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1 [CT119]

[CT119]

[01019] Particle Swarm Optimization Based Reliable Control Algorithm for Wireless Networks

Session Date & Time : 3C (Aug.23, 13:20-15:00)
Type : Contributed Talk
Abstract : This paper deals with the fault-tolerant control problem for Wireless networks based on the particle swarm optimization method. To cope the stability and fault-tolerants simultaneously, a novel fault-tolerant control algorithm is developed. The required conditions of the addressed system are developed with the aid of Lyapunov stability theory. Precisely, the particle swarm optimization algorithm is implemented to optimize the fuzzy controller. Finally, simulation results are provided to demonstrate the effectiveness of the obtained results.
Classification : 68M07, 68M12, 68M15
Author(s) :
- Ponnarasi Loganathan (Bharathiar University)
- Pankajavalli PB (Bharathiar University)

[00985] A Routing Protocol for Enhancing the QoS in Vehicular Ad hoc Networks

Session Date & Time : 3C (Aug.23, 13:20-15:00)
Type : Industrial Contributed Talk
Abstract : The vehicle ad hoc network (VANET) provides various services for safe driving to the driver. The main problem with VANET is routing, since it has much more variation in network topology and node density than conventional mobile ad hoc networks (MANET). In this paper, we propose a QoS routing protocol based on link state information for VANET. The proposed protocol provides an optimal path using link quality and link stability.
Classification : 68M10, 68M18, 68M15
Author(s) :
- Jin-Woo Kim (Duksung Women’s University)
- Jaehee Kim (Duksung Women’s University)

[01240] Machine Learning based Optimization Algorithm for Stress Prediction

Session Date & Time : 3C (Aug.23, 13:20-15:00)
Type : Contributed Talk
Abstract : In this work, an efficient optimization algorithm is developed to predict the stress of a person. The algorithm uses sensor data which are extracted from person’s physiological parameters. The proposed work uses various techniques for smoothing the data and to identify the features from the extracted data. Different experiments are done by considering various output metrics. Based on the comparison with the existing classification algorithms, the proposed algorithm identifies the stress prediction with high accuracy.
Classification : 68M18, 68M20, 65-04
Author(s) :
- Pankajavalli Palanisamy Balamani (Bharathiar University)

[01695] Power Management in Wireless Sensor Network Using Queueing with threshold policy

Session Date & Time : 3C (Aug.23, 13:20-15:00)
Type : Industrial Contributed Talk
Abstract : Wireless sensor networks (WSNs) play an important role in monitoring unfriendly physical environments. Each node in the WSN is connected to additional sensors, ranging in number from a few to hundreds or thousands. It also consists of a processor, memory, wireless antenna and battery. The micro-sensor nodes are battery-operated which consumes limited battery power. To optimize power consumption, sensor networks use Dynamic Power Management (DPM) technology, which turns devices off when not in use and wakes them up when needed. DPM is a useful tool for cutting system power usage without noticeably impairing the system's performance. In this work, we investigate the power saving mechanism of DPM using multiple vacation queueing policies with threshold and present the transient results. The proposed system consists of a busy state (transmit state), wake-up state, shutdown state and inactive state. In this model, the server switches to a shutdown state for a random duration of time after serving all the events (data packets) in the busy state. Events that arrive during the shutdown period cannot be served until the system size reaches the predetermined threshold value of k and further it requires start-up time and a change of state to resume service. At the end of the shutdown period, if the system size is less than k, then the server begins the inactive period; otherwise, the server switches to the wake-up state. The significance of the investigated system is as follows. The steady state probabilities of the system receive the majority of attention in the literature when discussing analytical conclusions for operating characteristics of various types of queueing systems. In practice, however, transient analysis of the system is often desired. Such a situation occurs when a system is being investigated right after it has been repaired and restarted, or it can happen while a new control policy is being implemented at the same time. According to the above-mentioned observation, the main objective of this work is to find an explicit expression for the queue-size distribution of the investigated model in the transient environment. Also, to determine the sensor node's least power consumption while considering each different data arrival rate, a threshold k has been developed. The effectiveness of this result is experimented by setting different threshold values. Furthermore, performance indices such as mean, variance and the probability that the server is in various stages of power management modes is computed.
Classification : 68M20, 60K25, 60K20
Author(s) :
- SUDHESH Ramupillai (BIT Campus, Anna University, Tiruchirappalli)

[00744] On the Burgers-type equations used in soft solid acoustics

Session Date & Time : 3C (Aug.23, 13:20-15:00)
Type : Contributed Talk
Abstract : A strain-rate model of soft viscoelastic solid is presented. The constitutive law accounts for finite strain, incompressibility, material frame-indifference, nonlinear elasticity, and viscous dissipation. Shear waves are governed by a nonlinear viscous wave equation, of which a one-way Burgers-type approximate equation is derived. Analysis of the travelling wave solutions shows that the two equations produce distinct solutions, unless amplitudes are infinitesimal. In the inviscid case, links with simple wave theory are established.
Classification : 74D10, 74J30, 74H10
Author(s) :
- Harold Berjamin (School of Mathematical and Statistical Sciences, University of Galway, University Road, Galway, Republic of Ireland)