The Internet of Battle Things
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Abstract (arXiv)
The battlefield of the future will be densely populated by a variety of entities ("things") -- some intelligent and some only marginally so -- performing a broad range of tasks: sensing, communicating, acting, and collaborating with each other and human warfighters. We call this the Internet of Battle Things, IoBT. In some ways, IoBT is already becoming a reality, but 20-30 years from now it is likely to become a dominant presence in warfare. To become a reality, however, this bold vision will have to overcome a number of major challenges. As one example of such a challenge, the communications among things will have to be flexible and adaptive to rapidly changing situations and military missions. In this paper, we explore this and several other major challenges of IoBT, and outline key research directions and approaches towards solving these challenges.
Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Dec 2017.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 1; 2024: 2; 2025: 2; 2026: 2.
11 papers.
- 2021Link Scheduling using Graph Neural Networkscited by 26
- 2022Distributed Link Sparsification for Scalable Scheduling Using Graph Neural Networkscited by 4
- 2022Delay-aware Backpressure Routing Using Graph Neural Networkscited by 3
- 2023Congestion-aware Distributed Task Offloading in Wireless Multi-hop Networks Using Graph Neural Networkscited by 3
- 2024Biased Backpressure Routing Using Link Features and Graph Neural Networkscited by 2
- 2021Game-Theoretic and Machine Learning-based Approaches for Defensive Deception: A Surveycited by 1
- 2026Knowledge Base Poisoning Attacks and Defense for Policy-Aware LLM-RAG Frameworkcited by 1
- 2024Robust synchronization and policy adaptation for networked heterogeneous agentscited by 0
- 2025Distributed Link Sparsification for Scalable Scheduling Using Graph Neural Networks (Journal Version)cited by 0
- 2025A Differentiable Digital Twin of Distributed Link Scheduling for Contention-Aware Networkingcited by 0
- 2026A Recommendation System Approach for Interference-Robust Sensor Subset Selectioncited by 0
- 2026A Recommendation System Approach for Interference-Robust Sensor Subset Selection11 Aug 2026
- 2026Knowledge Base Poisoning Attacks and Defense for Policy-Aware LLM-RAG Framework5 Jul 2026
- 2025A Differentiable Digital Twin of Distributed Link Scheduling for Contention-Aware Networking11 Dec 2025
- 2025Distributed Link Sparsification for Scalable Scheduling Using Graph Neural Networks (Journal Version)5 Sep 2025
- 2024Robust synchronization and policy adaptation for networked heterogeneous agents5 Sep 2024
- 2024Biased Backpressure Routing Using Link Features and Graph Neural Networks13 Jul 2024
- 2023Congestion-aware Distributed Task Offloading in Wireless Multi-hop Networks Using Graph Neural Networks5 Dec 2023
- 2022Delay-aware Backpressure Routing Using Graph Neural Networks19 Nov 2022
- 2022Distributed Link Sparsification for Scalable Scheduling Using Graph Neural Networks27 Mar 2022
- 2021Link Scheduling using Graph Neural Networks12 Sep 2021
- 2021Game-Theoretic and Machine Learning-based Approaches for Defensive Deception: A Survey21 Jan 2021