SBIR/STTR Research Award

Online Thread Detection in Social Networks Using Accelerators

Award identifier d669cb52391b24cbc9a2f39881cf49f43ccf9d5fb1987461859c089cfa463aa6Awarding agency Department of Energy

Award amount

$149,500

Program and phase

SBIR · Phase I

Award year

2015

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Award details

Awarding agency
Department of Energy
Branch
Not reported
Recipient company
Accelereyes LLC
Proposal award date
2015-02-17
Contract end date
2015-11-16
UEI
DPKMLZM47HL8
Solicitation number
DE-FOA-0001164
Topic code
03a

Research abstract

Problem Statement: Real-time analysis and monitoring of networks is crucial for threat detection. Networks are ubiquitous in todays world and can appear in many formats and to name a few we have: communication networks, social networks, and power networks. In many instances it is important to know who the key players are in the network these can be people, computers, or relay stations. One of the most widely used metrics for finding such players is between-centrality. Solution Statement: Betweenness centrality is computationally demanding. In recent times several approaches have been created that allow for tracking key-players in the network as it evolves (in real-time). These approaches have limited parallel scalability which limit the capability to analyze large(r) networks. Our work will focus on taking these new approaches and improving on the scalability by applying new load-balancing techniques to that analytic that will allow for faster and better real-time monitoring of the system. Phase I Goals: In Phase I we will apply several workload estimation schemas that will try to estimate at real time the expected amount of work that is required for updating the analytic due to the network-increment. In practice, we will need to estimated work for the two main stages of the algorithm. Once the work has been estimated, we will need to partition the work in a way that each computational resource (aka thread, core, or processor) will get an equal amount of work. Thus, our work is split into main phases: 1) estimate the work and 2) load-balance the work. Achieving these two goals will get us significantly closer to real-time monitoring of these networks. Commercial Applications and Other Benefits: There are multiple industries that would benefit from having fast real-time monitoring of networks. This includes communication companies that want to find key routers in their network to avoid a single point of failure, for recommendation systems to find key players that would help market their product, or for security applications it might direct you to the leader of an organization. Congressional Summary: This project would improve real-time capabilities for tracking key players in dynamically changing networks. The newly proposed research would allow faster tracking of important players in larger networks.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

8 SBIR/STTR records share this UEI (2010–2018). Reported award amounts total $5,328,836. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, Department of Health and Human Services, Department of Energy

Agency intelligence

Department of Energy

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