# Novel Multi-Level Dynamic Traffic Load-Balancing Protocol for Data Center
## 1 Introduction  
The exponential growth of the information technology (IT) industry and its storage demand forces to move toward cloud computing, in which a huge amount of computing and storage resources are provided in large data centers [1; 2]. These data centers are designed with high-speed, highly configured servers. The cloud servers are used to offer web searches, Amazon Elastic Compute Cloud (EC2), Microsoft azure storage, and personal and business storage [3; 4; 5]. As a consequence, the cloud servers handle a huge amount of data, and the interconnected networks and server resources eventually become unstable, which hits the performance of the network bandwidth [6]. Due to this, the network bandwidth, the latency-sensitive web services, and applications are suffering from a long network latency tail [7]. An illustrating image of the data center traffic load is shown in Figure 1.  
The multi-rooted topologies have been adopted for data center networks. This is to provide the high bisection bandwidth [8]. The existing multipath topologies are used to deliver the alternative routing paths between any two end-hosts under different switches. The load balancing for multiple paths with the utilization of whole network resources can improve throughput as well as reduce latency for data center applications [9]. The production data centers are used to operate under several uncertainty factors. The uncertainty factors are mainly the dynamicity of the traffics, unstable links, device heterogeneity, and switch failures [10]. To overcome these situations due to uncertain circumstances, the load-balancing technique is seriously effective. Using the load-balancing technique, the accuracy of the path-sensing conditions and path rerouting according to the path conditions can be improved. However, many of these protocols are unaffected by path conditions; the approach is to split blindly at a fixed granularity. The proposal was made by ignoring traffic conditions; however, it can be seen that it affects the performance, especially when asymmetry arises [7, 11]. The flowlet-based proposals have been proposed to sense the path conditions. However, it facilitates rerouting only when the flowlet emerges. The flowlet formation depends on various factors that are related to the applications and the transport layer. As a result, using a flowlet-based reaction to the path conditions does not provide a timely reaction to congestion [10]. In addition, switch modification-based approaches (CONGA and HULA) are based on switching or hardware modification that imposes impracticalities [12, 13]. Among other solutions, Hermes has been impressing through its better performance [14]. Hermes accomplishes per-flow load balancing to enact faster rerouting following the network status. It applies packets to react timely to overcome uncertainty challenges. However, it also imposes the congestion mismatch and packet reordering as well; in such conditions, Hermes reduces the frequency of rerouting to avoid congestion. Moreover, Hermes uses the unsystematic hashing, round robin, and seeks the best path to route and reroute based on the path conditions as well as flow status. However, stability is a key concern for the condition when flows interact in the network [10]. The bursty network congestion has been well addressed in [15, 16, 17] at the transport and link layers. Their performances can be further improved with the support from the load balancing schemes at network layer. The main contribution of this article is a multi-level dynamic traffic load-balancing (MDTLB) protocol. The key idea is to design a protocol using the functionalities of Hermes, multiple levels of path characterization, and an adaptive approach to setting parameters. Two algorithms are proposed, namely, the judging algorithm and the rerouting algorithm. The rest of the article is organized as follows. Section 2 discusses the background study, and Section 3 provides the motivation of the study. Section 4 discusses the methodology of the proposed approach.