C4.5: programs for machine learning
C4.5: programs for machine learning
Resource and service discovery in wireless ad-hoc networks with agile computing
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
Reasoning about knowledge in distributed systems using datalog
Datalog 2.0'12 Proceedings of the Second international conference on Datalog in Academia and Industry
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Tactical networking environments demand reliable, robust, and efficient approaches to disseminating information that are tolerant to unreliable and bandwidth-constrained networks. This paper describes DisService, an Agile Computing approach to information dissemination that opportunistically discovers and exploits excess communications, storage, and processing capacity in a distributed network to improve the performance of information dissemination. DisService is disruption tolerant and caches data throughout the network by replicating the data. Nodes subscribe to hierarchically organized groups. Information is published in the context of a group, and may also be tagged to differentiate between multiple types of data (e.g., blue-force tracking, sensor data, logistics, or other runtime information). Each node operates in a distributed, peer-to-peer manner while processing and communicating the published information and requested subscriptions from neighboring nodes. Information is disseminated using an efficient combination of push and pull, depending on the number of subscribers, the capacity of the network, the stability of nodes in the network, and the predicted information needs of users. Finally, DisService also supports efficient dissemination of large data by replicating and scattering fragments throughout the network. These features combine to realize an effective approach to information dissemination for tactical networks.