The main service interoperability models (SOA and REST) are currently implemented in the Web with text based technologies (XML, JSON, HTTP), conceived for large grained hypermedia documents. Their extension to the Internet of Things context, involving devices with constrained capabilities and unreliable wireless network protocols, implies using a subset of the features of those technologies and adapting the network and message level protocols. This chapter starts by establishing a layered interoperability framework, from the organizational down to the network protocol levels. Then, it assesses the constraints and limitations of current technologies, establishing goals to solve these problems. Finally, a new interoperability technology is presented, based on a distributed programming language (and its execution platform) that combines platform independence and self-description capabilities, which current data description languages exhibit, with behavior description (not just data), elimination of the need of a separate language for schema or interface description, complete separation of data and metadata (optimizing message transactions) and native support for binary data (eliminating the need for encoding or compression).

关键词：电子信息；物联网；服务；互操作

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The seven Florida Department of Transportation (FDOT) districts are multicounty districts that each interact with a number of county and municipal agencies, including local transit agencies. FDOT District 7 includes the Tampa-St. Petersburg-Clearwater areas, which are among the most populous and complex in the state. District 7 employees regularly need information from the many entities that may interact with transportation planning, design, construction and maintenance. Accessing this information usually nvolves multiple manual steps to locate, acquire, and convert data. To facilitate their work, District 7 has initiated an effort to create an electronic means for intraregional data sharing.

关键词：电子信息；GIS；地理信息系统；交通；数据模型

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关键词：物联网；专项行动；商用模式

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Computational methods have evolved over the years giving developers and researchers more sophisticated and faster ways to solve hard data processing tasks. However, with new data collecting and storage technologies, the amount of gathered data increases everyday making the analysis of it a more and more complex task. One of the main forms of storing data is plain unstructured text and one of the most common ways of analyzing this kind of data is through Text Mining. Text Mining is similar to other types of data mining but the problem is that differently from other forms of data that are properly structured (such as XML) in text mining data in the best case scenario is semi-structured. In order for them to derive valuable information, text mining systems have to execute a lot of complex natural language processing algorithms. In this chapter we focus on text processing tools dealing with stemming algorithms. Stemming is the step that deals with finding the stem (or root) of the word which is essential in every text processing procedure. Stemming algorithms are complex and require high computational effort. In this chapter we present an Apache Mahout plugin for a stemming algorithm making possible to execute the algorithm in a cloud computing environment. We investigate the performance of the algorithm in the cloud and show that the new approach significantly reduces the execution time of the original algorithm over a large dataset of text documents.

关键词：电子信息；云计算；堵文本；文本挖掘；数据收集；数据存储

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Cloud computing is an emerging technology that can help organizations become more efficient and agile, and respond more quickly and reliably to their customers’ needs. Many government and private sector organizations are currently using or considering the use of cloud computing to increase the performance and efficiency of their information system operations, and to improve the delivery of services.

关键词：电子信息；云计算；信息系统；安全；隐私

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关键词：4G牌照；山寨手机

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Mobile cloud computing is growing rapidly because its device (i.e., smart phone) is becoming one of the main processing devices for users nowadays. Due to the limitation of resources such as battery life time, CPU and memory capacity, etc., a mobile device cannot satisfy some applications which usually demand more resources than it can afford. To alleviate this, the mobile device should collaborate with external resources to increase its capacity. In order to address these problems, we introduce a collaboration of thin-thick clients which enhances thin client capacities. We further propose a strategy to optimize the data distribution, especially big data in cloud computing. Moreover, we present an algorithm to allocate resources to meet service level agreement (SLA) and conduct simulations to evaluate our approach. Our results evaluation shows that our approach can improve resource allocation efficiency and has better performance than existing approaches.

关键词：电子信息；云计算；数据分布；资源分配

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How should the Department of Defense (DoD) apply best business practices to Information Technology (IT) modernization, Data Center Consolidation (DCC), and the efficient, effective, and secure implementation of Cloud computing to support DoD business approaches and its warfighting mission.

关键词：电子信息；云计算；信息技术；整合

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This chapter focuses on how to monitor marine spills using powerful tools such as remote sensing and Geographic Information Systems (GIS). On the one hand, remote sensing has been widely used as one of the main ways to periodically monitor large areas, as it allows to obtain data under poor weather conditions and in spite of darkness. We particularly center upon a. sensor called "Advanced Synthetic Aperture Radar" (ASAR), which is part of the Envisat payload. On the other hand, GIS have emerged in recent years as a set of standards for data organization and representation that allow the management of geographic data. We provide a detailed description of the design and implementation of a tool that provides an integrated framework for the detection and localization of marine spills using remote sensing, GIS, and cloud computing. Cloud computing is used because of the enormous amount of data to be processed and the need of communication between users.

关键词：电子信息；云计算；GIS；海洋检测

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The DoD Cloud Computing Strategy has evolved to identify the most effective ways for the Department to capitalize on opportunities and take advantage of cloud computing benefits that accelerate IT delivery, efficiency, and innovation as an Enterprise. Prior drafts were informally coordinated and comments from across the Department were used to broaden the scope and depth of the current document; significant modifications and additions have been incorporated. In addition, DoD CIO and Defense Information Systems Agency (DISA) led a DoD Capability Assurance and Alignment Process (CAAP) Working Group to refine the approach and clarify required capabilities. The DoD Cloud Computing Strategy has been expanded to address use of commercial cloud services in the Department's multi-provider enterprise cloud environment. Adoption and implementation of commercially provided cloud services are being rapidly accelerated with the maturing of the Federal Cloud Computing Initiative, the Federal Risk and Authorization Management Program (Fed RAMP), and release of the 2012 National Defense Authorization Act.

关键词：电子信息；云计算；策略

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