Integrated Random Early Detection for Congestion Control at the Router Buffer

This paper proposed an Integrated Random Early Detection(IRED)method that aims to resolve the problems of the queue-based AQM and loadbased AQM and gain the benefits of both using indicators from both types.The arrival factor(e.g.,arrival rate,queue and capacity)and the departure factors are used to estimate the congestion through two integrated indicators.The utilized indicators are mathematically calculated and integrated to gain unified and coherent congestion indicators.Besides,IRED is built based on a new dropping calculation approach that fits the utilized congestion indicators while maintaining the intended buffer management criteria,avoiding global synchronization and enhancing the performance.The results showed that IRED,compared to RED,BLUE,ERED,FLRED,EnRED and DcRED,decreased packet delay and loss under various network status.Specifically,the results showed that in heavy and moderate traffic,the proposed IRED method outperformed the state-of-the-art methods in loss and delay by 18% and 10.6%,respectively.

User Station Security Protection Method Based on Random Domain Name Detection and Active Defense

The power monitoring system is the most important production management system in the power industry. As an important part of the power monitoring system, the user station that lacks grid binding will become an important target of network attacks. In order to perceive the network attack events on the user station side in time, a method combining real-time detection and active defense of random domain names on the user station side was proposed. Capsule network (CapsNet) combined with long short-term memory network (LSTM) was used to classify the domain names extracted from the traffic data. When a random domain name is detected, it sent instructions to routers and switched to update their security policies through the remote terminal protocol (Telnet), or shut down the service interfaces of routers and switched to block network attacks. The experimental results showed that the use of CapsNet combined with LSTM classification algorithm can achieve 99.16% accuracy and 98% recall rate in random domain name detection. Through the Telnet protocol, routers and switches can be linked to make active defense without interrupting services.

A FUZZY-LOGIC CONTROL ALGORITHM FOR ACTIVE QUEUE MANAGEMENT IN IP NETWORKS

Active Queue Management (AQM) is an active research area in the Internet community. Random Early Detection (RED) is a typical AQM algorithm, but it is known that it is difficult to configure its parameters and its average queue length is closely related to the load level. This paper proposes an effective fuzzy congestion control algorithm based on fuzzy logic which uses the pre- dominance of fuzzy logic to deal with uncertain events. The main advantage of this new congestion control algorithm is that it discards the packet dropping mechanism of RED, and calculates packet loss according to a preconfigured fuzzy logic by using the queue length and the buffer usage ratio. Theo- retical analysis and Network Simulator (NS) simulation results show that the proposed algorithm achieves more throughput and more stable queue length than traditional schemes. It really improves a router's ability in network congestion control in IP network.

AN EFFECTIVE NETWORK CONGESTION CONTROL METHOD FOR MULTILAYER NETWORK

The congestion control problem in a single node network has been solved by the nonlinearfeedback control method,which has been proven to be effective and robust for different router’s queuesize.However,these control models are based on the single layer network architecture,and the sendersand receivers are directly connected by one pair of routers.With the network architecture being moreand more complex,it is a serious problem how to cooperate many routers working in the multilayernetwork simultaneously.In this paper,an effective Active Queue Management(AQM)scheme toguarantee the stability by the nonlinear control of imposing some restrictions on AQM parameter inmultilayer network is proposed.The nonlinear control can rely on some heuristics and network trafficcontrollers that appear to be highly correlated with the multilayer network status.The proposedmethod is based on the improved classical Random Early Detection(RED)differential equation and atheorem for network congestion control.The theorem proposed in the paper proved that the stability ofthe fluid model can effectively ensure the convergence of the average rate to its equilibrium pointthrough many routers in multilayer network.Moreover,when the network capacity is larger,theproposed scheme can still approach to the fullest extensibility of utilization and ensure the stability ofthe fluid model.The paper reveals the reasons of congestion control in multilayer network,provides atheorem for avoiding network congestion,and gives simulations to verify the results.

Intelligent Spectrum Detection Model Based on Compressed Sensing in Cognitive Radio Network

In view of the uncertainty of the status of primary users in cognitive networks and the fact that the random detection strategy cannot guarantee cognitive users to accurately find available channels,this paper proposes a joint random detection strategy using the idle cognitive users in cognitive wireless networks.After adding idle cognitive users for detection,the compressed sensing model is employed to describe the number of available channels obtained by the cognitive base station to derive the detection performance of the cognitive network at this time.Both theoretical analysis and simulation results show that using idle cognitive users can reduce service delay and improve the throughput of cognitive networks.After considering the time occupied by cognitive users to report detection information,the optimal participation number of idle cognitive users in joint detection is obtained through the optimization algorithm.

BIFURCATIONS AND CHAOS CONTROL IN TCP-RED SYSTEM

Objective Analyzing the nonlinear dynamics of the TCP-RED congestion control system is of great importance. This study will help investigate the loss of stability in Internet and design a proper method for controlling bifurcation and chaos in such system. Methods Based on bifurcation diagram, the effect of parameter on system performance is discussed. By using the state feedback and parameter variation strategy, a simple real time control method is proposed to modify the existing RED scheme. Results With our control method, the parametric sensitivity of RED mechanism is attenuated. Moreover, a sufficient condition on the robust stability of the system is also derived to adjust the parameters in TCP-RED system. Conclusion The proposed method has the advantages of simple implementation and unnecessary knowledge of the exact system.

Traffic Queuing Management in the Internet of Things: An Optimized RED Algorithm Based Approach

Congestion control is one of the main obstacles in cyberspace traffic.Overcrowding in internet traffic may cause several problems;such as high packet hold-up,high packet dropping,and low packet output.In the course of data transmission for various applications in the Internet of things,such problems are usually generated relative to the input.To tackle such problems,this paper presents an analytical model using an optimized Random Early Detection(RED)algorithm-based approach for internet traffic management.The validity of the proposed model is checked through extensive simulation-based experiments.An analysis is observed for different functions on internet traffic.Four performance metrics are taken into consideration,namely,the possibility of packet loss,throughput,mean queue length and mean queue delay.Three sets of experiments are observed with varying simulation results.The experiments are thoroughly analyzed and the best packet dropping operation with minimum packet loss is identified using the proposed model.

Non-Detection Probability of a Diffusing Target by a Stationary Searcher in a Large Region

We revisit one of the classical search problems in which a diffusing target encounters a stationary searcher. Under the condition that the searcher’s detection region is much smaller than the search region in which the target roams diffusively, we carry out an asymptotic analysis to derive the decay rate of the non-detection probability. We consider two different geometries of the search region: a disk and a square, respectively. We construct a unified asymptotic expression valid for both of these two cases. The unified asymptotic expression shows that the decay rate of the non-detection probability, to the leading order, is proportional to the diffusion constant, is inversely proportional to the search region, and is inversely proportional to the logarithm of the ratio of the search region to the searcher’s detection region. Furthermore, the second term in the unified asymptotic expansion indicates that the decay rate of the non-detection probability for a square region is slightly smaller than that for a disk region of the same area. We also demonstrate that the asymptotic results are in good agreement with numerical solutions.

Bayesian edge detector for SAR imagery using discontinuity-adaptive Markov random feld modeling

Synthetic aperture radar（SAR）image is severely affected by multiplicative speckle noise,which greatly complicates the edge detection.In this paper,by incorporating the discontinuityadaptive Markov random feld（DAMRF）and maximum a posteriori（MAP）estimation criterion into edge detection,a Bayesian edge detector for SAR imagery is accordingly developed.In the proposed detector,the DAMRF is used as the a priori distribution of the local mean reflectivity,and a maximum a posteriori estimation of it is thus obtained by maximizing the posteriori energy using gradient-descent method.Four normalized ratios constructed in different directions are computed,based on which two edge strength maps（ESMs）are formed.The fnal edge detection result is achieved by fusing the results of two thresholded ESMs.The experimental results with synthetic and real SAR images show that the proposed detector could effciently detect edges in SAR images,and achieve better performance than two popular detectors in terms of Pratt＇s fgure of merit and visual evaluation in most cases.