Computer Science

The Peer-to-Peer systems (P2P) were led these last years as the major technology of access upon various resources on Internet. These systems build a cluster witch contains a very large number of peers. As the result the selection of peers who can answer for a given query is a very difficult problem. The efficiency of the selection algorithms can be improved by introducing of semantics into the process of queries routing. We present in this paper a novel improved version of our semantic routing algorithm LearningPeerSelection (LPS) presented in CORIA 2009, an incremental strategy of updating knowledge bases and an advanced experimental study. To test the proposed algorithm, we defined a layer of routing on the PeerSim simulator.

Aiming to minimize service delay, we propose a new random caching scheme in device-to-device (D2D)-assisted heterogeneous network. To support diversified viewing qualities of multimedia video services, each video file is encoded into a base layer (BL) and multiple enhancement layers (ELs) by scalable video coding (SVC). A super layer, including the BL and several ELs, is transmitted to every user. We define and quantify the service delay of multi-quality videos by deriving successful transmission probabilities when a user is served by a D2D helper, a small-cell base station (SBS) and a macro-cell base station (MBS). We formulate a delay minimization problem subject to the limited cache sizes of D2D helpers and SBSs. The structure of the optimal solutions to the problem is revealed, and then an improved standard gradient projection method is designed to effectively obtain the solutions. Both theoretical analysis and Monte-Carlo simulations validate the successful transmission probabilities. Compared with three benchmark caching policies, the proposed SVC-based random caching scheme is superior in terms of reducing the service delay.

In many scenarios, control information dissemination becomes a bottleneck, which limits the scalability and the performance of wireless networks. Such a problem is especially crucial in mobile ad hoc networks, dense networks, networks of vehicles and drones, sensor networks. In other words, this problem occurs in any scenario with frequent changes in topology or interference level on one side and with strong requirements on delay, reliability, power consumption, or capacity on the other side. If the control information changes partially, it may be worth sending only differential updates instead of messages containing full information to reduce overhead. However, such an approach needs accurate tuning of dissemination parameters, since it is necessary to guarantee information relevance in error-prone wireless networks. In the paper, we provide a deep study of two approaches for generating differential updates - namely, incremental and cumulative - and compare their efficiency. We show that the incremental approach allows significantly reducing the amount of generated control information compared to the cumulative one, while providing the same level of information relevance. We develop an analytical model for the incremental approach and propose an algorithm which allows tuning its parameters, depending on the number of nodes in the network, their mobility, and wireless channel quality. Using the developed analytical model, we show that the incremental approach is very useful for static dense network deployments and networks with low and medium mobility, since it allows us to significantly reduce the amount of control information compared to the classical full dump approach.

Vehicle-to-infrastructure and vehicle-to-vehicle communications has been introduced to provide high rate Internet connectivity to vehicles to meet the ubiquitous coverage and increasing high-data rate internet and multimedia demands by utilizing the 802.11 access points (APs) used along the roadside. In order to evaluate the performance of vehicular networks over WLAN, in this paper, we investigate the transmisison and network performance of vehicles that pass through AP by condidering contention nature of vehicles over 802.11 WLANs. Firstly, we derived an analytical traffic model to obtain the number of vehicles under transmision range of an AP. Then, incorporating vehicle traffic model with Markov chain model and for arrival packets, MG1K queuing system, we developed a model evaluating the performance of DCF mechanism with an optimal retransmission number. Based on traffic model, we also derived the probability of mean arrival rate to AP. A distinctive aspect of our work is that it incorporates both vehicular traffic model and backoff procedure with M/G/1/K queuing model to investigate the impact of various traffic load conditions and system parameters on the vehicular network system. Based on our model, we show that the delay and througput performance of the system reduces with the increasing vehicle velocity due to optimal retransmision number m, which is adaptively adjusted in the network with vehicle mobility.

In this paper, we show how the absorption and re-radiation energy from molecules in the air can influence the Multiple Input Multiple Output (MIMO) performance in high-frequency bands, e.g., millimeter wave (mmWave) and terahertz. In more detail, some common atmosphere molecules, such as oxygen and water, can absorb and re-radiate energy in their natural resonance frequencies, such as 60 GHz, 180 GHz and 320 GHz. Hence, when hit by electromagnetic waves, molecules will get excited and absorb energy, which leads to an extra path loss and is known as molecular attenuation. Meanwhile, the absorbed energy will be re-radiated towards a random direction with a random phase. These re-radiated waves also interfere with the signal transmission. Although, the molecular re-radiation was mostly considered as noise in literature, recent works show that it is correlated to the main signal and can be viewed as a composition of multiple delayed or scattered signals. Such a phenomenon can provide non-line-of-sight (NLoS) paths in an environment that lacks scatterers, which increases spatial multiplexing and thus greatly enhances the performance of MIMO systems. Therefore in this paper, we explore the scattering model and noise models of molecular re-radiation to characterize the channel transfer function of the NLoS channels created by atmosphere molecules. Our simulation results show that the re-radiation can increase MIMO capacity up to 3 folds in mmWave and 6 folds in terahertz for a set of realistic transmit power, distance, and antenna numbers. We also show that in the high SNR, the re-radiation makes the open-loop precoding viable, which is an alternative to beamforming to avoid beam alignment sensitivity in high mobility applications.

The increasing pervasive and ubiquitous presence of devices at the edge of the Internet is creating new scenarios for the emergence of novel services and applications. This is particularly true for location- and context-aware services. These services call for new decentralized, self-organizing communication schemes that are able to face issues related to demanding resource consumption constraints, while ensuring efficient locality-based information dissemination and querying. Voronoi-based communication techniques are among the most widely used solutions in this field. However, when used for forwarding messages inside closed areas of the network (called Areas of Interest, AoIs), these solutions generally require a significant overhead in terms of redundant and/or unnecessary communications. This fact negatively impacts both the devices' resource consumption levels, as well as the network bandwidth usage. In order to eliminate all unnecessary communications, in this paper we present the MABRAVO (Multicast Algorithm for Broadcast and Routing over AoIs in Voronoi Overlays) protocol suite. MABRAVO allows to forward information within an AoI in a Voronoi network using only local information, reaching all the devices in the area, and using the lowest possible number of messages, i.e., just one message for each node included in the AoI. The paper presents the mathematical and algorithmic descriptions of MABRAVO, as well as experimental findings of its performance, showing its ability to reduce communication costs to the strictly minimum required.

As vehicles playing an increasingly important role in people's daily life, requirements on safer and more comfortable driving experience have arisen. Connected vehicles (CVs) can provide enabling technologies to realize these requirements and have attracted widespread attentions from both academia and industry. These requirements ask for a well-designed computing architecture to support the Quality-of-Service (QoS) of CV applications. Computation offloading techniques, such as cloud, edge, and fog computing, can help CVs process computation-intensive and large-scale computing tasks. Additionally, different cloud/edge/fog computing architectures are suitable for supporting different types of CV applications with highly different QoS requirements, which demonstrates the importance of the computing architecture design. However, most of the existing surveys on cloud/edge/fog computing for CVs overlook the computing architecture design, where they (i) only focus on one specific computing architecture and (ii) lack discussions on benefits, research challenges, and system requirements of different architectural alternatives. In this paper, we provide a comprehensive survey on different architectural design alternatives based on cloud/edge/fog computing for CVs. The contributions of this paper are: (i) providing a comprehensive literature survey on existing proposed architectural design alternatives based on cloud/edge/fog computing for CVs, (ii) proposing a new classification of computing architectures based on cloud/edge/fog computing for CVs: computation-aided and computation-enabled architectures, (iii) presenting a holistic comparison among different cloud/edge/fog computing architectures for CVs based on functional requirements of CV systems, including advantages, disadvantages, and research challenges.

Cellular Vehicle-to-X (Cellular V2X) is a communication technology that aims to facilitate the communication among vehicles and with the roadside infrastructure. Introduced with LTE Release 14, Cellular V2X enables device-to-device communication to support road safety and traffic efficiency applications. We present Artery-C, a simulation framework for the performance evaluation of Cellular V2X protocols and V2X applications. Our simulator relies on the simulation framework SimuLTE and substantially extends it by implementing control and user planes. Besides the vehicle-to-network communication via the up-/downlink interface, it provides vehicle-to-vehicle and vehicle-infrastructure communication via the sidelink interface using the managed and the unmanaged mode of Cellular V2X (mode 3 and 4, respectively). The simulator also implements advanced features of 5G mobile networks, such as variable numerologies. For the transmission of of V2X messages, it adds a non-IP interface. Artery-C integrates seamlessly into the simulation framework Artery, which enables the simulation of standardized V2X messages at the facilities layer as well as the coupling to the mobility simulator SUMO. A specific feature of Artery-C is the support of dynamic switching between all modes of Cellular V2X. In order to demonstrate the capabilities of Artery-C, we evaluate V2X-based platooning as a representative use case and present results for mode 3, mode 4 and mode switching in a highway scenario.

Limited backhaul bandwidth and blockage effects are two main factors limiting the practical deployment of millimeter wave (mmWave) networks. To tackle these issues, we study the feasibility of relaying as well as caching in mmWave networks. A user association and relaying (UAR) criterion dependent on both caching status and maximum biased received power is proposed by considering the spatial correlation caused by the coexistence of base stations (BSs) and relay nodes (RNs). A joint UAR and caching placement problem is then formulated to maximize the backhaul offloading traffic. Using stochastic geometry tools, we decouple the joint UAR and caching placement problem by analyzing the relationship between UAR probabilities and caching placement probabilities. We then optimize the transformed caching placement problem based on polyblock outer approximation by exploiting the monotonic property in the general case and utilizing convex optimization in the noise-limited case. Accordingly, we propose a BS and RN selection algorithm where caching status at BSs and maximum biased received power are jointly considered. Experimental results demonstrate a significant enhancement of backhaul offloading using the proposed algorithms, and show that deploying more RNs and increasing cache size in mmWave networks is a more cost-effective alternative than increasing BS density to achieve similar backhaul offloading performance.

Achieving high bandwidth utilization in cloud computing is essential for better network performance. However, it is difficult to attain high bandwidth utilization in cloud computing due to the complex and distributed natures of cloud computing resources. Recently, a growing demand for multicast transmission is perceived in cloud computing, due to the explosive growth of multi-point communication applications, such as video conferencing, online gaming, etc. Nonetheless, the inherent complexity in multicast routing in cloud computing, existing multicast plans failed to produce effective and efficient protocol schemes, which limits the application of multicast communication on the Internet. In this paper, a technique is proposed in how the newly developed network architecture, Software Defined Network (SDN), can promote the design of the multicast protocol and improve the performance of the multicast transmission in the cloud computing. The approach is to use the SDN-cloud Computing-enabled multicast communication scheme with ultra-high bandwidth utilization. The bandwidth utilization is enhanced by measuring various routing trees for each multicast transmission session and distributing the traffic load over all available routes in the cloud computing resources. The SDN is utilized to tackle with various design hurdles in the cloud computing, including both the current ones with the conventional multicast pattern and the newly emerged ones with multi-tree multicast. The prototype implementation and experiments demonstrate the performance enhancement of the proposed approach in the cloud computing in compared to conventional single-tree multicast designs.