TeamBoost: Enhanced cloud connectivity through collaborative MPTCP

Recent data centers provide dense inter-connectivity between each pair of servers through multiple paths. These data centers offer high aggregate bandwidth and robustness by using multiple paths simultaneously. Multipath TCP (MPTCP) protocol is developed for improving throughput, fairly sharing network link capacity and providing robustness during path failure by utilizing multiple paths over multi-homed data center networks. Running MPTCP protocol for latency-sensitive rack-local short flows with many-to-one communication pattern at the access layer of multi-homed data center networks creates MPTCP incast problem. In this paper, Balanced Multipath TCP (BMPTCP) protocol is proposed to mitigate MPTCP incast problem in multi-homed data center networks. BMPTCP is a window-based congestion control protocol that prevents constant growth of each worker’s subflow congestion window size. BMPTCP computes identical congestion window size for all concurrent subflows by considering bottleneck Top of Rack (ToR) switch buffer size and increasing count of concurrently transmitting workers. This helps BMPTCP to avoid timeout events due to full window loss at ToR switch. Based on current congestion situation at ToR switches, BMPTCP adjust transmission rates of each worker’s subflow so that total amount of data transmitted by all concurrent subflows does not overflow bottleneck ToR switch buffer. Simulation results show that BMPTCP effectively alleviates MPTCP incast. It improves goodput, reduces flow completion time as compared to existing MPTCP and EW-MPTCP protocols.

Multipath Transmission Control Protocol (MPTCP) enables multi-homed devices to establish multiple simultaneous routes for data transmission. Congestion Control (CC) is a fundamental mechanism for implementing and designing MPTCP. The Internet of Things (IoT) networks generate a massive volume of heterogeneous traffic with high dimensional states and diverse QoS characteristics. The existing MPTCP CC algorithms are unable to perform efficiently under highly mobile and dynamic IoT environments. We propose a novel model-free SDN-based adaptive actor-critic deep reinforcement learning framework based on a fuzzy normalized neural network to address the issue of CC for MPTCP in the IoT networks. In the proposed method, an agent can learn efficiently and better approximate the state-action value function of the actor and the action function of the critic to adjust the sub-flows congestion windows size adaptively according to the dynamic condition of a network. Simulation results show that the proposed scheme outperforms the state of the art schemes in terms of the goodput under highly-dynamic IoT environments.

The spread of Edge Internet of Things (IoT) radically changes our lifestyle. However, the multimedia services in edge IoT are still stuck by inefficiency. The dynamic typologies perplex the transmission of massive real-time data. To solve this problem, multipath transmission control protocol (MPTCP) which has a natural advantage in transmission robustness and bandwidth aggregation is becoming a good choice. In this paper, failure-aware and delay-predicted multipath virtual queue scheduling (FD-MVQS) is proposed to optimize the MPTCP performance in edge IoT. FD-MVQS constructs a two-plane cooperative scheduling system. In the control plane, the transmission failure estimation and chaos theory-based arrival delay prediction methods are introduced to provide the foundation for prescheduling. In the data plane, the multipath virtual queue scheduling is designed to allocate segments to different subflows. Simulation results showed that the proposed FD-MVQS performed better than standard and typical multipath transmission solutions in throughput, delay, and segment disorder.

The number of mobile terminals that have both a cellular interface and a Wi-Fi interface has been growing in the recent years. Meanwhile, Multipath TCP (MPTCP) that enables the simultaneous use of multiple paths with multiple TCP flows while showing just one regular TCP connection with the application has been standardized by the IETF and has drawn more attention recently. One feature of MPTCP is that it can be realized only by operating system layers supporting multipath communication without any modifications of the application. However, it might be difficult to install MPTCP in all server operating systems. In this paper, we propose a method for applying a proxy that forwards TCP communication from a server to MPTCP communication on a mobile core network, and show the results of evaluation with the existing equipment.

With the development of the Internet of Things (IoT) and 5G, there are ubiquitous smart devices and network functions providing emerging network services efficiently and optimally through building many network connections based on WiFi, LTE/5G, Ethernet, and etc. The Multipath TCP (MPTCP) protocol that enables these devices to establish multiple paths for simultaneous data transmission, has been a widely used extension of standard TCP in smart devices and network functions. On the other hand, more heavy and time-varying traffic loads are generated in an MPTCP network, so that an efficient congestion control mechanism that schedules the traffic between multiple subflows and avoids congestion is highly required. In this paper, we propose a decentralized learning approach, DeepCC, to adapt to the volatile environments and realize the efficient congestion control. The Multi-Agent Deep Reinforcement Learning (MADRL) is used to learn a policy of congestion control for each subflow according to the real-time network states. To deal with the problem of the fixed state space and slow convergence, we adopt two self-attention mechanisms to receive the states and train the policy, respectively. Due to the asynchronous design of DeepCC, the learning process will not introduce extra delay and overhead on the decision-making process. Experiment results show that DeepCC consistently outperforms the well-known heuristic method and DRL-based MPTCP congestion control method in terms of goodput and jitter. Besides, DeepCC with the attention mechanism reduces convergence time by about 50% and increase goodput by about 80% compared with the commonly used structures of neural networks.

Today, there is a generalized standard usage of internet for all.The devices via multiple technologies that facilitates to provide few communication methods to scholars to work with. By forming multiple paths in the data center network, latest generation data centers offer maximum bandwidth with robustness. To utilize this bandwidth, it is necessary that different data flows take separate paths. In brief, a single-path transport seems inappropriate for such networks. By using Multipath TCP, we must reconsider data center networks, with a diverse approach as to the association between topology, transport protocols, routing. Multipath TCP allows certain topologies that single path TCP cannot use. In newer generation data centers, Multipath TCP is already deployable using extensively deployed technologies such as Equal-cost multipath routing. But, major benefits will come when data centers are specifically designed for multipath transports. Due to manifold of technologies like Cloud computing, social networking, and information networks there is a need to deploy the number of large data centers. While Transport Control Protocol is the leading Layer-3 transport protocol in data center networks, the operating conditions like high bandwidth, small-buffered switches, and traffic patterns causes poor performance of TCP. Data Center TCP algorithm has newly been anticipated as a TCP option for data centers which address these limitations. It is worth noting that traditional TCP protocol.

The growing popularity of mobile devices and Internet of Things (IoT) has inspired the advent of the Cloudlet concept-a "small data center" close to users at the edge. It is believed that the Quality of Experience (QoE) of end users would greatly improve if they can access required resources within a one-hop distance from Cloudlet servers. Over the years, many researchers have proposed using virtual machines (VMs) as such service-provisioning servers. However, seeing the potentiality of containers-a lightweight virtualization tool, this paper adopts LXC containers as Cloudlet platforms. To facilitate container migration between Cloudlets, CRIU (Checkpoint/Restore in Userspace) has been chosen as the migration tool. Since the migration process goes through the Wide Area Network (WAN), which may experience congestion or network failures, this paper adopts the MPTCP (Multipath TCP) protocol to address the challenge. The multiple subflows established within a MPTCP connection can improve the resilience of the migration process and reduce migration time. We have conducted a number of experiments to validate the proposed approach. The experimental results show that LXC containers are suitable candidates for the problem and MPTCP protocol is effective in enhancing the migration process.

Future WLAN devices will combine both IEEE 802.11ad and 802.11ac interfaces. The former provides multi-Gbps rates but is susceptible to blockage, whereas the latter is slower but offers reliable connectivity. A fundamental challenge is thus how to combine those complementary technologies, to make the most of the advantages they offer. In this work, we leverage Multipath TCP (MPTCP) to use both interfaces simultaneously in order to achieve a higher overall throughput as well as seamlessly switch to a single interface when the other one fails. We find that standard MPTCP often performs sub-optimally and can yield a throughput much lower than that of single path TCP over the faster of the two interfaces. We analyze the cause of these performance issues in detail and then design <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MuSher</i> , an agile MPTCP scheduler that allows MPTCP to fully utilize the channel resources available to both interfaces. Our evaluation in realistic scenarios shows that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MuSher</i> can provide a throughput improvement of 50%/130% under WLAN/Internet settings respectively, compared to the default MPTCP scheduler. It further speeds up the recovery of a traffic stream after disruption by a factor of 8x/75x.

Future WLAN devices will combine both IEEE 802.11ad and 802.11ac interfaces. The former provides multi-Gbps rates but is susceptible to blockage, whereas the latter is slower but offers reliable connectivity. A fundamental challenge is thus how to combine those complementary technologies, to make the most of the advantages they offer. In this work, we explore leveraging Multipath TCP (MPTCP) to use both interfaces simultaneously in order to achieve a higher overall throughput as well as seamlessly switching to a single interface when the other one fails. We find that standard MPTCP often performs sub-optimally and may even yield a throughput much lower than that of single path TCP over the faster of the two interfaces. We analyze the cause of these performance issues in detail and then design MuSher, an agile MPTCP scheduler that allows MPTCP to fully utilize the channel resources available to both interfaces. Our evaluation in realistic scenarios shows that MuSher provides a throughput improvement of up to 1.5x/2.3x and speeds up the recovery of a traffic stream, after disruption, by a factor of up to 8x/75x, under WLAN/Internet settings respectively, compared to the default MPTCP scheduler.

The textbook Internet architecture revolves around the end-to-end principle with smart endpoints and a dumb network, while the actual Internet is far messier, with middleboxes pervasively deployed and affecting end-to-end traffic in many ways. Today's Internet is fragile as most of the communications are affected by transparent stateful middleboxes deployed along the path. In this paper we propose an evolution of the Internet architecture to make the middleboxes an explicit part of the Internet communications. We do so using the new Multipath TCP (MPTCP) protocol recently standardized at the Internet Engineering Task Force. MPTCP allows us to change the endpoints of the connection and by extension to explicitly add middleboxes in the middle of an ongoing communication. We show that the proposed solution accommodates nicely several widely used use cases including load balancing, DDoS filtering and anycast services. We implement selected use cases as a proof of concept.

It is common to find multiple network interfaces connected to different Internet Service Providers (ISPs) in devices such as smartphones. Multipath TCP (MPTCP) enables TCP connections to use all these network interfaces in a single TCP connection in an application transparent manner. MPTCP schedules traffic of one TCP connection over subflows created over these network interfaces. It is evident that this requires some scheduling policy. There have been some attempts to allow applications to decide on the scheduling policy. However, this violates the application transparency of MPTCP, and applications do not have all the information required to decide on such a policy. In addition, this allows the applications to monopolize the network connection thus posing a security threat as well. We argue that only the owner of the device (the user) has the right to make that policy decision and only the user can make an informed decision on the scheduling policy. For example, the user has the information on the monetary cost of the connections through different interfaces. In this paper we present a mechanism that allows the user to provide hints to the TCP scheduler to alter its scheduling policy. While this is not a mechanism to implement generic scheduling policies, it demonstrates how a user can guide the scheduling policies. As a proof of the concept, we demonstrate how MPTCP scheduler can be influenced to select a less stable and lossy path over a stable path based on a user preference.

This paper proposed a mobility-aware multimedia data transfer mechanism using Multipath TCP in Vehicular Network. Since high transmission rate and low latency are the two key factors for multimedia data transmission that could provide stable video streaming services, therefore, we first adopted Multipath Transport Control Protocol which can transfer data concurrently for improving transmission rate and designed Quality-aware Data Distribution to dynamically allocate the data to different subflows. Moreover, in Vehicular Network, the mobile terminal, which means the vehicle, can communicate with remote server through roadside unit (RSU). However, the communication link between terminals and remote server will disrupt while the vehicle exceeding the communication range of roadside unit; and there also exists the situation that the vehicle is in the communication range of several RSU. Accordingly, we exploited a mobility-aware distance measurement for checking whether the vehicle has moved out of the communication range of any RSU or it is in multi-RSU's communication range. Afterwards, we designed a handover mechanism which transfer data to connected path (4G) for stable transmission using MPTCP when the vehicle exceeded the communication range of RSU; while one mobile can communicate with more than one RSU, we exploited a mechanism which can trigger new path for multipath data transmission and non-corporation Nash Equilibria was employed for solving the problem of fairness in the same kind of network technology multipath transmission. Simulation results show how mobility-aware multimedia data transfer mechanism improve the performance of transmission comparison with state-of-art solution.

&lt;div style="text-align: start;" align="center"&gt;&lt;span lang="EN-US"&gt;The fast emerging of internet of things (IoTs) has introduced fog computing as an intermediate layer between end-users and the cloud datacenters. Fog computing layer characterized by its closeness to end users for service provisioning than the cloud. However, security challenges are still a big concern in fog and cloud computing paradigms as well. In fog computing, one of the most destructive attacks is man-in-the-middle (MitM). Moreover, MitM attacks are hard to be detected since they performed passively on the network level. This paper proposes a MitM mitigation scheme in fog computing architecture. The proposal mapped the fog layer on software-defined network (SDN) architecture. The proposal integrated multi-path transmission control protocol (MPTCP), moving target defense (MTD) technique, and reinforcement learning agent (RL) in one framework that contributed significantly to improving the fog layer resources utilization and security. The proposed schema hardens the network reconnaissance and discovery, thus improved the network security against MitM attack. The evaluation framework was tested using a simulation environment on mininet, with the utilization of MPTCP kernel and Ryu SDN controller. The experimental results shows that the proposed schema maintained the network resiliency, improves resource utilization without adding significant overheads compared to the traditional transmission control protocol (TCP).&lt;/span&gt;&lt;/div&gt;

In this paper, we present a comprehensive analysis and comparison of several multipath schedulers under 5G/B5G hybrid networks. Specifically, we have developed a physical testbed and integrated nine different schedulers including schedulers from both multipath TCP (MPTCP) and multipath QUIC (MPQUIC) transport layer protocols. Our results present the systematic comparison of the schedulers under different packet loss ratio, bandwidth, delay, etc. Finally, we also present results to quantify the impact of bandwidth outages and fluctuations on the performance of the multipath transport layer schedulers. Additionally, we also present a systematic literature review (SLR) on multipath transport layer schedulers using preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines to gather and analyse the information on the current state-of-the-art. One of the main contributions of the SLR is to broadly classify the research in the multipath transport domain into different categories and identify the key findings of the current published literature.

An implementation of Min–Max optimization for multipath SCTP through bandwidth estimation based resource pooling technique