Informatics Publishing Limited

G. Maria Priscilla ¹, Antony Selvadoss Thanamani ²

Affiliations
1 Dept of Comp. Sci, SNR Sons College, Coimbatore, IN
2 NGM College, Pollachi, IN

Abstract

Internet the growing technology with the emergence of new applications and diverse quality of service requirements has become increasingly important. Congestion the major problem in internet requires some management in responsive and unresponsive flows. Active Queue Management (AQM) schemes are a class of queue management algorithms which are designed to overcome the drawbacks in the classical drop-tail queues and for congestion avoidance and congestion prevention. These AQM schemes are classified based on the decisions taken while dropping the packets. The types of marking or dropping the packets to improve the throughput , performance , fairness in bursty traffics and the packet loss ratio are involved. The reactive congestion control active queue management schemes are discussed in this paper.

Keywords

Congestion Control, AQM, RED, Queue Management.

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V. Savitha ¹, G. Maria Priscilla ¹

Affiliations
1 SNR Sons College, IN

Abstract

Active Queue Management (AQM) is the technique of signaling Transmission Control Protocol (TCP) sources from middle routers with the focus of managing queue utilization and delay. In wireless networks, where the accessible link bandwidth is unreliable with time, it is significant to examine the robustness of the congestion control algorithms against the capacity of disturbance. The main purpose of an RQM mechanism is to offer low delay and low loss service in best-effort service networks. In this work a modified RQM algorithm based on feedback compensation technique is proposed. The algorithm is called Modified Proportional Integral based series compensation, and Position feedback compensation (Modified PIP). The performance of Modified RQM with Feedback (MFPIP) is compared to existing RQM based on the End-to-End delay and bandwidth utilization. From the experiments and analysis it is found that the Modified RQM with Feedback (MFPIP) is more responsive to and robust under time-varying network conditions than existing RQM.

Keywords

Active Queue Management (AQM), Robust Queue Management (RQM), Modified Proportional Integral based Series Compensation and Position Feedback Compensation (Modified PIP).

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J. Jeyaboopathiraja ¹, G. Maria Priscilla ¹

Affiliations
1 Department of Computer Science, Sri Ramakrishna College of Arts and Science, IN

Abstract

Crime Prediction is an effort of determining future crime with the intention of diminishing them. Post-analysis of the data from past events, Crime prediction forecasts the future crime on the basis of time and location. In recent decades, the rapidly increasing series of criminal cases make accurate future crime prediction a difficult task. For crime trend prediction, a Prophet Model and Keras stateful LSTM has utilized in a recent study, in which missing value imputation and feature selection has carried out by simple computation as regards the enhancement of dataset quality and crime prediction. Though this method is simple to be applied, yet it has the inadequacy to prove its prediction accuracy. Because the sequence form of the input existed in LSTM maximizes the complexity while estimating the impact of each variable. For confronting these challenges, this study proposes a novel approach explicitly for crime trends prediction. In this model, the missing values have replaced by first Predictive Mean Matching method in the dataset. In addition, an improved bat optimization (IBAT) takes place to extract highly subjective features from the dataset, concerning the performance enhancement of trends forecasting and reduction of time computation. Ultimately, the convolution neural network algorithm has further involved predicting the crimes trends in order to reduce future crime.

Keywords

Crime Trends Forecasting, Bat Optimization, Analyzing Data And Convolution Neural Network.

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