Bottleneck Link Research Articles

Curing critical links in oscillator networks as power flow models

Modern societies crucially depend on the robust supply with electric energy so that blackouts of power grids can have far reaching consequences. Typically, large scale blackouts take place after a cascade of failures: the failure of a single infrastructure component, such as a critical transmission line, results in several subsequent failures that spread across large parts of the network. Improving the robustness of a network to prevent such secondary failures is thus key for assuring a reliable power supply. In this article we analyze the nonlocal rerouting of power flows after transmission line failures for a simplified AC power grid model and compare different strategies to improve network robustness. We identify critical links in the grid and compute alternative pathways to quantify the grid’s redundant capacity and to find bottlenecks along the pathways. Different strategies are developed and tested to increase transmission capacities to restore stability with respect to transmission line failures. We show that local and nonlocal strategies typically perform alike: one can equally well cure critical links by providing backup capacities locally or by extending the capacities of bottleneck links at remote locations.

Multi-Commodity Based Widest Congested Edge Disjoint Path Algorithm (MBWCEDP) using MPLS

Objectives: The paper deals with the Online Multipath Routing of the Traffic flows in MPLS networks. A good multipath routing algorithm fulfills all the online traffic demands at real time. Many conventional multipath routing algorithms were considered good in respect of many parameters but still suffered from their highly rejected online traffic demands rate. Methods/Statistical Analysis: The algorithm presented classifies the traffic demands into various profile classes (which are generated based on the SLAs signed by the Internet users). These profile classes work as a rough estimator of future traffic demands and are used to solve a multi commodity network flow problem. In the proposed algorithm Multicommodity network flow formulation groups the packet flows as per profile classes with the aim to minimize the cost, to prevent network hotspots i.e. bottleneck links and to ensure minimum rejected requests/ traffic demands. The algorithm works in two phases- In the preprocessing phase SLAs, Global and Local quasi static knowledge about the network are used to generate Multi-commodities based “Profile Classes” in the first phase and then these Multi-commodities based packet flows are distributed over widest residual bandwidth Disjoint Paths with respect to the bottleneck links in the second phase. The transmission of Multi-commodity based flows through disjoint paths w.r.t. bottleneck edges prevent the network from critical deadlock point which helps in minimizing the congestion, delays, rejected requests and maximizing the throughput, i.e. improving the overall performance of the network. Findings: To measure the performance of proposed algorithm to the Profile Based Algorithm a series of experiments were measured. Randomly generated request sequence is used for which a random sequence of individual flow request were generated and measured the performance both in terms of number of flows routed and total bandwidth request that was satisfied. Blocking probability for each edge is also considered random.In the findings is shown that out of total 1200 requests, performance of PBR is very poor as it rejects many requests due to overly strict admission control and minimum hop algorithm. The proposed algorithm cleverly controls traffic flow admission by considering congested edges in a disjoint way, so that one LSP does not interfere other LSPs. Application/Improvements: The network information is utilized to its extreme and most of the online path requests are accepted only a few requests are rejected.

Adaptive low-priority congestion control for high bandwidth-delay product and wireless networks

The low-priority service is an exciting and attractive choice for networking applications (e.g. automatic update, backup, peer-to-peer file share) which create traffic that is considered less urgent than that of others and become a renewed interest at the Internet Engineering Task Force (IETF). A low-priority protocol, which provides the low-priority service, can exploit the residual bandwidth of the bottleneck link and achieve the high throughput, low-latency data delivery in traditional networks. However, due to the conservative and inappropriate congestion control mechanisms, the existing low-priority protocols (e.g. LEDBAT) cannot effectively utilize the residual bandwidth of the bottleneck link in high bandwidth-delay product (HBDP) and wireless networks. In this paper, we propose an adaptive Congestion level-based Low-Priority congestion Control (CLPC) protocol to improve the efficiency of low-priority protocols and maintain the low-priority features. Specifically, the CLPC sender adopts an one-way path delay to estimate the congestion level and adjust the aggressiveness of congestion control mechanisms. Different from other low-priority protocols, the CLPC protocol is more aggressive when the bottleneck link of HBDP and wireless networks has residual bandwidth. This makes a faster convergence of link utilization in HBDP networks. Combining the random loss detection, CLPC can achieve the high throughput in wireless networks. The extensive simulations in NS-2 show that CLPC can improve the transmission performance significantly as compared to other low-priority protocols in HBDP and wireless networks. Furthermore, we implement the CLPC protocol in the Linux kernel (3.13) and setup a testbed to measure it. The results also indicate the feasibility and effectiveness of CLPC.

Improving Routing Performance Using Cooperative Spectrum Sensing in Cognitive Radio Networks

The traditional fixed spectrum assignment policy, in wireless networks, has led to significant underutilization (both spatially and temporally) of some licensed spectrum bands and crowdedness of unlicensed spectrum bands. These challenges gave birth to the new spectrum utilization paradigm called “Opportunistic Spectrum Access (OSA)”. Networks that operate under this new paradigm are called Cognitive Radio Networks, named after the enabling technology of OSA. The new paradigm allows unlicensed wireless users, also called Secondary Users (SUs), to use licensed spectrum bands as long as they are not in use by their licensed users, also called Primary Users (PUs). One of the most important properties of CRNs is that channel availability changes over time depending on the activity of PUs. Therefore, SUs must be able to detect PU activity on licensed spectrum bands, in order to use those bands for data communication when they are not in use by their PUs. This nature affects many functions in the network including routing. Routing in CRNs is different from traditional network routing, since it requires spectrum availability awareness. Therefore in CRNs, all intermediate SUs must sense channels availability periodically. However, the overall sensing time over a selected route cannot be neglected. In fact, the overall transmission time for SUs along a route is reduced, due to the time spent on the required periodic sensing for these SUs. In this paper, we introduce a novel Cooperative Spectrum Sensing (CSS) strategy, in which SUs along a selected route cooperate with their neighboring SUs to monitor PUs’ activities. In our proposed strategy, a SU along the route selects a neighboring SU, if exists, to conduct spectrum sensing on its behalf for a particular channel. This selection is based on the required channel sensing time, and the remaining available time of the candidate SU. Simulation results show that the proposed model improves routing performance such that it reduces the overall required sensing time along selected routes, and therefore, the available time that SUs can offer for data transmission is increased. Also, the end-to-end delay and the achieved bottleneck link rate are enhanced.

QoS routing with worst-case delay constraints: Models, algorithms and performance analysis

In a network where weighted fair-queueing schedulers are used at each link, a flow is guaranteed an end-to-end worst-case delays which depends on the rate reserved for it at each link it traverses. Therefore, it is possible to compute resource-constrained paths that meet target delay constraints, and optimize some key performance metrics (e.g., minimize the overall reserved rate, maximize the remaining capacity at bottleneck links, etc.). Despite the large amount of literature that has appeared on weighted fair-queueing schedulers since the mid ’90s, this has so far been done only for a single type of scheduler, probably because the complexity of solving the problem in general appeared forbidding. In this paper, we formulate and solve the optimal path computation and resource allocation problem for a broad category of weighted fair-queueing schedulers, from those emulating a Generalized Processor Sharing fluid server to variants of Deficit Round Robin. We classify schedulers according to their latency expressions, and show that a significant divide exists between those where routing a new flow affects the performance of existing flows, and those for which this do not happen. For the former, explicit admission control constraints are required to ensure that existing flows still meet their deadline afterwards. However, despite this major difference and the differences among categories of schedulers, the problem can always be formulated as a Mixed-Integer Second-Order Cone problem (MI-SOCP), and be solved at optimality in split-second times even in fairly large networks.

Delay Stability of Back-Pressure Policies in the Presence of Heavy-Tailed Traffic

We study multihop networks with flow-scheduling constraints, no constraints on simultaneous activation of different links, potentially multiple source-destination routes, and a mix of heavy-tailed and light-tailed traffic. In this setting, we analyze the delay performance of the widely studied class of Back-Pressure scheduling policies, known for their throughput optimality property, using as a performance criterion the notion of delay stability, i.e., whether the expected end-to-end delay in steady state is finite. Our analysis highlights the significance of “bottleneck links,” i.e., links that are allowed to serve the source queues of heavy-tailed flows. The main idea is that traffic that has to pass through bottleneck links experiences large delays under Back-Pressure. By means of simple examples, we provide insights into how the network topology, the routing constraints, and the link capacities may facilitate or hinder the ability of light-tailed flows to avoid bottlenecks. Our delay-stability analysis is greatly simplified by the use of fluid approximations, allowing us to derive analytical results that would have been hard to obtain through purely stochastic arguments. Finally, we show how to achieve the best performance with respect to the delay stability criterion, by using a parameterized version of the Back-Pressure policy.

Gating Control for a Single Bottleneck Link Based on Traffic Load Equilibrium

The purpose of this paper is to improve the intelligence and universality of the classical method for gating control in the SCOOT system. First, we introduce a method to identify spillovers, and use the occupancy threshold for spillover recognition to trigger this special control logic. Second, the interrelationship of the traffic flows among adjacent traffic links is analyzed. Accordingly, we present an influence rate model for upstream links of the bottleneck link and a share ratio model for the downstream links. With known threshold values for the influence rate and share ratio, we propose a rule and process for selecting the intersections that should be included in the sub-area of the gating control. Third, we determine total capacity adjustments for the incoming and outgoing streams of bottleneck links. Under the measures, the queue can be dissipated to a permissible length within a given period of time. After that, the apportion models for the total adjustments among different paths and links are presented. Therefore, the correlation coefficients of the traffic flows are between the bottleneck link and the other links. Next, we ascertain the capacity decrements and increments for the gated and benefiting streams. The optimization schemes are defined so as to calculate splits for the gated and benefiting intersections. Finally, we evaluate the advanced method using a VISSIM simulation. The results show that a new control method brings significant and positive effects to the bottleneck link itself and to the entire test area.

Large Data Throughput Optimization Model with Full C order model Parallel Flow Number Prediction Optical Domain

In order to address the low efficiency of traditional data-intensive extensible computing system in data source utilization and data transmission, a throughput optimization model of application layer based on parallel flow number prediction has been proposed. Firstly, for the purpose of improving accuracy of parallel flow number prediction and utilization efficiency of bottleneck link, selection method for equivalent parallel flow number has been designed; secondly, an full C order model has been established by using partial C order model and all of second order model as reference, and a low-sampling throughout optimization algorithm framework has been designed to reduce computational complexity; last, experiment based on data set of different sizes shows that prediction model of full C order model parallel flow number is more applicable to data transmission and is more efficient.

Tracing Road Network Bottleneck by Data Driven Approach.

Urban road congestions change both temporally and spatially. They are essentially caused by network bottlenecks. Therefore, understanding bottleneck dynamics is critical in the goal of reasonably allocating transportation resources. In general, a typical bottleneck experiences the stages of formation, propagation and dispersion. In order to understand the three stages of a bottle neck and how the bottleneck moves on a road network, traffic flow data can be used to reconstruct these dynamics. However, raw traffic flow data is usually flawed in many ways. For instance some portion of data may be missing due to the failure of data collection devices, or some random factors in the data make it hard to identify real bottlenecks. In this paper a “user voting method” is proposed to deal with such raw-data-related issues. In this method, road links are ranked according to the weighed sum of certain performance measures and the links that are ranked relatively high are regarded as recurrent bottlenecks in a network, and several bottlenecks form a bottleneck area. A series of bottleneck parameters can be defined based on the identified bottleneck areas, such as bottleneck coverage, bottleneck link length, etc. Identifying bottleneck areas and calculating the bottleneck parameters for each time interval can reflect the evolution of the bottlenecks and also help trace how the bottlenecks move.

A cell transmission model for dynamic lane reversal with autonomous vehicles

Autonomous vehicles admit consideration of novel traffic behaviors such as reservation-based intersection controls and dynamic lane reversal. We present a cell transmission model formulation for dynamic lane reversal. For deterministic demand, we formulate the dynamic lane reversal control problem for a single link as an integer program and derive theoretical results. In reality, demand is not known perfectly at arbitrary times in the future. To address stochastic demand, we present a Markov decision process formulation. Due to the large state size, the Markov decision process is intractable. However, based on theoretical results from the integer program, we derive an effective heuristic. We demonstrate significant improvements over a fixed lane configuration both on a single bottleneck link with varying demands, and on the downtown Austin network.

A model for evaluating sharing policies for network-assisted HTTP adaptive streaming

HTTP adaptive streaming (HAS) has become the dominant technology for streaming video over the Internet. It gained popularity because of its ability to adapt the video quality to the current network conditions and other appealing properties such as usage of off-the-shelf HTTP servers and easy firewall traversal. However, when multiple HAS players share a bottleneck link for streaming, the individual adaptation techniques in the players have difficulties to maintain a stable bitrate and fairly share the network resources. HAS-assisting network elements can solve these performance problems and allow execution of advanced policies for sharing the available bandwidth. Nonetheless, testing and evaluating new sharing policies is costly and time consuming. This motivated us to formulate a model that allows to differentiate between groups of users depending on the type of user or device, and that can describe the mean bitrate of the video streams and how often this bitrate is expected to change during playout. To show how our model can be used, we demonstrate two applications of our model. Furthermore, we validate the model based results against results obtained using our streaming testbed and proxy server based HAS-assistant. The results show that our model is highly accurate for both the mean bitrate and the number of changes in video bitrate. As such, our model is a useful tool for network administrators and internet service providers for evaluating the performance of sharing policies and for managing and provisioning video delivery networks.

Online coded caching

We consider a basic content distribution scenario consisting of a single origin server connected through a shared bottleneck link to a number of users each equipped with a cache of finite memory. T...

Online Coded Caching

We consider a basic content distribution scenario consisting of a single origin server connected through a shared bottleneck link to a number of users each equipped with a cache of finite memory. The users issue a sequence of content requests from a set of popular files, and the goal is to operate the caches as well as the server such that these requests are satisfied with the minimum number of bits sent over the shared link. Assuming a basic Markov model for renewing the set of popular files, we characterize approximately the optimal long-term average rate of the shared link. We further prove that the optimal online scheme has approximately the same performance as the optimal offline scheme, in which the cache contents can be updated based on the entire set of popular files before each new request. To support these theoretical results, we propose an online coded caching scheme termed coded least-recently sent (LRS) and simulate it for a demand time series derived from the dataset made available by Netflix for the Netflix Prize. For this time series, we show that the proposed coded LRS algorithm significantly outperforms the popular least-recently used caching algorithm.

Design and Analysis of Heterogeneous Physical Layer Network Coding

In this paper, physical layer network coding with heterogeneous modulations (HePNC) is proposed for the asymmetric two-way relay channel (TWRC) scenario. The existing PNC solutions using the same modulation for signals transmitted from two source nodes may not be desirable for practical situations when traffic loads exchanged between the sources are unequal and channel conditions of source-relay links are heterogeneous. HePNC includes two stages: multiple access (MA) and broadcast (BC) stages. In the MA stage, the two source nodes transmit to the relay simultaneously with heterogeneous modulations selected according to the channel conditions and the ratio of traffic loads exchanged between the sources, and then the signals superimposed at the relay are mapped to a network-coded symbol by a mapping function adaptively; in the BC stage, the relay broadcasts the network-coded symbol back to both sources with a modulation selected according to the bottleneck link’s channel condition. We present three HePNC designs, including QPSK-BPSK, 8PSK-BPSK and 16QAM-BPSK HePNC. How to design and optimize the mapping function is investigated and the error performance of QPSK-BPSK HePNC is analyzed. We further study the HePNC system performance, throughput upper bound and energy efficiency. Extensive simulations demonstrated that the proposed HePNC can substantially enhance the throughput and energy efficiency compared with the existing PNC.

Fundamental Limits of Caching in Wireless D2D Networks

We consider a wireless Device-to-Device (D2D) network where communication is restricted to be single-hop. Users make arbitrary requests from a finite library of files and have pre-cached information on their devices, subject to a per-node storage capacity constraint. A similar problem has already been considered in an ``infrastructure'' setting, where all users receive a common multicast (coded) message from a single omniscient server (e.g., a base station having all the files in the library) through a shared bottleneck link. In this work, we consider a D2D ``infrastructure-less'' version of the problem. We propose a caching strategy based on deterministic assignment of subpackets of the library files, and a coded delivery strategy where the users send linearly coded messages to each other in order to collectively satisfy their demands. We also consider a random caching strategy, which is more suitable to a fully decentralized implementation. Under certain conditions, both approaches can achieve the information theoretic outer bound within a constant multiplicative factor. In our previous work, we showed that a caching D2D wireless network with one-hop communication, random caching, and uncoded delivery, achieves the same throughput scaling law of the infrastructure-based coded multicasting scheme, in the regime of large number of users and files in the library. This shows that the spatial reuse gain of the D2D network is order-equivalent to the coded multicasting gain of single base station transmission. It is therefore natural to ask whether these two gains are cumulative, i.e.,if a D2D network with both local communication (spatial reuse) and coded multicasting can provide an improved scaling law. Somewhat counterintuitively, we show that these gains do not cumulate (in terms of throughput scaling law).

Stability, Rate, and Delay Analysis of Single Bottleneck Caching Networks

Caching has been widely considered an efficient way of reducing and balancing the growing traffic in communications networks in recent years. The cache network of interest consists of one content server connected via a shared link to a number of caching nodes, also known as a single bottleneck caching network. In this paper, for the first time, the stochastic requests traffic model in such networks is considered and a performance analysis is provided based on such a realistic assumption. In addition, we introduce new comprehensive performance metrics, which simultaneously take into account, the cache hit probability, load on the bottleneck link, and requests arrival rates. The main contribution of this paper is to present a system model based on queuing theory and provide an analysis of the stability, maximum stable throughput, load on the bottleneck link, and average response delay for various coded and uncoded caching schemes. Moreover, we propose a novel hybrid scheme that improves the shared link utilization factor, maximum stable throughput, and delay of single bottleneck caching networks compared to existing methods. Our results, validated against simulations and real trace-driven experiments, provide interesting insights into the performance of single bottleneck caching networks.

Equal Preference Multi-Path Routing for L2 Hierarchical Networks

The layer 2 network technology is extending beyond its traditional local area implementation and finding wider acceptance in provider’s metropolitan area networks and large-scale cloud data center networks. This is mainly due to its plug-and-play capability and native mobility support. Many efforts have been put to increase the bisection bandwidth in a layer 2 network, which has been constrained by the spanning tree protocol that a layer 2 network uses for preventing looping. The recent trend is to incorporate layer 3’s routing approach into a layer 2 network so that multiple paths can be used for forwarding traffic between any source-destination (S-D) node pair. ECMP (equal cost multipath) is one such example. However, ECMP may still be limited in generating multiple paths due to its shortest path (lowest cost) requirement. In this paper, we consider a non-shortest-path routing approach, called EPMP (Equal Preference Multi-Path) that can generate more paths than ECMP. The EPMP is based on the ordered semi-group algebra. In the EPMP routing, paths that differ in traditionally-defined costs, such as hops, bandwidth, etc., can be made equally preferred and thus become candidate paths. We found that, in comparison with ECMP, EPMP routing not only generates more paths, provides higher bisection bandwidth, but also allows bottleneck links in a hierarchical network to be identified when different traffic patterns are applied. EPMP is also versatile in that it can use various ways of path preference calculations to control the number and the length of paths, making it flexible (like policy-based routing) but also objective (like shortest path first routing) in calculating preferred paths.

Performance Evaluation of MPTCP over a Shared Bottleneck Link

Performance Evaluation of MPTCP over a Shared Bottleneck Link

Queue Management using Optimal Margin method to Improve Bottleneck Link Performance

In network routers, buffers are used to resolve congestion and reduce packet loss rate whenever congestion occurs at bottleneck link. Most of the existing methods to manage such buffers focus only on queue-length-based control as one loop which have some issues of low link utilization and system stability. In this paper, we propose a novel framework which exploits two-loop control method, e.g. queue-length and congestion window size, combined with optimal margin method to facilitate parameter choices. Simulation results in ns-2 demonstrate that bottleneck link performance can be improved with higher link utilization (85%) and shorter queue length (22%) than the current deployed scheme in commercial routers (RED and DropTail).

Adaptive rate‐based congestion control with weighted fairness through multi‐loop gradient projection internal model controller

As a transmission control protocol (TCP) implementation imposes the sources with small round trip time (RTT) to allocate the bottleneck unfairly, an adaptive congestion control is necessary to avoid packet loss along with fairness. The main idea of this paper is to design an adaptive rate-based queue management scheme based on gradient projection method and internal model control for network sources with different RTT values. The goal is to achieve weighted fairness, maximum utilisation and compatibility with both large and small RTTs. The communication network consisting of a bottleneck link and N TCP sources is considered as a multi-input single-output system. In the proposed approach, the number of the active TCP sources is determined adaptively and the utilisation factors are updated. For this purpose, the gradient method is used to design the adaptation rule for the utilisation factors in order to obtain weighted fairness, and then the projection method is augmented with the gradient procedure to achieve maximum bottleneck utilisation. The proposed procedure can tolerate both large and small RTTs, and consequently, it can be used in a wide range of communication networks. Extensive simulations based on network simulator NS2 and Simulink validate the analytical results.