Metrics
3 Record Views
Conference proceeding
A content and context-aware solution for network state exchange in tactical networks
MILCOM IEEE Military Communications Conference, pp.430-435
IEEE International Conference on Distributed Computing Systems (ICDCS), 39th (Dallas, Texas, USA, 07/07/2019–07/10/2019)
10/2017
Web of Science ID: WOS:000426935700074
Abstract
Efficient network communications are essential to enable network-centric warfare. However, tactical edge networks present an extremely challenging and heterogeneous networking environment due to heterogeneous architectures, dynamic topologies, unwanted adversarial behavior, interference, and other wireless channel conditions. In order to support end-user applications and guarantee system performance and interoperability in such constrained environments, it is critical to adapt the volume and type of traffic generated by applications to the continuously varying network conditions. To this end, we extended the Agile Computing Middleware (ACM) with capabilities specifically designed to provide network state detection and adaptation in constrained networks. In this paper, we present SENSEI (for Smart Estimation of Network StatE Information), a set of components of the ACM that provides effective strategies for the dissemination of network state information. SENSEI implements a content- and context-aware clustering-based algorithm for the distribution of network state information that can significantly reduce the overhead associated with network state information sharing.
Related links
Details
- Title
- A content and context-aware solution for network state exchange in tactical networks
- Publication Details
- MILCOM IEEE Military Communications Conference, pp.430-435
- Resource Type
- Conference proceeding
- Conference
- IEEE International Conference on Distributed Computing Systems (ICDCS), 39th (Dallas, Texas, USA, 07/07/2019–07/10/2019)
- Publisher
- IEEE
- Number of pages
- 6
- Copyright
- © 2019, IEEE
- Identifiers
- WOS:000426935700074; 99381512040806600
- Academic Unit
- Intelligent Systems and Robotics; Hal Marcus College of Science and Engineering
- Language
- English