Adaptive Mobile Networking at the Tactical Edge: A Social-Aware Perspective
Abstract
In military operations at the tactical edge, adaptability of mobile communication systems is crucial to ensure warfighters situational awareness and prompt access on the actionable tactical information, but is not well supported by the current communication systems used in the U.S. Army. We envision that such adaptability could be achieved from a unique social-aware perspective based on properly articulated multi-genre network analysis, which exploits the close coupling between mobile communication networks and human social networks at the tactical edge. This analysis interprets warfighters situational response to the heterogeneous battlefield contexts as their social dynamics, which are defined as the temporal and spatial variations of social relationship among warfighters and are autonomously characterized from warfighters contact patterns without manual inputs or configurations. However, due to the practical Disconnected, Intermittent, and Limited (DIL) network environment at the tactical edge which makes it hard to maintain persistent end-to-end wireless network connectivity among warfighters, there are many challenges of investigating, formulating, and exploiting such social dynamics for adaptive mobile networking, including: (1) the dynamics of warfighters contact patterns need to be analytically and accurately formulated; (2) a unified framework integrating models from multi-genre networks is needed to better characterize social dynamics among warfighters; (3) the global coordination and timely information exchange among warfighters are challenging due to the lack of end-to-end network connectivity, but are necessary for adaptive network decisions. The proposed research will address these challenges through stochastic modeling of various essential characteristics of warfighters behavior patterns, leading to timely and precise prediction of warfighters communication needs in the future and designs of adaptive mobile networking strategies at the tactical edge. Three major research thrusts are proposed for this project: (1) Adaptive Contact Prediction: improving the accuracy of contact prediction through formulation of the heterogeneous transient characteristics of warfighters contact patterns in both temporal and spatial dimensions; (2) Characterization of Social Dynamics: characterizing the social dynamics among warfighters by exploring the correspondence of various sociological concepts in DIL network environments; (3) Adaptive Networking Framework: developing social-aware data dissemination and cooperative caching schemes which autonomously adapt to the social dynamics among warfighters. The proposed network models, protocols, and architecture designs will be evaluated using a hybrid method of tactical trace-based simulations and realistic mobile testbed experimentation. We will first evaluate the adaptability of our proposed schemes over the multi-level Attica tactical network scenario which depicts the actual warfighters behavior patterns at the tactical edge. Then, we will further implement the proposed techniques as a mobile network testbed, which is used to emulate dynamic wireless network conditions, environmental contexts, and human factors at the tactical edge. This testbed will also become a unique research facility and prototype system that meet the Army s tactical needs. Meanwhile, through curriculum development and student mentoring, the proposed educational activities will significantly improve the involvement of underrepresented minority students into high-tech engineering research that is particularly critical to the DoD missions.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 12, 2017
- Source ID
- W911NF1510221
Entities
People
- Wei Gao
Organizations
- Army Contracting Command
- United States Army
- University of Tennessee