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The highly dynamic wireless communication environment poses a challenge for many applications (e.g., adaptive multimedia streaming services). Providing accurate TP can significantly improve performance of these applications. The scheduling algorithms in cellular networks consider various PHY metrics, (e.g., CQI) and throughput history when assigning resources for each user. This article explains how AI can be leveraged for accurate TP in cellular networks using PHY and application layer metrics. We present key architectural components and implementation options, illustrating their advantages and limitations. We also highlight key design choices and investigate their impact on prediction accuracy using real data. We believe this is the first study that examines the impact of integrating network-level data and applying a deep learning technique (on PHY and application data) for TP in cellular systems. Using video streaming as a use case, we illustrate how accurate TP improves the end user's QoE. Furthermore, we identify open questions and research challenges in the area of AI-driven TP. Finally, we report on lessons learned and provide conclusions that we believe will be useful to network practitioners seeking to apply AI.

This special issue of Internet Computing includes articles that tackle both the technical challenges and vast opportunities of AI-Powered 5G services. The first two papers deal with the use of AI and Machine Learning for improved resource utilization in 5G cellular networks, and provisioning in the 5G Core, respectively. The third paper presents a cautionary perspective by examining AI/ML for 5G and beyond through an adversarial lens, and finally, the last paper covers the study of a scalable 5G-based solution for real-time air quality monitoring that has the potential to improve the lives of millions impacted by air quality issues.

Network functions virtualization is an emerging technology that can significantly improve the flexibility of network service provisioning and offer potential cost savings. However, it is critical that service providers offer high reliability and availability of the network and services when moving from proprietary hardware appliances to virtualized network functions on commodity servers. In a network consisting of physical appliances, providers can deploy redundant hardware and extra capacity to handle failures, although this is quite expensive in practice. Virtualization of network functions lead to more challenges for resiliency, but also bring new opportunities to address these challenges in a more cost-effective manner. In this article, we explain the resiliency requirements for virtual network functions in order to provide carrier grade services, summarize the existing solutions in the literature, highlight several research challenges, and present a concrete case study to demonstrate how to decompose a type of virtual router and thus enhance its resiliency.

Network functions virtualization (NFV) promises to bring significant flexibility and cost savings to networking. These improvements are predicated on being able to run many virtualized network elements on a server, which leads to a fundamental question on how scalable an NFV platform can be. With this in mind, the authors build an experimental platform with commonly used NFV technologies. They evaluate the NFVs performance and scalability and, based on their demonstrated improvements, discuss best practices for achieving optimum NFV performance on commodity hardware. They also reveal the limitations on NFV scalability and propose a new architecture to address them.

IPTV service providers offering Video-on-Demand currently use servers at each metropolitan office to store all the videos in their library. With the rapid increase in library sizes, it will soon become infeasible to replicate the entire library at each office. We present an approach for intelligent content placement that scales to large library sizes (e.g., 100 Ks of videos). We formulate the problem as a mixed integer program (MIP) that takes into account constraints such as disk space, link bandwidth, and content popularity. To overcome the challenges of scale, we employ a Lagrangian relaxation-based decomposition technique combined with integer rounding. Our technique finds a near-optimal solution (e.g., within 1%–2%) with orders of magnitude speedup relative to solving even the linear programming (LP) relaxation via standard software. We also present simple strategies to address practical issues such as popularity estimation, content updates, short-term popularity fluctuation, and frequency of placement updates. Using traces from an operational system, we show that our approach significantly outperforms simpler placement strategies. For instance, our MIP-based solution can serve all requests using only half the link bandwidth used by least recently used (LRU) or least frequently used (LFU) cache replacement policies. We also investigate the tradeoff between disk space and network bandwidth.

Despite its widespread adoption and popularity, the Hypertext Transfer Protocol (HTTP) suffers from fundamental performance limitations. SPDY, a recently proposed alternative to HTTP, tries to address many of the limitations of HTTP (e.g., multiple connections, setup latency). In this paper, we perform a detailed measurement study to understand the benefits of using SPDY over cellular networks. Through careful measurements conducted over 4 months, we provide a detailed analysis of the performance of HTTP and SPDY, how they interact with the various layers, and their implications on Web design. Our results show that unlike in wired and 802.11 networks, SPDY does not clearly outperform HTTP over cellular networks. We identify negative interactions between the protocols used for Web access (HTTP/SPDY over TCP) and cellular radio resource management as the underlying cause. Overall performance suffers when devices go through a cellular radio state promotion after an idle period, and the consequent increase in latency. This impacts SPDY more because of the use of a single TCP connection. We conclude that a viable solution has to account for these unique cross-layer dependencies to achieve improved Web performance over cellular networks.

Network function virtualization was recently proposed to improve the flexibility of network service provisioning and reduce the time to market of new services. By leveraging virtualization technologies and commercial off-the-shelf programmable hardware, such as general-purpose servers, storage, and switches, NFV decouples the software implementation of network functions from the underlying hardware. As an emerging technology, NFV brings several challenges to network operators, such as the guarantee of network performance for virtual appliances, their dynamic instantiation and migration, and their efficient placement. In this article, we provide a brief overview of NFV, explain its requirements and architectural framework, present several use cases, and discuss the challenges and future directions in this burgeoning research area.