# Novel Multi-Level Dynamic Traffic Load-Balancing Protocol for Data Center
## 6 Related Work  
The most recent and related algorithms, schemes, and protocols studies are discussed for the data center load balancing. Table 6 shows the summary of the existing scheme under the algorithm or mechanism functionality. Researchers have proposed Presto, DRB, and RPS using per-packet per flow cell-based flow congestion load-balancing schemes [7; 11]. Many researchers had proposed congestion-aware switching techniques to balance the data center loads. However, from the assessment, it is evident that most of the schemes suffer from the congestion mismatch in an asymmetric condition [12; 18]. In continuation, to recover, the congestion mismatch issue advanced programmable switches that were engaged [13]. The main target was to achieve better visibility and throughput. Flowlet switching had projected balancing the traffic surrounded by parallel paths. Nevertheless, the flowlet has the limitation of reacting to the congestion situations under stable conditions that lead it to have slower  
Figure 14: Average throughput comparison among the protocols for the web search load. Figure 13: Average throughput comparison among the protocols for the general load. Figure 15: Average throughput comparison among the protocols for the data-mining load. convergence and suboptimal performance. A flowlet weighted round-robin based algorithm had been imposed at the end host where the path weight was estimated using piggybacked ECN signals [19]. A multipath transmission control protocol (MPTCP) [20; 21] has been using as a transport protocol to routes subflows toward multiple paths. This is because it cannot change paths, which is why the MPTCP routed paths congestion mismatch issue is very low [22; 23; 24]. However, it carries some limitations on the modification of the end host networking stacks, which really gives the challenge for the multiple customers. On top of that, there are bad incast scenarios. A DRILL-based load-balancing solution had appeared, which mainly maintained the per-packet load to overcome the microbursts under heavy load conditions [25]. Moreover, it has also a limitation for the asymmetric topologies that leads to the congestion mismatch issue. Another solution, namely flowbender [26], has appeared to reroute the flows blindly whenever the congestions are detected. This technique is used to apply the random and dynamic rerouting to carry the suboptimal performance under high load conditions. In reference [27], random packet spraying (RPS) is proposed. RPS is a random based load-balancing routing algorithm, which randomly assigns packets to one of the available shortest paths to the destination. CLOVE-ECN [28] adopts per-flowlet weighted round-robin attend hosts, where the path weights are calculated based on piggybacked ECN signals, due to their limited visibility and slow reaction to congestion. The authors in [29] presented DiffFlow with the help of SDN using random packet spraying (RPS) and a new load-balancing solution to detect the long flows and forward packets. In [30], the authors presented a mechanism named flow distribution aware load balancing in order to decrease the flow completion time and obtain higher scalability. Furthermore, the DFFR algorithm [31] was proposed to balance the flows in the data center networks. It is a scalable, distributed, and adaptive algorithm designed for maximizing network resources. A data center load-balancer named Beamer is developed to guarantee a stateless mux operation [32]. Moreover, in [33], the authors introduced a load-balancing protocol that was based on sampling named Luopan in order to overcome the shortcomings of the existing protocols.