TCP Incast Problem Research Articles

Poche: A Priority-Based Flow-Aware In-Network Caching Scheme in Data Center Networks

Datacenters currently deploy shallow-buffered switches to achieve low latency by avoiding long waiting time in the data plane. However, the limited buffer space in the switch causes the frequent overflow and the notorious TCP incast problem. Moreover, the simple scheduling strategy in buffer deprives the switch of the ability to offer deeply differentiated services. Therefore, we present a novel priority-based flow-aware in-network caching scheme, named Poche, which supplies more control capabilities for the network side through introducing some additional cache resource into switches. Poche classifies network traffic into multiple priorities according to the latency requirements of flows. The end server adds priority tags to packets and sets different RTO values for flows with distinct priorities. The switch monitors the buffer utilization of each port and performs the priority-based flow-aware caching and injecting strategies based on the analysis of the scheduling model between the buffer and cache. We conduct comprehensive experiments to compare Poche with the state-of-the-art traffic optimization schemes. The results demonstrate that Poche can reduce the FCTs of latency-sensitive flows by at least 59.1% and improve the network throughput by at least 54.4%, while ensuring the finite cached volume and effectively addressing the incast problem.

An application layer technique to overcome TCP incast in data center network using delayed server response

Applications running in data center networks exhibits barrier-synchronized many-to-one communication pattern. Under this pattern, multiple workers synchronously transmit data to single aggregator. Synchronized transmission from multiple workers overload small-sized buffer of switch connected to aggregator. This causes severe packet drops and leads to overall application goodput degradation. This is named as TCP Incast problem in data center network. In this paper, an application layer technique called Delayed Server Response at Application Layer (DSRAL) is proposed to mitigate TCP Incast problem. It is delay-based sequential data transmission technique. In DSRAL, aggregator first determines amount of time required by each worker to finish its data transmission. This can be done by knowing Server Request Unit (SRU) size, average Round Trip Time (RTT) and packet scheduling time. Then along with request packet, aggregator communicates distinct SRU transmission time with each worker and enforces them to transmit SRUs sequentially. Through simulation it is proved that DSRAL avoids TCP Incast problem and provides improved performance than existing application layer serialized method. It supports large number of workers and simultaneously achieves high application goodput without causing any packet loss.

FAMD: A Flow-Aware Marking and Delay-based TCP algorithm for datacenter networks

Datacenter networks have brought new challenges to meet datacenters’ unique performance requirements. Moreover, the many-to-one traffic pattern, which is quite common in datacenter networks, causes heavy network congestion and leads to TCP incast problem. To solve this problem, many TCP congestion control protocols have been proposed to mitigate the TCP incast. However, these protocols have more or less problems, including high computational complexity and implementation complexity. In this paper, we propose a flow-aware marking and delay-based TCP algorithm for datacenters, referred to as FAMD. FAMD is built on the delay-based protocols and leverages a DCTCP-like marking scheme to indicate the network congestion level and regulate the congestion window. Based on above mechanism, FAMD can maintain a low and stable transmission end-to-end delay. Furthermore, because of the disadvantage of fixed marking threshold, this paper shows how to choose an appropriate threshold dynamically and presents a flow-aware threshold adjustment algorithm, referred to FATA. Therefore, our FAMD can achieve a good generality for different scenarios. Our extensive evaluation shows that FAMD can gain a good throughput and low end-to-end delay.

A solution to MPTCP’s inefficiencies under the incast problem for Data Center Networks

In recent years several multipath data transport mechanisms, such as MPTCP and XMP, have been introduced to effectively exploit the path diversity of data center networks (DCNs). However, these multipath schemes have not been widely deployed in DCNs. We argue that two key factors among others impeded their adoption: TCP incast and minimum window syndrome . First, these mechanisms are ill-suited for workloads with a many-to-one communication pattern, commonly found in DCNs, causing frequent TCP incast collapses. Second, the syndrome we discover for the first time, results in 2-5 times lower throughput for single-path flows than multipath flows, thus severely violating network fairness.To effectively tackle these problems, we propose AMP: an adaptive multipath congestion control mechanism that quickly detects the onset of these problems and transforms its multipath flow into a single-path flow. Once these problems disappear, AMP safely reverses this transformation and continues its data transmission via multiple paths. Our evaluation results under a diverse set of scenarios in a fat-tree topology with realistic workloads demonstrate that AMP is robust to the TCP incast problem and improves network fairness between multipath and single-path flows significantly with little performance loss.

Optimizing data center network throughput by solving TCP Incast problem using k‐means algorithm

SummaryTCP in casting referred to as one of the complex problems in the data center, which receives a huge amount of traffic volume from n number of senders. There are many methods proposed to solve the TCP Incast problem. In this paper, there are two steps proposed: (i) grouping sender nodes using the k‐means algorithm and (ii) handling incoming packets from the senders after grouping. Grouping senders make it easy to handle the incoming packets effectively as the complexity reduces reasonably. This is achieved through the k‐means algorithm that groups the senders and makes a priority queue for each group. The second step can be achieved through Pro‐Ack (Pro‐Acknowledgement) control in one of the methods for handling a huge volume of data at the receiver side. We demonstrated how the incoming packets can be processed and handled effectively through Pro‐Ack control with the help of the k‐means algorithm. Along with the above concepts, the robust algorithm is proposed to make priority queues. The input throughput also out performs with the existing algorithms.

Flow-Aware Adaptive Pacing to Mitigate TCP Incast in Data Center Networks

In data center networks, many network-intensive applications leverage large fan-in and many-to-one communication to achieve high performance. However, the special traffic patterns, such as micro-burst and high concurrency, easily cause TCP Incast problem and seriously degrade the application performance. To address the TCP Incast problem, we first reveal theoretically and empirically that alleviating packet burstiness is much more effective in reducing the Incast probability than controlling the congestion window. Inspired by the findings and insights from our experimental observations, we further propose a general supporting scheme Adaptive Pacing (AP), which dynamically adjusts burstiness according to the flow concurrency without any change on switch. Additionally, a sender-based approach is proposed to estimate the flow concurrency. Another feature of AP is its broad applicability. We integrate AP transparently into different TCP protocols (i.e., DCTCP, L2DCT and D2TCP). Through a series of large-scale NS2 simulations and testbed experiments, we show that AP significantly reduces the Incast probability across different TCP protocols and the network goodput can be increased consistently by on average $7\times $ under severe congestion.

TCP Incast in Data Center Networks: Issue and Existing Solutions

Data centers networks supports heterogeneous kind of applications like social networking, e-commerce, web search, video data hosting, computation-intensive and data-storage. It has high-bandwidth links, low propagation delay and commodity switches with small-size buffers. Under cluster-based storage environment, data center supports barrier-synchronized many-to-one communication pattern where multiple worker nodes simultaneously transmit bulk of data to single aggregator node by running standard TCP protocol. This synchronized transmission may overload aggregator’s switch buffer, which leads to severe packet loss and overall throughput fall. This is called as TCP Incast problem. This paper analyses issue of TCP Incast and provides detailed survey about several solutions at link, transport and application layer to mitigate impact of TCP Incast in data center network. Solutions are described with their procedural approach for alleviating Incast. Comparative evaluation between these solutions provides understanding about their merits, demerits and applicability under various implementation circumstances.

Empirical Investigation of TCP Incast Congestion in Wireless Cloud Computing Networks

The promising services offered by cloud computing environments have led to huge amount of data that need to be processed and stored. Wireless cloud networks rely on Transmission Control Protocol/Internet Protocol (TCP/IP) for reliable transfer of data traffic between the cloud end-users and servers and vise-versa. Even though TCP has been successful for several applications, it, however, does not perform well in wireless cloud environments. The many-to-one communication pattern used in such environments with such huge amount of data resulted in TCP incast problem. Transmission Control Protocol incast problem happens in cluster based storage workloads where a lot of end-users communicate simultaneously to a server in the cloud through a bottleneck router, creating buffers overflows which lead to high packet loss. This paper presents an empirical study on TCP incast in current wireless cloud networks and how it is caused. It evaluates TCP-Vegas and TCP-Sack to examine their behaviors and suitability for short-lived connections in terms of queue occupancy level, packet drops, throughput, link utilization and bandwidth unfairness between the TCP connections. It was found that both protocols suffer from high packet loss and link underutilization with comparable throughput.

SDTCP: Towards Datacenter TCP Congestion Control with SDN for IoT Applications.

The Internet of Things (IoT) has gained popularity in recent years. Today’s IoT applications are now increasingly deployed in cloud platforms to perform Big Data analytics. In cloud data center networks (DCN), TCP incast usually happens when multiple senders simultaneously communicate with a single receiver. However, when TCP incast happens, DCN may suffer from both throughput collapse for TCP burst flows and temporary starvation for TCP background flows. In this paper, we propose a software defined network (SDN)-based TCP congestion control mechanism, referred to as SDTCP, to leverage the features, e.g., centralized control methods and the global view of the network, in order to solve the TCP incast problems. When we detect network congestion on an OpenFlow switch, our controller can select the background flows and reduce their bandwidth by adjusting the advertised window of TCP ACK packets of the corresponding background flows so as to reserve more bandwidth for burst flows. SDTCP is transparent to the end systems and can accurately decelerate the rate of background flows by leveraging the global view of the network gained via SDN. The experiments demonstrate that our SDTCP can provide high tolerance for burst flows and achieve better flow completion time for short flows. Therefore, SDTCP is an effective and scalable solution for the TCP incast problem.

An early congestion feedback and rate adjustment schemes for many-to-one communication in cloud-based data center networks

Cloud data centers are playing an important role for providing many online services such as web search, cloud computing and back-end computations such as MapReduce and BigTable. In data center network, there are three basic requirements for the data center transport protocol such as high throughput, low latency and high burst tolerance. Unfortunately, conventional TCP protocols are unable to meet the requirements of data center transport protocol. One of the main practical issues of great importance is TCP Incast to occur many-to-one communication sessions in data centers, in which TCP experiences sharp degradation of throughput and higher delay. This important issue in data center networks has already attracted the researchers because of the development of cloud computing. Recently, few solutions have been proposed for improving the performance of TCP in data center networks. Among that, DCTCP is the most popular protocol in academic as well as industry areas due to its better performance in terms of throughput and latency. Although DCTCP provides significant performance improvements, there are still some defects in maintaining the queue length and throughput when the number of servers is too large. To address this problem, we propose a simple and efficient TCP protocol, namely NewDCTCP as an improvement of DCTCP in data center networks. NewDCTCP modified the congestion feedback and window adjusting schemes of DCTCP to mitigate the TCP Incast problem. Through detailed QualNet experiments, we show that NewDCTCP significantly outperforms DCTCP and TCP in terms of goodput and latency. The experimental results also demonstrate that NewDCTCP flows provide better link efficiency and fairness with respect to DCTCP.

Modeling and Solving TCP Incast Problem in Data Center Networks

TCP Incast problem attracts much attention due to the catastrophic goodput drop. In this paper, a goodput model of the problem is built to understand why goodput collapse occurs and a solution to the problem based on the theoretical analysis is proposed. We found that the TCP Incast goodput deterioration is mainly caused by two types of timeouts, one happens at the tail of data blocks and dominates the goodput when the number of senders is small, while the other one at the head of data blocks and governs the goodput when the number of senders is large. The proposed model describes the relationship between these two types of timeouts and the Incast communication pattern, block size, bottleneck buffer size, and so on. The simulation results indicate that the model well characterizes the features of the TCP Incast problem. Enlightened by the analysis, a PRiority-based solution to the TCP INcast problem (PRIN) is proposed, which avoids timeouts at the head of blocks by reducing TCP send window and prevents timeouts at the tail of blocks by leveraging priority technology. The experimental results show that PRIN solves the TCP Incast problem.

IDTCP: An effective approach to mitigating the TCP incast problem in data center networks

Recently, TCP incast problem in data center networks has attracted a wide range of industrial and academic attention. Lots of attempts have been made to address this problem through experiments and simulations. This paper analyzes the TCP incast problem in data centers by focusing on the relationships between the TCP throughput and the congestion control window size of TCP. The root cause of the TCP incast problem is explored and the essence of the current methods to mitigate the TCP incast is well explained. The rationality of our analysis is verified by simulations. The analysis as well as the simulation results provides significant implications to the TCP incast problem. Based on these implications, an effective approach named IDTCP (Incast Decrease TCP) is proposed to mitigate the TCP incast problem. Analysis and simulation results verify that our approach effectively mitigates the TCP incast problem and noticeably improves the TCP throughput.

On Architecture Design, Congestion Notification, TCP Incast and Power Consumption in Data Centers

With rapid deployment of modern data center networks (DCNs), many problems with respect to DCN architecture, congestion notification, TCP Incast, and power consumption have been observed. In this paper, we provide a comprehensive survey of the most recent research activities in DCNs, with emphasis on the network architecture design, congestion notification algorithms, TCP Incast, and power consumption. We describe in detail the architecture of a typical modern DCN. Furthermore, we investigate the challenges of the typical tree-based hierarchical DCN architecture encountered today and the requirements for the optimal DCN architecture, and we classify the proposed DCN architectures into switch-centric topology and server-centric topology. A section is also devoted to describe some newly proposed DCN architectures. We present a brief overview of the TCP Incast problem along with previously proposed solutions. We also review the recent energy-efficient solutions to minimize the power consumption in DCNs. Finally, we outline possible future research topics in DCNs.

Safe and effective fine-grained TCP retransmissions for datacenter communication

This paper presents a practical solution to a problem facing high-fan-in, high-bandwidth synchronized TCP workloads in datacenter Ethernets---the TCP incast problem. In these networks, receivers can experience a drastic reduction in application throughput when simultaneously requesting data from many servers using TCP. Inbound data overfills small switch buffers, leading to TCP timeouts lasting hundreds of milliseconds. For many datacenter workloads that have a barrier synchronization requirement (e.g., filesystem reads and parallel data-intensive queries), throughput is reduced by up to 90%. For latency-sensitive applications, TCP timeouts in the datacenter impose delays of hundreds of milliseconds in networks with round-trip-times in microseconds. Our practical solution uses high-resolution timers to enable microsecond-granularity TCP timeouts. We demonstrate that this technique is effective in avoiding TCP incast collapse in simulation and in real-world experiments. We show that eliminating the minimum retransmission timeout bound is safe for all environments, including the wide-area.