Random Early Detection Research Articles

An EAODV routing approach based on DARED and integrated metric

Wireless Mesh Network (WMN) is a new high-capacity and high-speed distributed broadband access network. Because of supporting multi-band devices, WMN is suitable for different application in the Internet of Things. In order to meet the performance requirements of multimedia traffic transmission, the routing approach designed for WMN must be taken into account the combination of load balance and anti-interference. We propose an extended Ad hoc on demand distance vector (AODV, which is a peer-to-peer the reactive routing approach) routing approach which is based on distributed adaptive random early detection and integrated metric for WMN. We firstly introduce several typical WMN routing approaches, and then based on the optimization theorem and cross-layer design proposes an integrated metrics to improve AODV routing approach. The steps and example using convex programming method are presented to solve routing optimization problem. Finally the feasibility of the proposed algorithm is verified with Method simulation. Simulation and analysis results show that the proposed EAODV routing approach improves the performance of WMN significantly.

Enhanced Random Early Detection (ENRED)

ABSTRACT As the internet is expected to better support many applications such as multimedia with limit bandwidth, new mechanisms are needed to control the congestion in the network. Active Queue Management (AQM) algorithms play an important role to ensure the stability of the Internet. Random Early Detection (RED) is the first active queue management algorithm proposed for deployment in TCP/IP networks. RED has some parameters tuning issues that need to be carefully addressed for it to give good performance under different network scenarios.We propose a new algorithm called Enhanced Random Early Detection (ENRED). ENRED works to improve these parameters to provide better congestion control over the network while remaining the advantage of RED.This paper will introduce ENRED and some features about RED and its variants . 8We simulate the proposed algorithm (ENRED) using the well-known network simulator ns-2, by comparing it to the original RED. Simulation results show that the proposed algorithm achieves better queue size than RED and decreases the delay and losses.

The Modified Gaussian Function based RED (MGF-RED) Algorithm for Congestion Avoidance in Mobile Ad Hoc Networks

In this paper the idea is to rationale a new active queue management technique (MGF-RED) based on Random Early Detection (RED), a well known active queue management technique for congestion avoidance. The conventional RED uses the concept of minimum threshold, maximum threshold and average queue length. If the average queue length increases by minimum threshold then the algorithm start dropping the packets with some probability using linear function of average queue size. If the average queue size is greater than the maximum threshold then packets are dropped with 1 probability. The proposed algorithm will use Modified Gaussian function for calculating the likelihood of packet drop as the average queue length increases the minimum threshold. Simulation has been performed using NS-2.34. The simulation results show that the proposed algorithm will present better network performance in throughput, packet delivery fraction and number of dropped packets. General Terms MANET, RED, Gaussian Function.

A study of fairness among heterogeneous TCP variants over 10 Gbps high-speed optical networks

Several high-speed TCP variants are adopted by end users and therefore, heterogeneous congestion control has become the characteristic of newly emerging high-speed optical networks. In contrast to homogeneous TCP flows, fairness among heterogeneous TCP flows now depends on router parameters such as queue management scheme and buffer size. To the best of our knowledge, this is the first study of fairness performance among heterogeneous TCP variants over a 10Gbps high-speed optical network environment. Our evaluation scenarios for heterogeneous TCP flows consist of TCP variants with substantial presence in current Internet; therefore, TCP-SACK, CUBIC TCP (CUBIC) and HighSpeed TCP (HSTCP) compete for bottleneck bandwidth. Experimental results for fairness are presented for different queue management schemes, such as Drop-tail, Random Early Detection (RED), CHOose and Keep for responsive flows CHOose and Kill for unresponsive flows (CHOKe), and Approximate Fair Dropping (AFD), with varying degree of buffer sizes. We observe heterogeneous TCP flows induce more unfairness than homogeneous ones. Active queue management (AQM) schemes, RED, CHOKe, and AFD, improve fairness for large buffer sizes as compared to Drop-tail, whereas AQM schemes lose the fairness advantage for small buffer sizes. This study provides preliminary results for fairness challenges to deploy all-optical routers with limited buffer size.

Advanced Applications of Wireless Sensor Network Using Sensor Cloud Infrastructure

It is our pleasure to publish a special issue on advanced applications of wireless sensor network using sensor cloud infrastructure. This special issue contains seven high quality research papers related to the growing technologies of recent wireless sensor networks and sensor cloud infrastructure. The paper “Sensor resource sharing approaches in sensorcloud infrastructure” by Y. Lim and J. Park presents a survey on sensor-cloud infrastructure (SCI) and discusses technical issues of SCI such as architecture, sensor description methods, middleware based on publish/subscribe data exchange model, and case studies. The paper “Multiple wide tables with vertical scalability in multitenant sensor cloud systems” by K. Ma and B. Yang proposes the multitenant multiple wide tables with vertical scalability by analyzing the features of multitenant data and shows the effectiveness of the proposed method by the experiments. The paper “Semantic reasoning with contextual ontologies on sensor cloud environment” by K. Park et al. presents a massive contextual events handling scheme on a big data framework based on a context-aware inference model with the contextual ontologies and shows that the proposed collaboration framework allows many cooperating parties to collaborate with each other by sharing constituent entities. The paper “Modeling and analysis on congestion control for data transmission in sensor clouds” by J. Huang et al. proposes an Improved Random Early Detection (IRED) algorithm that meets sensor cloud networking requirements better and develops a queueing model coupled with an analysis technique to evaluate the performance of the proposed congestion control scheme. The paper “Agriculture sensor-cloud infrastructure and routing protocol in the physical sensor network layer” by K. Kimet al. proposes an agriculture sensor-cloud infrastructure to provide various services efficiently and to process largescale sensor data effectively and evaluates the proposed techniques by simulation experiments. The paper “Competition-based device-to-device transmission scheduling to support wireless cloud multimedia communications” byR. Yao et al. presents a new algorithm to improve the data transmission quality for a mobile multimedia cloud network (MMCN) in a cloud device-to-device (D2D) communication and demonstrates the simulation results to show the effects of the proposed algorithm. The paper “Towards an environmental measurement cloud: delivering pollution awareness to the public” by F. Dominguez et al. proposes a cloud platform with a federated two-layer architecture which integrates an environmental sensor network with a sensor web, in order to offer geographical environmental data to the public and also to serve as a test bed for scientific research on noise and air pollution. We hope that the papers of this issue contribute to the progress of research and the development of Wireless Sensor Networks.

English

Many applications (e.g., cluster based storage and Map Reduce) in modern data centers require a high fan-in, manytoone type of data communication (known as TCP in cast), which could cause severe in cast congestion in switches and result in TCP good put collapse, substantially degrading the application performance. The root cause of such a collapse is the long idle period of the Retransmission Timeout (RTO) that is triggered at one or more senders by packet losses in congested switches. In this paper We Study a packet labeling scheme PLATO, which improves the loss detection capabilities of New Reno using an innovative packet labeling system. Packets carrying this special label are preferentially en queued, at the switch. This allows TCP to detect packet loss using three duplicate acknowledgements, instead of the time expensive RTO; thus avoiding the good put collapse. PLATO makes minor modifications to New Reno and does not alter its congestion control mechanism. The implementation and simulations have been done in Network Simulator 3 (NS3). PLATO’s performance is significantly better than New Reno as well as state-of-art in cast solutions In cast Control TCP (ICTCP) and Data Center TCP (DCTCP). We also show that TCP PLATO can be implemented using commodity switches with Weighted Random Early Detection (WRED) function.

Active Queue Management in Wireless Networks by Using Nonlinear Extended Network Disturbance

This paper studies congestion control in local wireless networks supporting transmission control protocol (TCP) under random early detection (RED). In general, congestion delays may cause instability of the routers running active queue management (AQM) protocols such as RED. Moreover, its management efficiency could be reduced by serious queue oscillation. To improve these two drawbacks, we propose a robust congestion controller focusing on the queue oscillation suppression and time-delay compensation based on an idea of nonlinear extended network disturbance (NEND). The time-delay compensation is further performed via the NEND rejection. Furthermore, the proposed strategy has been validated on NS2 showing their applicability.

Efficient Path Selection and Data Transmission Using Queue in Open Shortest Path First

In network, information apportioning occurs between one communication points to another using TCP protocol. The collected data are shared among many users via Single Router or Access Point (AP). During routing, traffic is occurred in the network and that is known as Random Early Detection (RED). In order to overcome this, an alternative path must be preferred by using Alternative Path Selection method which utilizes the Queue Process (FIFO). In case the queue is full, it chooses an alternative queue by using channel sensing mode of path selection. Here, we use OSPF (Open Shortest Path First) which selects the shortest path in short period of time and also it delivers the data to the particular destination. However, delay is reduced in OSPF. Hence, efficiency and overall network lifetime is increased. Finally, the network performance is evaluated.

TCP PLATO: Packet Labelling to Alleviate Time-Out

Many applications (e.g., cluster based storage and MapReduce) in modern data centers require a high fan-in, many-to-one type of data communication (known as TCP incast), which could cause severe incast congestion in switches and result in TCP goodput collapse, substantially degrading the application performance. The root cause of such a collapse is the long idle period of the Retransmission Timeout (RTO) that is triggered at one or more senders by packet losses in congested switches. In this paper we develop a packet labelling scheme PLATO, which improves the loss detection capabilities of NewReno using an innovative packet labelling system. Packets carrying this special label are preferentially enqueued, at the switch. This allows TCP to detect packet loss using three duplicate acknowledgements, instead of the time expensive RTO; thus avoiding the goodput collapse. PLATO makes minor modifications to NewReno and does not alter its congestion control mechanism. The implementation and simulations have been done in Network Simulator 3 (NS3). PLATO's performance is significantly better than NewReno as well as state-of-art incast solutions Incast Control TCP (ICTCP) and Data Center TCP (DCTCP). We also show that TCP PLATO can be implemented using commodity switches with Weighted Random Early Detection (WRED) function.

LOSS MONITORING OF STAR TOPOLOGY SENSOR NETWORK BASED ON SCHEDULING ALGORITHM FOR ASSESSING STRUCTURAL HEALTH INFORMATION

Sensor network is the new invention for assessing civil building structural health information. The new challenge to sensor network: large volume of received data, analyzing result at the computing section, patient coverage area, accuracy and reliability of the system, real time response, optimization development. To cover the entire patient region, sensor topology network is as a key characteristic of Sensor Network (SN). In this article, we investigated the loss of the star topology base sensor network and also find efficient queueing method based on Constant Bit Rate (CBR) traffic and DropTail (DT), Stochastic Fair Queueing (SFQ), Random Early Discard (RED) queuing mechanism.

ANLRED: A Robust AQM Mechanism for Congestion Avoidance

Internet over the past few years has undergone dramatic changes in terms of scale, penetration rate and the diversity of applications. The demand for continuous network connectivity is profilerating. Moreover, it has been observed that the usage of real time applications like Voice over IP (VoIP) and Live Streaming has increased drastically. Passive Queue Management (PQM) mechanisms in the routers do not react to congestion till the buffers overflow. This has two severe consequences: (i) large queueing delays that hurt the performance of real time traffic because such traffic is sensitive to delay and (ii) a large number of consecutive packet drops which affect the network stability. Recently, there has been a lot of interest in the deployment of Active Queue Management (AQM) mechanisms in modern Internet routers to overcome drawbacks of buffer overflow. Although Random Early Detection (RED) is the most widely studied AQM mechanism, it is highly sensitive to parameter settings. In this paper, we propose a robust AQM mechanism named Adaptive Nonlinear RED (ANLRED) which minimizes the parameter sensitivity of RED. Results obtained using ns-2 in a wide variety of Internet scenarios show that ANLRED improves the overall performance of the network in terms of link utilization while maintaining an acceptable mean queue length and minimal packet drop rate. Moreover, ANLRED implementation requires minimum algorithmic changes and hence, is easy to deploy.

Reducing Packet loss in Active Queue Management

Random Early Detection (RED) is a network congestion control algorithm which detects incipient congestion according to current length of average queue. It detects congestion only after a packet has been dropped. In the recent, high speed networks, it is important to have some mechanisms that keep throughput high and average queue sizes low without packet loss and it would be undesirable to have large queue because it would significantly increase the average delay in the network.

Design of proportional-derivative-type state feedback controllers for congestion control of transmission control protocol networks

A new proportional-derivative-type state feedback controller is proposed for congestion control of transmission control protocol (TCP) networks. An analytical TCP model is adopted. In the proposed control scheme, it is possible to efficiently control the TCP traffic using only the queue length at the router without the need to know the TCP window size which is not available locally. The results are presented in terms of delay-dependent linear matrix inequality. The proposed method is verified by simulation examples using NS software, and the effectiveness and superiority of our method over other control schemes, such as the proportional-integral, random early detection and generalised minimum variancemethods, are also shown.

Network Video Transmission Quality Assurance Algorithm Based on Congestion Control

Time delay and packet loss rate during the network video transmission are the two important factors in network video transmission quality. The purpose of congestion control is to reduce the bad impact of network video transmission quality caused by time delay and packet loss rate. This paper proposed a network video transmission quality assurance algorithm based on unbalanced multiple descriptions coding scheme. The new algorithm predicts the congestion state of network by means of Markov model based on available bandwidth detection, changes video transmission path on the basis of the prediction. Experiments show that compared with RED (Random Early Detection) algorithm, the algorithm is much more effective to estimate network congestionreduce video packet loss rate and time delay, thus the network video transmission quality can be ensured more effectively.

Performance Improvement by Dynamic Queue Management in Mobile Ad hoc Network

Mobile Ad hoc network [MANET] consists of mobile nodes without any fixed infrastructure, communicating through wireless medium. In MANET, Congestion occurs in any intermediate nodes when data packets travel from source to destination and they incur higher packet loss rate and long delay, which cause the degradations in performance of a network. Congestion can be controlled by Active Queue Management [AQM] like Random Early Detection [RED]. But RED is very sensitive to traffic load and parameter configuration, and its average queue length varies greatly with the congestion degree and parameter settings. To resolve the above problems, this paper proposes Performance Improved RED (named PIRED) by using auto-tuning RED Queue thresholds parameters and packet dropping probability. An adaptive mechanism is designed to adjust the packet dropping probability and RED Queue thresholds parameters for stable average queue length. The key idea is that when the traffic load changes and therefore the queue length deviates from the target value, the algorithm adjusted RED Queue thresholds parameters and packet dropping probability to improve the network performance over the conventional RED.

BIFURCATION CONTROL OF A CONGESTION CONTROL MODEL VIA STATE FEEDBACK

This paper proposes to use a state feedback method to control the Hopf bifurcation for a novel congestion control model, i.e. the exponential random early detection (RED) algorithm with a single link and a single source. The gain parameter of the congestion control model is chosen as the bifurcation parameter. The analysis shows that in the absence of the state feedback controller, the model loses stability via the Hopf bifurcation early, and can maintain a stationary sending rate only in a certain domain of the gain parameter. When applying the state feedback controller to the model, the onset of the undesirable Hopf bifurcation is postponed. Thus, the stability domain is extended, and the model possesses a stable sending rate in a larger parameter range. Furthermore, explicit formulae to determine the properties of the Hopf bifurcation are obtained. Numerical simulations are given to justify the validity of the state feedback controller in bifurcation control.

Passive queue management algorithm based on synchronized queue

In order to mitigate the network congestion problem,a new passive queue management algorithm Drop Front n based on Synchronized Queue(DFSQ) was proposed by Drop Front.In this algorithm,the network queue length was deducted with synchronized queue,and drop packet probability and drop packet strategy were presented.Then,a simulation was conducted to research on the key influencing factors of queue length.The results show that,compared with Random Early Detection(RED) and Drop Tail algorithm,the performance of DFSQ is better.

RED-FT: A Scalable Random Early Detection Scheme with Flow Trust against DoS Attacks

In traditional Active Queue Management algorithms, e.g. RED, each flow, defined with the source and destination IP address of packets, fairly contends for the cache of bottleneck queues. However a malicious flow cannot be identified. And it enables potential network-layer attacks, e.g. the flooding Denial-of-Service (DoS) attack and the low-rate DoS attack. In this letter, we propose a new scheme using the flows trust values to defend against DoS attacks. Different from previous schemes, it employs the flow trust to safeguard legitimate flows. A router monitors network flows and calculates flows trust values, which are used for the relevant queue management. Malicious flows would be with lower trust values while legitimate flows would be with higher ones. Simulation results show that the scheme improves the throughput and delay in DoS attacking scenarios comparing with existing queue management algorithms. We consider the scheme is practical and effective to secure networks.

Performance Evaluation of Controlling High Bandwidth Flows by RED-PD

This paper proposed to investigate and evaluate the performance of one of the algorithm used to provide fair bandwidth allocation to the flows. First In First Out (FIFO) queuing is simple but does not protect responsive flows from unresponsive one, flows that are sending more than their fair share. One of FIFO queuing is Random Early Detection which it can effectively avoid congestion at routers, but it also cannot provide fair bandwidth for the flows. On the other hand, per-flow scheduling mechanisms provide max-min fairness but are more complex, it requires keeping state for all flows going through the router; it’s proved that high bandwidth flows at the time of congestion consume most of the bandwidth of the link, so this algorithm (RED-PD) is most candidates to provide fairness to the flows. Simulations with networks demonstrate that there are chances for RED-PD to enhance its work, by means of incorporating the test of unresponsive flows actively in response to changes in the packet drop rate.

Adaptive mechanism-based congestion control for networked systems

In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol–AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.