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Earth observation resources are becoming increasingly indispensable indisaster relief, damage assessment and related domains. Many unpredictedfactors, such as the change of observation task requirements, to the occurringof bad weather and resource failures, may cause the scheduled observationscheme to become infeasible. Therefore, it is crucial to be able to promptlyand maybe frequently develop high-quality replanned observation schemes thatminimize the effects on the scheduled tasks. A bottom-up distributedcoordinated framework together with an improved contract net are proposed tofacilitate the dynamic task replanning for heterogeneous Earth observationresources. This hierarchical framework consists of three levels, namely,neighboring resource coordination, single planning center coordination, andmultiple planning center coordination. Observation tasks affected byunpredicted factors are assigned and treated along with a bottom-up route fromresources to planning centers. This bottom-up distributed coordinated frameworktransfers part of the computing load to various nodes of the observationsystems to allocate tasks more efficiently and robustly. To support the promptassignment of large-scale tasks to proper Earth observation resources indynamic environments, we propose a multiround combinatorial allocation (MCA)method. Moreover, a new float interval-based local search algorithm is proposedto obtain the promising planning scheme more quickly. The experimentsdemonstrate that the MCA method can achieve a better task completion rate forlarge-scale tasks with satisfactory time efficiency. It also demonstrates thatthis method can help to efficiently obtain replanning schemes based on originalscheme in dynamic environments.

Bottom-up mechanism and improved contract net protocol for the dynamic task planning of heterogeneous Earth observation resources