In the design of a metasurface-assisted system for indoor environments, it is essential to take into account not only the performance gains and coverage extension provided by the metasurface but also the operating costs brought by its reconfigurability, such as powering and cabling. These costs can present challenges, particularly in indoor dense spaces (IDSs). A self-sustainable reconfigurable intelligent surface (ssRIS), which retains reconfigurability unlike a static metasurface (SMS), achieves a lower operating cost than a reconfigurable intelligent surface (RIS) by being self-sustainable through power harvesting. In this paper, in order to find a better trade-off between metasurface gain, coverage, and operating cost, the design and performance of an ssRIS-assisted indoor mmWave communication system are investigated. We simplify the use of the ssRIS by considering a preset-based element splitting scheme for maintaining self-sustainability and the formation of coverage groups by associating ssRISs with the closest user equipments (UEs). We propose a two-stage iterative algorithm to maximize the minimum data rate by jointly deciding the association between the UEs and the ssRISs, the phase shifts of the ssRISs, and allocating time resources for each UE. The non-convex optimization problem is tackled using the feasible point pursuit successive convex approximation method. To understand the best scenario for using ssRIS, the resulting performance is compared with that achieved with RIS and SMS. Our numerical results indicate that ssRISs are best utilized in a small environment where self-sustainability is easier to achieve when the budget for operating costs is tight.