PTP: Path-specified transport protocol for concurrent multipath transmission in named data networks

Cloud computing is an emerging area where all the network services are provided in the form of pay per use. Utilizing the available resources efficiently is one of the challenge in the data center network. Cloud resources are given as virtual machine to the end users. Sometimes, Virtual Machines (VMs) are overloaded or underloaded. The overloaded VMs degrade the performance of applications and underloaded VMs lead to inefficient resource utilization. To effectively utilize the available resources, we have proposed Dynamic Agent-Based’Load Balancing (DA-LB) on Software-Defined Networking (SDN) using Back Propagation Artificial Neural Network (BPANN). This load balancing algorithm uses the global visibility of SDN to efficiently migrate virtual machines in the data center network. The results show that our SDN load balancing approach improves the overall network efficiency and works well on data migration.The proposed algorithm helps to increase the processing speed and predict the loaded VM in heavy load conditions and optimizes the resource utilization. The migration process results are compared with Multi-Path TCP (MPTCP) and Heuristic algorithm (HA) and it is seen that our proposed algorithm takes less migration time compared to MPTCP and HA.

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.

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.

With the explosive growth of the Internet of Things (IoT), an increasing amount of sensor data generated by soft real-time IoT applications has been moved to data centers for storage and data analysis. Large amounts of these data are required to be processed within a given deadline to ensure application performance. Therefore, meeting the transmission deadlines of data flows for soft real-time applications has always been crucial yet challenging to current data centers. Recent progress has demonstrated that adopting parallel data transmission over multipath data center network combining with effective load balancing can achieve a high bisection network bandwidth, thus speeding up the network transfer of data flows. Nevertheless, the deadline miss ratios (DMRs) of these flows are not lowered as expected since the existing load balancing schemes are naturally agnostic to the deadline requirement. They are either unable to reroute traffic flexibly or aimlessly reroute these deadline-restrained flows, regardless of their urgent levels and path conditions. To address these inefficiencies, we propose a deadline-aware load-balancing scheme, namely, DLB, which perceives the deadline requirements and helps the urgent flows to timely switch to those faster transmission paths to complete quickly. Specifically, DLB computes the urgent level for each flow in real time to judge if the switch needs to make proactive rerouting. When a flow is nonurgent, DLB does not proactively change its transmission path, leaving more available paths to those flows with higher urgent levels. When a flow becomes extremely urgent, it immediately switches to those light-loaded paths to finish its data transmission before its deadline as far as possible. Experimental results of NS2 simulations and real testbed implementations show that DLB reduces the DMRs by up to 50% compared to the state-of-the-art data center load-balancing schemes, while only induces trivial overhead during deployment.

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.

With the growing demand of Internet services, network operators have put significant efforts to improve network error resilience and efficiency. Since there exist different wired/wireless technologies for Internet access such as digital subscriber line (DSL), Ethernet, and worldwide interoperability for microwave access (WiMax), a mobile host can use multiple access networks simultaneously with multipath transmission. Taking the advantage of heterogeneous environment, multipath transmission through the Internet can improve service reliability and network flexibility. Ensuring a reliable end-to-end connection oriented communication with satisfactory quality of service (QoS) and maintaining congestion control and flow control are the main responsibilities of the Transmission Control Protocol (TCP), the dominant transport layer protocol in the Internet. In this paper, we survey the state-of-the-art of multipath transmission techniques for QoS provisioning in wireless Internet access, focusing on the end-to-end transport layer protocols. The main challenges for the design of multipath TCP are reviewed, and the existing transport layer congestion control schemes are categorized. Multipath TCP and stream control transmission protocol (SCTP)-based transport layer protocols are discussed, and their limitations and/or impractical assumptions are addressed. Open research issues on the development of an effective, efficient, and practical multipath TCP protocol are summarized.

Named Data Networking (NDN) is a recently designed Internet architecture that benefits data names instead of locations and creates essential changes in the abstraction of network services from "delivering packets to specific destinations” to "retrieving data with special names" makes. This fundamental change creates new opportunities and intellectual challenges in all areas, especially network routing and communication, communication security, and privacy. The focus of this dissertation is on the forwarding aircraft feature introduced by NDN. Communication in NDN is done by exchanging interest and data packets. Consumers send interest packets to request data, routers send them based on the data prefix name, and manufacturers respond with data packets exactly how interest is received. During this process, routers maintain information about the status of suspended interests. As regards NDN is still in its early stage, none of these strong efficiency features have done systematically designed, measured, or tracked in data retrieval and multi-path detection. This paper tries to improve transport performance by combining label switching with adaptive transport methods. For this purpose, in addition to RTT, another timer called T is used, an RTT factor for interface rating. And uses the BDP to choose the best interface to respond to interest. During this process, response time, throughput, and data recovery time are improved by 12%, 10%, and 5%, respectively.

Reducing traffic burstiness for MPTCP in data center networks

In-network caching and multipath forwarding are prominent features of Named Data Networking (NDN). Network coding enabled NDN (NC-NDN) coordinates the in-network caching and multipath forwarding to improve content delivery performance. However, the existing NC-NDN lacks the considerations on the incorporation with caching schemes. It basically adopts the caching scheme of Caching Everything Everywhere (CEE) leading to cache redundancy and unnecessary and frequent cache replacement. On the other hand, the existing caching schemes for native NDN do not make use of the characteristic of network coded Data packets. To address these problems, this paper proposes a demand and responsiveness-based caching strategy specific to NC-NDN to enable cost-effective caching for network coded Data packets. In our proposed caching strategy, the caching decision at a caching node takes into account three factors, its present demand on the network coded Data packets of the requested generation of content, its distance to the original content provider, and its potential responsiveness to the future requests for the same generation based on the number of network coded Data packets locally cached and that would return for the requested generation. It commits to cache network coded Data packets of a generation of content at more valuable nodes along the transmission path. Our experimental studies show that the proposed caching strategy offers high-performance content delivery and reduces the caching overhead as compared to the existing strategies.

Cloud computing data services have extremely high requirements for transmission performance in high-concurrency and heterogeneous network environments, while traditional single-path transmission mechanisms are difficult to fully utilize the multi-link resources in the cloud-edge collaborative architecture. This paper proposes a deep reinforcement learning (DRL) strategy for cloud-edge multi-path transmission in cloud computing data services. By constructing a state-action-reward model, it realizes dynamic perception and decision optimization of link bandwidth, latency, packet loss rate, and congestion level. The method includes: (1) establishing a cloud-edge collaborative multi-link environment model and performing real-time sampling and normalization of link feature parameters; (2) designing an agent based on a double deep Q-network (DDQN) to learn the policy of transmission path and data allocation ratio; (3) improving learning efficiency through a prioritized experience replay mechanism; and (4) combining an adaptive reward function to achieve a balance between throughput and latency in the system. Experiments were conducted in simulated and real-world deployment environments. Compared with the traditional Multipath Transmission Control Protocol (MPTCP) and the optimization scheme without reinforcement learning, the proposed method improves the average throughput by about 28.3% and reduces the end-to-end latency by about 15.4% compared with MPTCP, while achieving a link utilization of 92%, demonstrating superior dynamic decision-making and self-optimization capabilities.

BIM2RT: BWAS-immune mechanism based multipath reliable transmission with fault tolerance in wireless sensor networks

Multipath Transmission Control Protocol (MPTCP) is a new transmission protocol designed by The Internet Engineering Task Force (IETF) for multipath transmission. In order to realize the large-scale and rapid deployment of MPTCP, the design of MPTCP needs to ensure fairness with traditional Transmission Control Protocol (TCP). The IETF organization designed a congestion control algorithm for the network fairness of MPTCP, but did not consider the bottleneck fairness of MPTCP. In this paper, we propose a congestion control algorithm based on Dynamic Time Warping (DTW) and Bottleneck Bandwidth and Round-trip time (BBR), which takes the bottleneck fairness in consideration for higher transmission efficiency. The experiments validate that the proposed algorithm can improve the recognition rate of shared bottlenecks, increase bandwidth utilization, and ensure fairness at the bottleneck.

Space-ground integrated networks (SGINs) have been recently regarded as a promising way to provide resilient, dependable as well as efficient data transmission in the high-speed railway (HSR) scenario. Applying multipath transmission control protocol (MPTCP) to SGIN can realize data transmission simultaneously via terrestrial and satellite networks. However, since the existing congestion control (CC) mechanisms of MPTCP fail to distinguish between adverse influences (such as packet loss and/or round-trip time increase) caused by congestion and those caused by handovers, it suffers severe performance degradation in the HSR scenario where handover frequently occurs. In this article, we first present the SGIN oriented HSR (SGIN-HSR) with MPTCP. Then leveraging cross-layer information (i.e., reference signal received power), we design a novel cross-layer aided MPTCP CC mechanism targeted at SGIN-HSR based on deep reinforcement learning, which is referred to as HSR-CC, to alleviate performance degradation problems induced by handover. The experimental results show that HSR-CC significantly enhances the goodput and outperforms state-of-the-art MPTCP CC algorithms in SGIN-HSR environments where handover frequently occurs.

An energy-efficient virtual machine placement and route scheduling scheme in data center networks

We highlight the advantages of dynamic wavelength allocation and path rerouting in hybrid optical flow-switched data center networks compared with static electronic packet-switched data center networks. Current electronic packet-switched networks perform routing based on lookup tables and shortest path routing over high speed optical connections. However, load balancing and path rerouting are not designed in coordination with the optical data plane. In this work, we design and analyze the performance of load balancing and resource allocation in hybrid flow data center architectures. In the hybrid flow architecture, the transport layer and control plane are responsible for load balancing, congestion control and reliable data delivery in wavelength division multiplexed networks. The transport layer abstracts the underlying network and data link layers from user applications. Applications are unaware of whether flows are transmitted via the electronic data plane, optical data plane, or both, where the relevant metric for applications is transaction delay. We show that the data center architecture that minimizes delay in the presence of elephant flows and dynamic loads is the hybrid flow architecture with dynamic resource allocation.