SPECIAL NOTICE
99 -- Fog Edge Computing Needs Statement
- Notice Date
- 8/1/2022 6:51:10 AM
- Notice Type
- Special Notice
- NAICS
- 541690
— Other Scientific and Technical Consulting Services
- Contracting Office
- 5611 COLUMBIA PIKE FALLS CHURCH VA 22041 USA
- ZIP Code
- 22041
- Solicitation Number
- CP-20220622-W-Fog-Edge-Computing
- Response Due
- 8/10/2022 2:00:00 PM
- Point of Contact
- CP Innovation Outreach
- E-Mail Address
-
osd.pentagon.ousd-atl.mbx.rrto-innovation@mail.mil
(osd.pentagon.ousd-atl.mbx.rrto-innovation@mail.mil)
- Description
- Fog and Edge Computing Needs Statement The Department of Defense�s (DoD) Under Secretary of Defense for Research and Engineering (R&E) Capability Prototypes Office, in coordination with the meeting sponsor Air Force Research Laboratory (AFRL) Transformational Capabilities Office (TCO), will conduct a virtual Solutions Meeting focused on Fog and Edge Computing in the Fall of 2022. The Solutions Meeting provides selected innovative companies with an opportunity to make short technical presentations to government representatives about their technologies and products. There is a potential for companies to be selected for pilot projects or experimentation if their technology match DoD�s needs. Background Across the DoD enterprise, platforms are equipped with a grid of sensors that collect massive amounts of data to carry out multi-domain missions. The DoD needs transformational computing technologies to increase on-board data analytics, limit communications latency and cost, increase human situational awareness and enable adaptive decisions, and provide energy efficient computing and architectures for data collection and processing. Additionally, the DoD needs collaborative computing and cutting-edge networking for fusion of multi-spatial, multi-signal, and multi-reports. Edge computing is the collection of technologies and capabilities necessary to enable processing of sensor data in real time, generate insights from that data, and interact with that data through applications in a distributed manner with varying levels of connectivity. Fog computing is a selective filter and provides additional data management and analysis between data at the Edge by sending it back to the Cloud for additional processing. AFRL is investigating solutions in Fog and Edge computing that focus on Human Computer Interfaces; Energy Efficient Computing and Architectures for Data Collection/Processing; and Collaborative Computing, Fusion and Networking. AFRL is looking for innovative technologies that enable Fog and Edge computing in the following areas: Human Computer Interfaces: Human Computer Interface (HCI) focuses on the design of computer technology to facilitate interaction between humans (the users) and computers in ways that result in enhanced task performance compared to humans or computers individually. Fog & Edge computing creates novel HCI challenges and opportunities for both proximal systems (edge nodes physically close to users where interaction can occur directly) and remote systems (edge nodes physically distant from the user where interaction must occur over a network connection). Fog & Edge computing also create challenges and opportunities with respect to the ability to leverage and exploit HCI for real time or near-real time tasks. AFRL is looking for innovative solutions to: Sense and adapt to user�s: Cognitive, physiological & physical state Tasks & goals Local physical environment Social & team interactions and preferences Enable flexibility of usage: Good size, weight, and power (SWaP) efficiency Scalable to platform or problem sizes Updatable and reconfigurable architectures/software Reducing user training requirements Enable processing and display: In real-time or near real-time Of multi-faceted information With potentially interconnected information Provide automatic and interpretable: Explanation or summarization of data Plans, reactions and decisions Intelligent multimodal displays for: Highly dynamic data Extremely large, heterogeneous, and multi-dimensional data sets Disparate and interconnected data Energy Efficient Computing and Architectures for Data Collection/Processing: Seeking energy efficiency at all points through the computer architecture, including the interconnected hardware (processing components and memory) and the data flow between components. Inputs and outputs to and from the processor or system can be environmental sensor inputs (RF, EO, auditory, etc.), human interfaces, or other computing systems. The processing system can be collocated with the input/output system or connected through a communication link. Challenges to the Edge processing field include (but are not limited to) reducing the latency and improving throughput, reducing the C-SWaP, improving interoperability for system scalability, ease of replacement or upgrades, and optimized system cooling. AFRL is looking for innovative solutions to: Improved latency and throughput in processing: For high-throughput data analysis For low-latency data-to-decision With adaptive and efficient architectures. Computational/control/communications electronics with:� Lower power consumption Lower heat dissipation Lower system and maintenance costs Scalable & redundancy architectures as in: Distributed memory/data storage Computational capability for broad data types Reconfigurable system for functions and/or redundancy System expandable for additional hardware resources Faster field upgrades for: Ease of programmability and integration Reduced firmware changes/upgrades time High-level design/modification tools Efficient system cooling solutions: Thermo-Electric Coolers (TEC) Mechanical / Contact Cooling Collaborative Computing, Fusion and Networking: Collaborative computing, fusion, and networking (CCFN) focuses on combining signals, features, data, and information across the network to enable decision making across all echelons at the speed of conflict. Future Fog and Edge computing capabilities must leverage collaborative computing, cutting-edge networking, and advances in artificial intelligence (AI) for fusion of multi-spatial, multi-signal, and multi-reports. Three key focus areas for DOD multi-modal, collaborative, and network Edge computing include: (1) sensing (unsupervised learning, rapid modeling, and tasking of new targets), (2) interoperable computing (use of open architectures to support decentralized execution), and (3) all-domain performance (tailored data flows for scalable performance). CCFN requires advances in hardware such as devices with reduced C-SWaP to enable use in various platforms to include airborne and man-portable systems. Advances in networking capabilities should provide resilient, high-bandwidth communications required for sensing and sense-making at the Edge as well as advances in processors for fusion and AI/ML applications. CCFN is focused on advances in theoretical methods and architectures to exploit Edge-AI; however, the mission, hardware, and software should be designed together to enhance performance. AFRL is looking for innovative solutions to: Edge-based sensing and fusion using: Generative adversarial networks Transfer learning Unsupervised learning for: Linking associations of features between modalities Utilizing physics over the operating conditions Joint learning and domain adaptation between modalities Scaling of same modality Sensing and fusion architectures: Decentralized learning methods Adaptive communication structure Mixed-modality awareness Interoperable collaborative computing as in: Distributed AI computing and processing for: Situation assessment Awareness and understanding of data across distributed systems Open standards and protocols for interoperability Networking technologies for connectivity and throughput Software development approaches as in: Continuous integration / continuous deployment (CI/CD) Use of containers Infrastructure as code Micro-service based architectures All-domain capability for: Tailorable multi-spatial, multi-signal, and multi-reports for: Data flows Knowledge sharing Coordination Timely, accurate and confident data-to-decision Optimal sensor management and tasking Transparency of data and accuracy of insights Model interpretability and adaptability across domains Explainability of generated insights and decisions Application Process Companies interested in participating in the Solutions Meeting should submit one (1) application to Capability Prototypes (formerly the Rapid Reaction Technology Office) via email to osd.pentagon.ousd-atl.mbx.rrto-innovation@mail.mil. Only one application is permitted per company, NOT one application per topic area or company business unit. The following information is required in the application. All application information should only be contained in the body of the email. No attachments are allowed. Email subject line �Fog and Edge Computing Solutions Meeting Application� Company name Website address Point of Contact (POC), email, phone number and alternate POC if desired One succinct single paragraph description (100 words or less in length and no bullets) of the technology that the company plans to discuss if they are selected to present at the Solutions Meeting. This description must focus on the technology and the envisioned use of that technology, and not a description of the company.� Select the one technology area of the three technology areas above (Human Computer Interfaces / Energy Efficient Computing and Architectures for Data Collection/Processing / Collaborative Computing, Fusion and Networking) that BEST fits your technology solution. Do not apply for multiple technology areas. All applications must be received on or before 5:00 PM EDT, August 10, 2022. Submission of an application does not guarantee an invitation to the Solutions Meeting. Selected companies are responsible for their travel and all other expenses associated with participation in the Fog and Edge Computing Solutions Meeting.
- Web Link
-
SAM.gov Permalink
(https://sam.gov/opp/4c263cb40f6b41ac8631bac48232d408/view)
- Place of Performance
- Address: Falls Church, VA 22041, USA
- Zip Code: 22041
- Country: USA
- Zip Code: 22041
- Record
- SN06408766-F 20220803/220801230126 (samdaily.us)
- Source
-
SAM.gov Link to This Notice
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