Distributed streaming platforms such as Pravega, Kafka, and Pulsar are widely used for high-throughput, low-latency data processing. As these platforms increasingly handle sensitive data, ensuring data confidentiality and integrity becomes critical. Trusted Execution Environments (TEEs) offer secure computations that can be used on client-side processing, but their impact on performance must be carefully assessed. This study evaluates the write latency of Pravega clients running in TEEs compared to those in standard (non-secured) environments. We found that under typical workloads, TEE-based clients experience approximately 50% higher latency due to the overhead of secure executions. However, when data rates exceed 976 MB/s, the Pravega broker reaches its throughput limit, causing latency to spike for standard clients. In contrast, TEE-based clients exhibit more stable latency under these high-throughput conditions. These findings can be helpful for data architects, as systems highlight a trade-off: while latency may increase, the impact could be acceptable in certain scenarios given the enhanced security benefits.

Summary This paper presents the design and prototype implementation of the SELFNET fifth‐generation (5G) mobile edge infrastructure. In line with the current and emerging 5G architectural principles, visions, and standards, the proposed infrastructure is established primarily based on a mobile edge computing paradigm. It leverages cloud computing, software‐defined networking, and network function virtualization as core enabling technologies. Several technical solutions and options have been analyzed. As a result, a novel portable 5G infrastructure testbed has been prototyped to enable the preliminary testing of the integrated key technologies and to provide a realistic execution platform for further investigating and evaluating software‐defined networking– and network function virtualization–based application scenarios in 5G networks.

The emerging Fifth Generation (5G) mobile networks have been attracting enormous attention from various stakeholders around the world. In particular, in the research community, prototyping 5G infrastructures and deploying 5G services have gained gears recently towards realising market-oriented 5G trials. However, accessing to and programming on real-world 5G infrastructure is almost prohibitive for most 5G researchers especially in academia. Therefore, it is critical to build realistic yet cost-efficient 5G infrastructure emulators for 5G research labs to enable credible 5G research activities. This paper proposes such a 5G infrastructure emulator that is able to emulate a realistic 5G network in a lab setting based on a small number of commercial-off-the-shelf servers by leveraging virtualization and other technologies. Moreover, this emulator allows a service provider to automatically deploy 5G services from `empty' machines through advanced automation. The emulation platform is described in details with the 5G infrastructure and service deployment procedure highlighted. Empirical results are presented to show the performance of the proposed emulator.

With the paradigm shift from the current 4G to the forthcoming 5G networks, novel network topology management interfaces become essential mainly due to the associated complexity introduced by the new softwarisation and virtualisation architecture. Moreover, the expected increasing number of users will require a very efficient management of the network resources. This paper proposes a new topology management scheme to report real-time topological information about the mobile users in a softwarised and virtualised 5G network. The proposed API has been designed and prototyped using Software Defined Radio (SDR) and the proven open source software OpenAirInterface and validated using commercial off-the-shelf user equipment.

The next generation mobile networks 5G are currently being intensively developed and standardized globally, with commercial prototyping 5G connections already emerging. At the 5G system level, one of the Key Performance Indicators (KPIs) defining 5G is substantially reduced service creation time for 5G network operators and/or service providers to increase the system efficiency and thus reduce operational costs. In this work, we focus on realize this challenging KPI in terms of speedy creation of monitoring services for 5G operators from scratch (no operating system pre-installed). A new 5G infrastructure orchestrator UWSIO is proposed to achieve fully automated deployment of 5G monitoring services. The architecture of this orchestrator is presented, which is compliant with the ETSI MANO standard to deal with both physical and virtual resources towards establishing the services running over the infrastructure. The proposed orchestrator is implemented in a real-world testbed and the implementation details are provided. Experimental results demonstrate that the performance of the design and implementation of this orchestrator is able to meet the KPI requirement for 5G operators.

With the advances of new‐generation wireless and mobile communication systems such as the fifth‐generation (5G) mobile networks and Internet of Things (IoT) networks, demanding applications such as Ultra‐High‐Definition video applications is becoming ever popular. These applications require real‐time monitoring and processing to meet the mission‐critical quality of service requirements and are expected to be supported by the emerging fog or edge computing paradigms. This paper presentsNFVMon, a novel monitoring architecture to enable flow monitoring capabilities of network traffic in a 5G multioperator mobile edge computing environment. The proposedNFVMonis integrated with the management plane of the Cloud Computing.NFVMonhas been prototyped and a reference implementation is presented. It provides novel capabilities to provide disaggregated metrics related to the different 5G mobile operators sharing infrastructures and also about the different 5G subscribers of each of such mobile operators. Extensive experiments for evaluating the performance of the system have been conducted on a mid‐sized infrastructure testbed.

The progress in realizing the Fifth Generation (5G) mobile networks has been accelerated recently towards deploying 5G prototypes with increasing scale. One of the Key Performance Indicators (KPIs) in 5G deployments is the service deployment time, which should be substantially reduced from the current 90 hours to the target 90 minutes on average as defined by the 5G Public‐Private Partnership (5G‐PPP). To achieve this challenging KPI, highly automated and coordinated operations are required for the 5G network management. This paper addresses this challenge by designing and prototyping a novel 5G service deployment orchestration architecture that is capable of automating and coordinating a series of complicated operations across physical infrastructure, virtual infrastructure, and service layers over a distributed mobile edge computing paradigm, in an integrated manner. Empirical results demonstrate the superior performance achieved, which meets the 5G‐PPP KPI even in the most challenging scenario where 5G services are installed from bare metal.