As software migrates from local PCs to distant Internet servers, users and developers alike go along for the ride.

Cloud computing

Diverse proprietary network appliances increase both the capital and operational expense of service providers, meanwhile causing problems of network ossification. Network function virtualization (NFV) is proposed to address these issues by implementing network functions as pure software on commodity and general hardware. NFV allows flexible provisioning, deployment, and centralized management of virtual network functions. Integrated with SDN, the software-defined NFV architecture further offers agile traffic steering and joint optimization of network functions and resources. This architecture benefits a wide range of applications (e.g., service chaining) and is becoming the dominant form of NFV. In this survey, we present a thorough investigation of the development of NFV under the software-defined NFV architecture, with an emphasis on service chaining as its application. We first introduce the software-defined NFV architecture as the state of the art of NFV and present relationships between NFV and SDN. Then, we provide a historic view of the involvement from middlebox to NFV. Finally, we introduce significant challenges and relevant solutions of NFV, and discuss its future research directions by different application domains.

Software-Defined Network Function Virtualization: A Survey

In embodiments of the present invention improved capabilities are described for a virtualization environment adapted for development and deployment of at least one software workload, the virtualization environment having a metamodel framework that allows the association of a policy to the software workload upon development of the workload that is applied upon deployment of the software workload. This allows a developer to define a security zone and to apply at least one type of security policy with respect to the security zone including the type of security zone policy in the metamodel framework such that the type of security zone policy can be associated with the software workload upon development of the software workload, and if the type of security zone policy is associated with the software workload, automatically applying the security policy to the software workload when the software workload is deployed within the security zone.

System and method for a cloud computing abstraction layer with security zone facilities

The rapid developments of the Internet of Things (IoT) and smart mobile devices in recent years have been dramatically incentivizing the advancement of edge computing. On the one hand, edge computing has provided a great assistance for lightweight devices to accomplish complicated tasks in an efficient way; on the other hand, its hasty development leads to the neglection of security threats to a large extent in edge computing platforms and their enabled applications. In this paper, we provide a comprehensive survey on the most influential and basic attacks as well as the corresponding defense mechanisms that have edge computing specific characteristics and can be practically applied to real-world edge computing systems. More specifically, we focus on the following four types of attacks that account for 82% of the edge computing attacks recently reported by Statista: distributed denial of service attacks, side-channel attacks, malware injection attacks, and authentication and authorization attacks. We also analyze the root causes of these attacks, present the status quo and grand challenges in edge computing security, and propose future research directions.

https://ieeexplore.ieee.org/ielaam/5/8789751/8741060-aam.pdf

Edge Computing Security: State of the Art and Challenges

Embodiments of the present invention provide a cloud gateway system, a cloud hypervisor system, and methods for implementing same. The cloud gateway system extends the security, manageability, and quality of service membrane of a corporate enterprise network into cloud infrastructure provider networks, enabling cloud infrastructure to be interfaced as if it were on the enterprise network. The cloud hypervisor system provides an interface to cloud infrastructure provider management systems and infrastructure instances that enables existing enterprise systems management tools to manage cloud infrastructure substantially the same as they manage local virtual machines via common server hypervisor APIs.

Cloud computing gateway, cloud computing hypervisor, and methods for implementing same

In order to support the maximum number of user and elastic service with the minimum resource, the Internet service provider invented the cloud computing. within a few years, emerging cloud computing has became the hottest technology. From the publication of core papers by Google since 2003 to the commercialization of Amazon EC2 in 2006, and to the service offering of AT&T Synaptic Hosting, the cloud computing has been evolved from internal IT system to public service, from cost-saving tools to revenue generator, and from ISP to telecom. This paper introduces the concept, history, pros and cons of cloud computing as well as the value chain and standardization effort.

Cloud Computing: An Overview

MapReduce is a parallel programming system to deal with massive data. It can automatically parallelize MapReduce jobs into multiple tasks, schedule to a cluster built by PCs. This paper describes a data distribution aware MapReduce task scheduling strategy. When worker nodes requests for tasks, it will compute and obtain nodes' priority according to the times for request, the number of tasks which can be executed locally and so on. Meanwhile, it can also calculate tasks' priority according to the numbers of copies executed by the task, latency time of tasks and so on. This strategy is based on node and task's scheduling priority, fully considers data distribution in the system and thus schedules Map tasks to nodes having data in high probability, to reduce network overhead and improve system efficiency.

A Data Distribution Aware Task Scheduling Strategy for MapReduce System

The demand of analyzing and processing mass data is increasing in recent years. Though several optimization versions developed, the traditional RDBMS still met a lot of difficulties when facing so huge volume of data. A newly designed distributed structured database HugeTable is proposed, which have the advantage of supporting very large scale of data and fast query speed. HugeTable also have a good compatibility with the standard SQL query language. The basic functions, system architecture and critical techniques are discussed in detail. The usability and efficiency are proved by experiments.

Distributed Structured Database System HugeTable

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Cloud Computing: An Overview

A Data Distribution Aware Task Scheduling Strategy for MapReduce System

Distributed Structured Database System HugeTable