Public safety and first-responder networks require technologies that outperform current emergency networks. 5G and Wi-Fi architectures seem to be promising solutions for those environments. However, seamless integration of these wireless networks needs to be well investigated to benefit from the advan-tages of both networks and to fulfill the firefighter requirements. For this purpose, we propose a gateway selection algorithm for firefighter interventions. Proximal Policy Optimization, a well-known reinforcement learning strategy, is used to define and train the agent. Simulation results demonstrate that the proposed framework outperforms the Host Network Association scheme defined in the Optimized Link State Routing Protocol in terms of network throughput and packet drop rate.

Virtual Machine (VM) migration presents several advantages for both cloud operators and cloud users. The benefits of VM migration are amplified in the context of Joint-clouds, in which multiple clouds owned by distinct operators exchange VMs. However, inter-cloud VM migrations might require the usage of the Internet, which creates the possibility of external threats and therefore, a risk to the VMs' integrity. Thus, we propose a novel approach to secure VM migration for Joint-clouds. We consider both local migration and inter-cloud migration. Our solution is based on a multi-blockchain system, in which each cloud provider participates in the maintenance of a consortium blockchain to store relevant information about the migrations. In addition, each cloud operator might choose to keep a local blockchain to secure its local VM migrations. Therefore, inter-blockchain communication plays an important role in our work.

The paradigm of Internet of Vehicles (IoV) as an extension to the Internet of Things (IoT) concept can assist the development of smart cities. IoV relies on vehicular communications to allow vehicles to communicate in real time with other vehicles, roadside infrastructure, and pedestrians. The main goal is to enable not only road safety services but also time-constrained IoT applications. In this context, Cellular Vehicle-to-Everything (C-V2X) communication is a prominent technology to accomplish IoV goals. Currently, there are two versions of C-V2X available, long-term evolution-V2X (LTE-V2X) and new radio-V2X (NR-V2X), and in both, mechanisms of resource allocation (RA) play an important role in their performance. Therefore, our goal in this article is to present an extensive state of the art of RA on C-V2X technology. Thus, we first present the main technical aspect related to LTE-V2X and NR-V2X technologies. Afterward, we present and categorize the related works for both technologies, pointing out their main differences, advantages, and drawbacks. Finally, we present the challenges, open issues, and future technical trends related to RA in C-V2X.

The surging traffic volumes and dynamic user mobility patterns pose great challenges for cellular network operators to reduce operational costs and ensure service quality. Cloud-radio access network (C-RAN) aims to address these issues by handling traffic and mobility in a centralized manner, separating baseband units (BBUs) from base stations (RRHs) and sharing BBUs in a pool. The key problem in C-RAN optimization is to dynamically allocate BBUs and map them to RRHs under cost and quality constraints, since real-world traffic and mobility are difficult to predict, and there are enormous numbers of candidate RRH-BBU mapping schemes. In this work, we propose a data-driven framework for C-RAN optimization. First, we propose a deep-learning-based Multivariate long short term memory (MuLSTM) model to capture the spatiotemporal patterns of traffic and mobility for accurate prediction. Second, we formulate RRH-BBU mapping with cost and quality objectives as a set partitioning problem, and propose a resource-constrained label-propagation (RCLP) algorithm to solve it. We show that the greedy RCLP algorithm is monotone suboptimal with worst-case approximation guarantee to optimal. Evaluations with real-world datasets from Ivory Coast and Senegal show that our framework achieves a BBU utilization above 85.2 percent, with over 82.3 percent of mobility events handled with high quality, outperforming the traditional and the state-of-the-art baselines.

Device-to-Device (D2D) communication is one of the revolutionary technologies in 5G cellular networks that enables mobile devices to communicate directly without the Base Station (BS) involvement. One of its major objectives is to provide seamless mobility satisfying QoS requirements that are not supported in LTE-A cellular network. Hence, 5G networks have to go through architecture processes rather than a series of technology updates. For that, we propose a new Software Defined Networking (SDN) based architecture able to manage D2D communications. In this paper, we introduce a new D2D handover management scheme to solve the D2D mobility issue. The proposed mechanism can enhance the handover performances, compared to the handover management in conventional LTE networks as well as increase the D2D service continuity.

Topology discovery is one of the most critical tasks of Software-Defined Network (SDN) controllers. Current SDN controllers use the OpenFlow Discovery Protocol (OFDP) as the de-facto protocol for discovering the underlying network topology. In a previous work, we have shown the functional, performance and security limitations of OFDP. In this paper, we introduce and detail a novel protocol called secure and efficient OpenFlow Discovery Protocol sOTDP. sOFTDP requires minimal changes to OpenFlow switch design, eliminates major vulnerabilities in the topology discovery process and improves its performance. We have implemented sOFTDP as a topology discovery module in Floodlight for evaluation. The results show that our implementation is more secure than OFDP and previous security workarounds. Also, sOFTDP reduces the topology discovery time several orders of magnitude compared to the original OFDP and existing OFDP improvements.

NB-IoT has been defined in 3GPP release 13. It modifies LTE radio access procedures and protocols to fulfill energy consumption, low data rate and latency requirements associated with IoT applications. One of the major issues of NB-IoT deployment is the design of performance evaluation models that make it possible to plan and dimension this new system. This work proposes a new analytical model based on stochastic geometry. It provides a closed form expression of the successful transmission of an NB-IoT system in the uplink for a given sensor spatial intensity. The accuracy of the proposed analytical model is validated by simulation.

In this paper, we address the tradeoff between network coding overhead and multi-layer video tolerated loss rate on multi-hop wireless networks. We aim, through a simulation study, to evaluate a bounded network coding redundancy, for scalable video, based on the measured packet loss and the targeted maximum application loss rate. We consider first applying the bounded redundancy on a generation based scheme, and evaluate the tradeoff between tolerated video loss and the introduced overhead. Second, since scalable video produces a high video quality with various levels of importance, we propose to apply the bounded redundancy to an Expanding Window based scheme. We carried out a performance evaluation of both network coding schemes with two video test sequences using ns-3 simulator. We show the benefits of our scheme particularly in terms of overhead and PSNR.

Device-to-Device (D2D) communication is one of the promising and revolutionary technologies in 5G cellular networks that enables mobile terminals to communicate directly without the base station involvement. One of the major objectives of 5G for this paradigm is to provide seamless mobility satisfying QoS requirements. Hence, the handover process between various radio cells is an important issue faced by D2D candidates. This paper presents a new analytical model in order to evaluate the handover performance of the D2D pair operating with the practical Reference Point Group Mobility (RPGM) mobility model. Such a system is modeled as a two-stage open network and a multidimensional Markov Chain to compute performance metrics, such as blocking probability of originating D2D calls, handover failure probability or missing and unnecessary handovers rate. General formulas are given and numerical results evaluating the system performance are presented.

An ever-growing number of embedded devices supports different kinds of applications, such as healthcare, surveillance, gas monitoring, and others, that require an elevated level of communication reliability. However, the expected high density of those embedded devices increases the competition for frequency spectrum, making it difficult to achieve a reliable machine-to-machine (M2M) communication. To overcome these difficulties, the use of link quality estimators (LQE) is crucial to provide a solid communication. In order to provide robust and faster communication under harsh conditions, this paper proposes a new LQE, called PRR2, which uses two metrics and two levels of PRR (Packet Received Ratio). The use of two PRR sliding windows captures link quality variations in the short term and also considers the long-term. PRR2is compared against the state of the art on a prototype using USRPs, and the results show that the proposal reduces the number of retransmissions and increases the delivery rate, which are two important metrics for link layer reliability.

Software-Defined Networking (SDN) controllers are considered as Network Operating Systems (NOSs) and often viewed as a single point of failure. Detecting which SDN controller is managing a target network is a big step for an attacker to launch specific/effective attacks against it. In this paper, we demonstrate the feasibility of fingerpirinting SDN controllers. We propose techniques allowing an attacker placed in the data plane, which is supposed to be physically separate from the control plane, to detect which controller is managing the network. To the best of our knowledge, this is the first work on fingerprinting SDN controllers, with as primary goal to emphasize the necessity to highly secure the controller. We focus on OpenFlow-based SDN networks since OpenFlow is currently the most deployed SDN technology by hardware and software vendors.

Bike sharing is booming globally as a green transportation mode, but the occurrence of over-demand stations that have no bikes or docks available greatly affects user experiences. Directly predicting individual over-demand stations to carry out preventive measures is difficult, since the bike usage pattern of a station is highly dynamic and context dependent. In addition, the fact that bike usage pattern is affected not only by common contextual factors (e.g., time and weather) but also by opportunistic contextual factors (e.g., social and traffic events) poses a great challenge. To address these issues, we propose a dynamic cluster-based framework for over-demand prediction. Depending on the context, we construct a weighted correlation network to model the relationship among bike stations, and dynamically group neighboring stations with similar bike usage patterns into clusters. We then adopt Monte Carlo simulation to predict the over-demand probability of each cluster. Evaluation results using real-world data from New York City and Washington, D.C. show that our framework accurately predicts over-demand clusters and outperforms the baseline methods significantly.

In lossy environment like wireless networks, random losses are treated by TCP as signals of congestion and TCP cuts down the sending rate, leading to the performance degradation. The practical network coding system TCP/NC can address this problem. TCP/NC masks the random losses by allowing the destination to acknowledge every degree of freedom even though original data is not decoded yet. Consequently, TCP smoothly reacts to random losses without reducing the performance. The sole problem from TCP/NC is that TCP/NC sends redundant traffic every pre-set interval which does not recover random losses in time. We suggest an end-to-end adaptive redundancy control based on re-designing the coding scheme from TCP/NC, called Dynamic Coding (DynCod). Our main idea is how the destination can inform to the source whether the latest data sent from the source is decodable or not and how many packet losses occur via acknowledgement packets. Particularly, we change the principle of the information delivered by TCP ACKs: the destination does not only acknowledge every degree of freedom, but also announces how many unseen packets (> 0) remain in the coding window. The source can be informed via TCP ACKs and adjust the number of redundant packets accordingly. We have compared the performances of DynCod and TCP/NC using NS-2. The simulation results show that DynCod outperforms the original TCP/NC in terms of throughput and packet delivery time.

Today's mobile terminals have several access network interfaces. New protocols have been proposed during the last few years to enable the concurrent use of multiple access paths for data transmission. In practice, the use of different access technologies is subject to different interconnection costs, and mobile users have preferences on interfaces jointly depending on performance and cost factors. There is therefore an interest in defining “light” multipath communication policies that are less expensive than greedy unconstrained ones such as with basic multipath TCP (MP-TCP) and that are strategically acceptable assuming a selfish endpoint behavior. With this goal, we analyze the performance-cost trade-off of multi-homed end-to-end communications from a strategic standpoint. We model the communication between multi-homed terminals as a specific non-cooperative game to achieve performance-cost decision frontiers. The resulting potential game always allows selecting multiple equilibria, leading to a strategic load-balancing distribution over the available interfaces, possibly constraining their use with respect to basic MP-TCP. By simulation of a realistic three-interface scenario, we show how the achievable performance is bound by the interconnection cost; we show that we can halve the interconnection cost with respect to basic (greedy) MP-TCP while offering double throughputs with respect to single-path TCP. Moreover, we evaluate the compromise between keeping or relaxing strategic constraints in a coordinated MP-TCP context.

Recent research shows that random linear network coding is adapted into current network systems to provide transmission reliability. In lossy environments, like wireless networks, a redundancy control is also needed to mitigate losses. Some implementations suggest adding a fixed amount of redundant packets per batch. This solution poses the risk of wasting bandwidth by over-redundancy or unsuccessful decoding due to packet insufficiency, dramatically degrading the performance. In this paper, we present the Adaptive Redundancy Control for Network Coding (ARC) that adds redundant packets dynamically to mitigate losses. First, ARC is based on the use of MAC acknowledgements as a feedback on the state of link quality. Second, instead of determining the correct number of redundant packets, we decide to find the suitable time to send the redundant packets to cover losses. We design the multi-batch coding scheme that continuously streams new packets while interpreting the received MAC acknowledgements as the feedback on the state of link quality. The state of link quality will be rechecked before every transmission to deduct if it is appropriate for pumping the redundant packets or transmitting the new data. We implemented and compared ARC with 802.11 and FRC - Fixed Redundancy Control in NS-2. Results show that ARC outperforms 802.11 and FRC.

Today's mobile terminals have several access network interfaces. In practice, the use of different access technologies is subject to different interconnection costs, and mobile users have preferences on interfaces jointly depending on performance and cost factors. There is therefore an interest in defining “light” yet rational multipath communication policies less expensive than greedy ones such as with basic Multipath TCP (MP-TCP). We analyze the performance-cost trade-off of multi-homed end-to-end communications from a strategic standpoint. We model the communication between multi-homed terminals as a multi-criteria non-cooperative game so as to achieve performance-cost decision frontiers. The resulting potential game always allows to select multiple equilibria, which correspond to a strategic load-balancing distribution over the available interfaces, possibly constraining their use with respect to basic MP-TCP. We specify how the resulting model may be in practice implemented by users willing to jointly control the interconnection cost and the performance, based on user Quality of Experience (QoE) assessments. By simulation of a realistic 3-interface scenario, we show how the achievable performance is bound by the interconnection cost; we show that we can halve the interconnection cost with respect to basic (greedy) MP-TCP under a reasonable trade-off, while offering double throughputs with respect to single-path TCP.

In wireless mesh networks, network coding can be adapted and deployed for performance enhancement. Some early results such as COPE, BEND and DCAR show that the use of network coding can outperform the original 802.11 networks. However, these network coding architectures have two limitations: (i) the coding chances inevitably depend on the established route, (ii) traffic is strictly coded based on the two-hop coding pattern. In this paper, a novel and enhanced network coding architecture, Distributed Opportunistic Diffused Encoding (DODE), is proposed. DODE combines (i) the diffused gain from BEND and (ii) the generalized coding condition from DCAR to completely solve the limitations present in the three previous propositions. In addition, we propose a routing metric called Shortest Path with Enriched Neighborhood routing Metric (SPENM) which allows DODE to follow the most enriched coding chance path and also to enjoy the diffused gain. We implement DODE system in NS-2. The simulation results show that DODE outperforms 802.11, COPE, BEND and DCAR.

In Cognitive Radio Networks (CRN), the appearance of more active primary users (PUs) might require blocking of one or more secondary user (SU) transmissions to maintain interference constraints at PU receivers and Quality of Service (QoS) constraints of SUs. In general, SU transmitters need to adjust their transmission powers to maintain these constraints at all times. In this paper, we are interested in maximizing the number of concurrent SU flows under new PU arrivals and performing power allocation for SU links belonging to maintained data flows to maximize the minimum flow capacity. In particular, we develop a flow maintenance and power control scheme to solve this problem, which is referred to as Flow-Based Power Control (FBPC). The proposed scheme comprises two phases where we attempt to find a best set of flows with maximum size in the first phase and maximize the minimum flow capacity through power control in the second phase. To reduce computation complexity required in the first phase, we develop a flow combination metric, which is used to find the best flow combination. Moreover, we formulate power allocation problem that maximizes the minimum flow capacity and show how to transform it into a geometric convex program. Numerical results are presented to show the efficiency of the proposed flow combination metric and the desirable performance of the proposed two-phase flow maintenance and power control scheme.

In wireless mesh networks for unicast traffic, opportunistic network coding are specifically introduced for improved network utilization. Some recent practical implementations like COPE, BEND, DCAR and DODE have shown the promising results over the original 802.11 conventional forwarding mechanism. For better performance, the aim of all mentioned network coding implementations is trying to find more and more coding chances in network topologies. However, they restricted the finding within a simple rule "a pair of coder and decoder". For every coded packet (the combination of natives packets of traffic flows) sent on the traffic flow, we always have one coder (which creates the coded packet) and one decoder (which retrieves the desired packet for the destination). The trivial rule limited coding chances much. In this paper, we are loosing this noose: we decouple the coding and decoding functions from strictly a pair of coder and decoder. For one coder, we can have multiple decoders on the path (up to the number of other traffic flows involved in the coding). With this, more coding chances are found, thus, improving the network performance. We extend our proposed DODE with this new idea, called Distributed Opportunistic and Diffused Coding with Multiple Decoders - DODEX. We implement DODEX system in NS-2. The simulation results show that DODEX can outperform its previous introducing systems.

In heterogeneous wireless networks, multi-interfaced mobile terminals may be connected to links with rapidly varying MAC and physical characteristics. On the other hand, current deployment of communication protocols rely on the information available at associated layer only. In order to improve transport layer performance for multi-homed mobile terminals, we propose a cross-layer approach to schedule data over multiple available paths. Our data-striping approach strengthens the cooperation between higher and lower layers and enables transport layer mechanism to exploit information provided by MAC layer. We compare our approach with existing techniques and prove that our cross-layer system improves multipath performance over single-layer multipath systems.

Quantum cryptography is considered as a promising solution towards absolute security in long-term cryptosystems. While the application of quantum cryptography in fiber networks has significant advances, research on the application of quantum cryptography in mobile networks is still premature. In this paper, we analyze the interests of using quantum technique for the distribution of encryption keys in 802.11 wireless networks. We also propose a scheme for the integration of quantum cryptography in 802.11i security mechanisms for the establishment of the PTK (pairwise transient key).