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      Two Effective Strategies to Support Cross-Organization Emergency Resource Allocation Optimization

      1 , 2 , 1 , 1
      Mobile Information Systems
      Hindawi Limited

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          Abstract

          Cross-organization emergency resource allocation optimization problem is essential to guarantee a successful emergency disposal, and it has become a research focus of modern emergency management. Generally speaking, there are two possible types of resource allocation scenarios: (1) if the emergency resources are overallocated, on the one hand, parallel execution of independent emergency activities can be supported and the emergency disposal time is reduced; on the other hand, too many idle resources may cause low resource utilization rate, high scheduling overhead, and high cost; and (2) if emergency resources are underallocated, this may lead to resource conflicts and the need for some emergency activities to wait for others to complete, and finally the emergency disposal time may increase. Therefore, reasonable emergency resource allocation strategies are highly desired. To the best of our knowledge, there is no formal approach to support the cross-organization emergency resource allocation issue. To handle this problem, we propose a two-layered framework to facilitate the allocation of limited emergency resources to meet its time constraints with high efficiency. More specifically, a kind of Petri net extended with time, resource, and message information, denoted as CE-net, is presented to model cross-organization emergency response processes. Based on the obtained CE-net, the minimum resource requirements are obtained with corresponding algorithms. Then, Minimum Execution Time (MET) strategy and Minimum Resource Consumption (MRC) strategy with their corresponding estimated execution intervals are introduced to facilitate the stakeholder to determine which strategy is suitable according to the timing requirements. A cross-organization fire emergency case is applied to validate the proposed approaches throughout the whole paper.

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          Most cited references37

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          Performance-effective and low-complexity task scheduling for heterogeneous computing

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            Pegasus: A Framework for Mapping Complex Scientific Workflows onto Distributed Systems

            This paper describes the Pegasus framework that can be used to map complex scientific workflows onto distributed resources. Pegasus enables users to represent the workflows at an abstract level without needing to worry about the particulars of the target execution systems. The paper describes general issues in mapping applications and the functionality of Pegasus. We present the results of improving application performance through workflow restructuring which clusters multiple tasks in a workflow into single entities. A real-life astronomy application is used as the basis for the study.
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              Optimized resource allocation for emergency response after earthquake disasters

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                Author and article information

                Contributors
                Journal
                Mobile Information Systems
                Mobile Information Systems
                Hindawi Limited
                1875-905X
                1574-017X
                January 4 2021
                January 4 2021
                : 2021
                : 1-15
                Affiliations
                [1 ]Department of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China
                [2 ]School of Computer Science and Technology, Shandong University of Technology, Zibo 255000, China
                Article
                10.1155/2021/7965935
                913ad2a5-324f-4158-bffd-51349c0920a5
                © 2021

                https://creativecommons.org/licenses/by/4.0/

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