Fair Share Of Bandwidth Research Articles

TCCC: A Throughput Consistency Congestion Control Algorithm for MPTCP in Mixed Transmission of Long and Short Flows

Existing congestion control algorithms for MPTCP that care about only long flow transmission aim at the Congestion-Avoidance (CA) phase and they need a long time to reach convergence states. We verified that the exponential growth of congestion window (cwnd) in the uncoupled Slow-Start (SS) leads to not only unfairness to TCP but also buffer overflow due to burst data. Moreover, these algorithms cannot support fair bandwidth sharing among TCP/MPTCP flows before reaching convergence at the bottleneck, which may reduce the transmission efficiency of short flows and even hurts long flows. In this paper, we propose a Throughput Consistency Congestion Control (TCCC) algorithm consisting of Coupled Slow-Start (CSS) and Aggressive Congestion Avoidance (ACA). To prevent packet loss caused by excessive burst data, CSS couples the increment of subflows’ cwnd and reset the ssthresh value to safely move the flows to CA when it achieves expected throughput. Based on CSS, ACA periodically detects path states and allocates the same throughput increment as the best TCP to subflows to achieve fair bandwidth share in CA. Finally, we implement TCCC in both NS3 and real testbed. The results show that TCCC reduces retransmissions, improves transmission efficiency, and maintains better fairness.

Mobile Ad-Hoc Wireless Networks In Medium Access Control Protocol

Nodes in an ad hoc wireless network share a common broadcast radio channel. The radio spectrum is limited, the bandwidth available for communication in such networks is also limited. Access to this shared medium should be controlled in such manner that all nodes receive a fair share of the available bandwidth, and that the bandwidth is utilized efficiently. Since the characteristics of the wireless medium are completely different from those of the wired medium ,and since ad hoc wireless networks need to address unique issues such as node mobility, limited bandwidth availability ,error-prone broadcast channel hidden and exposed terminals problems and power constraints that are not applicable to wired networks ,a different set of protocols is required for controlling access to the shared medium in such networks, This paper focuses on media access protocols for ad hoc wireless networks

Heavy-Traffic Insensitive Bounds for Weighted Proportionally Fair Bandwidth Sharing Policies

We consider a connection-level model proposed by Massoulié and Roberts for bandwidth sharing among file transfer flows in a communication network. We study weighted proportionally fair sharing policies and establish explicit-form bounds on the weighted sum of the expected numbers of flows on different routes in heavy traffic. The bounds are linear in the number of critically loaded links in the network, and they hold for a class of phase-type file-size distributions; that is, the bounds are heavy-traffic insensitive to the distributions in this class. Our approach is Lyapunov drift based, which is different from the widely used diffusion approximation approach. A key technique we develop is to construct a novel inner product in the state space, which then allows us to obtain a multiplicative type of state-space collapse in steady state. Furthermore, this state-space collapse result implies the interchange of limits as a byproduct for the diffusion approximation of the unweighted proportionally fair sharing policy under phase-type file-size distributions, demonstrating the heavy-traffic insensitivity of the stationary distribution.

Stability of a Subcritical Fluid Model for Fair Bandwidth Sharing with General File Size Distributions

This work concerns the asymptotic behavior of solutions to a (strictly) subcritical fluid model for a data communication network, where file sizes are generally distributed and the network operates under a fair bandwidth-sharing policy. Here we consider fair bandwidth-sharing policies that are a slight generalization of the [Formula: see text]-fair policies introduced by Mo and Walrand [Mo J, Walrand J (2000) Fair end-to-end window-based congestion control. IEEE/ACM Trans. Networks 8(5):556–567.]. Since the year 2000, it has been a standing problem to prove stability of the data communications network model of Massoulié and Roberts [Massoulié L, Roberts J (2000) Bandwidth sharing and admission control for elastic traffic. Telecommunication Systems 15(1):185–201.], with general file sizes and operating under fair bandwidth sharing policies, when the offered load is less than capacity (subcritical conditions). A crucial step in an approach to this problem is to prove stability of subcritical fluid model solutions. In 2012, Paganini et al. [Paganini F, Tang A, Ferragut A, Andrew LLH (2012) Network stability under alpha fair bandwidth allocation with general file size distribution. IEEE Trans. Automatic Control 57(3):579–591.] introduced a Lyapunov function for this purpose and gave an argument, assuming that fluid model solutions are sufficiently smooth in time and space that they are strong solutions of a partial differential equation and assuming that no fluid level on any route touches zero before all route levels reach zero. The aim of the current paper is to prove stability of the subcritical fluid model without these strong assumptions. Starting with a slight generalization of the Lyapunov function proposed by Paganini et al., assuming that each component of the initial state of a measure-valued fluid model solution, as well as the file size distributions, have no atoms and have finite first moments, we prove absolute continuity in time of the composition of the Lyapunov function with any subcritical fluid model solution and describe the associated density. We use this to prove that the Lyapunov function composed with such a subcritical fluid model solution converges to zero as time goes to infinity. This implies that each component of the measure-valued fluid model solution converges vaguely on [Formula: see text] to the zero measure as time goes to infinity. Under the further assumption that the file size distributions have finite pth moments for some p > 1 and that each component of the initial state of the fluid model solution has finite pth moment, it is proved that the fluid model solution reaches the measure with all components equal to the zero measure in finite time and that the time to reach this zero state has a uniform bound for all fluid model solutions having a uniform bound on the initial total mass and the pth moment of each component of the initial state. In contrast to the analysis of Paganini et al., we do not need their strong smoothness assumptions on fluid model solutions and we rigorously treat the realistic, but singular situation, where the fluid level on some routes becomes zero, whereas other route levels remain positive.

PPNet

Software-defined networking introduces opportunities to optimize the Internet Service Provider’s network and to improve client experience for the Video-on-Demand applications. Recent studies on SDN frameworks show that traffic engineering methods allow a fair share of bandwidth between adaptive video streaming clients. Additionally, ISPs can make better estimations of bandwidth and contribute to the bitrate selection for the clients. This study focuses on another aspect of network assistance in video delivery: CDN server selection. In a typical framework where the ISP contributes to the CDN selection, the video provider and the network provider interfaces are merged together. Clients connect to the ISP to get the best CDN server candidate for a given video. This exposes client requests to the ISP. However, video providers have been investing large resources for encrypted video provisioning to preserve their client’s information from third parties, especially network providers. The typical approach is not practical due to privacy concerns. In this study, we present a framework called PPNet to allow CDN-ISP collaboration while preventing the ISP’s access to the video request and availability information. Our framework introduces an isolation between the video provider’s and the ISP’s web interfaces. Clients connect to both of the interfaces and deliver information on a need-to-know basis. As a second contribution, PPNet introduces a practical optimization method for CDN selection. Real-time data collection capabilities of a typical OpenFlow network is used as the input for optimization. Congestion-awareness has been the priority. To adapt for changing network conditions, capability of utilizing multiple servers simultaneously for a single video is introduced. Instead of directing each video client into a CDN node, the proposed system performs request routing per video segment. Finally, we present a system prototype of PPNet and show that our multiple-host adaptive streaming method introduces a significant improvement in quality of experience when compared to the state of the art.

ARCH: A dual‐mode fairness‐driven AQM for promoting cooperative behaviour in best effort Internet

The cooperative behaviour of end-systems in efficiently and fairly utilizing the scarce bandwidth is of paramount significance in the best effort Internet. Not only does the uncooperative behaviour result in unfairness, but it may also induce congestion collapse. How to urge end-systems to share the bandwidth cooperatively is a problem that depends, in essence, on incentives. This study presents a novel fairness-driven active queue management (AQM)-based incentive scheme to detect and take punitive action against any uncooperative behaviour. Different from all other fairness-driven AQM schemes, the proposed scheme offers a dual-mode control function that can adaptively switch between stateless and partial-state modes in order to be scalable. The control function remains stateless at low to moderate congestion levels and maintains a partial-state when congestion becomes severe. In the stateless mode, the identification and restriction of unresponsive flows are based on a matched-drop mechanism having a dynamic drawing factor to differentially drop packets from unresponsive flows. In the partial-state mode, a fair-share is estimated and flows whose arrival rates exceed the fair-share bandwidth get their rates limited to the fair rate. Simulation results demonstrate the reasonable performance improvement of the proposed scheme over well-known fairness-driven AQM schemes.

SD‐MAC: Design and evaluation of a software‐defined passive optical intrarack network in data centers

AbstractWith rapid development of cloud computing services, traffic in data centers (DCs) increases dramatically. Top‐of‐rack Ethernet switches dominate network cost and energy consumptions in DCs. Optical switching technologies have been introduced into DC networks to increase switching capacity and to reduce energy consumption. However, how to design high‐performance optical intrarack networks is still a great challenge. This paper presents a software‐defined passive optical intrarack network (SD‐POIRN) based on optical coupler fabrics. The data plane of SD‐POIRN is a broadcast‐and‐select optical network combining wavelength division multiplexing and time division multiplexing technologies. The control plane of SD‐POIRN has a centralized rack controller for scheduling intrarack data transmissions. This paper proposes a software‐defined media access control (SD‐MAC) protocol for SD‐POIRN. The SD‐MAC utilizes dynamic transmission and receiving server grouping methods and max‐min fair share bandwidth allocation algorithms to dynamically allocate bandwidth among servers in an efficient and fair manner. Network performance evaluation results show that, when the offered load is high, the proposed SD‐MAC protocol effectively increases network throughput and reduces average packet delay compared with previous works.

Incast Mitigation in a Data Center Storage Cluster Through a Dynamic Fair-Share Buffer Policy

Incast is a phenomenon when multiple devices interact with only one device at a given time. Multiple storage senders overflow either the switch buffer or the single-receiver memory. This pattern causes all concurrent-senders to stop and wait for buffer/memory availability, and leads to a packet loss and retransmission-resulting in a huge latency. We present a software-defined technique tackling the many-to-one communication pattern-Incast-in a data center storage cluster. Our proposed method decouples the default TCP windowing mechanism from all storage servers, and delegates it to the software-defined storage controller. The proposed method removes the TCP saw-tooth behavior, provides a global flow awareness, and implements the dynamic fair-share buffer policy for end-to-end I/O path. It considers all I/O stages (applications, device drivers, NICs, switches/routers, file systems, I/O schedulers, main memory, and physical disks) while achieving the maximum I/O throughput. The policy, which is part of the proposed method, allocates fair-share bandwidth utilization for all storage servers. Priority queues are incorporated to handle the most important data flows. In addition, the proposed method provides better manageability and maintainability compared with traditional storage networks, where data plane and control plane reside in the same device.

ARFC: Advance response function of TCP CUBIC for IoT‐based applications using big data

SummaryThe throughput of a TCP flow depends on the average size of Congestion Window (cwnd) of a congestion control mechanism being used during the communication. The size of cwnd depends upon the usage of available link bandwidth during communication. The response function is a measure of average throughput of a single TCP flow of congestion control mechanism as the level of random packet loss is varied. Nowadays, many organizations are deploying IoT based applications for the analytics of their Big Data. TCP CUBIC and TCP Compound are the default congestion control mechanisms in Linux and Microsoft Windows Operating Systems respectively. Whereas, TCP Reno which is also known as Standard TCP congestion control mechanism is act as a trademark congestion control mechanism. During communication among different IoT applications, TCP CUBIC flows use more available link bandwidth as compared to TCP Reno flows, thus, the average cwnd size of TCP CUBIC flows are greater than the TCP Reno flows. It implies that these both kinds of flows are not sharing available link fairly, which refers as low TCP friendliness of TCP CUBIC. It means that the throughput of TCP CUBIC flows is higher than the trademark congestion control mechanism, i.e., TCP Reno flows. As a result, friendliness behavior or fair share of available link bandwidth among TCP CUBIC flows and TCP Reno flows is decreased. In other words, TCP friendliness of TCP CUBIC flows is reduced. Now, it is important to decrease the average cwnd size of TCP CUBIC flows, such that available link bandwidth can be shared fairly among flows of TCP CUBIC and TCP Reno. The aim of this research is to enhance the TCP friendliness behavior of TCP CUBIC congestion control mechanism for IoT based applications using Big Data. In this paper, an Advance Response Function of TCP CUBIC (ARFC) is designed to share fairly available link bandwidth among flows of TCP CUBIC and TCP Reno. Results show that TCP friendliness behavior of TCP CUBIC is increased by using ARFC. Overall, 18.6% performance is increased by using ARFC.

Heavy-Traffic Delay Insensitivity in Connection-Level Models of Data Transfer with Proportionally Fair Bandwidth Sharing

Motivated by the stringent requirements on delay performance in data center networks, we study a connection-level model for bandwidth sharing among data transfer flows, where file sizes have phase-type distributions and proportionally fair bandwidth allocation is used. We analyze the expected number of files in steady-state by setting the steady-state drift of an appropriately chosen Lyapunov function equal to zero. We consider the heavy-traffic regime and obtain asymptotically tight bounds on the expected number of files in the system. Our results show that the expected number of files under proportionally fair bandwidth allocation is insensitive in heavy traffic to file size distributions, thus complementing the diffusion approximation result of Vlasiou et al. [20].

On Improving Video Streaming Efficiency, Fairness, Stability, and Convergence Time Through Client–Server Cooperation

Many studies have shown that the dynamic adaptive streaming over HTTP scheme is limited in achieving efficiency, fairness, and stability. Solutions proposed in the recent literature target these objectives, but tackle them from either client or server side separately. This paper argues the use of a client–server cooperation-based approach to achieve the three objectives. Effectively, information available at the client side, such as buffer occupancy, available throughput, and previous played representation levels, can be used to better control the video streaming efficiency and stability at the client side. On the other hand, information available at the server side, such as the server’s shared bandwidth capacity, and the number of connected clients and their corresponding downloading bitrates, can be leveraged to better tune the system fairness at the server side. Furthermore, the envisioned client–server cooperation aims at shortening the convergence time of the different clients to the fair bitrate allocation without affecting the overall system smoothness while increasing or decreasing the bitrates. The proposed approach is evaluated through extensive simulations using the Network Simulator, NS-3. Its performance is compared against that of notable algorithms, such as the FESTIVE [1] and PANDA [2] schemes. The obtained results show that the cooperation between the client and the server defines a promising approach in enhancing the efficiency, the fairness, the stability as well as shortening the convergence time to the fair bandwidth share.

Proposed an Adaptive Bitrate Algorithm based on Measuring Bandwidth and Video Buffer Occupancy for Providing Smoothly Video Streaming

Dynamic adaptive streaming via HTTP (DASH) has been popular disseminated over the Internet especially under the circumstances of the time varying network, which it is currently the most challenging for providing smoothly video streaming via high quality. In DASH system, after completing the download of one segment, the player estimates the available network bandwidth by calculating the downloading throughput and then adapting the video bitrate level based on its estimations. However, the estimated bandwidth in the application layer is not accurate due to off-intervals appearance during the downloading process. To avoid the unfairness of bandwidth estimation by the clients, this work proposes a logarithmic approach for received network bandwidth, which includes increasing or decreasing this bandwidth logarithmically to converge the fair share bandwidth (estimated bandwidth). After obtaining the measured bandwidth, an adaptive bitrate algorithm is proposed by considering this measured bandwidth in addition to video buffer occupancy. The video buffer model is associated with three thresholds (i.e. one for initial startup and two for operating thresholds). When the video buffer’s level stays between the two operating thresholds, the video bitrate will keep unchanged. Otherwise, when the buffer occupancy is too high or too low, an appropriate video bitrate is chosen to avoid buffer overflow/underflow. Simulation results show that the proposed scheme is able to converge the measured bandwidth to the fair share bandwidth very quickly. Also the proposed scheme is compared with conventional scheme, we found that our proposed scheme outperforms in achieving the best performance in terms of efficiency, stability and fairness.

Instantaneous Fairness of TCP in Heterogeneous Traffic Wireless LAN Environments

Increasingly, numerous and various Internet-capable devices are connected in end user networks, such as a home network. Most devices use the combination of TCP and 802.11 DCF as a system platform, but whereas some devices such as a streaming video persistently generate traffic, others such as a motion sensor do so only intermittently with lots of pauses. This study addresses the issue of performance in this heterogeneous traffic wireless LAN environment from the perspective of fairness. First, instantaneous fairness is introduced as a notion to indicate how immediately and how closely a user obtains its fair share, and a new time-based metric is defined as an index. Second, extensive simulation experiments have been made with TCP Reno, Vegas, and Westwood to determine how each TCP congestion control corresponds to the instantaneous fairness. Overall, TCP Vegas yields the best instantaneous fairness because it keeps the queue length shorter than the other TCPs. In the simulations, about 60% of a fair share of the effective user bandwidth is immediately usable in any circumstance. Finally, we introduce two simple strategies for adjusting TCP congestion controls to enhance instantaneous fairness and validate them through simulation experiments.

A Cross-Layer MAC Protocol for Underwater Acoustic Sensor Networks

One of the major challenges for the deployment of underwater acoustic sensor networks is the development of a medium access control (MAC) protocol catering for the harsh underwater environment. In particular, an underwater MAC protocol should provide high end-to-end throughput, low channel access delay, and fair share of the scarce network bandwidth. In this paper, a cross-layer MAC protocol is proposed. It interacts with a price-based rate allocation scheme at the network layer. To accurately reflect the clique constraint of the wireless medium, the clique-based price is generalized to act as the congestion signal, which controls the end-to-end rates of multihop flows. The MAC protocol then schedules contention-free packet transmissions of single-hop subflows in each maximum clique. Both the MAC protocol and rate allocation algorithm are simple and direct, thus owning low computational complexity. Through analysis and simulation, we show that the proposed MAC protocol enables multihop flows to acquire the max-min fair share of the network bandwidth from the end-to-end perspective.

Towards fair and low latency next generation high speed networks: AFCD queuing

In packet switched high-speed networks, heterogeneous nature of TCP flows, a relatively newer characteristics of IP networks, and high burstiness have made it difficult to achieve low queuing delay and fair allocation of bandwidth among flows. Existing queue management (QM) schemes were designed to achieve either one or the other or both simultaneously and have been fairly successful at meeting either fairness or low queuing delay but not both at the same time. In this paper, unlike previous research efforts, the two requirements, fairness and low queuing delay are decoupled and addressed separately. We propose Approximated-Fair and Controlled-Delay (AFCD) queuing for next generation high speed networks that aims to meet following design goals: approximated fairness, controlled low queuing delay, high link utilization and simple implementation. The design of AFCD utilizes a novel synergistic approach by forming an alliance between approximated fair queuing and controlled delay queuing. It uses very small amount of state information in sending rate estimation of flows and makes drop decision based on a target delay of individual flow. Through experimental evaluation in a 10Gbps high speed networking environment, we show AFCD meets our design goals by maintaining approximated fair share of bandwidth among flows and ensuring a controlled very low queuing delay with a comparable link utilization. AFCD is locally stable for small target delay in a high speed networking environment.

Mitigating congestion based DoS attacks with an enhanced AQM technique

Denial of Service (DoS) attacks are currently one of the biggest risks any organization connected to the Internet can face. Hence, the congestion handling techniques at the edge router(s), such as Active Queue Management (AQM) schemes must take into account such attacks. Ideally, an AQM scheme should (a) ensure that each network flow gets its fair share of bandwidth, and (b) identify attack flows so that corrective actions (e.g. drop flooding traffic) can be explicitly taken against them to further mitigate the DoS attacks. This paper presents a proof-of-concept work on devising such an AQM scheme, which we name Deterministic Fair Sharing (DFS). Most of the existing AQM schemes do not achieve the above goals or have significant room for improvement. DFS uses the concept of weighted fair share (wfs) that allows it to dynamically self-adjust the router buffer usage based on the current level of congestion, while aiding in identifying malicious flows. By using multiple data structures (a comprehensive repository and a cache) for keeping state of legitimate and malicious flows, DFS is able to optimize its runtime performance (e.g. higher bandwidth flows being handled by the cache). We demonstrate the performance advantage of DFS via extensive simulation while comparing against other existing AQM techniques.

Fair Bandwidth Sharing Scheme Based on Upload Traffic Control

The current paper presents the evaluation of new fair downstream bandwidth sharing strategy and effective shared link utilization for TCP/IP networks. The proposed method provides download bandwidth fair sharing among multiple data flows based on their upload per-flow rate limitation. We evaluate the current approach by controlling upload rate to obtain fair download bandwidth sharing for each of the flows in the link. The performance of the proposed method is evaluated on physical test network. The experimental results demonstrate that our approach can successfully provide fair bandwidth distribution among multiple data flows and can be promising method for bandwidth management in the real data networks. DOI: http://dx.doi.org/10.5755/j01.eee.20.1.6172

Sharing Bandwidth by Allocating Switch Buffer in Data Center Networks

In today's data centers, the round trip propagation delay is quite small. Therefore, switch buffer sizes are much larger than the Bandwidth Delay Product (BDP). Based on this observation, in this paper we introduce a new transport protocol which provides bandwidth Sharing by Allocating switch Buffer (SAB) for data centers. SAB sets the congestion windows for flows based on the buffer size of the switches along the path. On one hand, as long as the total buffer allocated to all the flows is larger than the BDP, the network bandwidth can be fully utilized. On the other hand, since SAB only allocates the buffer space to flows, the totally injected traffic will not exceed the network capacity. Thus, SAB rarely loses packets. SAB also reduces flow completion time by allowing flows to reach their fair share of bandwidth quickly. The results of a series of experiments and simulations demonstrate that SAB has the features of fast convergence and rare packet loss. It reduces the latency of short flows and solves theTCP Incast and TCP Outcast problems.

Probe and Adapt: Rate Adaptation for HTTP Video Streaming At Scale

Today, the technology for video streaming over the Internet is converging towards a paradigm named HTTP-based adaptive streaming (HAS), which brings two new features. First, by using HTTP/TCP, it leverages network-friendly TCP to achieve both firewall/NAT traversal and bandwidth sharing. Second, by pre-encoding and storing the video in a number of discrete rate levels, it introduces video bitrate adaptivity in a scalable way so that the video encoding is excluded from the closed-loop adaptation. A conventional wisdom in HAS design is that since the TCP throughput observed by a client would indicate the available network bandwidth, it could be used as a reliable reference for video bitrate selection. We argue that this is no longer true when HAS becomes a substantial fraction of the total network traffic. We show that when multiple HAS clients compete at a network bottleneck, the discrete nature of the video bitrates results in difficulty for a client to correctly perceive its fair-share bandwidth. Through analysis and test bed experiments, we demonstrate that this fundamental limitation leads to video bitrate oscillation and other undesirable behaviors that negatively impact the video viewing experience. We therefore argue that it is necessary to design at the application layer using a "probe and adapt" principle for video bitrate adaptation (where "probe" refers to trial increment of the data rate, instead of sending auxiliary piggybacking traffic), which is akin, but also orthogonal to the transport-layer TCP congestion control. We present PANDA - a client-side rate adaptation algorithm for HAS - as a practical embodiment of this principle. Our test bed results show that compared to conventional algorithms, PANDA is able to reduce the instability of video bitrate selection by over 75% without increasing the risk of buffer underrun.

A Study of Fair Bandwidth Sharing with AIMD-Based Multipath Congestion Control

The multi-homed capability offers a good opportunity to explore multipath transmission. To ensure fair bandwidth sharing between multipath flows and legacy single-path flows, congestion control is an essential mechanism at the transport layer to regulate traffic flows for bandwidth consumption. However, in a multipath scenario, the congestion control algorithm of the dominant transport control protocol (TCP) may result in too aggressive behavior. In this paper, we consider the generic congestion control principle of additive increase and multiplicative decrease (AIMD) and investigate two AIMD-based multipath congestion control solutions. We derive the conditions for AIMD parameters to ensure TCP-friendliness and satisfy two constraints for fair bandwidth sharing between multipath and single-path flows. Simulation results demonstrate that the AIMD-based multipath solutions well achieve the fairness goals.