algorithm using a variable time quantum based on an analytic model. Our analytical model takes into consideration different parameters to determine the order of tasks execution. The use of burst time as parameters in our model ensures a more suitable time quantum. This algorithm can be applied in any operating system and therefore in the cloud computing environment. In order to assess the performance and effectiveness of the proposed approach, five different scenarios have been implemented; the comparisons made with existing works have shown that the proposed approach improves the average waiting time and the average turnaround time, which ensures better scheduling of tasks and better use of resources.

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