The Internet has led to the creation of a digital society, where (almost) everything is connected and is accessible from anywhere. However, despite their widespread adoption, traditional IP networks are complex and very hard to manage. It is both difficult to configure the network according to predefined policies, and to reconfigure it to respond to faults, load, and changes. To make matters even more difficult, current networks are also vertically integrated: the control and data planes are bundled together. Software-defined networking (SDN) is an emerging paradigm that promises to change this state of affairs, by breaking vertical integration, separating the network's control logic from the underlying routers and switches, promoting (logical) centralization of network control, and introducing the ability to program the network. The separation of concerns, introduced between the definition of network policies, their implementation in switching hardware, and the forwarding of traffic, is key to the desired flexibility: by breaking the network control problem into tractable pieces, SDN makes it easier to create and introduce new abstractions in networking, simplifying network management and facilitating network evolution. In this paper, we present a comprehensive survey on SDN. We start by introducing the motivation for SDN, explain its main concepts and how it differs from traditional networking, its roots, and the standardization activities regarding this novel paradigm. Next, we present the key building blocks of an SDN infrastructure using a bottom-up, layered approach. We provide an in-depth analysis of the hardware infrastructure, southbound and northbound application programming interfaces (APIs), network virtualization layers, network operating systems (SDN controllers), network programming languages, and network applications. We also look at cross-layer problems such as debugging and troubleshooting. In an effort to anticipate the future evolution of this new paradigm, we discuss the main ongoing research efforts and challenges of SDN. In particular, we address the design of switches and control platforms—with a focus on aspects such as resiliency, scalability, performance, security, and dependability—as well as new opportunities for carrier transport networks and cloud providers. Last but not least, we analyze the position of SDN as a key enabler of a software-defined environment.

pdf/software-defined-networking-a-comprehensive-survey-128fi8syly.pdf

Software-Defined Networking: A Comprehensive Survey

Software-Defined Networking (SDN) is an emerging paradigm that promises to change this state of affairs, by breaking vertical integration, separating the network's control logic from the underlying routers and switches, promoting (logical) centralization of network control, and introducing the ability to program the network. The separation of concerns introduced between the definition of network policies, their implementation in switching hardware, and the forwarding of traffic, is key to the desired flexibility: by breaking the network control problem into tractable pieces, SDN makes it easier to create and introduce new abstractions in networking, simplifying network management and facilitating network evolution. In this paper we present a comprehensive survey on SDN. We start by introducing the motivation for SDN, explain its main concepts and how it differs from traditional networking, its roots, and the standardization activities regarding this novel paradigm. Next, we present the key building blocks of an SDN infrastructure using a bottom-up, layered approach. We provide an in-depth analysis of the hardware infrastructure, southbound and northbound APIs, network virtualization layers, network operating systems (SDN controllers), network programming languages, and network applications. We also look at cross-layer problems such as debugging and troubleshooting. In an effort to anticipate the future evolution of this new paradigm, we discuss the main ongoing research efforts and challenges of SDN. In particular, we address the design of switches and control platforms -- with a focus on aspects such as resiliency, scalability, performance, security and dependability -- as well as new opportunities for carrier transport networks and cloud providers. Last but not least, we analyze the position of SDN as a key enabler of a software-defined environment.

Traditional standalone embedded system is limited in their functionality, flexibility, and scalability. Fog computing platform, characterized by pushing the cloud services to the network edge, is a promising solution to support and strengthen traditional embedded system. Resource management is always a critical issue to the system performance. In this paper, we consider a fog computing supported software-defined embedded system, where task images lay in the storage server while computations can be conducted on either embedded device or a computation server. It is significant to design an efficient task scheduling and resource management strategy with minimized task completion time for promoting the user experience. To this end, three issues are investigated in this paper: 1) how to balance the workload on a client device and computation servers, i.e., task scheduling, 2) how to place task images on storage servers, i.e., resource management, and 3) how to balance the I/O interrupt requests among the storage servers. They are jointly considered and formulated as a mixed-integer nonlinear programming problem. To deal with its high computation complexity, a computation-efficient solution is proposed based on our formulation and validated by extensive simulation based studies.

Joint Optimization of Task Scheduling and Image Placement in Fog Computing Supported Software-Defined Embedded System

The emerging software defined networking (SDN) paradigm separates the data plane from the control plane and centralizes network control in an SDN controller. Applications interact with controllers to implement network services, such as network transport with quality of service. SDN facilitates the virtualization of network functions so that multiple virtual networks can operate over a given installed physical network infrastructure. Due to the specific characteristics of optical (photonic) communication components and the high optical transmission capacities, SDN-based optical networking poses particular challenges, but holds also great potential. In this article, we comprehensively survey studies that examine the SDN paradigm in optical networks; in brief, we survey the area of software defined optical networks (SDONs). We mainly organize the SDON studies into studies focused on the infrastructure layer, the control layer, and the application layer. Moreover, we cover SDON studies focused on network virtualization, as well as SDON studies focused on the orchestration of multilayer and multidomain networking. Based on the survey, we identify open challenges for SDONs and outline future directions.

pdf/software-defined-optical-networks-sdons-a-comprehensive-5d4vdijy6b.pdf

Software Defined Optical Networks (SDONs): A Comprehensive Survey

Software defined networks

Predictive maintenance techniques are designed to help anticipate equipment failures to allow for advance scheduling of corrective maintenance, thereby preventing unexpected equipment downtime, improving service quality for customers, and also reducing the additional cost caused by over-maintenance in preventative maintenance policies. Many types of equipment--e.g., automated teller machines (ATMs), information technology equipment, medical devices, etc.--track run-time status by generating system messages, error events, and log files, which can be used to predict impending failures. Aiming at these types of equipment, we present a general classification-based failure prediction method. In our parameterized model, we systematically defined four categories of features to try to cover all possibly useful features, and then used feature selection to identify the most important features for model construction. The general solution is sufficiently flexible and complex to address failure prediction for target equipment types. We chose ATMs as the example equipment and used real ATM run-time event logs and maintenance records as experimental data to evaluate our method on the feasibility and effectiveness. In this paper, we also share insights on how to optimize the model parameters, select the most effective features, and tune classifiers to build a high-performance prediction model.

Predictive maintenance based on event-log analysis: a case study

Disclosed is a method and system to operate a governed data processing system in concert with a governing data processing system. The method includes operating a secure governing data processing system to monitor operation of at least one governed data processing system to detect a deviation from modeled user and governed data processing system behavior. The method further includes, upon detecting a deviation from the modeled behavior, taking proactive action to mitigate an occurrence of a potential adverse result of an occurrence of a cyber-security threat.

Systems, methods and computer programs providing impact mitigation of cyber-security failures

A method for enhancing resiliency of a service includes: decomposing at least one component associated with the service into a plurality of corresponding smaller elements; encrypting the elements to generate a corresponding plurality of encrypted elements; decomposing each of the encrypted elements into a corresponding plurality of smaller fragments; replicating each of the fragments; encapsulating the fragments into respective intelligent components, each of the intelligent components corresponding to a given one of the encapsulated fragments, each of the intelligent components being configured to independently determine a location of a first storage element in which to store itself; storing each of the intelligent components; and moving the intelligent components from the first storage element location to a second storage element location.

Methods and apparatus for enhancing business services resiliency using continuous fragmentation cell technology

During the past few years, enterprises have been increasingly aggressive in moving mission-critical and performance-sensitive applications to the cloud, while at the same time many new mobile, social, and analytics applications are directly developed and operated on cloud computing platforms. These two movements are encouraging the shift of the value proposition of cloud computing from cost reduction to simultaneous agility and optimization. These requirements (agility and optimization) are driving the recent disruptive trend of software defined computing, for which the entire computing infrastructure--compute, storage and network--is becoming software defined and dynamically programmable. The key elements within software defined environments include capability-based resource abstraction, goal-based and policy-based workload definition, and outcome-based continuous mapping of the workload to the available resources. Furthermore, software defined environments provide the tooling and capabilities to compose workloads from existing components that are then continuously and autonomously mapped onto the underlying programmable infrastructure. These elements enable software defined environments to achieve agility, efficiency, and continuous outcome-optimized provisioning and management, plus continuous assurance for resiliency and security. This paper provides an overview and introduction to the key elements and challenges of software defined environments.

/pdf/software-defined-environments-an-introduction-3jj19sr6bi.pdf

Software defined environments: an introduction

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Predictive maintenance based on event-log analysis: a case study

Systems, methods and computer programs providing impact mitigation of cyber-security failures

Methods and apparatus for enhancing business services resiliency using continuous fragmentation cell technology

Software defined environments: an introduction