We propose a short-term traffic flow prediction (STP) framework so that transportation authorities take early actions to control flow and prevent congestion. We anticipate flow at future time frames on a target road segment based on historical flow data and innovative features such as real time feeds and trajectory data provided by connected vehicles (CV) technology. To cope with the fact that existing approaches do not adapt to variation in traffic, we show how this novel approach allows advanced modelling by integrating into the forecasting of flow, the impact of the various events that CV realistically encountered on segments along their trajectory. We solve the STP problem with a Deep Neural Networks (DNN) in a multitask learning setting augmented by input from CV. Results show that our approach, namely MTL-CV, with an average Root-Mean-Square Error (RMSE) of 0.052, outperforms state-of-the-art ARIMA time series (RMSE of 0.255) and baseline classifiers (RMSE of 0.122). Compared to single task learning with artificial neural network (ANN), ANN had a lower performance, 0.113 for RMSE, than MTL-CV. MTL-CV learned historical similarities between segments, in contrast to using direct historical trends in the measure, because trends may not exist in the measure but do in the similarities.

Distributed denial of service attacks are cyber-attacks that target the availability of servers. As a result, legitimate users no longer have access to the service. This can have a negative impact on an organization, such as lack of reputation and economic losses. Therefore, it is important to design defense mechanisms against these attacks. There are systems for detecting distributed denial of service attacks in the literature, which still have various shortcomings. Some of these systems detect the presence of attack traffic without identifying the attack packets or flows. Others use static thresholds and therefore cannot adapt to changes in legitimate traffic. In this paper, we propose an online system that aims to detect flooding attacks in a short timeframe and a client–server environment. The proposed detection system consists of five modules, namely features extraction and connections construction, suspicious activity detection, attack connections detection, alert generation and threshold update. The suspicious activity detection module calculates the normalized Shannon entropy by considering the source Internet Protocol address as a random variable. Suspicious activity is detected when the computed entropy is below a threshold. The threshold calculation is based on Chebyshev’s theorem. We propose a dynamic threshold algorithm to track changes in legitimate traffic. We evaluate the proposed system through simulations and using a publicly available dataset. Compared to other similar works, the proposed detection system has a better performance in terms of detection rate, false positive rate, precision and overall accuracy.

In cloud computing, a fundamental management problem with the Infrastructure as a Service (IaaS) model lies in the efficient embedding of computational and networking resources onto distributed virtualized infrastructures owned by independent cloud providers (CPs). In such a context, this issue usually referred to as the Virtual Network Embedding (VNE) problem, adds more complexity since the entire embedding process requires two mayor phases of operation: the multicloud virtual network requests (VNRs) splitting, followed by the intracloud VNR segments mapping. This paper focuses on the splitting phase problem, by proposing a VNRs splitting strategy formalized as an Integer Linear Program (ILP) model, with the objective of improving the performance and QoS of resulting mapped VNR segments, while minimizing the resource provisioning expenditures. As the VNE is classified as an NP-hard problem, a hybrid metaheuristic approach based on the Ant Colony Optimization (ACO) combined with the Tabu Search (TS) as local search operator, is proposed in order to find good feasible solutions in reasonable time. The simulation results show the efficiency of the proposed approach, which generates, in a highly reduced computing time, solution costs very close to the exact solution, with an average cost gap ranging from 0 percent to a maximum of 3.42 percent.

Mobile devices are becoming an essential part of many users’ lives. Users exchange sometimes very sensitive data with remote servers. This raises a security problem in terms of the confidentiality and integrity of these data, and users’ privacy. Mutual authentication protocols allow a user and a server to confirm each other’s legitimacy and share a session key to encrypt subsequent communications. Several protocols have been proposed to achieve this goal. However, these have certain weaknesses, such as impersonation, lack of anonymity, the use of additional hardware, and the synchronization problem associated with the use of timestamps. In this paper, we propose a mutual authentication protocol based on elliptic curve cryptography for mobile client – server environments, which addresses the above problems. This protocol is intended to be lightweight as it is designed for resource constrained mobile devices. Moreover, we present a formal and informal analysis of the security of the proposed protocol. This latter has security attributes, such as session key security, perfect forward secrecy, user anonymity, resistance to impersonation, replay and insider attacks. Performance evaluation shows that we outperform similar protocols. Therefore, the proposed protocol is secure, efficient and suitable for mobile environments.

In cloud computing, a fundamental management problem with the Infrastructure as a Service model lies in the efficient embedding of computing and networking resources onto distributed virtualized infrastructures. This issue, usually referred to as the Virtual Network Embedding (VNE) problem, has been well studied for a single Cloud Provider (CP). However, wide-area services delivery may require to embed heterogeneous resources over multiple CPs. This adds more complexity and scalability issues, since the Virtual Network Requests (VNRs) embedding process requires two phases of operation: the multicloud VNRs splitting, followed by the intracloud VNR segments mapping. This paper addresses the problem of VNE across multiple CPs by proposing a VNRs splitting strategy which aims at improving the performance and QoS of resulting VNR segments. An Integer Linear Program (ILP) is used to formalize the splitting phase as a maximization problem with constraints. Subsequently, in order to minimize the overall delay, a multi-objective intracloud resource mapping approach formalized as a Mixed-Integer Linear Program (MILP) is adopted. Simulations with the exact method show the efficiency of the proposed strategy based on several performance criteria. In particular, the acceptance rate and the delay are respectively improved by 15.1 and 18.5 percent, while preventing QoS violations.

We developed a distributed data mining system to elaborate on a decision concerning the cause of urban traffic congestion via emerging connected vehicle (CV) technology. We observe this complex phenomena through the interactions between vehicles exchanging messages via vehicle to vehicle communication. Results are based on real-time simulation generated scenarios extended from the real-world traffic travel and activity patterns simulation cologne scenario. We evaluate a voting procedure that provides deeper insights using cooperation between vehicles, belief functions (BF) aimed at improving representation of information and a data association technique (DAT) aimed at data mining and extracting the association rules from the exchanged messages. Methods are tested and compared using a microscopic urban mobility simulator, SUMO, and a network simulator, ns-2, for the simulation of communication between CVs. Compared with the back-propagation algorithm (BP) extensively used in the past literature, our performance evaluation shows that the proposed methods enhance the estimation of the cause of congestion by 48% for the proposed VP, 58% for the BF, 71% for the DAT, and 70% for β-DAT. The methods also enhance detection time from 7.09% to 10.3%, and β-DAT outperforms BP by approximately 1.25% less false alarms triggered by the network, which can be significant in the context of real-time decision making. We show that a market penetration rate between 63% and 75% is enough to ensure satisfactory performance.

This paper aims to optimize cloud services' net profits and penalties with live placement of interdependent virtual machines (VMs). This optimization is a complex task as it is difficult to achieve a successful compromise between penalties and net profits on service level contracts. This paper studies this optimization problem to minimize services' penalties and maximizing net profits while achieving live migrations of interdependent VMs. This VM's live placement optimization problem is a NP-hard problem with exponential running time. A mathematical model was designed and approximations were conducted with an efficient PCH/PCH' heuristic. This Mixed Integer Non-Linear programming (MNLP) formulation and heuristic for cloud services was tested where the overall services' penalty needs to be minimized, overall net profits have to be maximized, and where efficient live migrations of VMs is a concern. Simulation results show how cloud providers may live place VMs. Finally, our results show that a PCH/PCH' heuristic: (i) finds better solutions than the existing machines' configuration of Google traces; (ii) is suitable for large-sized instances of cloud services; (iii) performs better than FF, FFD, and CPLEX in terms of overall penalties and net profits; and (iv) runs in less than six minutes over the last day's data.

Vehicular ad hoc networks (VANETs) can efficiently detect traffic congestion, but detection is not enough, because congestion can be further classified as recurrent and non-recurrent congestion (NRC). In particular, NRC in an urban network is mainly caused by incidents, work zones, special events, and adverse weather. We propose a framework for the real-time distributed classification of congestion into its components on a heterogeneous urban road network using VANET. We present models built on an understanding of the spatial and temporal causality measures and trained on synthetic data extended from a real case study of Cologne. Our performance evaluation shows a predictive accuracy of 87.63% for the deterministic classification tree, 88.83% for the nave Bayesian classifier, 89.51% for random forest, and 89.17% for the boosting technique. This framework can assist transportation agencies in reducing urban congestion by developing effective congestion mitigation strategies knowing the root causes of congestion.

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 operational transformation (OT) approach, used in many collaborative editors, allows a group of users to concurrently update replicas of a shared object and exchange their updates in any order. The basic idea is to transform any received update operation before its execution on a replica of the object. Concretely, OT consists of a centralized/decentralized integration procedure and a transformation function. In the context of decentralized integration, designing transformation functions for achieving convergence of object replicas is a critical and challenging issue. Indeed, the transformation functions proposed in the literature are all revealed inefficient. In this paper, we investigate the existence of transformation functions. From the theoretical point of view, two properties, named TP1 and TP2, are necessary and sufficient to ensure convergence. Using controller synthesis technique, we show that there are some transformation functions, which satisfy TP1 for the basic signatures of insert and delete operations. But, there is no transformation function, which satisfies both TP1 and TP2. Consequently, a transformation function which satisfies both TP1 and TP2 must necessarily have additional parameters in the signatures of some update operations. We propose, in this paper, a new transformation function and show formally that it ensures convergence.

On one hand, IMS are a research area that has been gaining attention from the research community. It aims to provide cellular access to all Internet services. It is a control architecture on the top of the IP layer whose goal is dependent on the provision of the Quality of Service (QoS), integrated services and fair charging scheme throughout standard interfaces. On the other hand, VANETs are a new communication paradigm that enables the wireless communication between vehicles moving with high speeds, as well as the vehicles and the road side equipments found along the roads. This opened the door to develop several new applications like traffic engineering, traffic management, dissemination of emergency information to avoid critical situations, comfort and entertainment and other user applications. Moreover, VANETs are sub-class of Mobile Ad-hoc Networks; the performance of the communication depends on how better the routing takes place in the network. This work proposes a presence-based architecture for the integration of VANETs with the IMS in the presence of WSNs too. The presence of the middleware is used to make an instantaneous awareness of the VANETs' changes as well as the IMS format and to select the best delivery strategy between the two architectures.

In the last few years, a large variety of wireless components are increasingly running applications that need real-time and high-bandwidth features. Hence, it is imperative for network service providers to make the best possible to ensure seamless roaming through different wireless technologies. In this context, mobility management remains an important task to be investigated to improve Quality of Service (QoS) during the handover disruption time. With the standardization of SCTP/mSCTP protocols, experiencing mobility at the transport layer becomes more attractive due to the high connectivity facilities offered at this level. In this sense, several SCTP-based mobility schemes have been proposed to provide seamless handoffs through homogeneous and heterogeneous networks. Nevertheless, the proposed solutions suffer from weaknesses such as unnecessary latency and signaling load when mobile users roam inside a same administrative domain. Additionally, the QoS relevant to the disruption time is affected quite considerably by failed Selective Acknowledgment messages (SACKs) and unnecessary chunk retransmissions due to RTO expiration. In this paper, we propose an Enhanced Hierarchical Transport layer Mobility scheme (E-HTM) that reduces handoff latency and improves throughputs observed during the handoff period. Moreover, it introduces a new mobility unit to effect more efficient handoff procedures. Simulation results show that E-HTM guarantees lower handoff latency and good throughput during handovers compared to previous mSCTP-based solutions.

The IP Multimedia Subsystem (IMS) aims to provide cellular access to all the services that the Internet offers; it is an overlay control layer on top of an IP layer. Wireless Sensor Networks (WSN) with mobile sinks are useful in a wide range of scenarios since they can improve the overall network lifetime and increase data capacity. Combining the capabilities of IMS with the rich set of contextual information captured by mobile sink WSNs will open the door to a wide range of novel multimedia services. This paper proposes an overlay architecture for the integration of IMS with mobile sink-based WSN. The Presence service is used as entry point to the IMS world. The gateway which is the heart of our architecture is an overlay built on top of the very same mobile phones that act as mobile sinks, presence publishers / watchers, and end-user devices. A prototype is built using JXME, an extension of JXTA with P2P middleware.

The recent development and deployment of wireless technologies has created different types of mobile networks. In order to take advantage of this heterogeneity, next generation mobile networks (NGMN) is projected to integrate all of those systems. Several integrating solutions are available in the literature, yet none can claim to be the ultimate and unique integrated solution. Moreover, these proposals fail to guarantee seamless mobility and service continuity. This paper proposes a new hybrid interworking architecture (HIA) for 4G networks. HIA aims to integrate current and future wireless systems while hiding their heterogeneities. HIA guarantees seamless roaming and service continuity by supporting both IP layer and transport layer mobility. Numerical results show that HIA exhibits a net improvement of handoff latency and packet loss.

Ad hoc wireless networks (AWNs) obey a unique organizational and behavioral logic since they operate without a fixed infrastructure. Mobile nodes must collaborate amongst themselves to interconnect, organize the topology and establish communication. Moreover, their networking characteristics highlight a new breed of unresolved routing and Quality of Service problems. This article presents new approach for QoS support in AWNs. The fundamental idea behind our approach is to identify nodes in the network that can partake in a QoS mobile routing backbone (MRB). Only nodes having routing abilities and sufficient resources can join the backbone. QoS is supported through efficient bandwidth allocation and load balancing. The routing mechanism guides incoming data flows through network regions made up of nodes rich in resources and interconnected through stable links. Results obtained are encouraging and bring to light the ability our mechanisms to support QoS in AWNs.

The UMTS system and architecture are designed to accommodate Internet-like mobile services and specific services like mobile commerce to mobile users. They bring attacks from Internet and mobile users as well. Denial-of-service (DoS) attacks aim to frustrate a legitimate user's access to mobile services or bring down servers by depleting system resources. Many approaches are proposed to thwart these attacks. A client puzzle from the server, which forces the client to resolve it before communication, is one of these approaches. The server can adjust the difficulty levels of the puzzle for access control and against DoS attacks according to current resource consumption and communication scenario. Currently, many types of client puzzles have no fine-grained control over difficulties. In a client puzzle, the next higher difficulty level is often twice as hard as the current one. In this paper, we propose a method based on partial collisions in hash functions. Our approach provides fine-grained control over difficulties by introducing a quasi partial collision concept. The results obtained confirm the fine granularity and efficiency of our approach.

Integration of heterogeneous networks constitutes the main concern of the next generation of mobile networks (4G). This integration is closely related to mobility management in the sense that a mobile user will move freely across mobile networks without connection disruption. Mobile IP based approaches suffers from drawbacks such as packet loss, high throughputs and handover latency. In this paper, we propose a new SCTP (stream control transmission protocol) mobility scheme supporting vertical handoff. The proposed scheme does not require any special infrastructure and presents less handoff latency compared to MIPv6 based approaches

Wireless sensor networks (WSNs) are composed of power-restrained nodes that limit their lifetime, since the sources of energy are often non-replaceable. In this work, we deal with the power consumption problem in one application of WSNs: objects tracking in a monitored region. Different protocols have been proposed to minimize the energy consumption in such environments. Most of them are based in prediction techniques to know in advance the locations of the object, taking advantage of this information to switch off the sensor nodes as much as possible. However, little work has been done to utilize regularity in the object's behavior to reduce energy consumption. In this paper we propose a profile-based algorithm (PBA) that aims to use the information contained in the network and in the object itself to optimize energy consumption, thus extending lifetime. Simulations show that this method outperforms prediction-based strategies for a wide range of predictability values

Domain oriented mobility management schemes like "hierarchical mobile IP" (HMIP) reduce the overwhelming binding updates signaling of a standard mobile IP. "Mobile anchor point" (MAP) which is a substitute of "home agent" (HA) in each domain of the network hides user's mobility from the outer domain. But there are still many deficiencies associated with the structure itself. The standard HMIPv6 structure depends on a single MAP for all users of the domain without considering their mobility patterns. Consequently, the system has to fall back to the mobile IP structure, if MAP functions improperly. Moreover vague definition of domain's boundary and ignoring users' traffic behavior are among the most addressed problems. This paper proposes a scheme which is built on top of the hierarchical architecture of HMIP. It tries to find an appropriate anchor point for each individual mobile user regarding its mobility pattern and its long term requested services. Simulation results show a considerable improvement in terms of location update cost and packet delivery delay in comparison with HMIP and two well known schemes in literature

Mobile ad hoc networks are a type of mobile network that functions without any fixed infrastructure. This new mobility context is highly dynamic. One of the weaknesses of ad hoc networks is node configuration. The configuration issue in MANET consists in assigning IP addresses to mobile nodes and dealing with the dynamic behavior of the network. To complete node configuration, new solutions prove to be necessary. Several solutions have been proposed in the literature. However, these approaches have many weaknesses. This paper proposes an autoconfiguration protocol for MANET (APM), which is based on direct configuration of new nodes and on centralized control of the configuration service. The APM considers node arrivals, node departures, and network partitioning and merge. Theoretical computation and simulation results show that APM has low latency and low overhead compared to most configuration methods based on conflict detection.

Third-generation mobile systems provide access to a wide range of services and enable mobile users to communicate regardless of their geographical location and their roaming characteristics. Due to the growing number of mobile users, global connectivity, and the small size of cells, one of the most critical issues regarding these networks is location management. In recent years, several strategies have been proposed to improve the performance of the location management procedure in 3G mobile networks. In this paper, we present a user pattern learning strategy (UPL) using neural networks to reduce the location update signaling cost by increasing the intelligence of the location procedure in UMTS. This strategy associates to each user a list of cells where she is likely to be with a given probability in each time interval. The implementation of this strategy has been subject to extensive tests. The results obtained confirm the efficiency of UPL in significantly reducing the costs of both location updates and call delivery procedures when compared to the UMTS standard and with other strategies well-known in the literature.