# Scalable and Reliable Data Center Networks by Combining Source Routing and Automatic Labelling
## 2 Related Work  
DCNs are implemented based on two different strands, based on whether the control logic is centralized or distributed. On the one hand, centralized approaches usually leverage the SDN [11, 12] paradigm. SDN allows a flexible definition of the behavior through a logically centralized controller connected to the network devices. Works like PortLand [2] o VL2 [3] are implemented with SDN. Nevertheless, this centralized control lacks scalability [8], specially to grant timely network monitoring to solve network failures [13], hence causing slow recovery times that hinders overall network performance.  
On the other hand, distributed implementations try to overcome the scalability and robustness limitations of the centralized ones, but they are constrained in flexibility and ease of configuration. LESS [14] and FZS [15] follow a distributed approach and they are currently the only works that try to tackle most of these challenges. They are also the closest to eTorii, as it is based on source routing [16] together with label assignment. However, differently from eTorii, LESS requires the addition of an initial header to reach the destination, which reduces performance. Moreover, it also entails a second header containing alternative routes (even when no malfunction occurs) to overcome network failures, which is not needed in eTorii as alternative routes can be directly deduced from current routes thanks to its synchronized labelling mechanism. Finally, in the case of FZS, although it does not suffer from the disadvantages of LESS mentioned before, it is only applicable to certain DCNs, and it lacks additional features provided by eTorii such as on-the-fly path repair.  
Additionally, some recent works in the state of the art focus on network resilience, which are worth mentioning. LetFlow [17] leverages flowlet switching to balance the load and to be resilient to asymmetry. This idea is supported by the elastic capabilities of flowlets to adapt to traffic. APS [18], CAPS [19] and QDAPS [20] follow a similar approach by dynamically separating flows based on different parameters, such as flow size (long vs. short) or queueing delay; thus, avoiding resource competition in congested networks. However, these previous approaches do not always guarantee timely re-routing, and are only focused on dynamically adapting the traffic in congested areas of the network. Hermes [21] acknowledges this problem and, for that reason, it defines an alternative approach based on network monitoring to carefully re-route traffic without causing additional problems due to abrupt changes. Although Hermes is the closest alternative to eTorii, the dependence on monitoring (not required in eTorii) might have potential scalability and performance issues in large DCNs.  
Accordingly, the main contributions of eTorii are:  
* Differently from most of the state of the art, it follows a distributed approach to maximize scalability and resilience.
* Packet forwarding follows a source-routing approach based on previously assigned labels, but no additional headers or fields are required, not even for network recovery upon failures.
* Thanks to the nature of its labels, routing tables are drastically reduced, independently of the active communication flows, and network recovery can be executed even on-the-fly (zero delay) in some scenarios.  
* Labels are automatically assigned at startup and after any network change, granting auto-configuration.
* It is generalized and applicable to any hierarchical DCN, guaranteeing flexibility.