Microservices are gaining tremendous traction in industry and a growing scientific interest in academia. More and more companies are adopting this architectural style for modernizing their products and taking advantage of its promised benefits (e.g., agility, scalability). Unfortunately, the process of moving towards a microservice-based architecture is anything but easy, as there are plenty of challenges to address from both technical and organizational perspectives. In this paper we report about an empirical study on migration practices towards the adoption of microservices in industry. Specifically, we designed and conducted a survey targeting practitioners involved in the process of migrating their applications and we collected information (by means of interviews and questionnaires) on (i) the performed activities, and (ii) the challenges faced during the migration. Our findings benefit both (i) researchers by highlighting future directions for industryrelevant problems and (ii) practitioners by providing a reference framework for their (future) migrations towards microservices.

In a world of open data and large-scale measurements, it is often feasible to obtain a real-world trace to fit to one's research problem. Feasible, however, does not imply simple. Taking next-generation cellular network planning as a case study, in this paper we describe a large-scale dataset, combining topology, traffic demand from call detail records, and demographic information throughout a whole country. We investigate how these aspects interact, revealing effects that are normally not captured by smaller-scale or synthetic datasets. In addition to making the resulting dataset available for download, we discuss how our experience can be generalized to other scenarios and case studies, i.e., how everyone can construct a similar dataset from publicly available information.

Microservices are a new trend rising fast from the enterprise world. Even though the design principles around microservices have been identified, it is difficult to have a clear view of existing research solutions for architecting microservices. In this paper we apply the systematic mapping study methodology to identify, classify, and evaluate the current state of the art on architecting microservices from the following three perspectives: publication trends, focus of research, and potential for industrial adoption. More specifically, we systematically define a classification framework for categorizing the research on architecting microservices and we rigorously apply it to the 71 selected studies. We synthesize the obtained data and produce a clear overview of the state of the art. This gives a solid basis to plan for future research and applications of architecting microservices.

Service providers are expected to play an increasingly central role in the mobile market and their relationship with the traditional mobile network operators (MNOs) is starting to change. The dilemma faced by over-the-top service-providers (OTTs) is now whether to enter into a service level agreement with the MNOs (in the same spirit of mobile virtual network operator agreements) or to invest in deploying their own network infrastructure to serve their demand. The purpose of this paper is to study the factors shaping the agreements between OTTs and MNOs and how these factors impact network planning decisions. To this end, we build a synthetic model of cellular network deployment that explores how traditional mobile operators and OTTs compete in deploying new infrastructure. Using our model in conjunction with real-world data, we find that service-driven networks are heavily influenced by regulatory decisions, and that cost structures and demand characteristics play non-marginal roles in the definition of service-driven networks.

Implementation of carrier sensing-based medium access control (MAC) protocols on inexpensive reconfigurable radio platforms has proven challenging due to long and unpredictable delays associated with both signal processing on a general purpose processor (GPP) and the interface between the radio frequency (RF) front end and the GPP. This paper describes the development and implementation of a split-functionality architecture for a contention-based carrier sensing MAC, in which some of the functions reside on an field-programmable gate array (FPGA) and others reside in the GPP. We provide an FPGA-based implementation of a carrier sensing block and develop two versions of a carrier sense multiple access (CSMA) MAC protocol based upon this block. We experimentally test the performance of the resulting protocols in a multihop environment in terms of end-to-end throughput and required frame retransmissions. We cross-validate these results with a network simulator with modules modified to reflect the mean and variance of delays measured in components of the real software-defined radio system.

In this paper, we investigate the performance of the dynamic allocation of resources between separate cellular networks. We propose a Dynamic Internetworking Carrier Aggregation (DI-CA) framework which involves every network operator releasing some of its exclusive, but excess, spectrum to another network operator for a limited time. We derive the basic condition for which DI-CA can improve the performance for all the operators and then propose a distributed scheduling framework that uses coalition formation with uncertainty, in which each independent operator can decide whether or not DI-CA can improve its performance without having information regarding channel conditions or load experienced by other operators. We propose a distributed Bayesian coalition formation algorithm to approach a neighborhood of the Bayesian Nash equilibrium.