A Survey on High-Speed Railway Communications: A Radio Resource Management Perspective

High-speed railway (HSR) communications will become a key feature supported by intelligent transportation communication systems. The increasing demand for HSR communications leads to significant attention on the study of radio resource management (RRM), which enables efficient resource utilization and improved system performance. RRM design is a challenging problem due to heterogenous quality of service (QoS) requirements and dynamic characteristics of HSR wireless communications. The objective of this paper is to provide an overview on the key issues that arise in the RRM design for HSR wireless communications. A detailed description of HSR communication systems is first presented, followed by an introduction on HSR channel models and characteristics, which are vital to the cross-layer RRM design. Then we provide a literature survey on state-of-the-art RRM schemes for HSR wireless communications, with an in-depth discussion on various RRM aspects including admission control, mobility management, power control and resource allocation. Finally, this paper outlines the current challenges and open issues in the area of RRM design for HSR wireless communications.Comment: 40 pages, 10 figures. Submitted to Computer Communication

Internet Protocol Version 6: Dead or Alive?

Internet Protocol (IP) is the narrow waist of multilayered Internet protocol stack which defines the rules for data sent across networks. IPv4 is the fourth version of IP and first commercially available for deployment set by ARPANET in 1983 which is a 32 bit long address and can support up to 232 devices. In April 2017, all Regional Internet Registries (RIRs) confirmed that IPv4 addresses are exhausted and cannot be allocated anymore implying any new organization requesting a block of Internet addresses will be allocated IPv6. This creates troubles of interoperability, migration and deployment, and therefore organizations hesitated to use IPv6 borrowing IPv4 addresses from other big organizations instead. Currently, when IPv4 is not available, and IPv6 is not adopted for around 20 years, the question arises whether IPv6 will still be accepted by the computer society or will it have an end of life soon with alternate better protocol such as ID based networks taking its place. This paper claims that IPv6 has lost its deployment window and can be safely skipped when new ID based protocols are available which not only have simple interoperability, deployment and migration guidelines but also provide advanced features as compared to IPv6. The paper provides answers to these questions with a comprehensive comparison of IPv6 with its available alternatives and reasons of IPv6 failures in its adoption. Finally, the paper declares IPv6 as a dead protocol and suggests to use newer available protocols in future.Comment: 16:198:553 Rutgers CS Course Pape

Fast User-Guided Video Object Segmentation by Interaction-and-Propagation Networks

We present a deep learning method for the interactive video object segmentation. Our method is built upon two core operations, interaction and propagation, and each operation is conducted by Convolutional Neural Networks. The two networks are connected both internally and externally so that the networks are trained jointly and interact with each other to solve the complex video object segmentation problem. We propose a new multi-round training scheme for the interactive video object segmentation so that the networks can learn how to understand the user's intention and update incorrect estimations during the training. At the testing time, our method produces high-quality results and also runs fast enough to work with users interactively. We evaluated the proposed method quantitatively on the interactive track benchmark at the DAVIS Challenge 2018. We outperformed other competing methods by a significant margin in both the speed and the accuracy. We also demonstrated that our method works well with real user interactions.Comment: CVPR 201

BaPu: Efficient and Practical Bunching of Access Point Uplinks

Today's increasing demand for wirelessly uploading a large volume of User Generated Content (UGC) is still significantly limited by the throttled backhaul of residential broadband (typically between 1 and 3Mbps). We propose BaPu, a carefully designed system with implementation for bunching WiFi access points' backhaul to achieve a high aggregated throughput. BaPu is inspired by a decade of networking design principles and techniques to enable efficient TCP over wireless links and multipath. BaPu aims to achieve two major goals:1) requires no client modification for easy incremental adoption; 2) supports not only UDP, but also TCP traffic to greatly extend its applicability to a broad class of popular applications such as HD streaming or large file transfer. We prototyped BaPu with commodity hardware. Our extensive experiments shows that despite TCP's sensitivity to typical channel factors such as high wireless packet loss, out-of-order packets arrivals due to multipath, heterogeneous backhaul capacity, and dynamic delays, BaPu achieves a backhaul aggregation up to 95% of the theoretical maximum throughput for UDP and 88% for TCP. We also empirically estimate the potential idle bandwidth that can be harnessed from residential broadband.Comment: 15 pages, 17 figures, experiment results obtained from real prototype system. BaPu is a sub-project under the Open Infrastructure project at the Wireless Networks Lab, College of Computer and Information Science in Northeastern University. (http://www.ccs.neu.edu/home/noubir/projects/openinfrastructure

Distortion-Aware Concurrent Multipath Transfer for Mobile Video Streaming in Heterogeneous Wireless Networks

The massive proliferation of wireless infrastructures with complementary characteristics prompts the bandwidth aggregation for Concurrent Multipath Transfer (CMT) over heterogeneous access networks. Stream Control Transmission Protocol (SCTP) is the standard transport-layer solution to enable CMT in multihomed communication environments. However, delivering high-quality streaming video with the existing CMT solutions still remains problematic due to the stringent QoS (Quality of Service) requirements and path asymmetry in heterogeneous wireless networks. In this paper, we advance the state of the art by introducing video distortion into the decision process of multipath data transfer. The proposed Distortion-Aware Concurrent Multipath Transfer (CMT-DA) solution includes three phases: 1) per-path status estimation and congestion control; 2) quality-optimal video flow rate allocation; 3) delay and loss controlled data retransmission. The term `flow rate allocation' indicates dynamically picking appropriate access networks and assigning the transmission rates. We analytically formulate the data distribution over multiple communication paths to minimize the end-to-end video distortion and derive the solution based on the utility maximization theory. The performance of the proposed CMT-DA is evaluated through extensive semi-physical emulations in Exata involving H.264 video streaming. Experimental results show that CMT-DA outperforms the reference schemes in terms of video PSNR (Peak Signal-to-Noise Ratio), goodput, and inter-packet delay.Comment: This paper has already accepted for publication in IEEE Transactions on Mobile Computing on Jun, 23rd, 201

A Survey and Taxonomy of Urban Traffic Management: Towards Vehicular Networks

Urban Traffic Management (UTM) topics have been tackled since long time, mainly by civil engineers and by city planners. The introduction of new communication technologies - such as cellular systems, satellite positioning systems and inter-vehicle communications - has significantly changed the way researchers deal with UTM issues. In this survey, we provide a review and a classification of how UTM has been addressed in the literature. We start from the recent achievements of "classical" approaches to urban traffic estimation and optimization, including methods based on the analysis of data collected by fixed sensors (e.g., cameras and radars), as well as methods based on information provided by mobile phones, such as Floating Car Data (FCD). Afterwards, we discuss urban traffic optimization, presenting the most recent works on traffic signal control and vehicle routing control. Then, after recalling the main concepts of Vehicular Ad-Hoc Networks (VANETs), we classify the different VANET-based approaches to UTM, according to three categories ("pure" VANETs, hybrid vehicular-sensor networks and hybrid vehicular-cellular networks), while illustrating the major research issues for each of them. The main objective of this survey is to provide a comprehensive view on UTM to researchers with focus on VANETs, in order to pave the way for the design and development of novel techniques for mitigating urban traffic problems, based on inter-vehicle communications

Towards Enabling Novel Edge-Enabled Applications

Edge computing has emerged as a distributed computing paradigm to overcome practical scalability limits of cloud computing. The main principle of edge computing is to leverage on computational resources outside of the cloud for performing computations closer to data sources, avoiding unnecessary data transfers to the cloud and enabling faster responses for clients. While this paradigm has been successfully employed to improve response times in some contexts, mostly by having clients perform pre-processing and/or filtering of data, or by leveraging on distributed caching infrastructures, we argue that the combination of edge and cloud computing has the potential to enable novel applications. However, to do so, some significant research challenges have to be tackled by the computer science community. In this paper, we discuss different edge resources and their potential use, motivated by envisioned use cases. We then discuss concrete research challenges that are in the critical path towards realizing our edge vision. We conclude by proposing a research agenda to allow the full exploitation of the potential for the emerging hybrid cloud/edge paradigm

Web Application for Collaborative Semantic Web Information Architecture

In this paper is analyzed the prototyping of the information visualization on a Web Application for community purposes in a collaborative environment representing an evolution of the actual social networks like Facebook, Instagram, Twitter, Linkedin, VirgilioPeople,... The intent of this work is to identify the most common features of Web App for the information visualization based on the Semantic Web and discuss how they support the user's requirements in a "collaborative" environment. A solution for the context-aware development of UI is based on "joint meaning" understood as a joint construal of the creator of the community contents and the user of the community contents thanks to the context and interface adaptation using the faced taxonomy with the Semantic Web. A proof-of concept prototype allows showing that the proposed methodological approach can also easily be applied to existing presentation components, built with different languages and/or component technologies.Comment: 7 pages, 3 figures, 2 tables, for details see: http://www.maxdalmas.co

Edge Intelligence: The Confluence of Edge Computing and Artificial Intelligence

Along with the rapid developments in communication technologies and the surge in the use of mobile devices, a brand-new computation paradigm, Edge Computing, is surging in popularity. Meanwhile, Artificial Intelligence (AI) applications are thriving with the breakthroughs in deep learning and the many improvements in hardware architectures. Billions of data bytes, generated at the network edge, put massive demands on data processing and structural optimization. Thus, there exists a strong demand to integrate Edge Computing and AI, which gives birth to Edge Intelligence. In this paper, we divide Edge Intelligence into AI for edge (Intelligence-enabled Edge Computing) and AI on edge (Artificial Intelligence on Edge). The former focuses on providing more optimal solutions to key problems in Edge Computing with the help of popular and effective AI technologies while the latter studies how to carry out the entire process of building AI models, i.e., model training and inference, on the edge. This paper provides insights into this new inter-disciplinary field from a broader perspective. It discusses the core concepts and the research road-map, which should provide the necessary background for potential future research initiatives in Edge Intelligence.Comment: 13 pages, 3 figure

Trends and Challenges in Wireless Channel Modeling for an Evolving Radio Access

With the advent of 5G, standardization and research are currently defining the next generation of the radio access. Considering the high constraints imposed by the future standards, disruptive technologies such as Massive MIMO and mmWave are being proposed. At the heart of this process are wireless channel models that now need to cover a massive increase in design parameters, a large variety of frequency bands, and heterogeneous deployments. This tutorial describes how channel models address this new level of complexity and which tools the community prepares to efficiently but accurately capture the upcoming changes in radio access design. We analyze the main drivers behind these new modeling tools, the challenges they pose, and survey the current approaches to overcome them.Comment: 5 figures. To appear in IEEE Communication Magazin