All one needs to know about fog computing and related edge computing paradigms: A complete survey

With the Internet of Things (IoT) becoming part of our daily life and our environment, we expect rapid growth in the number of connected devices. IoT is expected to connect billions of devices and humans to bring promising advantages for us. With this growth, fog computing, along with its related edge computing paradigms, such as multi-access edge computing (MEC) and cloudlet, are seen as promising solutions for handling the large volume of security-critical and time-sensitive data that is being produced by the IoT. In this paper, we first provide a tutorial on fog computing and its related computing paradigms, including their similarities and differences. Next, we provide a taxonomy of research topics in fog computing, and through a comprehensive survey, we summarize and categorize the efforts on fog computing and its related computing paradigms. Finally, we provide challenges and future directions for research in fog computing.

All One Needs to Know about Fog Computing and Related Edge Computing Paradigms: A Complete Survey

Industrial IoT has special communication requirements, including high reliability, low latency, flexibility, and security. These are instinctively provided by the 5G mobile technology, making it a successful candidate for supporting Industrial IoT (IIoT) scenarios. The aim of this paper is to identify current research challenges and solutions in relation to 5G-enabled Industrial IoT, based on the initial requirements and promises of both domains. The methodology of the paper follows the steps of surveying state-of-the art, comparing results to identify further challenges, and drawing conclusions as lessons learned for each research domain. These areas include IIoT applications and their requirements; mobile edge cloud; back-end performance tuning; network function virtualization; and security, blockchains for IIoT, Artificial Intelligence support for 5G, and private campus networks. Beside surveying the current challenges and solutions, the paper aims to provide meaningful comparisons for each of these areas (in relation to 5G-enabled IIoT) to draw conclusions on current research gaps.

5G support for Industrial IoT Applications - Challenges, Solutions, and Research gaps

A hybrid software defined networks (SDN) network contains both traditional and SDN network, which combines the robustness of traditional protocols with the flexibility of SDN while avoiding their limitations and incompatibility However, a hybrid SDN network comes with its own set of challenges, including error-prone deployment processes, risks of inconsistency, and complex incremental deployment strategies In this paper, we present a survey of the deployment solutions and optimization strategies for hybrid SDN networks We systematically review solutions to control plane and data plane deployments, and describe typical use cases of hybrid SDN networks We discuss and compare various optimization strategies from perspectives of traffic engineering, resource saving, network control capacity, and network security This paper aims to provide insights to researchers into the future development of hybrid SDN networks and inspire more efforts in this area

A Survey of Deployment Solutions and Optimization Strategies for Hybrid SDN Networks

OpenFlow is an amazingly expressive dataplane programming language, but this expressiveness comes at a severe performance price as switches must do excessive packet classification in the fast path. The prevalent OpenFlow software switch architecture is therefore built on flow caching, but this imposes intricate limitations on the workloads that can be supported efficiently and may even open the door to malicious cache overflow attacks. In this paper we argue that instead of enforcing the same universal flow cache semantics to all OpenFlow applications and optimize for the common case, a switch should rather automatically specialize its dataplane piecemeal with respect to the configured workload. We introduce ESwitch, a novel switch architecture that uses on-the-fly template-based code generation to compile any OpenFlow pipeline into efficient machine code, which can then be readily used as fast path. We present a proof-of-concept prototype and we demonstrate on illustrative use cases that ESwitch yields a simpler architecture, superior packet processing speed, improved latency and CPU scalability, and predictable performance. Our prototype can easily scale beyond 100 Gbps on a single Intel blade even with complex OpenFlow pipelines.

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Dataplane Specialization for High-performance OpenFlow Software Switching

Edge computing is a (r)evolutionary extension of traditional cloud computing. It expands central cloud infrastructure with execution environments close to the users in terms of latency in order to enable a new generation of cloud applications. This paradigm shift has opened the door for telecommunications operators, mobile and fixed network vendors: they have joined the cloud ecosystem as essential stakeholders considerably influencing the future success of the technology. A key problem in edge computing is the optimal placement of computational units (virtual machines, containers, tasks or functions) of novel distributed applications. These components are deployed to a geographically distributed virtualized infrastructure and heterogeneous networking technologies are invoked to connect them while respecting quality requirements. The optimal hosting environment should be selected based on multiple criteria by novel scheduler algorithms which can cope with the new challenges of distributed cloud architecture where networking aspects cannot be ignored. The research community has dedicated significant efforts to this topic during recent years and a vast number of theoretical results have been published addressing different variants of the related mathematical problems. However, a comprehensive survey focusing on the technical and analytical aspects of the placement problem in various edge architectures is still missing. This survey provides a comprehensive summary and a structured taxonomy of the vast research on placement of computational entities in emerging edge infrastructures. Following the given taxonomy, the research papers are analyzed and categorized according to several dimensions, such as the capabilities of the underlying platforms, the structure of the supported services, the problem formulation, the applied mathematical methods, the objectives and constraints incorporated in the optimization problems, and the complexity of the proposed methods. We summarize the gained insights and important lessons learned, and finally, we reveal some important research gaps in the current literature.

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Survey on Placement Methods in the Edge and Beyond

Software-Defined Networking (SDN) offers a new way to operate, manage, and deploy communication networks and to overcome many long-standing problems of legacy networking. However, widespread SDN adoption has not occurred yet due to the lack of a viable incremental deployment path and the relatively immature present state of SDN-capable devices on the market. While continuously evolving software switches may alleviate the operational issues of commercial hardware-based SDN offerings, namely lagging standards-compliance, performance regressions, and poor scaling, they fail to match the cost-efficiency and port density. In this paper, we propose HARMLESS, a new SDN switch design that seamlessly adds SDN capability to legacy network gear, by emulating the OpenFlow switch OS in a separate software switch component. This way, HARMLESS enables a quick and easy leap into SDN, combining the rapid innovation and upgrade cycles of software switches with the port density and cost-efficiency of hardware-based appliances into a fully dataplane-transparent and vendor-neutral solution. HARMLESS incurs an order of magnitude smaller initial expenditure for an SDN deployment than existing turnkey vendor SDN solutions while, at the same time, yields matching, or even better, data plane performance for smaller enterprises.

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Transition to SDN is HARMLESS: Hybrid Architecture for Migrating Legacy Ethernet Switches to SDN

Scalable edge cloud platforms for IoT services

With the soar of Software Defined Networking planning a network service becomes harder of a task than ever before. Selecting traditional network elements that provide the best value for money given the performance requirements and the allocated budget is not the only option today: one might also take the software solution on generic hardware alternative. The problem is that the set of available solutions and the possible combinations of software and hardware components in this nowadays' alternative is frustratingly vast while the decision maker lacks any clear benchmarking comparison between the existing options. Our solution presented in this paper provides an answer to this critical need: we propose a benchmarking tool that allows the user to measure the important performance metrics of any network function realized on any hardware and software combination, and then to compare the results on a web interface with those of all the setups collected in our database.

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NFPA: Network function performance analyzer

Kubernetes has become the most popular cluster manager during the past 5 years. It is used primarily for orchestrating data center deployments running web applications. Its powerful features, e.g., self-healing and scaling, have attracted a huge community, which in turn, is inducing a meteoric rise of this open source project. We venture to shape Kubernetes to be suited for edge infrastructure. As mostly delay-sensitive applications are to be deployed in the edge, a topology-aware Kubernetes is needed, extending its widely-used feature set with regard to network latency. Moreover, as the edge infrastructure is highly prone to failures and is considered to be expensive to build and maintain, self-healing features must receive more emphasis than in the baseline Kubernetes. We therefore designed a custom Kubernetes scheduler that makes its decisions with applications' delay constraints and edge reliability in mind. In this demonstration we show the novel features of our Kubernetes extension, and describe the solution that we release as open source.

Mark Szalay

Papers

Survey on Placement Methods in the Edge and Beyond

Transition to SDN is HARMLESS: Hybrid Architecture for Migrating Legacy Ethernet Switches to SDN

Scalable edge cloud platforms for IoT services

NFPA: Network function performance analyzer

Sharpening Kubernetes for the Edge