Department of Energy
August 12, 2013
August 12, 2013
SBIR / 7
October 15, 2013
NOTE: The Solicitations and topics listed on this site are copies from the various SBIR agency solicitations and are not necessarily the latest and most up-to-date. For this reason, you should use the agency link listed below which will take you directly to the appropriate agency server where you can read the official version of this solicitation and download the appropriate forms and rules.
The official link for this solicitation is: http:--science.doe.gov-grants-pdf-SC_FOA_0000969.pdf
Network operators face a growing need for advanced tools and services to better manage their infrastructure. Network users also need better tools and services to 1) deal with the increasing amounts of data being generated, moved, and archived; and 2) help in reporting real problems that impact their ability to use the network. Hardening existing tools and services that manage the explosive growth in data will make it easier for users to use the network. Developing new technologies, tools, or high-level services that promote a modular use of measurement and monitoring data will make it easier for network operators to manage their infrastructure. These new modular tools and services should provide multiple levels of detail to authorized personnel with decisions on the level of detail to release under the control of the infrastructure owner. Applications should also be permitted to retrieve summary information to assist users in reporting problems. This will allow network operators to receive the detailed information needed to fix a problem while simplifying the users ability to report a problem. Meeting both types of needs using a single measurement and monitoring infrastructure would greatly improve the network experience for a large number of users. This topic solicits proposals that address issues related to building, operating, and maintaining large network infrastructures, developing tools and services that report performance problems in a manner suitable for network engineers or application users, or hardening existing tools and services that deal with Big Data.
Network infrastructure must be actively managed to ensure that the infrastructure itself does not become a performance bottleneck. This management requires an understanding of how traffic is currently flowing, making predictions about how traffic flows will change in the future, and, increasingly, how much energy this infrastructure is using. Network operations staff need tools and services to make real-time decisions regarding the current performance of the network. Operators also need tools and services that handle longer term capacity planning activities which balance multiple parameters e.g. cost, performance, and energy usage. perfSONAR (http:--www.perfsonar.net) is an architecture developed by the Research and Education Network community for developing multi-domain measurement and monitoring services. This architecture separates the collection of measurement and monitoring data from the analysis of this data. Using this architecture tools and services that collect unique data values can be developed and deployed by operators and-or users who find these tools useful. Tools and services that analyze data can draw from a wide collection of data sources without needing to deploy boxes in hundreds to thousands of locations. Grant applications are sought to develop advanced tools and services suitable for managing large distributed network infrastructures. Issues include, but are not limited to: hardening of existing research tools that leverage a modular architecture to generate or consume data; tools that collect data from unique devices or services; data analysis tools that simplify a network operators task of running a network; data analysis tools that inform network users where performance bottlenecks exist; intuitive displays of performance or operational data tailored to network operators or network users; capacity planning tools that allow operators to determine how to effectively grow the network to meet future demands; or tools that allow operators to optimize the network balancing performance, cost, and energy consumption.
Optical networks have revolutionized wide-area network infrastructure deployments, providing ever-increasing amounts of bandwidth at ever-decreasing costs. As costs have dropped, optical network components moved out of the wide area and into the metro area, and now the residential distribution environment. This expansion requires a shift away from small numbers of very expensive optical test gear to a world with large numbers of inexpensive gear that operates over a wide range of speeds and distances. It also requires the mass production of support tools and services to aid in the installation, testing, operations, and growth of this optical infrastructure. Grant applications are sought that address the emerging need for massive deployment of optical network infrastructure. Issues include, but are not limited to: tools that decrease the cost of terminating or splicing optical cables, components to test optical signal quality, components that operate at 100+ Gigabit per sec line rates.
The growing ubiquity, volume, and velocity of data is having a transformative impact on many sectors of modern society including, energy, science, and defense. DOE operates a broad assortment of scientific facilities such as light sources, observatories, and supercomputing facilities that generate vast amounts of data. Over the years DOE has invested in the development of tools, services, visualization systems, data analytic technologies, and network capabilities to manage the massive science data sets being generated by these facilities. These capabilities, originally developed to address DOEs data-intensive science, are now available to be adopted and extended to solve challenging Big Data problems. Grant applications are sought to engage and expose the small business communities working to; a) leverage DOEs vast portfolio of scientific data management technologies to provide production quality Big Data tools and services, and b) develop new innovative technologies to address related Big Data management challenges. These include but are not limited to 1) production quality Big Data management tools, value-added services, cloud-based services, and turnkeys solutions; and 2) Big Data infrastructure sub-systems such as storage systems technologies, data movement services and technologies, data center-Science DMZ networking technologies, and data security systems; and 3) and scalable data analysis and visualization tools and services for knowledge discovery and data mining.
In addition to the specific subtopics listed above, the Department invites grant applications in other areas that fall within the scope of the topic description above.
Good security metrics are required to make good decisions about how to design security countermeasures, to choose between alternative security architectures, and to improve security during operations. Therefore, in essence, cyber security measurements can be viewed as a decision aid. The lack of sound and practical security metrics is severely hampering progress in the development of secure systems. A Cyberspace Security Econometrics System (CSES) can provide quantitative measures (i.e., a quantitative indication) of reliability, performance and-or safety of a system that accounts for the criticality of each requirement as a function of one or more stakeholders interests in that requirement. For a given stakeholder, CSES accounts for the variance that may exist among the stakes one attaches to meeting each requirement. CSES is a hardware device for implementing an econometrics-based control system. The device includes a processor, a memory in communication with the processor and configured to store processor implementable instructions. The processor implementable instructions are programmed to correlate a plurality of system requirements with each of a plurality of system stakeholders, identify a stake relating to each of the plurality of system stakeholders and the correlated plurality of system requirements such that the stake is identified by each of the plurality of system stakeholders, determining a mean failure cost as a function of the identified stake and a failure probability, and analyzing the mean failure cost to determine a control strategy. The device may further comprise a communication component in communication with the processor and the memory, the communication component configured to communicate the control strategy to a component operable within the control system such that the component implements the control strategy.