1,502 research outputs found

    Wireless Heterogeneous Networks and Next Generation Internet

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    The recent advances in wireless access technologies as well as the increasing number of mobile applications have made Wireless Internet a reality. A wide variety of bandwidth demanding services including high speed data delivery and multimedia communication have been materialized through the convergence of the next generation Internet and heterogeneous wireless networks. However, providing even higher bandwidth and richer applications necessitates a fundamental understanding of wireless Internet architecture and the interactions between heterogeneous users. Consequently, fundamental advances in many concepts of the wireless Internet are required for the ultimate goal of communication anytime anywhere. This special issue of the ACM Mobile Networks and Applications Journal is dedicated to the recent advances in the area of Wireless Internet. We accepted 10 papers out of 59 submissions from all over the world with a 17% acceptance rate. Papers describing management schemes, protocols, models, evaluation methods, and experimental studies of Wireless Internet are included in this special issue to provide a broad view of recent advances in this field

    Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions

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    The ever-increasing number of resource-constrained Machine-Type Communication (MTC) devices is leading to the critical challenge of fulfilling diverse communication requirements in dynamic and ultra-dense wireless environments. Among different application scenarios that the upcoming 5G and beyond cellular networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the unique technical challenge of supporting a huge number of MTC devices, which is the main focus of this paper. The related challenges include QoS provisioning, handling highly dynamic and sporadic MTC traffic, huge signalling overhead and Radio Access Network (RAN) congestion. In this regard, this paper aims to identify and analyze the involved technical issues, to review recent advances, to highlight potential solutions and to propose new research directions. First, starting with an overview of mMTC features and QoS provisioning issues, we present the key enablers for mMTC in cellular networks. Along with the highlights on the inefficiency of the legacy Random Access (RA) procedure in the mMTC scenario, we then present the key features and channel access mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT. Subsequently, we present a framework for the performance analysis of transmission scheduling with the QoS support along with the issues involved in short data packet transmission. Next, we provide a detailed overview of the existing and emerging solutions towards addressing RAN congestion problem, and then identify potential advantages, challenges and use cases for the applications of emerging Machine Learning (ML) techniques in ultra-dense cellular networks. Out of several ML techniques, we focus on the application of low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future publication in IEEE Communications Surveys and Tutorial

    Resilient availability and bandwidth-aware multipath provisioning for media transfer over the internet (Best Paper Award)

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    Traditional routing in the Internet is best-effort. Path differentiation including multipath routing is a promising technique to be used for meeting QoS requirements of media intensive applications. Since different paths have different characteristics in terms of latency, availability and bandwidth, they offer flexibility in QoS and congestion control. Additionally protection techniques can be used to enhance the reliability of the network. This paper studies the problem of how to optimally find paths ensuring maximal bandwidth and resiliency of media transfer over the network. In particular, we propose two algorithms to reserve network paths with minimal new resources while increasing the availability of the paths and enabling congestion control. The first algorithm is based on Integer Linear Programming which minimizes the cost of the paths and the used resources. The second one is a heuristic-based algorithm which solves the scalability limitations of the ILP approach. The algorithms ensure resiliency against any single link failure in the network. The experimental results indicate that using the proposed schemes the connections availability improve significantly and a more balanced load is achieved in the network compared to the shortest path-based approaches

    Seamless Multimedia Delivery Within a Heterogeneous Wireless Networks Environment: Are We There Yet?

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    The increasing popularity of live video streaming from mobile devices, such as Facebook Live, Instagram Stories, Snapchat, etc. pressurizes the network operators to increase the capacity of their networks. However, a simple increase in system capacity will not be enough without considering the provisioning of quality of experience (QoE) as the basis for network control, customer loyalty, and retention rate and thus increase in network operators revenue. As QoE is gaining strong momentum especially with increasing users' quality expectations, the focus is now on proposing innovative solutions to enable QoE when delivering video content over heterogeneous wireless networks. In this context, this paper presents an overview of multimedia delivery solutions, identifies the problems and provides a comprehensive classification of related state-of-the-art approaches following three key directions: 1) adaptation; 2) energy efficiency; and 3) multipath content delivery. Discussions, challenges, and open issues on the seamless multimedia provisioning faced by the current and next generation of wireless networks are also provided
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