IEEE Communications Surveys & Tutorials • 2nd Quarter 2006 2dvances in wireless communication and electronics have enabled the development of low-cost, lowpower, multifunctional sensor nodes. These tiny sensor nodes, consisting of sensing, data processing, and communication components, make it possible to deploy Wireless Sensor Networks (WSNs), which represent a significant improvement over traditional wired sensor networks. WSNs can greatly simplify system design and operation, as the environment being monitored does not require the communication or energy infrastructure associated with wired networks [1].WSNs are expected to be solutions to many applications, such as detecting and tracking the passage of troops and tanks on a battlefield, monitoring environmental pollutants, measuring traffic flows on roads, and tracking the location of personnel in a building. Many sensor networks have mission-critical tasks and thus require that security be considered [2,3]. Improper use of information or using forged information may cause unwanted information leakage and provide inaccurate results.While some aspects of WSNs are similar to traditional wireless ad hoc networks, important distinctions exist which greatly affect how security is achieved. The differences between sensor networks and ad hoc networks are [4]: • The number of sensor nodes in a sensor network can be several orders of magnitude higher than the nodes in an ad hoc network.• Sensor nodes are densely deployed.• Sensor nodes are prone to failures due to harsh environments and energy constraints.• The topology of a sensor network changes very frequently due to failures or mobility.• Sensor nodes are limited in computation, memory, and power resources.• Sensor nodes may not have global identification.These differences greatly affect how secure data-transfer schemes are implemented in WSNs. For example, the use of radio transmission, along with the constraints of small size, low cost, and limited energy, make WSNs more susceptible to denial-of-service attacks [5]. Advanced anti-jamming techniques such as frequency-hopping spread spectrum and physical tamper-proofing of nodes are generally impossible in a sensor network due to the requirements of greater design complexity and higher energy consumption [5]. Furthermore, the limited energy and processing power of nodes makes the use of public key cryptography nearly impossible. While the A YONG WANG, GARHAN ATTEBURY, AND BYRAV RAMAMURTHY UNIVERSITY OF NEBRASKA-LINCOLN ABSTRACTWireless Sensor Networks (WSNs) are used in many applications in military, ecological, and health-related areas. These applications often include the monitoring of sensitive information such as enemy movement on the battlefield or the location of personnel in a building. Security is therefore important in WSNs. However, WSNs suffer from many constraints, including low computation capability, small memory, limited energy resources, susceptibility to physical capture, and the use of insecure wireless communication channels. These constraints ...
Data analysis in HEP has often relied on batch systems and event loops; users are given a non-interactive interface to computing resources and consider data event-by-event. The “Coffea-casa” prototype analysis facility is an effort to provide users with alternate mechanisms to access computing resources and enable new programming paradigms. Instead of the command-line interface and asynchronous batch access, a notebook-based web interface and interactive computing is provided. Instead of writing event loops, the columnbased Coffea library is used. In this paper, we describe the architectural components of the facility, the services offered to end users, and how it integrates into a larger ecosystem for data access and authentication.
Abstract-Data distribution, storage and access are essential to CPU-intensive and data-intensive high performance Grid computing. A newly emerged file system, Hadoop distributed file system (HDFS), is deployed and tested within the Open Science Grid (OSG) middleware stack. Efforts have been taken to integrate HDFS with other Grid tools to build a complete service framework for the Storage Element (SE). Scalability tests show that sustained high inter-DataNode data transfer can be achieved for the cluster fully loaded with data-processing jobs. The WAN transfer to HDFS supported by BeStMan and tuned GridFTP servers shows large scalability and robustness of the system. The hadoop client can be deployed at interactive machines to support remote data access. The ability to automatically replicate precious data is especially important for computing sites, which is demonstrated at the Large Hadron Collider (LHC) computing centers. The simplicity of operations of HDFS-based SE significantly reduces the cost of ownership of Petabyte scale data storage over alternative solutions.
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