Network Orchestration Research Articles

KeySFC: Traffic steering using strict source routing for dynamic and efficient network orchestration

Current service function chaining (SFC) solutions are cumbersome adaptations of classic routing mechanisms, which lack flexibility and agility to cope with new dynamic services required by network functions virtualization (NFV). These SFC solutions require modification of forwarding tables in both physical and virtual elements in the path when updating a chain. In addition, current SFC implementations restrict traffic engineering to sub-optimal resource allocation solutions, because limited switch table sizes prevent the consideration of all possible traffic paths. Moreover, overlay chaining decisions are usually decoupled from the actual underlay routing of packets across service functions. To tackle these issues, we propose KeySFC, a traffic steering scheme that uses software-defined networking (SDN) and strict source routing. KeySFC exploits the fabric network concept in data center networks (DCNs) in two ways: (i) edge software switches classify, encapsulate, forward, and decapsulate flows with SFC labels; and (ii) core tableless switches forward packets based on simple modulo operations over these labels. Thus, the modification of a small number of flow entries in edge elements allows changing of SFC labels and effectively stitching paths via SDN. An OpenStack-based prototype demonstrates that the traffic steering scheme provided by KeySFC has the potential to enable efficient traffic engineering and to provide agile path migration per SFC segment.

Scalable knowledge-defined orchestration for hybrid optical–electrical datacenter networks [Invited

To better provision fast-emerging network applications with various quality-of-service demands, datacenter network (DCN) operators need an effective network orchestration scheme that can coordinate IT and bandwidth resources for differentiated services in a timely manner. In this work, we consider a hybrid optical–electrical DCN (HOE-DCN) and study how to achieve scalable knowledge-defined network orchestration (KD-NO) for managing the delay-sensitive and delay-tolerant applications in it. For delay-sensitive applications, we leverage a multi-agent scheme to distribute the tasks of placing virtual machines (VMs) in server racks and routing VM traffic in electrical–optical inter-rack clouds to two cooperative deep reinforcement learning modules, respectively. Then, we utilize a classic-algorithm-based module to provision delay-tolerant applications with the residual resources in the HOE-DCN. We design the operation and coordination procedure of the KD-NO system and build a small HOE-DCN testbed that consists of four server racks to demonstrate its performance experimentally. Experimental results indicate that our KD-NO system can make timely and correct network orchestration decisions and have better convergence performance compared with the existing benchmark.

5G V2X System-Level Architecture of 5GCAR Project

One of the goals of the 5G Communication Automotive Research and innovation (5GCAR) project has been to evaluate and propose system architecture enhancements aiming at supporting the strict requirements of vehicle-to-everything (V2X) use cases. In this paper, we provide an overview of 3GPP 5G system architecture, which is used as a baseline architecture in the project, and we present the main architectural enhancements introduced by 5GCAR. The work of the project focused on the following categories: (i) end-to-end security, also including aspects of privacy; (ii) network orchestration and management; (iii) network procedures; (iv) edge computing enhancements; and (v) multi-connectivity cooperation. The enhancements introduced by 5GCAR to above-listed categories are discussed in this paper, while a more detailed analysis of some selected features is presented.

Orchestration of heterogeneous wireless networks: State of the art and remaining challenges

Wireless devices have a plethora of technologies at their disposal to connect to the Internet and other services. Management and control of each technology are traditionally isolated, and coordination between technologies is nearly non-existent. This isolation leads to poor resource usage, which in turn reduces performance and service guarantees. To satisfy growing user demands, we need to leverage the different service guarantees offered by each technology. Additionally, we need to improve orchestration between technologies to increase performance and flexibility while offering a more extensive range of service guarantees and maximizing resource utilization across networks and users. In this work, we present the general challenges one encounters when managing heterogeneous wireless networks. We argue that the primary challenge is the heterogeneity itself, the number of different devices and technologies, the different service requirements, and the increasing complexity as a consequence. However, technology abstraction can overcome these challenges. We provide an overview of state of the art commercial and scientific solutions and show their strengths and weaknesses. Based on this, we discuss the current status and what future challenges still await to provide full seamless heterogeneous wireless network management.

Artificial Intelligence for Elastic Management and Orchestration of 5G Networks

The emergence of 5G enables a broad set of diversified and heterogeneous services with complex and potentially conflicting demands. For networks to be able to satisfy those needs, a flexible, adaptable, and programmable architecture based on network slicing is being proposed. A softwarization and cloudification of the communications networks is required, where network functions (NFs) are being transformed from programs running on dedicated hardware platforms to programs running over a shared pool of computational and communication resources. This architectural framework allows the introduction of resource elasticity as a key means to make an efficient use of the computational resources of 5G systems, but adds challenges related to resource sharing and efficiency. In this article, we propose Artificial Intelligence (AI) as a built-in architectural feature that allows the exploitation of the resource elasticity of a 5G network. Building on the work of the recently formed Experiential Network Intelligence (ENI) industry specification group of the European Telecommunications Standards Institute (ETSI) to embed an AI engine in the network, we describe a novel taxonomy for learning mechanisms that target exploiting the elasticity of the network as well as three different resource elastic use cases leveraging AI. This work describes the basis of a use case recently approved at ETSI ENI.

Hybrid Orchestration in Multi-stakeholder Innovation Networks: Practices of mobilizing multiple, diverse stakeholders across organizational boundaries

The prominence of inter-organizational networks for innovation raises questions about how to support collaboration between multiple, diverse stakeholders. We focus on network orchestration and examine the practices that support orchestrators in dealing with the challenges brought by the number and diversity of stakeholders. Using qualitative, longitudinal data from an innovation network of 57 stakeholders, we identify three types of orchestration practices – connecting, facilitating and governing – and observe how they underlie innovation trajectories over time, each supporting the achievement of distinct network outcomes. Within and across trajectories, we observe how orchestrators rely on hybrid orchestration: they switch between dominating and consensus-based orchestration modes, in response to emergent network challenges. By switching between modes, orchestrators address the complexities of simultaneously and temporally dealing with a large number and diversity of stakeholders. With these findings, we present a toolbox of practices for network orchestrators to address distinct challenges in different types of networks and underscore that network research should consider the plurality of networks, rather than treat them as universalistic. Orchestrators play a key role in managing this plurality: they act as environmental scanners who address emergent network challenges through hybrid orchestration. This realization opens new avenues for network research, for example, relating to the skills and capabilities of orchestrators.

Hybrid Orchestration in Multi-stakeholder Innovation Networks: Practices of mobilizing multiple, diverse stakeholders across organizational boundaries:

The prominence of inter-organizational networks for innovation raises questions about how to support collaboration between multiple, diverse stakeholders. We focus on network orchestration and exam...

Service Shifting: A Paradigm for Service Resilience in 5G

Many real-world services can be provided through multiple virtual network function (VNF) graphs, corresponding, for example, to high- and low-complexity variants of the service itself. Based on this observation, we extend the concept of service scaling in network orchestration to service shifting, that is, upgrading or downgrading the VNF graph to use among those implementing the same service. Service shifting can serve multiple goals, from reducing operational costs to reacting to infrastructure problems. Furthermore, it enhances the flexibility of service-level agreements between network operators and third-party content providers (verticals). In this article, we introduce and describe the service shifting concept, its benefits, and the associated challenges, with special reference to how service shifting can be integrated within real-world 5G architectures and implementations. We conclude that existing network orchestration frameworks can be easily extended to support service shifting, and its adoption has the potential to make 5G network slices easier for the operators to manage under highload conditions, while still meeting the verticals' requirements.

Artificial Intelligence for Elastic Management and Orchestration of 5G Networks

Artificial Intelligence for Elastic Management and Orchestration of 5G Networks

Predictive Analytics Based Knowledge-Defined Orchestration in a Hybrid Optical/Electrical Datacenter Network Testbed

For datacenter networks (DCNs), it is always important to have an effective network orchestration scheme that can coordinate the usages of IT and bandwidth resources timely. In this paper, we consider the hybrid optical/electrical DCNs (HOE-DCNs) and propose a knowledge-defined network orchestration (KD-NO) system for them. The KD-NO system follows the predictive analytics in human behaviors, which includes forecasting based on memory and decision making based on knowledge. To explain the design of our KD-NO system, we first discuss how to fetch low-level knowledge from the telemetry data about the resource utilization in an HOE-DCN. Then, we describe how to optimize the HOE-DCN's configuration for network orchestration. Specifically, we design an online scheme based on deep reinforcement learning, and make sure that it can extract high-level knowledge from the low-level input and come up with optimal HOE-DCN configurations on-the-fly. We prototype the proposed KD-NO system and demonstrate it in an HOE-DCN testbed. The experiments run Hadoop applications in the testbed and show that our KD-NO system can make timely and correct decisions in different experimental schemes by leveraging the two-level knowledge, maintain a high matching degree between the HOE-DCN's configuration and the applications running in it, and thus, effectively reduce the job completion time.

Hybrid Communication Path Orchestration for 5G Heterogeneous Ultra-Dense Networks

The heterogeneous ultra-dense network (UDN) has been widely regarded as a promising architecture for coping with the massive data traffic in future mobile networks including fifth generation mobile networks. There have been innumerable research efforts toward boosting the capacity of UDNs. Global communication path orchestration can better utilize UDN capacity; unfortunately, few studies focus on this topic. In this article, we propose a communication path orchestration architecture for heterogeneous UDNs. In this architecture, data can be transported from one interior communication node (i.e., a base station or user device) to another interior node along a hybrid device communication path (HDCP). HDCPs can be used for communications between two user devices and can be used to migrate traffic between backhaul links. Application- layer-assisted data forwarding allows HDCP to include various communication links including access links, backhaul links, and device-to-device links using licensed and unlicensed spectrum resources. HDCPs are centrally arranged to meet specific requirements and designated optimization objectives. We introduce two HDCP orchestration methods in this article. Our proposed solution can be used as a significant supplement to existing techniques for heterogeneous UDNs.

Orchestrating international production networks when formal authority shifts

We investigate how a brand-owning MNE can coordinate and safeguard exchanges in its international production network following a decline in formal authority and a shift in ‘hub firm’ status to another member of the network. Our empirical material is drawn from a case study of a Norwegian shipbuilder. We illuminate what mechanisms are used by a network orchestrator in a peripheral position with limited formal authority, when they are used, and by whom they are developed and deployed. Our findings question and extend theorizations that assume a single, stable orchestrator, and that typically give primacy to the ‘executive suite’.

5G‐Hander: A network service for handover detection in 5G networks

In the next Fifth Generation (5G) networks, Telco Operators will assign network slices to their users and will guarantee very stringent requirements even in mobility. In this context, detecting handover events will be challenging in order to design management and orchestration policies allowing resource allocation and network slice assignment dynamically. To this purpose, this letter proposes a network service called 5G‐Hander that enables the Network Orchestrator to be alerted of an incoming handover before it is completed, in order to decide resource reallocation or even to inhibit its occurrence. Numerical results show how the proposed network service works in a little, but realistic, network.

Combining Soft Systems Methodology with Interpretive Structural Modeling and System Dynamics for Network Orchestration: Case Study of the Formal Science and Technology Collaborative Networks in Iran

The orchestration of collaborative networks plays a fundamental role in shaping and configuring network cooperation and ensuring the success of a network. Despite a notable number of studies conducted, the issue of orchestrating collaborative networks and establishing a relationship among their diverse and dispersed components has not been designed and developed in the form of a coherent model. The purpose of the present study is to cast light on the process of determining the dimensions of formal science and technology collaborative networks in Iran. Soft Systems Methodology (SSM) was utilized due to its high capability to deal with the dynamic complexity of the problem, the various stakeholders and actors involved, and the conflicting interests of these stakeholders. Accordingly, in addition to investigating and interviewing the informants and obtaining a rich picture of the situation, interpretive structural modeling (ISM) was used to design a conceptual model. The results show that in order to improve the problem condition and achieve an effective output of the network, the communication processes of the founding organization, Steering Board, the network leaderboard, and the members should all be subject to proper changes at the right time. Finally, in order to facilitate the analysis of effective variables and the role of the orchestrator in the formal science and technology collaborative networks in Iran by using System Dynamics (SD), a dynamic model was proposed. According to the obtained results, the orchestrator’s ability, trust and motivation of network members, the socialization process of members, and network sustainability are among the most important factors in network orchestration.

Machine Learning in Quantitative Protein-peptide Affinity Prediction: Implications for Therapeutic Peptide Design.

Protein-peptide recognition plays an essential role in the orchestration and regulation of cell signaling networks, which is estimated to be responsible for up to 40% of biological interaction events in the human interactome and has recently been recognized as a new and attractive druggable target for drug development and disease intervention. We present a systematic review on the application of machine learning techniques in the quantitative modeling and prediction of protein-peptide binding affinity, particularly focusing on its implications for therapeutic peptide design. We also briefly introduce the physical quantities used to characterize protein-peptide affinity and attempt to extend the content of generalized machine learning methods. Existing issues and future perspective on the statistical modeling and regression prediction of protein- peptide binding affinity are discussed. There is still a long way to go before establishment of general, reliable and efficient machine leaningbased protein-peptide affinity predictors.

Orquestração de redes de inovação constituídas com o conceito de living lab para o desenvolvimento de inovações sociais

Neste artigo tem-se por objetivo investigar como são orquestradas redes de inovação constituídas com o conceito de living lab, para o desenvolvimento de inovações sociais. Pesquisa pautada na abordagem qualitativa, caracterizada como estudo de caso, tendo como base a coleta de dados a partir de 11 entrevistas semiestruturadas com os responsáveis por dois living labs brasileiros já vinculados a European Network of Living Labs (ENoLL). As interpretações dos textos foram realizadas por meio da técnica de análise de conteúdo e da técnica de adequação ao padrão a partir do conjunto de processos e ações específicas, denominado de “orquestração de redes de inovação”. O estudo promove a conexão da noção de “orquestração de recursos” preconizada na Visão Baseada em Recursos (VBR) com os processos de “orquestração de redes de inovação”. As evidências obtidas demonstram que a adição do processo de gestão da co-criação ao conjunto, reforçado através de algumas ações específicas (empoderamento, engajamento social e conexão social) permite a orquestração de redes de inovação para o desenvolvimento de inovações sociais constituídas em torno do conceito de living lab.

Understanding Digital Innovation from a Layered Architectural Perspective

Digitization of analogue everyday artifacts, i.e. when physical products are equipped with digital capabilities, has a profound impact on today’s society. Some examples of these digital innovations aimed at consumer markets are the “connected” car, the digitized television set, and in the near future, digitized IKEA furniture. Digital innovation provides endless opportunities for providing value adding products and services. However, in digital innovation there is a need to find new ways of organizing network activities, i.e. activities such as e.g. production and translation of knowledge and enrollment of actors. These activities need to embrace and build on the networked aspects and the complexity inherent to digital innovation. This requires network activities that can overcome challenges with the ambiguous and messy characteristics of digital innovation. In this thesis, I propose that the theoretical perspective of network orchestration can enlighten fruitful ways to address challenges that are encountered when organizing network activities in digital innovation. Inspired by practical challenges with digital innovation, as well as contemporary calls for research within IS, this thesis investigates: How can network activities be orchestrated in digital innovation? Two cases of digital innovation aimed at consumer markets are studied. The first case concerns the digitization of the newspaper. The second case regards the digitization of door locks. Literature about digital innovation is used to understand the context of the studied phenomenon. Furthermore, theories about network orchestration as well as activities in innovation are used as a theoretical framework to help answer the research question. The thesis is based on an interpretative perspective where a multi-method approach has been applied to address the research question. The contribution is divided into two different parts. The first part presents four categories of empirically derived network activities that address socio-technical challenges with organizing digital innovation. The second part is a proposed model detailing orchestration of network activities in digital innovation. The model is based around the four suggested categories of network activities: (1) Supporting flexible innovation networks, (2) Production and translation of layered architectural knowledge, (3) Addressing heterogeneous user communities, and (4) Harnessing generativity to leverage value. The categories of network activities can be viewed as building blocks for the orchestration process. By emphasizing both a proactive and a reactive way of orchestrating digital innovation, the model proposes a means for organizations to address the ambiguity and complexity of digital innovation.

Computationally Assisted Discovery and Assignment of a Highly Strained and PANC-1 Selective Alkaloid from Alaska's Deep Ocean.

We report here the orchestration of molecular ion networking and a set of computationally assisted structural elucidation approaches in the discovery of a new class of pyrroloiminoquinone alkaloids that possess selective bioactivity against pancreatic cancer cell lines. Aleutianamine represents the first in a new class of pyrroloiminoquinone alkaloids possessing a highly strained multibridged ring system, discovered from Latrunculia ( Latrunculia) austini Samaai, Kelly & Gibbons, 2006 (class Demospongiae, order Poecilosclerida, family Latrunculiidae) recovered during a NOAA deep-water exploration of the Aleutian Islands. The molecule was identified with the guidance of mass spectrometry, nuclear magnetic resonance, and molecular ion networking (MoIN) analysis. The structure of aleutianamine was determined using extensive spectroscopic analysis in conjunction with computationally assisted quantifiable structure elucidation tools. Aleutianamine exhibited potent and selective cytotoxicity toward solid tumor cell lines including pancreatic cancer (PANC-1) with an IC50 of 25 nM and colon cancer (HCT-116) with an IC50 of 1 μM, and represents a potent and selective candidate for advanced preclinical studies.

Group A Streptococcus-Mediated Host Cell Signaling.

In the past decade, the field of the cellular microbiology of group A Streptococcus (S. pyogenes) infection has made tremendous advances and touched upon several important aspects of pathogenesis, including receptor biology, invasive and evasive phenomena, inflammasome activation, strain-specific autophagic bacterial killing, and virulence factor-mediated programmed cell death. The noteworthy aspect of S. pyogenes-mediated cell signaling is the recognition of the role of M protein in a variety of signaling events, starting with the targeting of specific receptors on the cell surface and on through the induction and evasion of NETosis, inflammasome, and autophagy/xenophagy to pyroptosis and apoptosis. Variations in reports on S. pyogenes-mediated signaling events highlight the complex mechanism of pathogenesis and underscore the importance of the host cell and S. pyogenes strain specificity, as well as in vitro/in vivo experimental parameters. The severity of S. pyogenes infection is, therefore, dependent on the virulence gene expression repertoire in the host environment and on host-specific dynamic signaling events in response to infection. Commonly known as an extracellular pathogen, S. pyogenes finds host macrophages as safe havens wherein it survives and even multiplies. The fact that endothelial cells are inherently deficient in autophagic machinery compared to epithelial cells and macrophages underscores the invasive nature of S. pyogenes and its ability to cause severe systemic diseases. S. pyogenes is still one of the top 10 causes of infectious mortality. Understanding the orchestration of dynamic host signaling networks will provide a better understanding of the increasingly complex mechanism of S. pyogenes diseases and novel ways of therapeutically intervening to thwart severe and often fatal infections.

VNF Placement and Resource Allocation for the Support of Vertical Services in 5G Networks

One of the main goals of 5G networks is to support the technological and business needs of various industries (the so-called verticals), which wish to offer to their customers a wide range of services characterized by diverse performance requirements. In this context, a critical challenge lies in mapping in an automated manner the requirements of verticals into decisions concerning the network infrastructure, including VNF placement, resource assignment, and traffic routing. In this paper, we seek to make such decisions jointly, accounting for their mutual interaction, and efficiently. To this end, we formulate a queuing-based model and use it at the network orchestrator to optimally match the vertical's requirements to the available system resources. We then propose a fast and efficient solution strategy, called MaxZ, which allows us to reduce the solution complexity. Our performance evaluation, carried out accounting for multiple scenarios representative of real-world services, shows that MaxZ performs substantially better than state-of-the-art alternatives and consistently close to the optimum.