This paper considers a network design problem using Unmanned Aerial Vehicles (UAVs). It aims to create a network to provide communication and computation service to a set of source-destination ground node pairs. The main performance metric is the minimum amount of computed data among a set of source-destination pairs. To optimize this metric, we outline two mixed Integer Linear Programs (MILPs), namely S-MILP and NS-MILP, which are designed respectively for splittable and non-splittable traffic flow models. They jointly optimize the placement of UAVs, assignment of Virtualized Network Functions (VNFs), and routing of unprocessed and processed flow. Further, NS-MILP optimizes the path selection of each source-destination pair. A key challenge is that these MILPs require an exhaustive collection of network topologies. To this end, this paper outlines two heuristic algorithms, called Resource-Aware Location Selection (RALS) and Resource-Aware Path and Location Selection (RAPLS), respectiv
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On May 31, 2023, the IRS released a Notice of Proposed Rulemaking (Proposed Rules)[1] concerning the low-income communities bonus tax credit program…