TY - GEN
T1 - Learning Service Semantics for Self-Organization in Distributed Environments
T2 - 2018 IEEE Military Communications Conference, MILCOM 2018
AU - Bent, Graham
AU - De Mel, Geeth
AU - Ganti, Raghu
AU - La Porta, Tom
AU - Pearson, Gavin
AU - Pham, Tien
AU - Stein, Sebastian
AU - Tassiulas, Leandros
AU - Taylor, Ian
N1 - Funding Information:
This research was sponsored by the U.S. Army Research Laboratory and the U.K. Ministry of Defence under Agreement Number W911NF-16-3-0001. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Army Research Laboratory, the U.S. Government, the U.K. Ministry of Defence or the U.K. Government. The U.S. and U.K. Governments are authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation hereon.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/7/2
Y1 - 2018/7/2
N2 - A key challenge in performing analytics in distributed environments is to automatically compose services to dynamically match operational tasks to information requirements, accounting for impact, in a many-to-many temporally and spatially complicated and complex situations. In dynamic and agile environments, such as coalition environments, the state of the network and resources cannot be completely known in advance nor controlled due to the evolving nature of the network and constraints that may preclude partners from accessing complete state information about different parts of the system. In addition, there may be requests made to the system that have not been made before, requiring services to be created on the fly. Motivated by these observations, in this paper, we present a critical analysis of gaps in the state-of-the-art and our vision to address those through novel theoretical contributions. We envision that such formalized and theorized fundamentals will enable service elements to automatically configure themselves to perform analytic tasks based on user specified goals by taking account of context-be it system or user context.
AB - A key challenge in performing analytics in distributed environments is to automatically compose services to dynamically match operational tasks to information requirements, accounting for impact, in a many-to-many temporally and spatially complicated and complex situations. In dynamic and agile environments, such as coalition environments, the state of the network and resources cannot be completely known in advance nor controlled due to the evolving nature of the network and constraints that may preclude partners from accessing complete state information about different parts of the system. In addition, there may be requests made to the system that have not been made before, requiring services to be created on the fly. Motivated by these observations, in this paper, we present a critical analysis of gaps in the state-of-the-art and our vision to address those through novel theoretical contributions. We envision that such formalized and theorized fundamentals will enable service elements to automatically configure themselves to perform analytic tasks based on user specified goals by taking account of context-be it system or user context.
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U2 - 10.1109/MILCOM.2018.8599809
DO - 10.1109/MILCOM.2018.8599809
M3 - Conference contribution
AN - SCOPUS:85061429127
T3 - Proceedings - IEEE Military Communications Conference MILCOM
SP - 1080
EP - 1085
BT - 2018 IEEE Military Communications Conference, MILCOM 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 29 October 2018 through 31 October 2018
ER -