Swarup Kumar Mitra

An Optimized Lifetime Enhancement scheme for data gathering in wireless sensor networks

Design of energy efficient schemes for data gathering is an important concern for lifetime enhancement of wireless sensor networks. Variation in the distances of nodes from the Base Station and differences in inter-nodal distances are primary factors causing unequal energy dissipation among the nodes. Thus energy difference between the various nodes increases with time resulting in degraded network performance. The LEACH and PEGASIS schemes which provided elegant solutions to the problem suffer basic drawbacks due to randomization of cluster heads and greedy chain formation respectively. In this paper, we propose an Optimized Lifetime Enhancement (OLE) Scheme which shows enhanced performance over these schemes. OLE increases the network performance by ensuring a sub-optimal energy dissipation of the individual nodes despite their random deployment. It employs modern heuristics like particle swarm optimization instead of the greedy algorithm as in PEGASIS to construct energy efficient routing paths. Extensive simulations validate the improved performance of OLE.

An efficient hybrid data-gathering scheme in wireless sensor networks

For time-sensitive applications requiring frequent data gathering from a remote wireless sensor network, it is a challenging task to design an efficient routing scheme that can minimize delay and also offer good performance in energy efficiency and network lifetime. In this paper, we propose a new data gathering scheme which is a combination of clustering and shortest hop pairing of the sensor nodes. The cluster heads and the super leader are rotated every round for ensuring an evenly distributed energy consumption among all the nodes. We have implemented the proposed scheme in nesC and performed simulations in TOSSIM. Successful packet transmission rates have also been studied using the interference-model. Compared with the existing popular schemes such as PEGASIS, BINARY, LBEERA and SHORT, our scheme offers the best “energy × delay” performance and has the capability to achieve a very good balance among different performance metrics.

A robust mobile anchor–based localisation technique for wireless sensor network using smart antenna

This paper introduces a range–based localisation technique namely row matching algorithm (RMA) for wireless sensor network (WSN). In WSN, all stationary targets are configured to broadcast beacon messages periodically using their IDs towards a mobile anchor node equipped with global positioning system (GPS) receiver and smart antennas. The anchor frequently selects a cluster of targets for localisation having received signal strength (RSS) above a pre–defined threshold value. It estimates precise angle of arrival (AOA) and distance using well–known total least squares–estimation of signal parameters via rotational invariance techniques (TLS–ESPRIT) algorithm and path loss model, respectively. Thus, any target can estimate its location taking only two successive beacon messages containing distance and angle information from two different anchor positions and toggles to sleep mode for energy saving. The simulation results validate the robustness of this scheme both in accuracy and energy efficiency without increasing hardware and computational complexity to the targets.

Data gathering in wireless sensor network using realistic power control

Wireless Sensors Network consists of irreplaceable nodes after being deployed with limited energy resources. The data gathering protocol needs more realistic power consumptions model to estimate the network performance for various pervasive and ubiquitous applications. In this paper we have implemented the chain based and shortest hop data gathering and routing protocols that demonstrate how realistic power model assumptions can affect the system performance in comparison with the results obtained by considering the first order radio model. We formulated a data sheet which gives details of the energy required to transmit data packets on distance basis incorporating Log Normal Shadowing Model for obtaining the received signal strength. We also justified the reason to eradicate the power levels which are unnecessary and gives rise to complications. Moreover we have observed a comparative study of the proposed method in TinyOS platform while running the simulation in TOSSIM for realistic comparison of our model.

An Optimized Reduced Energy Consumption (OREC) Algorithm for Routing in Wireless Sensor Networks

Wireless Sensor Network (WSN) is constrained by limited available energy for data communication. Utilization of energy and enhancing network lifetime is a challenging task for the next generation wireless sensor network. In this paper we have designed an algorithm that performs the routing with low energy consumption. We have experimentally optimized the number of clusters that should be formed for escalating the lifetime of the network with provisions made to include equal number of nodes in each cluster. Our analysis and simulation results show that with realistic radio model we have achieved better load balance than several existing protocols, like LBEERA, HDS, SHORT, PEGASIS, LEACH and BINARY. A suitable node deployment strategy was adopted for ensuring wireless connectivity between each node. Moreover we have made simulations in NS-2 which supports our propositions to a greater extend.

Realization of PSO-Based Adaptive Beamforming Algorithm for Smart Antennas

A novel beamforming technique based on Particle Swarm Optimization (PSO) algorithm and its subsequent implementation on Xilinx Virtex4 Field-Programmable Gate Arrays (FPGA) board is described. A prescribed limit in Side-Lobes Level (SLL), Beamwidth between the First Nulls (FNBW) and depth of the nulls steered at various interfering directions are considered as beam controlling attributes in this work. All these criteria are included first in two dissimilar reference templates using Dolph–Chebyshev polynomial and Cosine function. Stochastic process is used next to optimize the physical and electrical parameters of a linear antenna array satisfactorily complying with the desired pattern features altogether. System design using Finite State Machine with Datapath (FSMD) modeling and suitable COordinate Rotation DIgital Computer (CORDIC) functional blocks are prepared for its final realization on a dedicated hardware. Its performance is then evaluated with several fixed-point simulations in terms of beamforming accuracy and computational overheads under both Additive White Gaussian Noise (AWGN) and Rayleigh fading channel conditions. These results corroborate its competency comparable to the existing beamforming methods of smart antennas.