C. S. Kumar

QoS-aware fuzzy rule-based vertical handoff decision algorithm incorporating a new evaluation model for wireless heterogeneous networks

AbstractNext generation networks are envisioned to be heterogeneous in nature with an increase in demand towards ubiquitous services in wireless networks. As various networks have widely different characteristics, it is difficult to maintain the quality of service (QoS) after executing a handoff from one network to another network. Maintaining the QoS, based on applications, during the handoff in an heterogeneous networks needs an intelligent handoff decision mechanism. This article proposes a QoS-aware fuzzy rule-based vertical handoff mechanism that makes a multi-criteria-based decision, found to be effective for meeting the requirements of different applications in a heterogeneous networking environment. The QoS parameters considered are available bandwidth, end-to-end delay, jitter, and bit error rate. A new evaluation model is proposed using a non-birth–death Markov chain, in which the states correspond to the available networks. Simulation results show that compared to other vertical handoff algorithms, the proposed algorithm gives better performance for different traffic classes.

QoS aware fuzzy rule based vertical handoff decision algorithm for wireless heterogeneous networks

Increasing demands of ubiquitous services in wireless networks and evolution towards heterogeneous solutions has driven the necessity of developing efficient QoS aware vertical handoff (handoff between different networks) mechanisms. This paper proposes a QoS aware fuzzy rule based vertical handoff mechanism that makes a multi-criteria based decision, found to be effective for meeting the requirements of different applications. The QoS parameters considered are available bandwidth, end-to-end delay, jitter, and bit error rate (BER). A new evaluation model is proposed using a non birth-death Markov chain, in which the states correspond to the available networks. Simulation results show that compared to other vertical handoff algorithms, the proposed algorithm gives better performance for different traffic classes.

Energy and quality of service aware FUZZY-technique for order preference by similarity to ideal solution based vertical handover decision algorithm for heterogeneous wireless networks

Next generation networks will use multiple transport technologies that offer unrestricted user access to different service providers and support generalised mobility to allow consistent and ubiquitous service provisioning to users. Different networks have widely varying characteristics, which makes it difficult to maintain the requested quality of service (QoS) after executing handoff from one transport technology to another. Maintaining the QoS during handoff in heterogeneous networks needs an intelligent decision mechanism. Moreover, the developed algorithms should be energy aware as the devices involved rely on battery power. This study proposes a novel vertical handover decision mechanism namely FUZZY-technique for order preference by similarity to ideal solution (FUZZY-TOP), obtained by combining a fuzzy rule-based mechanism with the technique for order preference by similarity to ideal solution approach. Simulation results based on a generalised Markov chain show that compared with existing vertical handover decision algorithms, the proposed FUZZY-TOP decision algorithm performs better for different traffic classes.

Fault detection in a multistage gearbox by time synchronous averaging of the instantaneous angular speed

The paper deals with an instantaneous angular speed (IAS) based algorithm for fault detection in a multistage gearbox. Fast Fourier transform (FFT) is a well established technique for analysis of a stationary signal. However, the IAS signal from the multistage gearbox is a combination of periodic signal and structure borne noise. This structure borne noise makes the IAS signal non stationary. Hence, FFT is no longer suitable for this non stationary signal analysis. Therefore in this paper, the IAS signal is time synchronously averaged with respect to lay shaft speed and then followed by FFT reveals the gear mesh frequency and rotational frequencies which are synchronous with the gearbox’s rotating speed. Thus, the algorithm can accurately and reliably detect the fault in multistage gearbox using the IAS. The paper also investigated the behavior of IAS signal for three different gearboxes (healthy, one tooth and two teeth broken) under two different speeds and three different loading conditions.

A New Tracking Controller Design for Underwater Vehicles Using Quadratic Stabilization

This paper proposes a new tracking controller for autonomous underwater vehicles (AUVs) using the concept of simultaneous quadratic stabilization. The nonlinear underwater vehicle system is viewed as a set of locally linear time invariant systems obtained by linearizing the system equations on the reference trajectory about some discrete points. A single stabilizing controller is then designed for the set of systems so obtained. However, this controller requires the exact parameters of the system. Since the hydrodynamic parameters of AUVs are generally not known with sufficient accuracy, the proposed controller is used for the known part of the dynamics and an adaptation algorithm is used to estimate the unknown parameters online and compensate for the rest of the plant dynamics. The proposed controller can thus adaptively handle the complete nonlinear uncertain dynamics of the plant. Simulation results are presented and discussed for a typical AUV.

A Neural Network Online Controller for Autonomous Underwater Vehicle

Designing a control law for Autonomous Underwater Vehicle (AUV) has been a considerable challenge from classical and modern control view point. Neural Network based control is seen as an emerging technology for intelligent control of complex system. Here we consider an approach to model the controller for the AUV using Recurrent Neural Networks (RNN). RNN had been selected to model the system as it has very good capability to incorporate the dynamics of the system. The AUV dynamic equations had been modeled to obtain the data required for training the neural network. A controller has been developed which can learn change in the dynamics on the fly. Results have been shown for online learning controller. Back Propagation Algorithm had been used in upgrading the controller weights during online learning control techniques.

A joint parametric prediction model for wireless internet traffic using Hidden Markov Model

Addressing performance related issues of networks and ensuring better Quality of Service (QoS) for end-users calls for simple, tractable and realistic traffic models. The work reported here focuses on modelling the Wireless Internet traffic using realistic traffic traces collected over wireless networks and forecasting the end-to-end QoS parameters for the networks. A measurement framework is set-up to collect the QoS parameters and a traffic model is designed based on Hidden Markov Model considering joint distribution of End to End Delay (E2ED or d), Inter-Packet Delay Variation (IPDV) and Packet Size. States are mapped to the four traffic classes namely conversational, streaming, interactive, and background. The model is validated by forecasting QoS parameters and the results are shown to be within the tolerance limit.

Test-bed for Navigation and Control of a Thruster based AUV

A thruster controlled AUV is being developed for the Indian AUV project. All motions and control is carried out by a set of five thrusters for controlling positions in two attitudes and three linear directions. As a prototype and verification system for the above AUV, a test-bed to develop and validate the control schemes was found necessary and has been developed at IIT Kharagpur. This paper describes the design criteria of the test-bed and the methods used to develop control scheme for such class of underwater vehicles, which are wholly thruster controlled and can be implemented in this test-bed. The design and capabilities of such a test-bed has been considered for taking into account similar thruster actuated AUVs which may be used in conditions like low speed motion as well as high maneuverability, station keeping etc. Such vehicles are different from the hydroplane controlled vehicles which are more effective above a certain operational velocity. The test-bed proposed here is targeted to generate valuable experimental data for full thruster controlled underwater vehicles operating over a range of operational velocities including station keeping to cruising modes.

Web Based Simulation and Remote Triggered Laboratory for Robots

This paper describes a web based virtual laboratory developed to facilitate learning robot kinematics and control through simulation and online control of some well-known robots in real-time with vision feedback system. The web based self-learning content and tools can be used in engineering education for both graduates and research scholars. Using Java Server Pages (JSPs), WAMP and Python, we provide a standard and robust platform for client environment. The website primarily addresses the delivery of basic concepts in robot kinematics.

Amplitude Demodulation of Instantaneous Angular Speed for Fault Detection in Multistage Gearbox

Traditional fault detection processes in gearbox are mostly based on vibration signal analysis. However, many a times extraction of fault features by the vibration signal analysis becomes difficult as the signal carries structure-borne noise. Moreover, position of the vibration sensor affects the signal to noise ratio of the signal. The presence of a fault in a gearbox changes the rotating dynamics of the system which varies the speed of the output shaft. Therefore, aim of this paper is to analyse the varying speed of the output shaft for detection of fault in a multistage automobile gearbox. Here, the varying speed is measured as instantaneous angular speed (IAS). Besides carrying information related to the fault, this IAS signal carries less structure borne noise due to direct response of rotating dynamics. Furthermore, in presence of fault, this varying speed signal or IAS signal is frequency modulated signal. Besides frequency modulation, the IAS signal becomes amplitude modulated under the application of load. Demodulation is a well known technique in the area of signal processing, which extracts the modulating part from a signal. Hence, the amplitude demodulation technique has been applied to the IAS signal which reveals various important frequencies related to the gearbox. Thus the technique helps to detect the fault in a multistage automobile gearbox under different load conditions.