A Two-Phase Task Allocation Strategy With a Hybrid Architecture
In complex disaster relief or unmanned delivery scenarios, the collaboration of heterogeneous UAVs faces numerous difficulties with dynamic and harsh environments, such as limited resource capacity and communication constraints. Especially for task allocation, the computational and communication bur...
Saved in:
Published in | 2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) pp. 55 - 60 |
---|---|
Main Authors | , , , , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
08.05.2024
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | In complex disaster relief or unmanned delivery scenarios, the collaboration of heterogeneous UAVs faces numerous difficulties with dynamic and harsh environments, such as limited resource capacity and communication constraints. Especially for task allocation, the computational and communication burden poses many challenges for real-time task assignment and execution. To achieve a high allocation efficiency, this paper presents a Two-Phase task allocation strategy within a hybrid architecture. In the centralized phase, considering UAVs' task requirements and capability, an initial task allocation is made from an overall perspective. In this phase, it determines the suitable types and numbers of UAVs, which guarantees the completion of tasks and reduces the potential communication to the greatest extent. In the distributed phase, specific UAVs within type-specific clusters are selected for executing tasks considering individual capability and physical location. This reduces the risk of single-UAV failures, enhancing the robustness and scalability of task allocation. Additionally, during the distributed phase, an incremental update method is employed to reduce communication latency and resource consumption. Experimental analysis and comparisons with the existing approaches demonstrate that our approach effectively reduces communication overhead and significantly improves task allocation efficiency. Furthermore, in the event of UAV failure or malfunction, it allows for a swift reallocation of tasks to other available UAVs. |
---|---|
AbstractList | In complex disaster relief or unmanned delivery scenarios, the collaboration of heterogeneous UAVs faces numerous difficulties with dynamic and harsh environments, such as limited resource capacity and communication constraints. Especially for task allocation, the computational and communication burden poses many challenges for real-time task assignment and execution. To achieve a high allocation efficiency, this paper presents a Two-Phase task allocation strategy within a hybrid architecture. In the centralized phase, considering UAVs' task requirements and capability, an initial task allocation is made from an overall perspective. In this phase, it determines the suitable types and numbers of UAVs, which guarantees the completion of tasks and reduces the potential communication to the greatest extent. In the distributed phase, specific UAVs within type-specific clusters are selected for executing tasks considering individual capability and physical location. This reduces the risk of single-UAV failures, enhancing the robustness and scalability of task allocation. Additionally, during the distributed phase, an incremental update method is employed to reduce communication latency and resource consumption. Experimental analysis and comparisons with the existing approaches demonstrate that our approach effectively reduces communication overhead and significantly improves task allocation efficiency. Furthermore, in the event of UAV failure or malfunction, it allows for a swift reallocation of tasks to other available UAVs. |
Author | Wang, Wen Ren, Shuangyin Gong, Xiaomin Wang, Jingchao Zhang, Xiaoyu Yang, Yuxuan |
Author_xml | – sequence: 1 givenname: Xiaoyu surname: Zhang fullname: Zhang, Xiaoyu organization: People's Liberation Army,Institute of Systems Engineering, Academy of Military Sciences,Beijing,China – sequence: 2 givenname: Wen surname: Wang fullname: Wang, Wen organization: People's Liberation Army,Institute of Systems Engineering, Academy of Military Sciences,Beijing,China – sequence: 3 givenname: Shuangyin surname: Ren fullname: Ren, Shuangyin organization: People's Liberation Army,Institute of Systems Engineering, Academy of Military Sciences,Beijing,China – sequence: 4 givenname: Xiaomin surname: Gong fullname: Gong, Xiaomin organization: People's Liberation Army,Institute of Systems Engineering, Academy of Military Sciences,Beijing,China – sequence: 5 givenname: Yuxuan surname: Yang fullname: Yang, Yuxuan organization: People's Liberation Army,Institute of Systems Engineering, Academy of Military Sciences,Beijing,China – sequence: 6 givenname: Jingchao surname: Wang fullname: Wang, Jingchao email: wangjc.2000@tsinghua.org.cn organization: People's Liberation Army,Institute of Systems Engineering, Academy of Military Sciences,Beijing,China |
BookMark | eNo1j9tKw0AURUdRsNb8gQ_zA6nnzH2eJMRLhYJCA30sk-TEjNZEkojk7y2osGGxXhbsS3bW9R0xxhFWiOBv8m2-uzOoji5AqBWCdseZE5Z4653UIJVHp07ZQljjUvSgLlgyjm8AIAWi8XbBbjNefPfpSxtG4kUY33l2OPRVmGLf8e00hIleZ76LU8sDX8_lEGueDVUbJ6qmr4Gu2HkTDiMlf1yy4uG-yNfp5vnxKc82aVTepJZkY2ypa2iEp8ahMQQuCFvWTqJGY61WKMjURnqr6iZoKK1pSAYpIFRyya5_s5GI9p9D_AjDvP-_LH8A7DFLjg |
ContentType | Conference Proceeding |
DBID | 6IE 6IL CBEJK RIE RIL |
DOI | 10.1109/CSCWD61410.2024.10580586 |
DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP All) 1998-Present |
DatabaseTitleList | |
Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://proxy.k.utb.cz/login?url=https://ieeexplore.ieee.org/ sourceTypes: Publisher |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Engineering |
EISBN | 9798350349184 |
EISSN | 2768-1904 |
EndPage | 60 |
ExternalDocumentID | 10580586 |
Genre | orig-research |
GrantInformation_xml | – fundername: Nature funderid: 10.13039/501100020487 |
GroupedDBID | 6IE 6IL 6IN ABLEC ADZIZ ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ CBEJK CHZPO IEGSK OCL RIE RIL |
ID | FETCH-LOGICAL-i496-7e3f67b5d0f29ef8166e08a27bd831516775412e6d63974dfa50b76fe3a320ac3 |
IEDL.DBID | RIE |
IngestDate | Wed Jul 17 05:50:32 EDT 2024 |
IsPeerReviewed | false |
IsScholarly | false |
Language | English |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-i496-7e3f67b5d0f29ef8166e08a27bd831516775412e6d63974dfa50b76fe3a320ac3 |
PageCount | 6 |
ParticipantIDs | ieee_primary_10580586 |
PublicationCentury | 2000 |
PublicationDate | 2024-May-8 |
PublicationDateYYYYMMDD | 2024-05-08 |
PublicationDate_xml | – month: 05 year: 2024 text: 2024-May-8 day: 08 |
PublicationDecade | 2020 |
PublicationTitle | 2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD) |
PublicationTitleAbbrev | CSCWD |
PublicationYear | 2024 |
Publisher | IEEE |
Publisher_xml | – name: IEEE |
SSID | ssj0003211697 |
Score | 1.9152015 |
Snippet | In complex disaster relief or unmanned delivery scenarios, the collaboration of heterogeneous UAVs faces numerous difficulties with dynamic and harsh... |
SourceID | ieee |
SourceType | Publisher |
StartPage | 55 |
SubjectTerms | Autonomous aerial vehicles Clustering algorithms communication overhead Computer architecture Federated learning heterogeneous UAVs hybrid architecture Real-time systems Robustness Scalability task reallocation Two-Phase task allocation |
Title | A Two-Phase Task Allocation Strategy With a Hybrid Architecture |
URI | https://ieeexplore.ieee.org/document/10580586 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1NSwMxEA22J734VfGbHLxmjdndZHOSUi1FsBRcaW8lHxNaKq3oFqm_3mTbrVUQhBxCIBBmCI_Me2-C0BWTqTOcWsKtFiToLoiMHSfAuR9M0diGesdjl3eek4dBOliZ1UsvDACU4jOIwrTk8u3MzEOpzN_wNPOD11Ato2xp1loXVGL_lOFSVGodKq9bT63-HQ9CRv8OZElUbf_xkUqJI-1d1K1OsJSPTKJ5oSPz-as547-PuIca35Y93FuD0T7agukB2tnoNniIbps4_5iR3sgDF87V-wQ3XwKUhdTgVZfaBe6PixFWuLMIVi7c3OAZGihv3-etDln9n0DGieREgA-60KmljklwgSAEmikmtM1iD_Q8NL-7YcBtIPcS61RKteAOYhUzqkx8hOrT2RSOEQbDAfwWFUhamQjJrXNSSaONEkbZE9QIoRi-LjtkDKsonP6xfoa2Q0ZK4WB2jurF2xwuPLgX-rJM6hcF-qI8 |
link.rule.ids | 310,311,786,790,795,796,802,27958,55109 |
linkProvider | IEEE |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV1NSwMxEA1aD-rFr4rf5uA1a9yPZHOSUi2rtqXgSr2VbDKhpdKKbpH660223VoFQcghBHYJM4RH5r15QejCF5FRjGrCdMaJ010QERhGgDE7fEkD7eodrTZLnsL75-h53qxe9MIAQCE-A89NCy5fj9XElcrsCY9iO9gqWrNAT8WsXWtRUgnsZYYJXup1qLisP9a7N8xJGe1N0A-98gc_nlIpkKSxhdrlHmYCkqE3yTNPff6yZ_z3JrdR9btpD3cWcLSDVmC0izaX_Ab30HUNpx9j0ulb6MKpfB_i2osDM5ccPPepneLuIO9jiZOpa-bCtSWmoYrSxm1aT8j8BQUyCAUjHGzYeRZpanwBxlGEQGPp80zHgYV65uzvrnxg2tF7oTYyohlnBgIZ-FSqYB9VRuMRHCAMigHYT6SjaUXIBdPGCClUpiRXUh-iqgtF73XmkdEro3D0x_o5Wk_SVrPXvGs_HKMNl51CRhifoEr-NoFTC_V5dlYk-AvI26WS |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2024+27th+International+Conference+on+Computer+Supported+Cooperative+Work+in+Design+%28CSCWD%29&rft.atitle=A+Two-Phase+Task+Allocation+Strategy+With+a+Hybrid+Architecture&rft.au=Zhang%2C+Xiaoyu&rft.au=Wang%2C+Wen&rft.au=Ren%2C+Shuangyin&rft.au=Gong%2C+Xiaomin&rft.date=2024-05-08&rft.pub=IEEE&rft.eissn=2768-1904&rft.spage=55&rft.epage=60&rft_id=info:doi/10.1109%2FCSCWD61410.2024.10580586&rft.externalDocID=10580586 |