Congestion Detection Mechanism Research Articles

Revisiting Congestion Detection in Lossless Networks

Congestion detection is the cornerstone of end-to-end congestion control. Through in-depth observations and understandings, we reveal that existing congestion detection mechanisms in mainstream lossless networks (i.e., Converged Enhanced Ethernet and InfiniBand) are improper, due to failing to cognize the interaction between hop-by-hop flow controls and congestion detection behaviors in switches. We define the ternary states of switch ports and present Ternary Congestion Detection (TCD) for mainstream lossless networks. TCD utilizes the ON-OFF sending pattern and the feature of queue length evolutions to detect the transitions among ternary states. We also enable TCD under the practical multiple queues scenario by TCD-MQ. Testbed and extensive simulations demonstrate that TCD can detect congestion ports accurately and identify flows contributing to congestion as well as flows only affected by hop-by-hop flow controls. Meanwhile, we shed light on how to incorporate TCD with rate control. Case studies show that existing congestion control algorithms can achieve 3.3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times$</tex-math> </inline-formula> and 2.0 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times$</tex-math> </inline-formula> better median and 99th-percentile FCT slowdown by combining with TCD.

An Energy-Efficient Clustering and Fuzzy-Based Path Selection for Flying Ad-Hoc Networks

Flying Ad-hoc Networks (FANET) allow for an ad-hoc networking among Unmanned Aerial Vehicles (UAV), have recently gained popularity in a variety of military and non-militant applications. The existing work used the Glowworm Swarm Optimization (GSO) algorithm to create a self-organization depending on clustering technique for FANET. Owing to UAV increased mobility, network topology might vary over time, providing route discovery and maintenance is one of the most difficult tasks. And also, the network throughput is still more worsened by the network congestion. To solve this problem, the proposed work designed an energy efficient clustering and fuzzy-based path selection for FANET. In this work, initially, the clustering is performed using the UAV distance. For efficient communication and energy consumption, optimal selection of Cluster Head (CH) is performed by using Adaptive Mutation with Teaching-Learning-Based Optimization (AMTLBO) algorithm. To improve the optimal selection of CH nodes, the best fitness values are calculated. The fitness function depends on Link capacity, remaining energy and neighbor UAV distance. Next to that, nodes begin communications as well as transmit their information to their CH. Improved Fuzzy-based Routing (IFR) is introduced for improving the route discovery process. The goal is to find routes that have a high level of flying autonomy, minimal mobility, and a higher Received Signal Strength Indicator (RSSI). As a result, the energy usage of network is decreased, as well as the cluster’s lifespan is extended. Finally, an adaptive and reliable congestion detection mechanism is introduced to transmit the packets with congestion free path. The experimental result shows that the proposed AMTLBO system attains higher performance compared to the existing system in terms of energy usage, throughput, delay, overhead and packet delivery ratio.

Congestion Detection and Alleviation Mechanism Using a Multi-Level Cluster Based Cuckoo Hosted Rider Search Multi-Hop Hierarchical Routing Protocol in Wireless Sensor Networks

Wireless sensor networks congestion occurs easily due to its centralized traffic pattern. Normally, mono-sync wireless sensor network experiences multiple traffic flow congestion in the dense environment of the network, which leads to excess energy consumption and severe packet loss. To overcome these issues, a congestion detection and alleviation mechanism using cluster based heuristic optimized hierarchical routing protocol is proposed in this paper. Here, congestion detection and alleviation utilize the features of sensor nodes. The congestion is categorized into two types: (i) node level congestion and (ii) link level congestion. The node level congestion is detected by assessing the buffer utilization and the interval amid the consecutive data packets. The link level congestion is considered with computing link usage utilizing back-off step of round robin carrier sense multi-access with collision avoidance. Congestion detection and alleviation reactively affected node/link through cuckoo hosted rider search multi-hop routing algorithm. It has two phases: the cluster head selection and multi-path routing. Cluster head selection is performed through Taylor multiple random forest kernel fuzzy C-means clustering algorithm and multi-path routing is performed through cuckoo hosted rider search multi-hop routing algorithm. The simulation of the proposed method is done in network simulator tool. Here, the performance metrics, like packet delivery ratio, delay, energy consumption, packet drop, overhead, network lifetime and throughput are calculated. The experimental outcomes of the proposed technique shows 11.6%, 18.4% and 28.1% lower delay, 78.2%, 65.4% and 52.6% higher packet delivery ratio, and 29.2%, 37.4% and 40.8% lower packet drop compared with the existing methods, like congestion detection and alleviation using multi-attribute decision-making in optimization-based hybrid congestion alleviation routing protocol in wireless sensor networks, congestion detection and alleviation using hybrid K-means with greedy best first search algorithms in packet rate reduction utilizing adaptive weight firefly algorithm ant colony optimization based routing protocol in wireless sensor networks and congestion detection and alleviation using multi-input time on task optimization algorithm for altered gravitational search algorithm routing protocol in wireless sensor networks.

An Effective Transmission Scheme Based on Early Congestion Detection for Information-Centric Network

As one of the candidates for future network architecture, Information-Centric Networking (ICN) has revolutionized the manner of content retrieval by transforming the communication mode from host-centric to information-centric. Unlike a traditional TCP/IP network, ICN uses a location-independent name to identify content and takes a receiver-driven model to retrieve the content. Moreover, ICN routers not only perform a forwarding function but also act as content providers due to pervasive in-network caching. The network traffic is more complicated and routers are more prone to congestion. These distinguished characteristics pose new challenges to ICN transmission control mechanism. In this paper, we propose an effective transmission scheme by combining the receiver-driven transport protocol and the router-driven congestion detection mechanism. We first outline the process of content retrieval and transmission in an IP-compatible ICN architecture and propose a practical receiver-driven transport protocol. Then, we present an early congestion detection mechanism applied on ICN routers based on an improved Active Queue Management (AQM) algorithm and design a receiver-driven congestion control algorithm. Finally, experiment results show that the proposed transmission scheme can maintain high bandwidth utilization and significantly reduce transmission delay and packet loss rate.

Decentralized Additive Increase and Multiplicative Decrease-Based Electric Vehicle Charging

Electric vehicle (EV) transition and low-cost renewable energy generation are putting power grid under a challenging transformation. Number of power electronics actuators connected to the grid is increasing, and the legacy control methods employed on the grid are not responsive to this growing demand. Thus, the grid integration of EVs and their charging management requires a system-wide solution that is scalable, autonomous, and stable. In this article, we investigate two very complex networks: Internet and power grid in the context of controlling mass-scale EV charging problem. We adapt the well-known additive increase-multiplicative decrease (AIMD) algorithm used in the Internet congestion control to EV charging in a distributed fashion. We develop an adaptation of the Internet's congestion control method for power grid considering the unique grid constraints using a decentralized concept. The advantage of the proposed method lies in its low-cost (memory-less) congestion detection mechanism based on only local voltage measurements. Results show that decentralized AIMD can successfully help flatten the peak loading caused by high EV penetration. To test the algorithm, a distribution grid model is designed based on IEEE 37-node test feeder with realistic load modeling. Finally, the results are presented in comparison with two other control architectures.

A New Fault Tolerant Routing Algorithm for Networks on Chip

To provide correct data transmission and to handle the communication requirements, the routing algorithm should find a new path to steer packets from the source to the destination in a faulty network. Many solutions have been proposed to overcome faults in network-on-chips (NoCs). This article introduces a new fault-tolerant routing algorithm, to tolerate permanent and transient faults in NoCs. This solution called DINRA can satisfy simultaneously congestion avoidance and fault tolerance. In this work, a novel approach inspired by Catnap is proposed for NoCs using local and global congestion detection mechanisms with a hierarchical sub-network architecture. The evaluation (on reliability, latency and throughput) shows the effectiveness of this approach to improve the NoC performances compared to state of art. In addition, with the test module and fault register integrated in the basic architecture, the routers are able to detect faults dynamically and re-route packets to fault-free and congestion-free zones.

CoAR: Congestion-Aware Routing Protocol for Low Power and Lossy Networks for IoT Applications.

The IPv6 routing protocol for low power and lossy networks (RPL) was designed to satisfy the requirements of a wide range of Internet of Things (IoT) applications, including industrial and environmental monitoring. In most scenarios, different from an ordinary environment, the industrial monitoring system under emergency scenarios needs to not only periodically collect the information from the sensing region, but also respond rapidly to some unusual situations. In the monitoring system, particularly when an event occurs in the sensing region, a surge of data generated by the sensors may lead to congestion at parent node as data packets converge towards the root. Congestion problem degrades the network performance that has an impact on quality of service. To resolve this problem, we propose a congestion-aware routing protocol (CoAR) which utilizes the selection of an alternative parent to alleviate the congestion in the network. The proposed mechanism uses a multi-criteria decision-making approach to select the best alternative parent node within the congestion by combining the multiple routing metrics. Moreover, the neighborhood index is used as the tie-breaking metric during the parent selection process when the routing score is equal. In order to determine the congestion, CoAR adopts the adaptive congestion detection mechanism based on the current queue occupancy and observation of present and past traffic trends. The proposed protocol has been tested and evaluated in different scenarios in comparison with ECRM and RPL. The simulation results show that CoAR is capable of dealing successfully with congestion in LLNs while preserving the required characteristics of the IoT applications.

A Cross-Layer Fault Tolerant Protocol with Recovery Mechanism for Clustered Sensor Networks

This article describes how fault tolerance is an essential issue for many WSN (Wireless Sensor Network) applications such as wildlife monitoring, battlefield surveillance and health monitoring. It represents a great challenge for researchers regarding to the characteristics of sensor nodes which are prone to failures due essentially to their limited resources. Faults may occur, not only when sensor nodes exhaust their energy, but also when the congestion phenomenon emerges, because of a high traffic in the network and limited storage capacity of the sensor nodes. In order to support fault tolerance in WSNs, the authors propose a new scheme which incorporates a link quality estimation algorithm and a congestion detection mechanism to enable nodes that present high quality links to be chosen for routing in a non-congested area in case of faults. Evaluations through simulations under NS2 show that our proposed protocol tolerates faults with a minimum cost relatively to HEEP protocol and improves network's performances comparatively to other fault tolerant protocols such as EF-LEACH.

The PeRvasive Environment Sensing and Sharing Solution

To stimulate better user behavior and improve environmental and economic sustainability, it is of paramount importance to make citizens effectively aware of the quality of the environment in which they live every day. In particular, we claim that users could significantly benefit from cost-effective efficient Internet-of-Things (IoT) solutions that provide them with up-to-date live information about air pollution in the areas where they live, suitably adapted to different situations and with different levels of dynamically selected granularities (e.g., at home/district/city levels). Our PeRvasive Environment Sensing and Sharing (PRESS) project has the ambition of increasing users’ awareness of the natural environment they live in, as a first step towards improved sustainability; the primary target is the efficient provisioning of real-time user-centric information about environmental conditions in the surroundings, and in particular about air pollution. To this purpose, we have designed, implemented, and thoroughly evaluated the PRESS framework, which is capable of achieving good flexibility and scalability while integrating heterogeneous monitoring data, ranging from sensed air pollution to user-provided quality perceptions. Among the elements of technical originality, PRESS exploits extended Kura IoT gateways with novel congestion detection and recovery mechanisms that allow us to optimize bandwidth allocation between in-the-field PRESS components and the cloud. The reported performance results show the feasibility of the proposed solution, by pointing out not only the scalability and efficiency of the adopted message-based solution that uses Message Queue Telemetry Transport (MQTT) and WebSockets, but also the capability of PRESS to quickly identify and manage traffic congestions, thus, ensuring good quality levels to final users.

Congestion Detection and Alleviation in Multihop Wireless Sensor Networks

Multiple traffic flows in a dense environment of a mono-sink wireless sensor network (WSN) experience congestion that leads to excessive energy consumption and severe packet loss. To address this problem, a Congestion Detection and Alleviation (CDA) mechanism has been proposed. CDA exploits the features and the characteristics of the sensor nodes and the wireless links between them to detect and alleviate node- and link-level congestion. Node-level congestion is detected by examining the buffer utilisation and the interval between the consecutive data packets. However, link-level congestion is detected through a novel procedure by determining link utilisation using back-off stage of Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA). CDA alleviates congestion reactively by either rerouting the data traffic to a new less congested, more energy-efficient route or bypassing the affected node/link through ripple-based search. The simulation analysis performed in ns-2.35 evaluates CDA with Congestion Avoidance through Fairness (CAF) and with No Congestion Control (NOCC) protocols. The analysis shows that CDA improves packet delivery ratio by 33% as compared to CAF and 54% as compared to NOCC. CDA also shows an improvement in throughput by 16% as compared to CAF and 36% as compared to NOCC. Additionally, it reduces End-To-End delay by 17% as compared to CAF and 38% as compared to NOCC.

Continuous One-Way Detection of Available Bandwidth Changes for Video Streaming Over Best-Effort Networks

Video streaming over best-effort networks, such as the Internet, is now a significant application used by most Internet users. However, best-effort networks are characterized by dynamic and unpredictable changes in the available bandwidth, which adversely affect the quality of video. As such, it is important to have real-time detection mechanisms of bandwidth changes to ensure that video is adapted to the available bandwidth and transmitted at the highest quality. In this paper, we propose a Bayesian instantaneous end-to-end bandwidth change prediction model and method to detect and predict one-way bandwidth changes at the receiver. Unlike existing congestion detection mechanisms, which use network parameters such as packet loss probability, round trip time (RTT), or jitter, our approach uses weighted interarrival time of video packets at the receiver side. Furthermore, our approach is continuous, since it measures available bandwidth changes with each incoming video packet, and therefore detects congestion occurrence in <;200 ms, on average, which is significantly faster than existing approaches. In addition, it is a one-way scheme, since it only takes into account the characteristics of the incoming path and not the outgoing path, as opposed to other approaches, which use RTT and are hence less accurate. In this paper, we provide extensive experimental simulations and real-world network implementation. Our results indicate that the proposed detection method is superior to existing solutions.

Congestion Control in WMSNs by Reducing Congestion and Free Resources to Set Accurate Rates and Priority

The main intention of this paper is focus on mechanism for reducing congestion in the network by free resources to set accurate rates and priority data needs. If two nodes send their packets in the shortest path to the parent node in a crowded place, a source node must prioritize the data and uses data that have lower priorities of a suitable detour nodes consisting of low or nonactive consciously. The proposed algorithm is applied to the nodes near the base station (which convey more traffic) after the congestion detection mechanism detected the congestion. Obtained results from simulation test done by NS-2 simulator demonstrate the innovation and validity of proposed method with better performance in comparison with CCF, PCCP and DCCP protocols.

Design of an energy‐efficient and reliable data delivery mechanism for mobile ad hoc networks: a cross‐layer approach

SummaryIn a mobile ad hoc network, the data packet may fail to be delivered for various reasons mostly for route failure, congestion, and battery energy drain. Hence, providing reliable and timely data delivery in this network in an energy‐efficient way is challenging. Although there exist several solutions to solve these problems, they can handle either route failure or congestion or energy‐efficient routing. Hence, to cope up with all the problems simultaneously, we propose a route failure and congestion‐aware energy‐efficient cross‐layer design that spans the transport and network layer. In the transport layer, we introduce the concept of local packet buffering during link failure and congestion. As a result, the packet dropping rate of the network and energy consumption decreases. In the network layer, a routing protocol is proposed for selecting the energy‐efficient path for data transmission. It uses the buffering mechanism in case of route maintenance. In addition, we employ a multilevel congestion detection and control mechanism at the source and intermediate nodes that can judiciously take the most appropriate decision for congestion control in the network proactively. The simulation results showed that the proposed cross‐layer design provided better performance as compared with the state‐of‐the‐art protocols. Copyright © 2014 John Wiley &amp; Sons, Ltd.

A novel distributed congestion control for bufferless network-on-chip

Bufferless Network-on-Chip (NoC) emerges as an interesting option for NoC design in recent years, which can save considerable router power and area. However, bufferless NoC only works well under low-to-medium load because it becomes more easily congested as message injection rate increases. In this paper, we propose a novel distributed source-throttling congestion control mechanism that relieves the effect of congestion in bufferless NoC under high load, called Cbufferless. The proposed strategy uses a novel congestion detection and control mechanism, computing average deflection rate of routing flit and distributed throttling message injection. Utilizing the new mechanism, the congestion information can be directly obtained inside node, which allows the mechanism to be fully distributed without requiring any transmission of global congestion information among neighbor routers and within a router. Simulation results show that the proposed mechanism improves system throughput by up to $$\sim $$ ~ 30 and $$\sim $$ ~ 15.5 %, saves energy consumption by up to $$\sim $$ ~ 40 and $$\sim $$ ~ 19 % than that of baseline and injection rate throttling bufferless NoCs, respectively, and keeps lower message latency under congested load when compared.

A Novel Solution for Discriminating Wormhole Attacks in MANETs from Congested Traffic using RTT and Transitory Buffer

Nowadays, the computing and communication services are accessed while on the move. Setting up of fixed access points and backbone infrastructure is not always viable. So in order to provide communication where there is lack of infrastructure or inconvenience in using the existing infrastructure, Mobile Adhoc Networks (MANETs) are used. This inherent flexibility allows MANETs to be used for a wide range of applications such as rescue operations, military applications, vehicular communication, and business meetings. As there is no apriori trust relationship between the nodes of an ad hoc network and basic network functions like packet forwarding and routing are performed by the available nodes, security is an essential component in MANETs. Various attacks in MANETs are blackhole attack, byzantine attack, resource consumption attack, rushing attack, and wormhole attack. Wormhole attack is a severe threat among the other threats in MANET. Existing solutions to detect wormhole attacks include Packet Leashes, SECTOR, DelPHI, RTT-TC, TTM, etc. These solutions require special hardware or strict synchronized clocks or cause message overhead. Some solutions do not locate the wormhole, and some other may generate false alarms or does not consider network congestion into account. In this paper, wormhole attack detection is proposed based on RTT between successive nodes and congestion detection mechanism. If the RTT between two successive nodes is higher than the threshold value, a wormhole attack is suspected. If a wormhole is suspected, node‘s transitory buffer is probed to determine whether the long delay between the nodes is due to wormhole or not, as delays can be caused due to congestion or by queuing delays. The proposed method prevents both the hidden and the exposed attack. Advantage of our proposed solution is that it does not require any specialized hardware or synchronized clocks. Index Terms — MANET, Wormhole attack, RTT, Transitory buffer

LOT

We present LOT, a lightweight plug and play secure tunneling protocol deployed at network gateways. Two communicating gateways, A and B, running LOT would automatically detect each other and establish an efficient tunnel, securing communication between them. LOT tunnels allow A to discard spoofed packets that specify source addresses in B’s network and vice versa. This helps to mitigate many attacks, including DNS poisoning, network scans, and most notably (Distributed) Denial of Service (DoS). LOT tunnels provide several additional defenses against DoS attacks. Specifically, since packets received from LOT-protected networks cannot be spoofed, LOT gateways implement quotas, identifying and blocking packet floods from specific networks. Furthermore, a receiving LOT gateway (e.g., B) can send the quota assigned to each tunnel to the peer gateway (A), which can then enforce near-source quotas, reducing waste and congestion by filtering excessive traffic before it leaves the source network. Similarly, LOT tunnels facilitate near-source filtering, where the sending gateway discards packets based on filtering rules defined by the destination gateway. LOT gateways also implement an intergateway congestion detection mechanism, allowing sending gateways to detect when their packets get dropped before reaching the destination gateway and to perform appropriate near-source filtering to block the congesting traffic; this helps against DoS attacks on the backbone connecting the two gateways. LOT is practical: it is easy to manage (plug and play, requires no coordination between gateways), deployed incrementally at edge gateways (not at hosts and core routers), and has negligible overhead in terms of bandwidth and processing, as we validate experimentally. LOT storage requirements are also modest.

A Fuzzy Multiobjective Particle Swarm Optimized TS Fuzzy Logic Congestion Controller for Wireless Local Area Networks

A Takagi-Sugeno Fuzzy Logic Congestion Detection (TSFLCD) mechanism is proposed for IEEE 802.11 wireless Local Area Networks. A Fuzzy Preference based Multi-Objective Particle Swarm Optimization (FPMOPSO) mechanism, for tuning the input membership functions and the output scalars, is also proposed. An online adaptation mechanism that finetunes the output scalars based on system dynamics is implemented. Compared to the Adaptive Random Early Detection (ARED) and the Mamdani inference based Fuzzy Logic Congestion Detection (FLCD) mechanisms, simulation results show that the TSFLCD mechanism leads to more than 40% reduction in packet loss rate. It also leads to more than 25% and up to 14% reductions in jitter and delay respectively for real time traffic. This work lays a foundation for the development of simple multiobjective fuzzy congestion controllers in wireless LANs.

Zone-based congestion detection and control using routing method on the internet

The rapid growth of information technology has resulted in severe congestion problems in the internet. Due to micro-level congestion (such as link and router), it is hard to detect and control the congestion from the internet. To reduce and/or overcome this problem, we introduce, a macro-level congestion detection mechanism and congestion control method across the internet. Here, a zone is a collection of hundreds or thousands of networks situated in a geographical region. A zone has a zone-manager and border routers; they can cooperate with each other by controlling information. Using our method, zones can prevent congestion and produce better zone performance.

Delay-based early congestion detection and adaptation in TCP: impact on web performance

Concerns over the scalability of TCP's end-to-end approach to congestion control and its AIMD congestion adaptation have led to proposals for router-based congestion control, specifically, active queue management (AQM). In this paper we present an end-to-end alternative to AQM—a new congestion detection and reaction mechanism for TCP based on measurements of one-way transit times of TCP segments within a TCP connection. Our design, called Sync-TCP, places timestamps in TCP headers, measures variation in one-way transit times, and uses these measurements as a form of early congestion notification. We demonstrate empirically that: (1) Sync-TCP provides better throughput and HTTP response-time performance than TCP Reno, (2) Sync-TCP provides better early congestion detection and reaction than the Adaptive Random Early Detection with Explicit Congestion Notification AQM mechanism, (3) Sync-TCP's congestion detection and adaptation mechanisms are robust against clock drift, (4) Sync-TCP is an incrementally deployable protocol—Sync-TCP connections can co-exist with TCP Reno connections in a network, and (5) the performance of TCP Reno connections are improved with the addition of even a small percentage of Sync-TCP connections.

Performance evaluation and comparison of Westwood+, New Reno, and Vegas TCP congestion control

TCP congestion control has been designed to ensure Internet stability along with fair and efficient allocation of the network bandwidth. During the last decade, many congestion control algorithms have been proposed to improve the classic Tahoe/Reno TCP congestion control. This paper aims at evaluating and comparing three control algorithms, which are Westwood+, New Reno and Vegas TCP, using both Ns-2 simulations and live Internet measurements. Simulation scenarios are carefully designed in order to investigate goodput, fairness and friendliness provided by each of the algorithms. Results show that Westwood+ TCP is friendly towards New Reno TCP and improves fairness in bandwidth allocation whereas Vegas TCP is fair but it is not able to grab its bandwidth share when coexisting with Reno or in the presence of reverse traffic because of its RTT-based congestion detection mechanism. Finally results show that Westwood+ remarkably improves utilization of wireless links that are affected by losses not due to congestion.