Parallel Data Transfer Protocol

Transferring very high quality digital objects over the optical network is critical in many scientific applications, including video streaming/conferencing, remote rendering on tiled display walls, 3D virtual reality, and so on. Current data transfer protocols rely on the User Datagram Protocol (UDP) as well as a variety of compression techniques. However, none of the protocols scale well to the parallel model of transferring large scale graphical data. The existing parallel streaming protocols have limited synchronization mechanisms to synchronize the streams efficiently, and therefore, are prone to slowdowns caused by significant packet loss of just one stream. In this chapter, the authors propose a new parallel streaming protocol that can stream synchronized multiple flows of media content over optical networks through Cross-Stream packet coding, which not only can tolerate random UDP packet losses but can also aim to tolerate unevenly distributed packet loss patterns across multiple streams to achieve a synchronized throughput with reasonable coding overhead. They have simulated the approach, and the results show that the approach can generate steady throughput with fluctuating data streams of different data loss patterns and can transfer data in parallel at a higher speed than multiple independent UDP streams.

Security Information and Event Management Implementation Guidance

This chapter is about guidance and implementation prepared by the Cloud Security Alliance (CSA) Security as a Service (SecaaS) workgroup, which is made up of users and practitioners in the field of information security. In preparing this implementation guide, input has been sought from experts throughout Europe, the Middle East, and the United States. A lot of professional judgment and experience are applied in the architecture, engineering, and implementation of a Security Information and Event Management (SIEM) guide to ensure that it logs the information necessary to successfully increase visibility and remove ambiguity, surrounding the security events and risks that an organization faces. By providing SIEM as a service under SecaaS, the provider has to be able to accept log and event information, customer information and event feeds, and conduct information security analysis, correlation, and support incident response. By providing flexible real-time access to SIEM information, it allows the party consuming the SIEM service to identify threats acting against their environment cloud. This identification then allows for the appropriate action and response to be taken to protect or mitigate the threat. The simple step of increasing visibility and removing ambiguity is a powerful tool to understanding the information security risks that an organization is facing.

Border Adaptive Micro-Base-Station for Wireless Communications

This chapter presents a novel architecture, namely the border adaptive micro-base-station network, which can sufficiently meet the bandwidth requirements for the future wireless networks. From the three screens convergence point, the goal is to make the wireless service performance match that of the wired systems, instead of downgrading the performance of wired network applications to the wireless level. Based on the analysis of Shannon theory, the only way to build future wireless networks is to adopt this micro-base-station approach instead of progressively improving the traditional large-cell-base-station systems, such as Long-Term Evolution (LTE).

Data Protection in the Cloud Era

In this chapter, the authors examine a potential enterprise customer’s strategy and scenario to protect its data in the cloud computing era. CorpFort is the name of a hypothetical company. This chapter starts with the problem statement in the data protection space at CorpFort. Then, it describes a vision in the protection of data in the ideal state. Finally, it creates the strategy and solutions for realizing the vision.

Cloud Strategy Leads Innovation in China

Cloud computing is a historically significant trend in the development of information technology and applications. The cloud concept and the corresponding series of changes in technology, business, application, and service models are inevitable results of such developments in the information industry. In recent years, governments and major IT companies have introduced new IT strategies based on cloud computing, such as innovative platforms, services, and applications. More and more data and applications are migrating into the cloud, and the development of cloud computing is in full swing (Shen & Zhang, 2013).

Main Components of Cloud Computing

Cloud-era Information Technology (IT) contains three main themes: The information hub (cloud), network communications (pipes), and intelligent terminals. In this chapter, the developmental stages of these three main components of cloud computing are discussed, with emphasis on future development. The Internet of things is also examined, which is expected to thrive as a direct result of the development of cloud computing.

Impact of Cultural Differences on the Cloud Computing Ecosystems in the USA and China

The IT industry is both fundamental and strategic to a nation’s economy. It continues to play a critical role in the industry’s upgrade and economic development in the foreseeable future. The future of the IT industry lies in cloud computing. In the recent years, many countries in the world are responding to cloud computing with much enthusiasm. The USA, Japan, and European countries have created strategies to develop cloud computing, aiming to become the leader of the new era. The Chinese government also sees cloud computing as a historic opportunity to rebuild competitive advantages and leapfrog Western countries. Against this backdrop, this chapter compares and contrasts the evolution of IT towards cloud computing between China and the Western countries, especially the USA.

Big Data Overview

This chapter provides an overview of big data and its environment and opportunities. It starts with a definition of big data and describes the unique characteristics, structure, and value of big data, and the business drivers for big data analytics. It defines the role of the data scientist and describes the new ecosystem for big data processing and analysis.

Enterprise Security Monitoring with the Fusion Center Model

In the past few years, we have witnessed cyber-attacks of unprecedented sophistication and reach. These attacks demonstrate that malicious actors have the ability to compromise and control millions of computers that belong to governments, enterprises, and ordinary citizens. If we are to prevent motivated adversaries from attacking our systems, stealing our data, and harming our critical infrastructure, we have to first understand emerging threats to develop proactive security solutions to safeguard the information and the physical infrastructure that rely on it. This chapter discusses one possible approach to defending against malicious actors at the enterprise level.

Cloud Infrastructure

This chapter focuses on the different aspects of cloud computing virtualization. It introduces the fundamental concepts of computer virtualization, storage virtualization, network virtualization, and application virtualization. Virtualization techniques, infrastructure, components, and implementation are described in detail.