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The Industrial Internet of Things (IIoT) is an emerging paradigm to makeindustrial operations more efficient and intelligent by deploying a massivenumber of wireless devices to industry scenes. However, due to the limitedcomputing capability and batteries, the Industrial Internet of Things Devices(IIoTDs) can't perform the computation-intensive or delay-sensitive tasks welland provide long-term services in practical. To tackle these challenges, wepresent an effective global joint resource allocation scheme for UnmannedAerial Vehicle (UAV) service of Pervasive Edge Computing (PEC) in IndustrialInternet of Things (IIoTs) and studied a collaborative UAV server-IIoTDs schemein this paper. In our proposed scheme, the IIoTDs can keep high-efficiencyperformance even their battery ran out, by deploying the UAV as a PEC serverand a mobile power source to provide task offloading and energy harvestingopportunities for IIoTDs. In consideration of the offloading positionselection, devices resource allocation and system performance, we aim tominimize the overall service latency of all IIoTDs consisting of taskcomputation latency and offloading latency, by joint optimizing the taskoffloading decisions, charging resources allocation, connection management, andUAV computation resources allocation. However, the formulated optimizationproblem is a mixed-integer nonlinear programming (MINLP) problem which ischallenging to solve in general. In order to address the problem, we decomposeit into multiple convex sub-problems based on block-coordinate descent (BCD)method to obtain the optimal solution. Performance evaluation demonstrates thatour scheme outperforms the existing schemes in terms of the overall servicelatency of IIoTDs.

GJRA: A Global Joint Resource Allocation Scheme for UAV service of PEC in IIoTs