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المؤلفAboualola, Mohamed
المؤلفAbualsaud, Khalid
المؤلفKhattab, Tamer
المؤلفZorba, Nizar
تاريخ الإتاحة2024-03-26T11:56:47Z
تاريخ النشر2022
اسم المنشورProceedings - IEEE Global Communications Conference, GLOBECOM
المصدرScopus
الرقم المعياري الدولي للكتاب23340983
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/GLOBECOM48099.2022.10001114
معرّف المصادر الموحدhttp://hdl.handle.net/10576/53529
الملخصWith the emergence of three new paradigms, namely the Internet of Things (IoT), cloud/edge computing and mobile social networks; Mobile Crowd Sensing (MCS) has emerged as a potential approach for data collecting in numerous applications, such as traffic management, infotainment, disaster management or public safety. MCS mechanisms are receiving a lot of attention, both from research and development areas, showing their impact and benefit. But their optimization is still under development, mainly due to the large number of involved parameters. A major field within MCS relates to crowd management for emergency situations, where the management and optimization mechanisms become crucial to local authorities. To tackle this problem, in this work, we propose an MCS hybrid worker selection scheme that operated various modes depending on the delay-cost requirements. Our scheme exploits the user behavior to achieve an optimal bi-objective for any delay-cost requirement. We use simulations to evaluate the performance of our proposal, and we show the optimal and different sub-optimal solutions that can match the delay-cost requirements.
راعي المشروعThis work was supported by Qatar University Grants M-QJRC-2020-4 and QUHI-CENG-21/22-1. The statements made herein are solely the responsibility of the authors.
اللغةen
الناشرIEEE
الموضوعCrowd Management
Hybrid System
MCS
Sub-Optimal
Task Allocation
العنوانNovel Task Allocation Method for Emergency Events under Delay-Cost Tradeoff
النوعConference Paper
الصفحات6236-6240
dc.accessType Abstract Only


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