AI Bibliography
AI Bibliography |
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Bertino, E., Calo, S., Toma, M., Verma, D., Williams, C., & Rivera, B. 2017, A cognitive policy framework for next-generation distributed federated systems: Concepts and research directions. Paper presented at 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS). |
| Resource type: Proceedings Article BibTeX citation key: Bertino2017 View all bibliographic details  |
Categories: Cognitive Science, Computer Science, Data Sciences, Decision Theory, Engineering, General, Military Science Subcategories: Big data, Cloud computing, Command and control, Cyber, Drones, Internet of things, Neural nets, Robotics Creators: Bertino, Calo, Rivera, Toma, Verma, Williams Publisher: Collection: 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS) |
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Next-generation collaborative activities and missions will be carried out by autonomous groups of devices with a large variety of cognitive capabilities. These devices will have to operate in environments characterized by uncertainty, insecurity (both physical and cyber), and instability. In such environments, communications may be fragmented. Proper policy-based management of such autonomous device groups is thus critical. However current policy management systems have many limitations, including lack of flexibility. In this paper, we articulate novel architectural approaches addressing the requirements for the effective management of autonomous groups of devices and discuss the notion of generative policies - a novel paradigm that enhances the flexibility of policy-based approaches to management. In this paper, we also survey types of policy that are essential for managing device groups. Even though many such policy types exist in conventional settings, their use in our context poses novel challenges that we articulate in the paper. We also introduce a research roadmap discussing several research directions towards the development of a cognitive and flexible policy-based approach to the management of autonomous groups of devices for collaborative missions. Finally, as our proposed policy paradigm is data-intensive, we discuss the problem of supplying the data required for policy decisions in environments characterized by mobility, uncertainly, and fragmented communications.
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