One of the key features of next-generation mobile networks is the ability to satisfy the requirements coming from different verticals. For satisfying these requirements, 5G networks will need to dynamically reconfigure the deployment of the network functions. However, the current deployments of mobile networks are experiencing difficulties in exhibiting the required flexibility. At the same time, the research on connectivity provisioning in use cases such as after-disaster scenarios or battlefields has converged toward the idea of Network-In-aBox. This idea revolves around fitting all software and hardware modules needed by a mobile network in a single or a handful of physical devices. A Network-In-a-Box inherently offers a high level of flexibility that makes it capable of providing connectivity services in a wide range of scenarios. Therefore, the Network-In-a-Box concept represents an alternative approach for satisfying the requirements of next-generation mobile networks. In this survey, we analyze the state-of-the-art of Network-In-a-Box solutions proposed by academia and industry in the time frame starting from 1998 up to early 2017. First, we present the main use cases around which the concept has been conceived. Then, we abstract the common features of the Network-In-a-Box implementations, and discuss how different proposals offer these features. We then draw our conclusions and discuss possible future research directions, including steps required to reach an even higher level of flexibility. The aim of our analysis is twofold. On one hand, we provide a comprehensive view of the idea of Network-In-aBox. On the other hand, through the analysis, we present the features that future mobile networks should exhibit to achieve their design goals. In particular, we show how the Network-Ina-Box fosters the transition toward the next-generation mobile networks.

The virtual resources of 5G networks are expected to scale and support migration to other locations within the substrate. In this context, a configuration for 5G network slices details the instantaneous mapping of the virtual resources across all slices on the substrate, and a feasible configuration satisfies the Service-Level Objectives (SLOs) without overloading the substrate. Reconfiguring a network from a given source configuration to the desired target configuration involves identifying an ordered sequence of feasible configurations from the source to the target. The proposed solutions for finding such a sequence are optimized for data centers and cannot be used as-is for reconfiguring 5G network slices. We present Matryoshka, our divide-and-conquer approach for finding a sequence of feasible configurations that can be used to reconfigure 5G network slices. Unlike previous approaches, Matryoshka also considers the bandwidth and latency constraints between the network functions of network slices. Evaluating Matryoshka required a dataset of pairs of source and target configurations. Because such a dataset is currently unavailable, we analyze proof of concept roll-outs, trends in standardization bodies, and research sources to compile an input dataset. On using Matryoshka on our dataset, we observe that it yields close-to-optimal reconfiguration sequences 10X faster than existing approaches.

Mobile networks are expected to serve a wide range of verticals, however the Long Term Evolution (LTE) network is optimized for basic mobile operator services only. The network functions serving LTE networks are largely implemented as dedicated single function devices that offer poor customization options. This intrinsic inflexibility makes current LTE networks unable to meet the requirements of future mobile networks. For example, LTE networks experience signaling storms because the signals exchanged by the network functions cannot be optimized according to the current usage pattern of mobile services. Modularizing these network functions would enable a refactoring of the LTE network, allowing operators to compose networks that adapt and evolve with the influx of verticals. In this article, we present a new approach for refactoring the network functions serving LTE networks which can be leveraged to compose a modular mobile network optimized for the verticals using its services. As an example, we demonstrate that deploying network functions at the edge significantly reduces the signals exchanged within a mobile network.

Network function (NF) developers have traditionally prioritized performance when creatingnew packet processing capabilities. This was usually driven by a market demand for highly available solu-tions with differentiating features running at line rate, even at the expense of flexibility and tightly-coupledmonolithic designs. Today, however, the market advantage is achieved by providing more features in shorterdevelopment cycles and quickly deploying them in different operating environments. In fact, networkoperators are increasingly adopting continuous software delivery practices as well as new architectural styles(e.g.,microservices) to decouple functionality and accelerate development. A key challenge in revisiting NFdesign is state management, which is usually highly optimized for a deployment by carefully selecting theunderlying data store. Therefore, migrating to a data store that suits a different use case is time-consumingas it requires code refactoring and adaptation to new application programming interfaces, APIs. As aresult, refactoring NF software for different environments can take up to months, reducing the pace atwhich new features and upgrades can be deployed in production networks. In this paper, we demonstrateexperimentally that it is feasible to introduce an abstraction layer to decouple NF state management from thedata store adopted while still approaching line-rate performance. We presentFlexState, a state managementsystem that exposes data store functionality asconfiguration options, which reduces code refactoring efforts.Experiments show that FlexState achieves significant flexibility in optimizing the state management, andaccelerates deployment on new scenarios while preserving performance and scalability.

In recent years, the number of appliances connected to the Interned has steadily increased thanks to the wide popularity of WiFi/3G enabled mobile devices. This has led to an increase of multimedia resource consumption, causing traffic overload problems for classic resource providers. Different solutions have been studied to shift this traffic overhead from the server(s) towards the client(s) through the employment of the so called swarming protocols. However, most of these solutions have been verified only through simulations. While simulations consist in a necessary first step, they can be far from the actual outcome of employing real protocols and devices. To this end, in this paper we describe BlueFall, an application that could allow to test swarming protocols using actual mobile phones. Pursuing our goal, we provide some preliminary evidence on two simple swarming schemes we have implemented in our testbed.