Internet of Things (IoT) a paradigm that brought several new communication technologies, allowing more ubiquity and real-time applications. This innovation sped up the implementation of intelligent transportation systems in smart cities. However, the use of these technologies needs the original routing protocols. The latters must meet real-time application requirements, such as reduced transmission delay, minimal packet loss, and less power consumption. This paper comes up with a novel solution LoRaWAN-based Geographic Routing Protocol (LGRP) using a multi-criteria metric taking into account delay, packet loss, distance, and relative velocity. The hybridization of LoRaWAN with 802.11p technologies is introduced to overcome challenges of urban scenarios in our protocol achievement. We carry out the routing protocol using the Network Simulator 3 (NS-3). Then, we assess its effectiveness in comparison with the greedy perimeter stateless routing (GPSR), the Ad hoc On-Demand Distance Vector (AODV), the Cross-Layer Weighted Position-based Routing (CLWPR), and the blended OpenFlow-Optimized Link State Routing (Centralized). The simulation results show that the proposed routing protocol outmatches the comparative ones in packet delivery and end-to-end delay.

Heterogeneous Vehicular Network (HetVNET) is a highly dynamic type of network that changes very quickly. Regarding this feature of HetVNETs and the emerging notion of network slicing in 5G technology, we propose a hybrid intelligent Software-Defined Network (SDN) and Network Functions Virtualization (NFV) based architecture. In this paper, we apply Conditional Generative Adversarial Network (CGAN) to augment the information of successful network scenarios that are related to network congestion and dynamicity. The results show that the proposed CGAN can be trained in order to generate valuable data. The generated data are similar to the real data and they can be used in blueprints of HetVNET slices.

Network congestion-related studies consist mainly of two parts: congestion detection and congestion control. Several researchers have proposed different mechanisms to control congestion and used channel loads or other factors to detect congestion. However, the number of studies concerning congestion detection and going beyond into congestion prediction is low. On this basis, we decide to propose a method for congestion prediction using supervised machine learning. In this paper, we propose a Naive Bayesian network congestion warning classification method for Heterogeneous Vehicular Networks (HetVNETs) using simulated data that can be locally applied in a fog device in a HetVNET. In addition, we propose a centralized and dynamic cloud-fog-based architecture for HetVNET. The Naive Bayesian network congestion warning classification method can be applied in this architecture. Support Vector Machine (SVM), K Nearest Neighbor (KNN) and Random Forest classifiers, which are popular methods in classification problems, are considered to generate congestion warning prediction models. Numerical results show that the proposed Naive Bayesian classifier is more reliable and stable and can accurately predict the data flow warning state in HetVNET. Moreover, based on the obtained simulation results, applying the proposed congestion classification approach can improve the network’s performance in terms of the packet loss ratio, average delay and average throughput, especially in the dense vehicular environments of HetVNET.

Finite capacity of network resources and enormous data generated by vehicles using safety and comfort applications, have made network congestion a challenge to manage in Heterogeneous Vehicular Network (HetVNET). In this paper, we propose a reliable network congestion model based on a Multiple Linear Regression (MLR), which is a supervised machine learning algorithm to predict network congestion in HetVNET. We have evaluated the performance of our proposed network congestion prediction model using a Cross-Validation test approach. Numerical results show that the proposed linear congestion prediction model is reliable, which can explain and support variability of the response as well. Moreover, we have weighted effectiveness of each considered HetVNET parameters, in association with congestion situation in HetVNET.

The smart city is an ecosystem that interconnects various devices like sensors, actuators, mobiles, and vehicles. The intelligent and connected transportation system (ICTS) is an essential part of this ecosystem that provides new real-time applications. The emerging applications are based on Internet-of-Things (IoT) technologies, which bring out new challenges, such as heterogeneity and scalability, and they require innovative communication solutions. The existing routing protocols cannot achieve these requirements due to the surrounding knowledge supported by individual nodes and their neighbors, displaying partial visibility of the network. However, the issue grew ever more arduous to conceive routing protocols to satisfy the ever-changing network requirements due to its dynamic topology and its heterogeneity. Software-Defined Networking (SDN) offers the latest view of the entire network and the control of the network based on the application’s specifications. Nonetheless, one of the main problems that arise when using SDN is minimizing the transmission delay between ubiquitous nodes. In order to meet this constraint, a well-attended and realistic alternative is to adopt the Machine Learning (ML) algorithms as prediction solutions. In this paper, we propose a new routing protocol based on SDN and Naive Bayes solution to improve the delay. Simulation results show that our routing scheme outperforms the comparative ones in terms of end-to-end delay and packet delivery ratio.

The classical resource reservation protocol (RSVP) is a flow-based signaling protocol used for reserving resources in the network for a given session. RSVP maintains state information for each reservation at every router along the path. Even though this protocol is very popular, he has some weaknesses. Indeed, RSVP does not include a bidirectional reservation process and it requires refresh messages to maintain the soft states in the routers for each session. In this paper, we propose a senderoriented version of RSVP that can reserve the resources in both directions with only one message, thus reducing the delay for establishing the reservations. We also suggest a refreshment mechanism without any refresh message which could be applied to any soft states protocol. Simulation results show that the proposed protocol is approximately twice faster than RSVPv2 for establishing bidirectional reservations with almost no control overhead during the session.

Many interconnected smart devices manage and control different areas in cities using information and communication technologies. Such networked devices, exchanging information through real-time applications, are characterized by their high mobility, which require developing optimized routing metrics. In the literature, several solutions are proposed to solve such an information routing problem. Most of them use many network parameters in routing metrics calculation, such as the node position, the node speed, the link quality and the network density. However, the existing routing solutions may require combining simultaneously the end to end delay, the packet loss and the distance. This adds more efficiency in data transmission since the realtime applications require no packet loss and less delay. In this paper, we consider these parameters to propose a mathematical modeling of new multicriteria routing metric. Subsequently, we solve it with three different methods: exact method, A star method and A star with obstacles method. The simulation results show the efficiency of the A star method in terms of response time and iteration number.

The transport protocols for Wireless Body Area Networks (WBANs) must provide end-to-end reliability and Quality of Service (QoS) for the whole network. This task can be accomplished through the reduction of the PLR (Packet Loss Ratio) and the latency while keeping fairness and low energy consumption between the nodes. The IEEE 802.15.6 Standard supports QoS, but it does not suggest any transport protocol for WBANs. This paper proposes a transport protocol for WBANs based on an energy-efficient and emergency-aware MAC (Medium Access Control) protocol and the IEEE 802.15.6 Standard. This new transport protocol is a cross-layer design that uses loss-recovery and fairness to provide reliability to the network. The protocol detects out-of-sequence packets and requests retransmission of the lost packets. It outperforms the MAC protocol and the IEEE 802.15.6 Standard in the percentage of the packet loss with and without emergency traffic, while keeping a similar energy consumption.

Congestion control is one of the most important factors when a Wireless Body Area Network (WBAN) is designed, due to its direct impact in the Quality of Service (QoS) and the energy efficiency of the network. The congestion in a WBAN can produce packet loss and high energy consumption. The IEEE 802.15.6 Standard supports QoS, but it does not suggest any explicit congestion control scheme. This paper proposes a new rate control scheme for mitigating congestion in WBANs based on an energy-efficient and emergency-aware MAC (Medium Access Control) protocol and the IEEE 802.15.6 Standard. The scheme is context-aware and responses to emergency events in any node controlling the normal traffic rate. The proposed solution improves the performance of both the MAC protocol and the IEEE 802.15.6 Standard.

The Medium Access Control (MAC) protocol for a Wireless Body Area Network (WBAN) should allow body sensors to get quick access to the channel and send data to the hub, especially in emergency situations while reducing power consumption. IEEE 802.15.6 Standard proposes a MAC protocol that could be applicable to all kinds of WBAN. The WBAN MAC protocol proposed in this paper is based on the existing MAC protocol described on IEEE 802.15.6 Standard, but taking into account characteristics for some WBAN where low emergency traffic and a very high normal traffic can be expected. The proposed protocol is energy-efficient and emergency-aware and it changes transmission schedules in order to provide quality of service for emergency traffic.

In this paper, we propose a hybrid iterated local search (ILS) heuristic, named GPP4G-ILS, to solve the global planning problem of survivable wireless networks. The planning problem of wireless networks is to determine a set of sites among potential sites to install the various network devices in order to cover a given geographical area. It should also make the connections between the devices in accordance with well-defined constraints. The global planning consists in solving this problem without dividing it into several subproblems. The objective is to minimize the cost of the network while maximizing its survivability. The GPP4G-ILS algorithm is a new form of hybridization between the ILS algorithm and the integer linear programing (ILP) method. We propose a configuration that allows to reuse a previously developed ILP algorithm by integrating it in the ILS algorithm. This allows to benefit from the advantages of both methods. The ILS algorithm is used to effectively explore the search space, while the ILP algorithm is used to intensify the solutions obtained. The performance of the algorithm was evaluated using an exact method that generates optimal solutions for small instances. For larger instances, lower bounds have been calculated using a relaxation of the problem. The results show that the proposed algorithm is able to reach solutions that are, on average, within 0.06% of the optimal solutions and 2.43% from the lower bounds for the instances that cannot be solved optimally, within a reduced computation time.

The main problem of firewall configuration is to ensure the filtering rules consistency w.r.t. a global security policy. However, the overall firewalls configuration on a network, which requires a human intervention, is often an error-prone process. Therefore, automated solutions are needed in order to detect firewall configuration inconsistencies and to check the inter-firewalls consistency. In this paper, we propose a formal modeling and verification framework based on model checking. It allows to verify automatically the end-to-end security behavior of a set of firewalls w.r.t. a global security policy. To deal with state explosion problem, two abstractions are proposed and evaluated in term of space and time complexity, according to the network size and connectivity rate.

In this paper, we propose a global model for WiMAX networks planning. This model represents the network planning problem and helps to solve it entirely without dividing it into several subproblems. The objective of the model is to minimize the cost of the network while maximizing its survivability. The model has been compared to a sequential model with the same constraints, which consists in solving the subproblems sequentially, and to a global model without reliability constraints. The results show that the proposed model performs on an average 25% better than the other models.

The 3G universal mobile telecommunications system (UMTS) planning problem is combinatorially explosive and difficult to solve optimally, though solution methods exist for its three main subproblems (cell, access network, and core network planning). We previously formulated the entire problem as a single integrated mixed-integer linear program (MIP) and showed that only small instances of this global planning problem can be solved to optimality by a commercial MIP solver within a reasonable amount of time (St-Hilaire, Chamberland, & Pierre, 2006). Heuristic methods are needed for larger instances. This paper provides the first complete formulation for the heuristic sequential method (St-Hilaire, Chamberland, & Pierre, 2005) that re-partitions the global formulation into the three conventional subproblems and solves them in sequence using a MIP solver. This greatly improves the solution time, but at the expense of solution quality. We also develop a new hybrid heuristic that uses the results of the sequential method to generate constraints that provide tighter bounds for the global planning problem with the goal of reaching the provable optimum solution much more quickly. We empirically evaluate the speed and solution accuracy of four solution methods: (i) the direct MIP solution of the global planning problem, (ii) a local search heuristic applied to the global planning problem, (iii) the sequential method and (iv) the new hybrid method. The results show that the sequential method provides very good results in a fraction of the time needed for the direct MIP solution of the global problem, and that optimum results can be provided by the hybrid heuristic in greatly reduced time.

Considering the introduction of new internet protocol (IP) services, such as the high definition television (HDTV) over IP (IPTV) service, new network architectures and technologies should be introduced for the access network to improve the access rate. Actually, the best solution is to use the fiber-to-the-home (FTTH) architecture. However, this solution is still costly and cannot be widely deployed today. An interesting tradeoff is the fiber-to-the-node (FTTN) architecture, which reduces the copper portion of the access network. In this paper, we propose to tackle the FTTN network planning problem with the objective of minimizing the cost of the access network. An integer mathematical programming model is proposed for this problem. Next, a heuristic algorithm based on the tabu search principle is proposed to find “good” feasible solutions within a reasonable amount of computational time. Finally, numerical results are presented and analyzed.

In this paper, we tackle the wireless sensor network (WSN) planning problem considering coverage, target localization and network connectivity constraints. First, a combinatorial optimization model is proposed for this problem and next, a starting greedy heuristic is proposed followed by a tabu search metaheuristic to find “good” feasible solutions rapidly. The solutions are compared to the optimal solutions found using CPLEX. The test results show the proposed approach finds good quality solutions.

In this paper, we propose a global model for WiMAX networks planning. This model consists in solving, in one shot, the network planning problem without dividing it in several subproblems. The objective of the model is to minimize the cost of the network while maximizing its survivability. The results show that the proposed model performs up to 40% better than the sequential one, which consists on solving the subproblems sequentially.

In this paper, we address the global problem of designing reliable wavelength division multiplexing (WDM) networks including the traffic grooming. This global problem consists in finding the number of optical fibers between each pair of optical nodes, finding the configuration of each node with respect to transponders, finding the virtual topology (i.e., the set of lightpaths), routing the lightpaths, grooming the traffic (i.e, grouping the connections and routing them over the lightpaths) and, finally, assigning wavelengths to the lightpaths. Instead of partitioning the problem into subproblems and solving them successively, we propose a mathematical programming model that addresses it as a whole. This approach has the advantage of providing better results since, in general, optimal solutions to all subproblems do not provide an optimal solution to the global problem. Numerical results show the relevance of designing the physical layer and finding the traffic grooming simultaneously.

In this paper, we propose to tackle the design problem of two-level metropolitan Internet protocol (IP) networks with modular routers including the design of the points of presence. We first propose a model that deals with selecting the number of routers and their types to install in each point of presence, selecting the interface card types to install in each router, finding the access and the backbone networks, interconnecting the routers in each point of presence, selecting the link types and finally, routing the traffic. The objective is to find the minimum cost network. Moreover, we consider that a minimum information rate (in bps) is guaranteed between each pair of clients for the normal state of the network and for the failure scenarios of interest to the network planner. A tabu search metaheuristic algorithm is proposed to find near-optimal approximate solutions of the model. Finally, we present numerical results to assess the performance of the proposed algorithm.