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JOX: An event-driven orchestrator for 5G network slicing
... • We show how to perform coordinated actions between the TSN control plane and a multi-layer transport network controller. • We present implementation experience using the JOX open source orchestration software [8], Open Air Interface (OAI) [9], and TSN-enabled prototype devices. ...
... In contrast with related work, we describe in detail the way TSN technology can serve as an enabler for realizing the concept of network slicing under deterministic performance constraints. We also report implementation experience over a real testbed using a prototype solution with TSN-enabled hardware, OpenAirInterface [9], and JOX slice orchestrator [8]. An OAI-based disaggregated Radio Access Network (RAN) testbed was built, where TSN-enabled devices were used to interconnect the different components. ...
... In this section, we describe a primitive end-to-end implementation of the approach. We exploit a TSN hardware prototype solution, OAI testbed implementing the disaggregated RAN, and JOX open-source event-based orchestrator [8]. JOX is part of the MOSAIC-5G ecosystem 4 and is used as an integrated orchestrator for both the mobile network and the TSN network. ...
In this work, we present and analyze methods and mechanisms for interconnecting a network slice control and management system of the mobile network, with an IEEE Time-Sensitive Network (TSN) control plane. IEEE TSN is gaining momentum as a key technology that is able to provide network service guarantees for Ethernet-based communications. Although Ultra-Reliable Low-Latency Communications (URLLC) have been thoroughly investigated in 5G, incorporating TSN technologies in the Transport Network is expected to unleash the potential of end-to-end deterministic communications, especially in industrial environments and time-critical applications like factory automation. We elaborate on the concepts of a TSN-aware Xhaul network, present a novel architecture, and describe a set of amendments required in order to enable network slicing. With the devised approach, a slice-aware TSN-enabled transport network can be controlled and managed in an end-to-end orchestrated way. Implementation experience and evaluation results are reported using TSN-enabled prototype devices, OpenAirInterface (OAI), and JOX slice orchestrator.
... 2.50%), only 37.50% (resp. 60.0%) of < T, L, T, S > (resp. < S, L, T, S >) instances 8.4. ...
... Complementary, centralized functionalities have few instances that are installed in CUs and are shared by a specific sub-set of DUs. The dependency factors such as varying network latency and capacity has recently motivated experimenting dynamic functional splitting, where the split decision can be reconfigured on a short time scale for one or a few split options[60]. ...
One goal of 5G networks is to integrate into a single physical network a variety of services, each with specific requirements, so that each service can use a logical network tailored to its requirements. The concept of "network slicing" is widely studied for 5G and is considered as the key mechanism for coexisting different services in the same physical infrastructure. A network slice instance can be defined as a set of network functions and resources to execute them and constituting a logical network with the characteristics required by the requested service. The network slicing allows an operator to create logical networks adapted to provide optimized solutions to the different market segments (vertical) according to their requirements (SLA) (performance, isolation, ...). A major challenge is to be able to satisfy these requirements within an end-to-end slice, from the user's equipment to the core network, via the access network, the mobile core and the network of transport. In order to design and manage such networks, several locks must be lifted. In particular, addressing the end-to-end requires to consider heterogeneous resources and networks of very large sizes. In addition, there are several temporal dimensions that need to be addressed together: long-term allocation and short-term allocation, slices, services, and granularity (traffic routing vs. slice resource allocation) . In this context, several challenges need to be addressed: -design the "slices" network according to the requirements of the services, -allocate physical resources to "slices" by respecting isolation properties and possible priorities between slices -determine orchestration rules for each slice to ensure that each traffic flow respects its SLAs. The overall goal of the thesis is to study the problem of slice management and end-to-end 5G networks and to propose mathematical models and innovative algorithms to solve it. For this, it is expected a implementation of a global approach integrating the three challenges stated above into a single problem that will need to be modeled, studied and solved, using the tools of linear programming (decomposition techniques ...) and respecting the technological constraints being defined by 5G standardization organizations.
... We use a reference environment for all the different orchestration software, and similar baseline images for the services, and execute the experiments across a different set of nodes. The orchestration software that we focus on are: 1) for Virtual Machines Openstack [7] and OpenVIM [8], 2) for docker services Kubernetes [9], Nomad [10] and Openstack ZUN [11], and 3) for Linux containers Fog05 [12] and JOX [13]. The provided results reveal the time needed to deploy the reference services over the same platform, and highlight the pros and cons of each of the employed solutions. ...
... JOX [13] has been designed and developed by Eurecom for the requirements of the Mosaic5G [17] initiative. It is an open-source python-based orchestrator specifically created to support network slicing for virtualized networks. ...
The adoption of Network Functions Virtualization (NFV) is considered as one of the enablers for a fully softwarized 5G architecture, that allows significantly higher flexibility for network service providers to instantiate services, conFigure and update them, as well as to truly realize multi-tenancy. The key enablers of the NFV technology lie in the evolution of virtualization technologies, such as the long established Virtual Machines, and the more recent paradigms of containers for micro-services, like docker and LXC. Such technologies allow the virtualization to span even to the wireless RAN, with fully softwarized base station architectures. Nevertheless, with the plethora of different virtualization technologies, several Virtual Infrastructure Managers (VIMs) and service orchestrators have emerged, each of them addressing different aspects for the provided services e.g. possible nomadic behaviour of the hosting computers, resource constrained devices hosting the services and services deployed for time critical services to name a few. In this work, we use a reference setup and experiment with some of the most widely adopted infrastructure managers, trying to experimentally derive and validate their differences under varying loads of traffic. Our results reveal the time needed for instantiating the same service function, for dockers, containers and Virtual Machines, for a different number of VNFs.
... JOX [99] is a Juju-based service orchestrator that can interact with CN functionalities using the orchestrator plugins. JOX supports the orchestration of the virtualized network to deploy the network slices. ...
Fifth-generation (5G) mobile networks fulfill the demands of critical applications, such as Ultra-Reliable Low-Latency Communication (URLLC), particularly in the automotive industry. Vehicular communication requires low latency and high computational capabilities at the network's edge. To meet these requirements, ETSI standardized Multi-access Edge Computing (MEC), which provides cloud computing capabilities and addresses the need for low latency. This paper presents a generalized overview for implementing a 5G-MEC testbed for Vehicle-to-Everything (V2X) applications , as well as the analysis of some important testbeds and state-of-the-art implementations based on their deployment scenario, 5G use cases, and open source accessibility. The complexity of using the testbeds is also discussed, and the challenges researchers may face while replicating and deploying them are highlighted. Finally, the paper summarizes the tools used to build the testbeds and addresses open issues related to implementing the testbeds.
... A design with a similar target but distinct differences to our approach is JOX [11], a Juju-based slicing-oriented orchestration scheme. Although the design of JOX does not preclude an NSMF operation, it is more oriented towards providing NSSMF functionality and does not address slice selection issues. ...
Through network slicing, different requirements of different applications and services can be met. These requirements can be in terms of latency, bandwidth, mobility support, defining service area, as well as security. Through fine and dynamic tuning of network slices, services can have their delivery platforms constantly customized according to their changing needs. In this article, we present our implementation of an E2E network slice orchestration platform, evaluate its performance in terms of dynamic deployment of network slices in an E2E fashion, and discuss how its functionality can be enhanced to better customize the network slices according to the needs of their respective services.
... As it is a closed-loop architecture, the second part is to continuously monitor the orchestrated resources and update the system for optimal resource configuration. Hence, perceiving the current state of the system and projecting the system status to the NN model, the future state of the system is determined, which proactively updates the system configurations to assure service provisioning [25][26][27][28][29][30][31][32][33]. ...
The scope of the 5G network is not only limited to the enhancements in the form of the quality of service (QoS), but it also includes a wide range of services with various requirements. Besides this, many approaches and platforms are under the umbrella of 5G to achieve the goals of end-to-end service provisioning. However, the management of multiple services over heterogeneous platforms is a complex task. Each platform and service have various requirements to be handled by domain experts. Still, if the next-generation network management is dependent on manual updates, it will become impossible to provide seamless service provisioning in runtime. Since the traffic for a particular type of service varies significantly over time, automatic provisioning of resources and orchestration in runtime need to be integrated. Besides, with the increase in the number of devices, amount, and variety of traffic, the management of resources with optimization becomes a challenging task. To this end, this manuscript provides a solution that automates the management and service provisioning through multiple platforms while assuring various aspects, including automation, resource management and service assurance. The solution consists of an intent-based system that automatically manages different orchestrators, and eliminates manual control by abstracting the complex configuration requirements into simple and generic contracts. The proposed system considers handling the scalability of resources in runtime by using Machine Learning (ML) to automate and optimize service resource utilization.
... Complementary, centralized functionalities have few instances that are installed in CUs and are shared by a specific sub-set of DUs. The dependency factors such as varying network latency and capacity has recently motivated experimenting dynamic functional splitting, where the split decision can be reconfigured on a short time scale for one or a few split options [43]. Table III depicts different fronthaul (FH) bitrates and latency indicators for each functional split. ...
We model the network slice provisioning as an optimization problem including novel mapping and provisioning requirements rising with new radio and core function placement policies. We propose an open-access framework based on an MILP formulation that encompasses flexible functional splitting, with possibly different splitting for different slices and slice subnets, while taking into account different network sharing policies from 5G specifications. We also consider novel mapping and continuity constraints specific to the 5G architectures and beyond. We show by numerical simulations the impact of taking into full and partial consideration these peculiar novel technical constraints.
... The Maestro platform in [21] provides an NFV orchestrator for wireless environments, aware of the features of the VNFs that it is going to deploy. Similarly, in [22] the authors build an orchestrator that can deploy software base stations based on the OpenAirInterface platform [4] and compatible radio front-ends (SDRs). In [23] the authors model and use simulations to validate their approach on adaptive and dynamic VNF allocation problem when considering VNF migration in service function chains, even when using wireless networks for their control channel. ...
Network Functions Virtualization Management and Orchestration (NFV-MANO) provides a standardized approach for the management and effortless deployment of (virtual) services. Although NFV-MANO initially focused on the deployment of services over datacenters, the introduction of fully softwarized network architectures even for the wireless network creates fertile ground for the re-conception of the manner through which the underlying hardware is managed. In this paper, we consider the case of an open experimentation testbed, with focus on wireless networking, and adopt the Open Source MANO framework for provisioning virtual services on top of the experimentation equipment. We extend the Virtual Infrastructure Managers (VIMs) of the NFV-MANO architecture in two well-known frameworks (Openstack and OpenVIM) for the testbed in order to create and handle virtualized wireless network interfaces, hosted on the generic networking nodes of the testbed. Through our contributions, existing VNFs can be deployed over the testbed interconnected over wireless links, specified during the on-boarding phase. The extensions are introduced transparently to the existing operation of the platform, in order to allow the portability of network services and network functions to other instances as well. We focus on providing virtual functions inter-networked over wireless links, which traditionally are not handled by the framework, and allow easier interaction of the end-users with the testbed. We benchmark the framework in terms of performance and analyze the deployment case of a softwarized 5G Radio Access Network in a real testbed deployment.
... Although the Cloudify was not worked on the basis of NFV MANO. JOX [14] is another open-source orchestrator developed by EURECOM and MOSAIC5G, it is an event-driven orchestrator for network slicing and implemented with JujuCharms NFs. The MOSAIC community [15] have been also provided the solution for slicing the RAN resources with the FlexRAN controller. ...
Network slicing is an important pillar of 5G networks that empowers the network operators to provide the different quality of services (QoS) to the users. It enables network operators to split the physical network into multiple logical networks to meet different QoS requirements. In this research paper, we have designed an intent-based network slicing framework that can slice and manage the core network and radio access network (RAN) resources efficiently. It is an automated system, where users just needs to provide higher-level information in the form of intents/contracts for a network slice, and in return our system deploys and configures the requested resources. Moreover, a deep learning model Generative Adversarial Neural Network (GAN) has been used for the management of network resources. Several tests have been performed by creating three slices with our system, which shows better performance in terms of bandwidth and latency.
... One of the most popular open-source implementations for mobile networks is Open Air Interface (OAI) 9 , which provides SDR implementations of UE and Evolved Node B (eNB), as well as support for a small EPC. OAI is now also used in the Mosaic5G an initiative targeting the development of 5G open-source networks, for instance in [HNS + 17a] they describe their low latency MEC implementation or in [KNH18] they cover their orchestrator for network slicing. SRS 10 also provides an open-source implementation of a base station and a UE with support for the VOLK 11 acceleration libraries to improve performance, some examples of usage can be found in [GZW18] and [GSN + 17], which provides results for a system to combine LTE Unlicensed (LTE-U) with Wi-Fi. ...
Mission Critical Communications (MCC) have been typically provided by proprietary radio technologies, but, in the last years, the interest to use commercial-off-the-shelf mobile technologies has increased. In this thesis, we explore the use of LTE to support MCC. We analyse the feasibility of LTE networks employing an experimental platform, PerformNetworks. To do so, we extend the testbed to increase the number of possible scenarios and the tooling available. After exploring the Key Performance Indicators (KPIs) of LTE, we propose different architectures to support the performance and functional requirements demanded by MCC.
We have identified latency as one of the KPI to improve, so we have done several proposals to reduce it. These proposals follow the Mobile Edge Computing (MEC) paradigm, locating the services in what we called the fog, close to the base station to avoid the backhaul and transport networks. Our first proposal is the Fog Gateway, which is a MEC solution fully compatible with standard LTE networks that analyses the traffic coming from the base station to decide whether it has to be routed to the fog of processed normally by the SGW. Our second proposal is its natural evolution, the GTP Gateway that requires modifications on the base station. With this proposal, the base station will only transport over GTP the traffic not going to the fog.
Both proposals have been validated by providing emulated scenarios, and, in the case of the Fog Gateway, also with the implementation of different prototypes, proving its compatibility with standard LTE network and its performance. The gateways can reduce drastically the end-to-end latency, as they avoid the time consumed by the backhaul and transport networks, with a very low trade-off.
... Orchestrators for 5G network slicing are becoming complementary to allow fast innovation, which is why most of the current solutions are open-source [207] . In order to realize the network slicing vision, an Orchestrator , a software responsible for automating the creation, monitoring and deployment of resources and services in the underlying softwarized and the virtualized environment is required. ...
In this paper, we provide a comprehensive review and updated solutions related to 5G network slicing using SDN and NFV. Firstly, we present 5G service quality and business requirements followed by a description of 5G network softwarization and slicing paradigms including essential concepts, history and different use cases. Secondly, we provide a tutorial of 5G network slicing technology enablers including SDN, NFV, MEC, cloud/Fog computing, network hypervisors, virtual machines & containers. Thidly, we comprehensively survey different industrial initiatives and projects that are pushing forward the adoption of SDN and NFV in accelerating 5G network slicing. A comparison of various 5G architectural approaches in terms of practical implementations, technology adoptions and deployment strategies is presented. Moreover, we provide a discussion on various open source orchestrators and proof of concepts representing industrial contribution. The work also investigates the standardization efforts in 5G networks regarding network slicing and softwarization. Additionally, the article presents the management and orchestration of network slices in a single domain followed by a comprehensive survey of management and orchestration approaches in 5G network slicing across multiple domains while supporting multiple tenants. Furthermore, we highlight the future challenges and research directions regarding network softwarization and slicing using SDN and NFV in 5G networks.
... Orchestrators for 5G network slicing are becoming complementary to allow fast innovation, which is why most of the current solutions are open-source [206]. In order to realize the network slicing vision, an Orchestrator, a software responsible for automating the creation, monitoring and deployment of resources and services in the underlying softwarized and the virtualized environment is required. ...
The increasing consumption of multimedia services and the demand of high-quality services from customers has triggered a fundamental change in how we administer networks in terms of abstraction, separation, and mapping of forwarding, control and management aspects of service. The industry and the academia are embracing 5G as the future network capable to support next generation vertical applications with different service requirements. To realize this vision in 5G network, the physical network has to be sliced into multiple isolated logical networks of varying sizes and structures which are dedicated to different types of services based on their requirements with different characteristics and requirements(e.g., a slice for massive IoT devices, smartphones or autonomous cars, etc.). Softwarization using Software-Defined Networking (SDN) and Network Function Virtualization (NFV)in 5G networks are expected to fill the void of programmable control and management of network resources.
In this paper, we provide a comprehensive review and updated solutions related to 5G network slicing using SDN and NFV. Firstly, we present 5G service quality and business requirements followed by a description of 5G network softwarization and slicing paradigms including essential concepts, history and different use cases. Secondly, we provide a tutorial of 5G network slicing technology enablers including SDN, NFV, MEC, cloud/Fog computing, network hypervisors, virtual machines & containers. Thidly, we comprehensively survey different industrial initiatives and projects that are pushing forward the adoption of SDN and NFV in accelerating 5G network slicing. A comparison of various 5G architectural approaches in terms of practical implementations, technology adoptions and deployment strategies is presented.. Moreover, we provide discussion on various open source orchestrators and proof of concepts representing industrial contribution.. The work also investigates the standardization efforts in 5G networks regarding network slicing and softwarization. Additionally, the article presents the management and orchestration of network slices in a single domain followed by a comprehensive survey of management and orchestration approaches in 5G network slicing across multiple domains while supporting multiple tenants. Furthermore, we highlight the future challenges and research directions regarding network softwarization and slicing using SDN and NFV in 5G networks.
... It generates S1-U tunnel and SGI tunnel for every slice. This is represented by the creation of a GTP-Tunnel between the UE and the vSPGW-U upon PDU session establishment [16]. ...
The upcoming 5G networks not only have to support increasing data rates but also must provide a common infrastructure on which new services with vastly different network QoS requirements with lower delay are delivered. More precisely, applications for VANETs, that are mainly oriented to safety issues and entertainment (e.g. video streaming and video-on-demand, web browsing) are increasing. Most of these applications have strict latency constraints of the order of few milliseconds, and very high reliability requirements. To address such needs, a 5G platform needs the ability to dynamically create programmable virtual networks and differentiated traffic treatment utilizing solutions such as network slicing. To this end, in this paper, we propose a programmable and dynamic end-to-end slicing mechanism in an M-CORD based LTE network. One of the key features of M-CORD that the proposed network slicing mechanism utilizes is the virtualized EPC that enables customization and modification. M-CORD provides necessary functionality to program slice definitions, where the proposed mechanism fully follows its software-defined approach. Furthermore, we demonstrate how end devices placed in different slices can be allocated with different QoS treatments from the network operator based on end-user type. The results show that the proposed network slicing mechanism selects appropriate slices and allocates resources to users specific to their needs and service type.
... The work in [8] proposes an event-driven slice management framework capable of orchestrating network slices composed by VNFs, Physical Network Functions (PNFs) and Virtualized Network Applications (VNAs). The proposed framework relies on plugins for supporting additional network resources (e.g. ...
This paper proposes a slice management and orchestration framework for abstracting the instantiation of end-to-end network slices, which are composed by a chain of both physical and virtual network functions. In this line, the proposed SliMANO framework is a plug-in based system that requests network resources and coordinates the interaction among network orchestration entities for its instantiation and chaining in order to perform an end-to-end slice. These entities could range from management and orchestration (MANO), Software Defined Networking (SDN) controllers and Radio Access Network (RAN) controllers. A proof-of-concept prototype was implemented and experimentally evaluated, with results showcasing its feasibility. The results revealed a increase in the delay, associated with instantiation and deletion operations, when compared with the recently introduced network slicing feature (NetSlice) of the Open-source Management and Orchestration (OSM). Results showed that the delay is mostly associated to SliMANO being an entity external to the orchestrator itself, which comes as a trade-off for its added inter-operation capabilities. Moreover, SliMANO goes beyond the MANO domain and actually allows the interaction with SDN and RAN controllers.
... Paper [3] proposed that the stricter intra-slice separation would require more bandwidth, and more stringent E2E deploy requirements impact resource utilization and request acceptance rate. JOX [4] is an event-driven network slicing orchestrator, which is implemented with the jujucharms [5]. JOX supportes virtualized service chains, could be deployed on KVM or LXC. ...
... Although the needed time is longer that in the previous case, this is less than 250 ms. Therefore, the framework is capable of configuring a slice for a given requester in a very short time; the attained figures seem to be highly competitive in comparison with other slicing frameworks [24]. Besides, the life-time for each slice instance is configurable in our platform, e.g., according to the latency requirements of the transported traffic. ...
Internet of Vehicles (IoV) is a hot research niche exploiting the synergy between Cooperative Intelligent Transportation Systems (C-ITS) and the Internet of Things (IoT), which can greatly benefit of the upcoming development of 5G technologies. The variety of end-devices, applications, and Radio Access Technologies (RATs) in IoV calls for new networking schemes that assure the Quality of Service (QoS) demanded by the users. To this end, network slicing techniques enable traffic differentiation with the aim of ensuring flow isolation, resource assignment, and network scalability. This work fills the gap of 5G network slicing for IoV and validates it in a realistic vehicular scenario. It offers an accurate bandwidth control with a full flow-isolation, which is essential for vehicular critical systems. The development is based on a distributed Multi-Access Edge Computing (MEC) architecture, which provides flexibility for the dynamic placement of the
Virtualized Network Functions (VNFs) in charge of managing network traffic. The solution is able to integrate heterogeneous radio technologies such as cellular networks and specific IoT communications with potential in the vehicular sector, creating isolated network slices without risking the Core Network (CN) scalability. The validation results demonstrate the framework capabilities of short and predictable slice-creation time, performance/QoS assurance and service scalability of up to one million connected devices.
... A 5G-EmPOWER controller was used to prototype a Radio Access Network (RAN) Slicing on a wireless LAN environment [16]. Furthermore, a multiservice orchestrator that was developed as a part of the Mosaic5G opensource ecosystem called JOX is described in [17]. Mosaic5G provides agile mobile network service delivery platforms for research and development of 4G and 5G mobile networks. ...
This paper presents the evaluation of the quality of service parameters provided by the network slicing approach for 5G networks based on a software-defined networking environment. The open source controller Floodlight made bandwidth allocation decisions by assigning network slices to user profiles on particular topologies. The objective is to control the bandwidth resources that allow to guarantee latency and reliability values according to the type of service in a sliced 5G network. Thus, it was possible to demonstrate the versatility and scalability of the Floodlight controller, which reduced the loss rate by 10% in a congested network and ensured delays of less than 700ms in applications such as VoIP and video streaming sharing a channel with a limited bit rate of 5 Mbps.
... The MANO architecture is realized by several open-source solutions. For example, Open Source MANO (OSM) [6], Tacker [7], ONAP [8], JOX [9], and SONATA [10]. Most of these solutions focus on orchestration of services consisting of virtual network functions on top of limited resource types. ...
... (1) JOX [13] is an event-driven Juju [3]-based service orchestrator core with several plugins to interact with different network domains, e.g., RAN and CN. (2) Store [15] includes a constellation of platform packages, software development kits (SDKs), network control applications and datasets. ...
Network slicing is one of the key enablers to provide the required flexibility and to realize the service-oriented vision toward fifth generation (5G) mobile networks. In that sense, virtualization, softwarization, and disaggregation are core concepts to accommodate the requirements of an end-to-end (E2E) service to be either isolated, shared, or customized. They lay the foundation for a multi-service and multi-tenant architecture, and are realized by applying the principles of software-defined networking (SDN), network function virtualization (NFV), and cloud computing to the mobile networks. Research on these principles requires agile and flexible platforms that offer a wide range of real-world experimentations over different domains to open up innovations in 5G. To this end, we present Mosaic5G, a community-led consortium for sharing platforms, providing a number of software components, namely FlexRAN, LL-MEC, JOX and Store, spanning application, management, control and user plane on top of OpenAirInterface (OAI) platform. Finally, we show several use cases of Mosaic5G corresponding to widely-mentioned 5G research directions.
Network Slicing (NS) is one of the pillars of the fifth/sixth generation (5G/6G) of mobile networks. It provides the means for Mobile Network Operators (MNOs) to leverage physical infrastructure across different technological domains to support different applications. This survey analyzes the progress made on NS resource management across these domains, with a focus on the interdependence between domains and unique issues that arise in cross-domain and End-to-End (E2E) settings. Based on a generic problem formulation, NS resource management functionalities (e.g., resource allocation and orchestration) are examined across domains, revealing their limits when applied separately per domain. The appropriateness of different problem-solving methodologies is critically analyzed, and practical insights are provided, explaining how resource management should be rethought in cross-domain and E2E contexts. Furthermore, the latest advancements are reported through a detailed analysis of the most relevant research projects and experimental testbeds. Finally, the core issues facing NS resource management are dissected, and the most pertinent research directions are identified, providing practical guidelines for new researchers.
With the exponential growth of Internet of Things (IoT) devices, IoT has become a transformative technology with applications spanning various domains. It encompasses a wide range of public and industrial vertical services that come with diverse and stringent Quality of Service (QoS) requirements. Traditional networks often struggle to meet the demands of these diverse IoT services. As a result, the introduction of 5G and Beyond 5G (B5G) networks holds promise in accommodating these diverse IoT services through network slicing technology. Network slicing involves partitioning a single physical network infrastructure into multiple logically isolated networks and ensures dedicated resources to each service as per QoS requirements. Additionally, Multi-Access Edge Computing (MEC) in B5G networks presents an innovative solution to facilitate low-latency communication for IoT services. However, the automatic provisioning and management of end-to-end (e2e) network slicing for IoT services across multi-domain infrastructures pose significant challenges, including manual error-prone resource configuration, network slice template preparation, and human intervention. This paper proposes an automated Artificial Intelligence (AI) and MEC-enabled solution for provisioning and managing network slice resources across multiple domains specifically tailored for IoT services. Our solution provides an abstraction layer that generates slice templates for each domain and automates the deployment of resources based on the specified QoS requirements. It automates the slice resource configuration process, reduces human intervention, and manages the complete lifecycle of IoT slices. We have conducted several tests with our system, creating multiple IoT slices, and have observed stable performance in slice design, resource provisioning, slice isolation, and management.
Network slicing is a critical feature of the beyond fifth-generation (B5G) network that supports a wide range of innovative services from 5.0 industries, next-generation consumer electronics, smart healthcare, etc. Network slicing guarantees the provisioning of quality of service (QoS) aware dedicated resources to each service. However, the orchestration and management of network slicing is very challenging because of the complex configuration process for underlying network resources. Furthermore, the third generation partnership project (3GPP) presented artificial intelligence (AI) based network data analytics function (NWDAF) in 5G for proactive management and intelligence. Therefore, we have developed an intent-based networking (IBN) system for automating network slices and an AI-driven NWDAF for proactive and intelligent resource assurance. The network data analytics function uses a hybrid stacking ensemble learning (STEL) algorithm to predict network resource utilization and a novel automated machine learning (AutoML) and voting ensemble learning-based mechanism to detect and mitigate network anomalies. To validate the performance of the implemented work, real-time datasets were employed, and a comparative analysis was conducted. The experimental result shows that our STEL model enhances the accuracy by 20% and reduces the error rate by 45%. The AutoML and ensemble learning-based optimized model achieved 99.22% accuracy for anomaly detection.
Network slicing in 5G is a solution to accommodate a wide range of services. It also enables the network operators to establish multiple end-to-end (e2e) logically isolated and customized networks with shared or dedicated resources over the same infrastructure. Although, many tools and platforms have been developed to accomplish the management and orchestration (MANO) of e2e network slicing automatically, it is still challenging. Each of these platforms requires expertise and manual effort to define the requirements for the provisioning of the resources. The other issue is the generation of well-defined network slice configurations with lifecycle parameters. To this end, this paper proposes an efficient solution that automates the configuration process and performs the management and orchestration of network slices. This solution contains a one-touch Intent-based Networking (IBN) platform that effectively orchestrates and manages the lifecycle of multi-domain slice resources. IBN automates the process of slice configuration generation, service provisioning, service update, and service assurance by eliminating experts and manual effort. Furthermore, it has an intelligent Deep Learning (DL) based resource update and assurance mechanism which handles the run-time resource scalability and assurance.
Network slicing (NS) presents the key enabler of cellular network improvements. It allows enhancing the performance of diverse requirements supported for verticals industries. The concept of NS was carefully studied over the previous few years, and the primary operational principles were developed. However, there is an important need for more investigations on studying NS to enable further development. This article offers a deep study related to the NS principle, the recent standardization process for Third Generation Partnership Project and Fifth Generation Public Private Partnership, the diverse broad use cases, NS key concepts, NS architectures, and NS management and orchestration. Besides, it discusses radio access network slicing and sharing, the algorithms, the projects, and the NS practical experience and practices. Finally, this article proposes and highlights a possible solution to several open research issues.
The fifth-generation mobile network presents a wide range of services which have differentrequirements in terms of performance, bandwidth, reliability, and latency. The legacy networksare not capable to handle these diverse services with the same physical infrastructure. In this way,network virtualization presents a reliable solution named network slicing that supports serviceheterogeneity and provides differentiated resources to each service. Network slicing enables networkoperators to create multiple logical networks over a common physical infrastructure. In this researcharticle, we have designed and implemented an intent-based network slicing system that can sliceand manage the core network and radio access network (RAN) resources efficiently. It is anautomated system, where users just need to provide higher-level network configurations in theform of intents/contracts for a network slice, and in return, our system deploys and configuresthe requested resources accordingly. Further, our system grants the automation of the networkconfigurations process and reduces the manual effort. It has an intent-based networking (IBN) toolwhich can control, manage, and monitor the network slice resources properly. Moreover, a deeplearning model, the generative adversarial neural network (GAN), has been used for the managementof network resources. Several tests have been carried out with our system by creating three slices,which shows better performance in terms of bandwidth and latency.
The rising of diverse requirements and the traffic explosion lead to many challenges for traditional mobile network architecture on flexibility, scalability, and deployability. Service-based architecture is introduced into mobile networks to meet new requirements in the 5G era. The monolithic network elements are split into smaller network functions to provide customized services. However, the management and deployment of network function in service-based 5G core networks are still big challenges. In this paper, we propose the network automation using Kubernetes for automating application deployment, while using Openshift Operator as a tool to manage 5G services. This operator lets us deploy all Mosaic 5G inside pods. In this Mosaic 5G Operator, especially in custom resource, we define the composition of core network, Radio Access Network (RAN), FlexRAN, ElasticSearch, and Kibana (as data visualization). For this purpose, we use the containerized OpenAirInterface (OAI) to deploy and demonstrate the automatability with extensive slicing radio support.
Index Terms-Mosaic 5G, Kubernetes, OAI, Virtualization, 5G
Through network slicing, different requirements of different applications and services can be met. These requirements can be in terms of latency, bandwidth, mobility support, defining service area, and security. Through fine and dynamic tuning of network slices, services can have their delivery platforms constantly customized according to their changing needs. In this article, we present our implementation of an E2E network slice orchestration platform, evaluate its performance in terms of dynamic deployment of network slices in an E2E fashion, and discuss how its functionality can be enhanced to better customize the network slices according to the needs of their respective services.
The ever-increasing traffic demand is pushing network operators to find new cost-efficient solutions towards the deployment of future 5G mobile networks. The network sharing paradigm was explored in the past and partially deployed. Nowadays, advanced mobile network multi-tenancy approaches are increasingly gaining momentum paving the way towards further decreasing Capital Expenditures and Operational Expenditures (CAPEX/OPEX) costs, while enabling new business opportunities. This paper provides an overview of the 3GPP standard evolution from network sharing principles, mechanisms and architectures to future on-demand multi-tenant systems. In particular, it introduces the concept of the 5G Network Slice Broker in 5G systems, which enables mobile virtual network operators, over-the-top providers and industry vertical market players to request and lease resources from infrastructure providers dynamically via signaling means. Finally, it reviews the latest standardization efforts considering remaining open issues for enabling advanced network slicing solutions taking into account the allocation of virtualized network functions based on ETSI NFV, the introduction of shared network functions and flexible service chaining.
Network Function Virtualization (NFV) has drawn significant attention from both industry and academia as an important shift in telecommunication service provisioning. By decoupling Network Functions (NFs) from the physical devices on which they run, NFV has the potential to lead to significant reductions in Operating Expenses (OPEX) and Capital Expenses (CAPEX) and facilitate the deployment of new services with increased agility and faster time-to-value. The NFV paradigm is still in its infancy and there is a large spectrum of opportunities for the research community to develop new architectures, systems and applications, and to evaluate alternatives and trade-offs in developing technologies for its successful deployment. In this paper, after discussing NFV and its relationship with complementary fields of Software Defined Networking (SDN) and cloud computing, we survey the state-of-the-art in NFV, and identify promising research directions in this area. We also overview key NFV projects, standardization efforts, early implementations, use cases and commercial products.
The idea of programmable networks has recently re-gained considerable momentum due to the emergence of the Software-Defined Networking (SDN) paradigm. SDN, often referred to as a "radical new idea in networking", promises to dramatically simplify network management and enable innovation through network programmability. This paper surveys the state-of-the-art in programmable networks with an emphasis on SDN. We provide a historic perspective of programmable networks from early ideas to recent developments. Then we present the SDN architecture and the OpenFlow standard in particular, discuss current alternatives for implementation and testing of SDN-based protocols and services, examine current and future SDN applications, and explore promising research directions based on the SDN paradigm.
The upcoming 5G ecosystem is envisioned to build business-driven Network Slices to accommodate the different needs of divergent service types, applications and services in support of vertical industries. In this paper, we describe the Network Slicing concept, by unveiling a novel Network Slicing architecture for integrated 5G communications. Further, we demonstrate its realization, for the case of evolved LTE, using state of the art
technologies. Finally, we elaborate on the LTE specific requirements towards 5G and point out existing challenges and open issues.
Allocating resources to virtualized network functions and services to meet service level agreements is a challenging task for NFV management and orchestration systems. This becomes even more challenging when agile development methodologies, like DevOps, are applied. In such scenarios, management and orchestration systems are continuously facing new versions of functions and services which makes it hard to decide how much resources have to be allocated to them to provide the expected service performance. One solution for this problem is to support resource allocation decisions with performance behavior information obtained by profiling techniques applied to such network functions and services. In this position paper, we analyze and discuss the components needed to generate such performance behavior information within the NFV DevOps workflow. We also outline research questions that identify open issues and missing pieces for a fully integrated NFV profiling solution. Further, we introduce a novel profiling mechanism that is able to profile virtualized network functions and entire network service chains under different resource constraints before they are deployed on production infrastructure.
Although the radio access network (RAN) part of mobile networks offers a significant opportunity for benefiting from the use of SDN ideas, this opportunity is largely untapped due to the lack of a software-defined RAN (SD-RAN) platform. We fill this void with FlexRAN, a flexible and programmable SD-RAN platform that separates the RAN control and data planes through a new, custom-tailored southbound API. Aided by virtualized control functions and control delegation features, FlexRAN provides a flexible control plane designed with support for real-time RAN control applications, flexibility to realize various degrees of coordination among RAN infrastructure entities, and programmability to adapt control over time and easier evolution to the future following SDN/NFV principles. We implement FlexRAN as an extension to a modified version of the OpenAirInterface LTE platform, with evaluation results indicating the feasibility of using FlexRAN under the stringent time constraints posed by the RAN. To demonstrate the effectiveness of FlexRAN as an SD-RAN platform and highlight its applicability for a diverse set of use cases, we present three network services deployed over FlexRAN focusing on interference management, mobile edge computing and RAN sharing.
As a chain is as strong as its weakest element, so are the efficiency, flexibility, and robustness of a mobile network, which relies on a range of different functional elements and mechanisms. Indeed, the mobile network architecture needs particular attention when discussing the evolution of 3GPP EPS because it is the architecture that integrates the many different future technologies into one mobile network. This article discusses 3GPP EPS mobile network evolution as a whole, analyzing specific architecture properties that are critical in future 3GPP EPS releases. In particular, this article discusses the evolution toward a "network of functions," network slicing, and software-defined mobile network control, management, and orchestration. Furthermore, the roadmap for the future evolution of 3GPP EPS and its technology components is detailed and relevant standards defining organizations are listed.
Network Function Virtualization (NFV) continues to draw immense attention from researchers in both industry
and academia. By decoupling Network Functions (NFs) from the physical equipment on which they run, NFV promises to reduce Capital Expenses (CAPEX) and Operating Expenses (OPEX), make networks more scalable and flexible, and lead to increased service agility. However, despite the unprecedented interest it has gained, there are still obstacles that must be overcome before NFV can advance to reality in industrial deployments, let alone delivering on the anticipated gains. While doing so, important challenges associated with network and function Management and Orchestration (MANO) need to be addressed. In this article,
we introduce NFV and give an overview of the MANO framework that has been proposed by the European Telecommunications Standards Institute (ETSI). We then present representative projects and vendor products that focus on MANO, and discuss their features and relationship with the framework. Finally, we
identify open MANO challenges as well as opportunities for future research.
End-to-end service delivery often includes transparently inserted Network Functions (NFs) in the path. Flexible service chaining will require dynamic instantiation of both NFs and traffic forwarding overlays. Virtualization techniques in compute and networking, like cloud and Software Defined Networking (SDN), promise such flexibility for service providers. However, patching together existing cloud and network control mechanisms necessarily puts one over the above, e.g., OpenDaylight under an OpenStack controller. We designed and implemented a joint cloud and network resource virtualization and programming API. In this demonstration, we show that our abstraction is capable for flexible service chaining control over any technology domains.
In this demo, we show a novel method to multi-layer serviceorchestration in a multi-domain network. This method is a basic implementation of the three layered concept with multi-layer orchestration designed by the UNIFY project. A global orchestrator is capable of instantiating service elements, i.e., virtual network functions (VNFs), in separate domains. Dedicated local orchestrators indifferent infrastructure domains are responsible for setting up new VNF instances and configuring the underlying network. Our implementation is based on the ESCAPE prototyping framework and an OpenStack (OS) data center with the OpenDaylight (ODL) controller.
A unifying operating platform for 5g end-to-end and multi-layer orchestration
- A Manzalini
- D R Lopezz
- H Lonsethagen
- L Suciu
- R Bifulcozz
- M.-P Odinixi
- G Celozzix
- B Martinixv
- F Rissoy
- J Garayx
Description of Network Slicing concept
- N Alliance
OpenAirInterface: A flexible platform for 5G research
- N Nikaein
- M K Marina
- S Manickam
- A Dawson
- R Knopp
- C Bonnet