Abstract: The developments of connected vehicles are heavily influenced by information and communications technologies, which have fueled a plethora of innovations in various areas, including networking, caching, and computing. Nevertheless, these important enabling technologies have traditionally been studied separately in the existing works on vehicular networks. In this paper, we propose an integrated framework that can enable dynamic orchestration of networking, caching, and computing resources to improve the performance of next generation vehicular networks. We formulate the resource allocation strategy in this framework as a joint optimization problem, where the gains of not only networking but also caching and computing are taken into consideration in the proposed framework. The complexity of the system is very high when we jointly consider these three technologies. Therefore, we propose a novel deep reinforcement learning approach in this paper. Simulation results with different system parameters are presented to show the effectiveness of the proposed scheme.

Abstract: Purpose The purpose of this paper is to explore how multinational corporations (MNCs) orchestrate internal and external resources to help their multi-tier supply chains learn sustainability-related knowledge. Design/methodology/approach An exploratory multiple case study approach was adopted and three MNCs’ sustainable initiatives in China were examined. The data were primarily collected through 43 semi-structured interviews with managers of focal companies and their multi-tier suppliers. Findings The authors found that in order to facilitate their supply chains to learn sustainability, MNCs tend to orchestrate in breadth by internally setting up new functional departments and externally working with third parties, and orchestrate in depth working directly with their extreme upstream suppliers adopting varied governance mechanisms on lower-tier suppliers along the project lifecycle. The resource orchestration in breadth and depth and along the project lifecycle results in changes of supply chain structure. Practical implications The proposed conceptual model provides an overall framework for companies to design and implement their multi-tier sustainable initiatives. Companies could learn from the suggested learning stages and the best practices of case companies. Originality/value The authors extend and enrich resource orchestration perspective (ROP), which is internally focused, to a supply chain level, and answer a theoretical question of how MNCs orchestrate their internal and external resources to help their supply chains to learn sustainability. The extension of ROP refutes the resource dependence theory, which adopts a passive approach of relying on external suppliers and proposes that MNCs should proactively work with internal and external stakeholders to learn sustainability.

Abstract: The world of connected devices has led to the rise of the Internet of Things paradigm, where applications rely on multiple devices, gathering and sharing data across highly heterogeneous networks The variety of possible mechanisms, protocols, and hardware has become a hindrance in the development of architectures capable of addressing the most common IoT use cases, while abstracting services from the underlying communication subsystem Moreover, the world is moving toward new strict requirements in terms of timeliness and low latency in combination with ultra-high availability and reliability Thus, future IoT architectures will also have to support the requirements of these cyber-physical applications In this regard, edge computing has been presented as one of the most promising solutions, relying on the cooperation of nodes by moving services directly to end devices and caching information locally Therefore, in this article, we propose a modular and scalable architecture based on lightweight virtualization The provided modularity, combined with the orchestration supplied by Docker, simplifies management and enables distributed deployments, creating a highly dynamic system Moreover, characteristics such as fault tolerance and system availability are achieved by distributing the application logic across different layers, where failures of devices and micro-services can be masked by this natively redundant architecture, with minimal impact on the overall system performance Experimental results have validated the implementation of the proposed architecture for on-demand services deployment across different architecture layers

Abstract: Generally, a service request must specify its required virtual network functions (VNFs) and their specific order, which is known as the service function chain (SFC). When mapping SFCs, network providers face many challenges due to the requirements of maintaining the correct order and satisfying other constraints of VNFs. Furthermore, SFC orchestration becomes a more difficult problem when considered in multi-domain networks, because the confidentiality of the topology information of each domain must be considered. In this paper, we study the problem of SFC orchestration across multiple domains. We first use the full mesh aggregation approach to construct an abstracted network to guide the orchestration process, and then propose two efficient methods for SFC partitioning. Based on the SFC partitioning results, we also propose two heuristic algorithms for deploying the sub-chains in multiple domains. Moreover, when the partitioning results cannot be mapped completely, a feedback mechanism is used to repartition the SFC and improve the success ratio of orchestrating the SFC. Finally, to save bandwidth resources, we further improve our heuristic algorithms by migrating the deployment position of VNFs. The simulation results demonstrate that our proposed algorithm achieves better performance compared to existing solutions.

Abstract: Telecommunication networks are evolving toward a data-center-based architecture, which includes physical network functions, virtual network functions, as well as various types of management and orchestration systems. The primary purpose of this type of heterogeneous network is to provide efficient and convenient communication services for users. However, the diverse factors of a heterogeneous network such as bandwidth, delay, and communication protocol, bring great challenges for routing recommendations. In addition, the growing volume of big data and the explosive deployment of heterogeneous networks have started a new era of applying big data technologies to implement routing recommendations. In this article, a tensor-based big-data-driven routing recommendation framework, including the edge plane, fog plane, cloud plane, and application plane, is proposed. In this framework, a tensor-based, holistic, hierarchical approach is introduced to generate efficient routing paths using tensor decomposition methods. Also, a tensor matching method including the controlling tensor, seed tensor, and orchestration tensor is employed to realize routing recommendation. Finally, a case study is used to demonstrate the key processing procedures of the proposed framework.

Abstract: With software-defined networking (SDN) and network function virtualization (NFV) technologies, network slicing is a promising solution for resource orchestration to achieve quality-of-service (QoS) isolation in customized services in fifth-generation (5G) networks. In this article, we propose a comprehensive network slicing framework for end-to-end (E2E) QoS provisioning, with differentiated resource types in both wireless and wired network domains considered.

Abstract: Dynamic binary analysis techniques play a central role to study the security of software systems and detect vulnerabilities in a broad range of devices and applications. Over the past decade, a variety of different techniques have been published, often alongside the release of prototype tools to demonstrate their effectiveness. Unfortunately, most of those techniques’ implementations are deeply coupled with their dynamic analysis frameworks and are not easy to integrate in other frameworks. Those frameworks are not designed to expose their internal state or their results to other components. This prevents analysts from being able to combine together different tools to exploit their strengths and tackle complex problems which requires a combination of sophisticated techniques. Fragmentation and isolation are two important problems which too often results in duplicated efforts or in multiple equivalent solutions for the same problem – each based on a different programming language, abstraction model, or execution environment. In this paper, we present avatar2, a dynamic multi-target orchestration framework designed to enable interoperability between different dynamic binary analysis frameworks, debuggers, emulators, and real physical devices. Avatar2 allows the analyst to organize different tools in a complex topology and then “move” the execution of binary code from one system to the other. The framework supports the automated transfer of the internal state of the device/application, as well as the configurable forwarding of input/output and memory accesses to physical peripherals or emulated targets. To demonstrate avatar2 usage and versatility, in this paper we present three very different use cases in which we replicate a PLC rootkit presented at NDSS 2017, we test Firefox combining Angr and GDB, and we record the execution of an embedded device firmware using PANDA and OpenOCD. All tools and the three use cases will be released as open source to help other researchers to replicate our experiments and perform their own analysis tasks with avatar2.

Abstract: By providing especially tailored instances of a virtual network,network slicing allows for a strong specialization of the offered services on the same shared infrastructure. Network slicing has profound implications on resource management, as it entails an inherent trade-off between: (i) the need for fully dedicated resources to support service customization, and (ii) the dynamic resource sharing among services to increase resource efficiency and cost-effectiveness of the system. In this paper, we provide a first investigation of this trade-off via an empirical study of resource management efficiency in network slicing. Building on substantial measurement data collected in an operational mobile network (i) we quantify the efficiency gap introduced by non-reconfigurable allocation strategies of different kinds of resources, from radio access to the core of the network, and (ii) we quantify the advantages of their dynamic orchestration at different timescales. Our results provide insights on the achievable efficiency of network slicing architectures, their dimensioning, and their interplay with resource management algorithms.

Abstract: Network slicing allows mobile operators to offer, via proper abstractions, mobile infrastructure (radio, networking, computing) to vertical sectors traditionally alien to the telco industry (e.g., automotive, health, construction). Owning to similar business nature, in this paper we adopt yield management models successful in other sectors (e.g. airlines, hotels, etc.) and so we explore the concept of slice overbooking to maximize the revenue of mobile operators.The main contribution of this paper is threefold. First, we design a hierarchical control plane to manage the orchestration of slices end-to-end, including radio access, transport network, and distributed computing infrastructure. Second, we cast the orchestration problem as a stochastic yield management problem and propose two algorithms to solve it: an optimal Benders decomposition method and a suboptimal heuristic that expedites solutions. Third, we implement an experimental proof-of-concept and assess our approach both experimentally and via simulations with topologies from three real operators and a wide set of realistic scenarios.Our performance evaluation shows that slice overbooking can provide up to 3x revenue gains in realistic scenarios with minimal footprint on service-level agreements (SLAs).

Abstract: With the development of mCRAHNs, more emerging mobile applications and services could be foreseen and applied in our human society. In this article, we propose an emotion-aware cognitive system (ECS), which aims to provide a systematic approach that can facilitate deployment of different emotion-aware mobile applications in mCRAHNs. ECS is constructed to provide multidimensional emotional data collection and processing approaches for mobile applications working in mCRAHNs. Also, we present a flow of emotion-aware solution designed on ECS, and highlight the implementation and orchestration of several key technologies and schemes we apply in this system for different emotion-aware mobile applications in runtime. In addition, we demonstrate the feasibility of the proposed ECS by presenting a novel emotion-aware mobile application, iSmile, and evaluate the system performance based on this application.

Abstract: The pedagogical modelling of everyday classroom practice is an interesting kind of evidence, both for educational research and teachers' own professional development. This paper explores the usage of wearable sensors and machine learning techniques to automatically extract orchestration graphs (teaching activities and their social plane over time), on a dataset of 12 classroom sessions enacted by two different teachers in different classroom settings. The dataset included mobile eye-tracking as well as audiovisual and accelerometry data from sensors worn by the teacher. We evaluated both time-independent and time-aware models, achieving median F1 scores of about 0.7-0.8 on leave-one-session-out k-fold cross-validation. Although these results show the feasibility of this approach, they also highlight the need for larger datasets, recorded in a wider variety of classroom settings, to provide automated tagging of classroom practice that can be used in everyday practice across multiple teachers.

Abstract: When used in classrooms, personalized learning software allows students to work at their own pace, while freeing up the teacher to spend more time working one-on-one with students. Yet such personalized classrooms also pose unique challenges for teachers, who are tasked with monitoring classes working on divergent activities, and prioritizing help-giving in the face of limited time. This paper reports on the co-design, implementation, and evaluation of a wearable classroom orchestration tool for K-12 teachers: mixed-reality smart glasses that augment teachers' realtime perceptions of their students' learning, metacognition, and behavior, while students work with personalized learning software. The main contributions are: (1) the first exploration of the use of smart glasses to support orchestration of personalized classrooms, yielding design findings that may inform future work on real-time orchestration tools; (2) Replay Enactments: a new prototyping method for real-time orchestration tools; and (3) an in-lab evaluation and classroom pilot using a prototype of teacher smart glasses (Lumilo), with early findings suggesting that Lumilo can direct teachers' time to students who may need it most.

Abstract: The adoption of advanced Internet of Things (IoT) technologies has impressively improved in recent years by placing such services at the extreme Edge of the network. There are, however, specific Quality of Service (QoS) trade-offs that must be considered, particularly in situations when workloads vary over time or when IoT devices are dynamically changing their geographic position. This article proposes an innovative capillary computing architecture, which benefits from mainstream Fog and Cloud computing approaches and relies on a set of new services, including an Edge/Fog/Cloud Monitoring System and a Capillary Container Orchestrator. All necessary Microservices are implemented as Docker containers, and their orchestration is performed from the Edge computing nodes up to Fog and Cloud servers in the geographic vicinity of moving IoT devices. A car equipped with a Motorhome Artificial Intelligence Communication Hardware (MACH) system as an Edge node connected to several Fog and Cloud computing servers was used for testing. Compared to using a fixed centralized Cloud provider, the service response time provided by our proposed capillary computing architecture was almost four times faster according to the 99th percentile value along with a significantly smaller standard deviation, which represents a high QoS.

Abstract: The Industrial Internet technologies are anticipated to enable agile manufacturing processes in response to the growing demand for personalised products/services with shorter lifecycles. This trend has resulted in a gradual transformation of traditional ‘tree-like’ and monolithic systems into complex networks of self-contained and autonomous ‘components’ (a.k.a., Internet of things) and ‘services’ (a.k.a., Internet of services). Cloud Manufacturing is an emerging concept that enables modularisation and service-orientation in the context of manufacturing, in which systematic orchestration, matching, and sharing of services and components are the key. This work develops a framework for dynamic integration of manufacturing services and components in a collaborative network of organisations. The framework dynamically recommends the best matching of services, components and organisations, as well as the best collaboration decisions in terms of sharing (shareable) services and/or components between organisation...

Abstract: The traffic explosion and the rising of diverse requirements lead to many challenges for traditional mobile network architecture on flexibility, scalability, and deployability. To meet new requirements in the 5G era, service based architecture is introduced into mobile networks. The monolithic network elements (e.g., MME, PGW, etc.) are split into smaller network functions to provide customized services. However, the management and deployment of network functions in service based 5G core network are still big challenges. In this paper, we propose a novel management architecture for 5G service based core network based on NFV and SDN. Combined with SDN, NFV and edge computing, the proposed framework can provide distributed and on-demand deployment of network functions, service guaranteed network slicing, flexible orchestration of network functions and optimal workload allocation. Simulations are conducted to show that the proposed framework and algorithm are effective in terms of reducing network operating cost.

Abstract: The role of the International Labour Organization (ILO) in the governance of global supply chains is typically neglected or simply dismissed as ineffective. This is understandable as global supply ...

Abstract: Recent advances in ICT enable the evolution of the manufacturing industry to meet the new requirements of the society. Cyber-physical systems, Internet-of-Things (IoT), and Cloud computing, play a key role in the fourth industrial revolution known as Industry 4.0. The microservice architecture has evolved as an alternative to SOA and promises to address many of the challenges in software development. In this paper, we adopt the concept of microservice and describe a framework for manufacturing systems that has the cyber-physical microservice as the key construct. The manufacturing plant processes are defined as compositions of primitive cyber-physical microservices adopting either the orchestration or the choreography pattern. IoT technologies are used for system integration and model-driven engineering is utilized to semi-automate the development process for the industrial engineer, who is not familiar with microservices and IoT. Two case studies demonstrate the feasibility of the proposed approach.

Abstract: Automating the provisioning of telecommunications services, deployed over a heterogeneous infrastructure (in terms of domains, technologies, and management platforms), remains a complex task, yet driven by the constant need to reduce costs and service deployment time. This is more so, when such services are increasingly conceived around interconnected functions and require allocation of computing, storage, and networking resources. This automation drives the development of service and resource orchestration platforms that extend, integrate, and build on top of existing approaches, macroscopically adopting software-defined networking principles, leveraging programmability, and open control in view of interoperability. Such systems are combining centralized and distributed elements, integrating platforms whose development may happen independently and parallel, and are constantly adapting to ever changing requirements, such as virtualization and slicing. Of specific interest is the (optical) transport network segment, traditionally operated independently via closed proprietary systems, and characterized by being relatively complex and hard to reach consensus regarding modeling and abstraction. In view of the targets, the transport network segment needs to be integrated into such service orchestration platforms efficiently. In this context, this paper aims at providing an introduction to control, management, and orchestration systems, of which the network control is a core component, along their main drivers, key benefits, and functional/protocol architectures. It covers multidomain and multilayer networks and includes complex use cases, challenges and current trends such as joint cloud/network orchestration and 5G network slicing.

Abstract: Warehouse-scale cloud datacenters co-locate workloads with different and often complementary characteristics for improved resource utilization. To better understand the challenges in managing such intricate, heterogeneous workloads while providing quality-assured resource orchestration and user experience, we analyze Alibaba's co-located workload trace, the first publicly available dataset with precise information about the category of each job. Two types of workload---long-running, user-facing, containerized production jobs, and transient, highly dynamic, non-containerized, and non-production batch jobs---are running on a shared cluster of 1313 machines. Our multifaceted analysis reveals insights that we believe are useful for system designers and IT practitioners working on cluster management systems.

Abstract: The question of how information technology-both as an operand resource and as an operant resource-impacts on innovation processes and innovation outcomes remains largely uninvestigated in the manufacturing enterprises. Building on an in-depth case study of a manufacturing enterprise in China, we present a resource orchestration for innovation model and examine the dual role of IT in three distinct innovation processes. The model highlights the multilevel nature of the computerisation process, showing that it entails different IT role and be associated with a particular innovation outcome at each process. This study synthesises resource orchestration framework and IT concepts to elaborate the synergistic relationships between various resources at all levels both inside and between enterprises. Our study not only contributes to broadening the theoretical perspectives by exploring the dual role of IT in managerial issues but also provides some practical suggestions for business leaders to facilitate ...

Abstract: Autonomous management and orchestration (MANO) of virtualized resources and services, especially in large-scale network function virtualization (NFV) environments, is a big challenge owing to the stringent delay and performance requirements expected of a variety of network services. The quality-of-decisions (QoD) of a MANO system depends on the quality and timeliness of the information received from the underlying monitoring system. The data generated by monitoring systems is a significant contributor to the network and processing load of MANO systems, impacting thus their performance. This raises a unique challenge: how to jointly optimize the QoD of MANO systems while at the same minimizing their monitoring loads at runtime? This is the main focus of this paper. In this context, we propose a novel automated NFV orchestration solution, namely z-TORCH (zero Touch Orchestration) that jointly optimizes the orchestration and monitoring processes by exploiting machine-learning-based techniques. The objective is to enhance the QoD of MANO systems achieving a near-optimal placement of virtualized network functions at minimum monitoring costs.

Abstract: With the ever growing diversity of devices and applications that will be connected to 5G networks, flexible and agile service orchestration with acknowledged QoE that satisfies end-user's functional and QoS requirements is necessary. SDN (Software-Defined Networking) and NFV (Network Function Virtualization) are considered key enabling technologies for 5G core networks. In this regard, this paper proposes a reinforcement learning based QoS/QoE-aware Service Function Chaining (SFC) in SDN/NFV-enabled 5G slices. First, it implements a lightweight QoS information collector based on LLDP, which works in a piggyback fashion on the southbound interface of the SDN controller, to enable QoS-awareness. Then, a DQN (Deep Q Network) based agent framework is designed to support SFC in the context of NFV. The agent takes into account the QoE and QoS as key aspects to formulate the reward so that it is expected to maximize QoE while respecting QoS constraints. The experiment results show that this framework exhibits good performance in QoE provisioning and QoS requirements maintenance for SFC in dynamic network environments.

Abstract: Building on recent dialogue between sustainability transition theories and Science and Technology Studies (STS), this article conceptually and empirically studies and analyses the orchestration of households as collectives of participation in the process of distributed energy transition. Synthesising across past studies, we explore three types of what we call ‘collectives of orchestration’, relatively durable collectives that work to orchestrate participation at a distance in space and time. These are: a) collectives of policy production and regulation, b) collectives of research, development and innovation, and c) collectives of technology design. We explore how these collectives enroll households, and the ways in which they mediate participation through different strategies and techniques, producing conditions for various modes of participation. We proceed to discuss the co-production of participation in and by households, including ways in which households can re-configure issues around which research and demonstration projects are set up. Through this exercise, we identify four distinct processes through which orchestration is enacted: 1) the production of visions, expectations and imaginations, 2) network construction and re-configuration, 3) scripting and 4) domestication.

Abstract: Containers are becoming the de facto standard to package and deploy applications and micro-services in the cloud. Several cloud providers (e.g., Amazon, Google, Microsoft) begin to offer native support on their infrastructure by integrating container orchestration tools within their cloud offering. At the same time, the security guarantees that containers offer to applications remain questionable. Customers still need to trust their cloud provider with respect to data and code integrity. The recent introduction by Intel of Software Guard Extensions (SGX) into the mass market offers an alternative to developers, who can now execute their code in a hardware-secured environment without trusting the cloud provider. This paper provides insights regarding the support of SGX inside Kubernetes, an industry-standard container orchestrator. We present our contributions across the whole stack supporting execution of SGX-enabled containers. We provide details regarding the architecture of the scheduler and its monitoring framework, the underlying operating system support and the required kernel driver extensions. We evaluate our complete implementation on a private cluster using the real-world Google Borg traces. Our experiments highlight the performance trade-offs that will be encountered when deploying SGX-enabled micro-services in the cloud.

Abstract: Since the invention of the steam engine in the 18th century, innovation drove the development of industrial processes. The next industrial revolution will form an ecosystem of over 20 billion connected devices with unforeseeable influence to the gross domestic product by 2020, and connected assets will generate about 44ZB of data, which pose interesting challenges related to privacy, connectivity, scalability, and others. A current line of action that leads to this direction is the development of cyber-physical systems; considered as the coupling of physical processes and the digital world, its influence in the next industrial revolution is essential. In this work, we discuss its implementation, taking the Fog computing paradigm into consideration. As a starting point, we are extending a standard-compliant machine-to-machine communication architecture to support container-based orchestration mechanisms to enable cyber-physical systems to be programmable, autonomous, and to communicate peer-to-peer. As the primary field of application, we are considering Industrial Internet domains in general and Smart Factory environments in particular. In this paper, we present an architecture for Fog Nodes, as well a more in-depth discussion on the orchestration system and programmable characteristics of the Fog Node. On the basis of a simulation model, we show the advantages of having a programmable Fog Node supported by an orchestration system. Finally, we open a discussion about our solution and its application in the field of Smart Factories.

Abstract: Purpose Developing and implementing strategies to maximize profitability is a fundamental challenge facing manufacturers. The complexity of orchestrating resources in practice has been overlooked in the operations field and it is now necessary to go beyond the direct effects of individual resources and uncover different resource configurations that maximize profitability. The paper aims to discuss these issues. Design/methodology/approach Drawing on a sample of US manufacturing firms, multiple regression analysis (MRA) and fuzzy set qualitative comparative analysis (fsQCA) are performed to examine the effects of resource orchestration on firm profitability over time. By comparing the findings between analyses, the study represents a move away from examining the net effects of resource levers on performance alone. Findings The findings characterize the resource conditions for manufacturers’ high performance, and also for absence of high performance. Pension and retirement expense is a core resource condition with R&D and SG&A as consistent peripheral conditions for profitability. Moreover, although workforce size was found to have a significant negative effect under MRA, this plays a role in manufacturers’ performance as a peripheral resource condition under fsQCA. Originality/value Accounting for different resource deployment configurations, this study deepens knowledge of resource orchestration and presents findings that enable manufacturers to maximize profitability. An empirical contribution is offered by the introduction of a new method for examining manufacturing strategy configurations: fsQCA.

Abstract: A new level of factory automation demands processing vast amounts of data, complex orchestration of cyber-physical systems, and coordination of computation as well as communication resources in real-time. Virtualization and decentralized computation is becoming a de-facto solution for factory automation. Edge Computing (EC) is a promising approach to achieve the low latencies required by many industrial systems. It employs resource rich edge servers distributed within a factory that are placed close to end devices and assist them in executing computation intensive tasks and also in coordinating with each other. This paper discusses the requirements and challenges of EC for factory automation applications. In a distributed EC infrastructure, safe and timely operation of industrial applications require load balancing and mobility support and thus a seamless service migration between the edge servers. With the recent advances in virtualization and due to its advantages, virtual machine (VM) and container technologies are pavings its way into factory. Though containers have some distinctive advantages over VMs in EC, the service live migration has comparatively high downtime. This paper proposes a novel live migration scheme called redundancy migration that reduces the downtime by a factor of 1.8 compared to the stock migration in linux containers.

Abstract: With the widespread use of smart mobile devices, the exponential growth of mobile Internet traffic and newly emerging services, such as Internet of Things, virtual reality/augmented reality, and serious games, the network performance requirements for delay and bandwidth are increasing. The inherent long-distance propagation and possible network congestion of mobile cloud computing may lead to excessive latency, which cannot satisfy the new delay-sensitive mobile applications. The proximity of edge computing provides the possibility of low-latency access and raises increasing interest from non-mobile operators; therefore, edge computing faces a variety of access network technologies, including wired (fixed) and wireless (mobile) access. In this paper, we propose an integrated heterogeneous networking scheme for multi-access edge computing and fiber-wireless access networks that uses network virtualization to achieve the dynamic orchestration of the network, storage, and computing resources to meet diverse application demands. The global view and centralized control of the entire network and the unified scheduling of the resources in the scheme anticipate the convergence of various types of access networks and the edge cloud. The multipath transmission of the service flows is further combined as an instance of integrated edge cloud networking. An experimental testbed is established in the laboratory, and the performance of the multi-access edge computing and networking is evaluated to verify the feasibility and effectiveness of the scheme. The results demonstrate that the scheme can effectively improve the network performance.