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Flexible Resource Assignment in Sensor Networks : A Hybrid Reasoning Approach

de Mel, Geeth, Sensoy, Murat, Vasconcelos, Wamberto and Preece, Alun David ORCID: 2009. Flexible Resource Assignment in Sensor Networks : A Hybrid Reasoning Approach. Presented at: 1st International Workshop on the Semantic Sensor Web (SemSensWeb), Heraklion, Crete, Greece, 2009. pp. 1-15.

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Today, sensing resources are the most valuable assets of critical tasks (e.g., border monitoring). Although, there are various types of assets available, each with different capabilities, only a subset of these assets is useful for a specific task. This is due to the varying information needs of tasks. This gives rise to assigning useful assets to tasks such that the assets fully cover the information requirements of the individual tasks. The importance of this is amplified in the intelligence,surveillance, and reconnaissance (ISR) domain, especially in a coalition context. This is due to a variety of reasons such as the dynamic nature of the environment, scarcity of assets, high demand placed on available assets, sharing of assets among coalition parties, and so on. A significant amount of research been done by different communities to effciently assign assets to tasks and deliver information to the end user. However, there is little work done to infer sound alternative means to satisfy the information requirements of tasks so that the satisfiable tasks are increased. In this paper, we propose a hybrid reasoning approach (viz., a combination of rule-based and ontology-based reasoning) based on current Semantic Web technologies to infer assets types that are necessary and sufficient to satisfy the requirements of tasks in a flexible manner.

Item Type: Conference or Workshop Item (Paper)
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Uncontrolled Keywords: Sensors ; Platforms ; Resource Assignment ; Semantic Web ; Rules ; Hybrid Reasoning.
Last Modified: 17 Oct 2022 09:43

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