# Towards Rack Utilization in Internet Datacenters: An Approach Based on Dynamic Programming
## 1 Introduction  
Large-scale Internet Service Providers (ISPs) like Google, Facebook, Amazon and Tencent [1] usually rent Internet Data Centers (IDCs) to deploy their Internet services. Generally, IDCs are composed of infrastructure (e.g., servers, storage and network devices essential for the provision of Internet services, which are packaged in racks) and supporting environment (e.g., machine rooms, electricity, refrigeration, and network access needed for guaranteeing the normal running of infrastructure). As for large ISPs, there are two major methods of constructing IDCs. The first one requires ISPs to construct and manage all of the infrastructure of IDCs and their supporting environments, and we call it \"self-building mode\". The other method requires the ISP to build and manage the infrastructure of IDC, while the supporting environment is leased from a Data Center Provider (DCP). Thus, we call it \"leasing mode\", e.g., Google, Amazon and Yahoo lease the supporting environment from Equinix (Redwood City, CA, USA), an American public corporation providing carrier-neutral data centers and internet exchanges to enable interconnection [2]. Although Google et al. are trying the self-building mode, the leasing mode is still used widely due to its low construction cost, professional maintenance, and scalability, etc. In addition, it is quite difficult to build an IDC overseas because of national security policies. That is why the leasing mode is the common option of most ISPs. The operating cost under leasing mode mainly includes the lease expense to DCP. For convenience, DCP usually charges ISPs for the supporting environment at the unit of \"rack per year\", rather than according to specific services it offers. That is, the more racks an ISP uses, the more lease expense it should pay the DCP. Therefore, to reduce the rack number by enhancing rack utilization is an effective way to lower the operating cost of ISP. There are several factors limiting the rack utilization, which are as follows:* the total height of all servers in one rack should not exceed the height of the rack;
* the number of servers should not exceed the total number of switch ports in one rack;
* the total power used by servers should not exceed the power allocated to one rack. As the IDC infrastructure including racks and switches are customized by ISPs, DCP usually sets no limitation on the height of rack and the number of switch ports in a rack. However, since the power supply system is pre-determined when building an IDC, the power of racks is subject to the power supply system in IDC. That is to say, the power of rack is the key limiting factor of rack utilization in IDC with leasing mode, and the rack utilization we focus on is essentially the utilization of rack power Studies [3, 4] have found that the power used by servers is always far below their power rating. Taking Figure 1 as an example, assuming the power demand of a server over time is as shown in Figure 1a, if we set its power budget at the power rating as shown in Figure 1b, there will be a huge power margin in the area shaded by dashed line. Specifically, the power margin is the part of the power budget that is not consumed by the servers, which directly decreases the rack utilization. To eliminate the power margin in servers, the server consolidation approach [5; 6; 7] unites as many applications as possible into fewer servers to make full use of the power budget. However, there are some problems with this method in real-world datacenters [8]. First, due to the higher density of applications in a server, a single point of failure will affect more applications. Meanwhile, server consolidation is typically based on virtualization, which could bring some overhead and unfair contentions among applications. Finally, there is an inevitable cost of application migration when consolidating applications. Another approach to eliminate the power margins is to restrict power budgets of servers [9; 10; 11; 12], that is, to set a lower power budget by using power capping technology.