Next-generation 6G networks are envisioned to be a key enabler for low-latency services (e.g., extended reality, remote surgery), which cannot be potentially realized by currently deployed networks. Network function virtualization (NFV) and software-defined networking (SDN) are going to continue playing their key role as two promising technologies in 6G to realize these services due to flexibility, agility, scalability, and cost-efficiency. Although NFV and SDN bring several benefits, provisioning latency-sensitive network services (NSs) in an NFV-based infrastructure remains a challenge, as they require stringent service deadlines. To efficiently meet such stringent service deadlines, VNF placement and scheduling need to be carried out jointly. Most of the existing studies tackle these two problems separately. In this paper, we study the joint VNF placement and scheduling problem for latency-sensitive NSs. We aim at optimally determining whether to place new VNFs or to reuse the already deployed VNFs to optimize profits while guaranteeing stringent deadlines. To solve the problem, we formulate it as an integer linear programming (ILP) problem. Due to its complexity, we also propose two efficient heuristics, namely, greedy-based and Tabu search-based algorithms to solve the problem. The simulation results show that our proposed algorithms achieve higher profits than the existing benchmarks.