Conference Papers

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Author: search.filters.author.Shetty D, D.P.Has files: No

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    K-distinct strong minimum energy topology problem in wireless sensor networks
    (Springer Verlag, 2015) Panda, B.S.; Shetty D, D.P.; Pandey, A.
    Given a set of sensors, the strong minimum energy topology (SMET) problem is to assign transmit power to each sensor such that the resulting topology containing only bidirectional links is strongly connected and the total energy of all the nodes is minimized. The SMET problem is known to be NP-hard. Currently available sensors in the market support a finite set of transmission ranges. So we consider the k- Distinct-SMET problem, where only k transmission power levels are used. We prove that the k-Distinct-SMET problem is NP-complete for k ≥ 3. However, on the positive side, we show that the 2-Distinct- SMET problem can be solved in polynomial time. The energy cost of transmitting a bit is higher than the cost of computation, and hence it may be advantageous to organize the sensors into clusters and form a hierarchical structure. This motivated the study of k-Distinct-rStrong Minimum Energy Hierarchical Topology (k-Distinct-rSMEHT) problem: Given a sensor network consisting of n sensors, and integers k and r, assign transmit powers to all sensors out of the k distinct power levels such that (i) the graph induced using only the bi-directional links is connected, (ii) at most r sensors are connected to two or more sensors by a bidirectional link and (iii) the sum of the transmit powers of all the sensors is minimum. We Propose a(formula presented.) approximation algorithm for the k-Distinct-rSMEHT problem for any fixed r and arbitrary k. © Springer International Publishing Switzerland 2015.
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    Algorithms for minimizing the receiver interference in a wireless sensor network
    (Institute of Electrical and Electronics Engineers Inc., 2016) Shetty D, D.P.; Lakshmi, M.P.
    Limiting Interference between the nodes in a Wireless Sensor Network (WSN) is of considerable importance for energy-efficiency of the network. Minimizing the interference in a WSN minimizes the overall energy consumption of the network by reducing the number of conflicting transmissions. We consider Receiver interference minimization problem. Two types of interference are defined in a WSN, namely Sender interference and Receiver interference. In this paper we consider the Receiver interference problem, where the objective is to minimize the maximum Receiver interference. The problem of minimizing the maximum Receiver interference is proved to be NP-hard. In this paper we propose two algorithms named MinMax-RIP and a modified version of the same to minimize the maximum Receiver interference in a WSN. We evaluate the performance of our algorithms through simulation. We then consider the interference minimization problem in a broadcast network. We propose MinMax-BRIP algorithm for optimal range assignment which gives minimum total Receiver interference for connectivity predicate Broadcast. © 2016 IEEE.
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    Total Power Minimization Using Dual Power Assignment in Wireless Sensor Networks
    (Institute of Electrical and Electronics Engineers Inc., 2016) Sisodiya, N.; Shetty D, D.P.
    To minimize the energy consumption in a wireless sensor network (WSN) is very important task as the sensors are generally very small and have a power battery attached to it which cannot have very large power capacity. In a wireless sensor network any sensor node must be able to retrieve information from any other sensor node in the network, so the connectivity of the network is also very important concern. The range assignment problem in WSN is to assign transmission power levels to the nodes of a WSN such that some constraints like connectivity is satisfied. In practice it is usually impossible to assign arbitrary power levels to the sensor nodes in a wireless sensor network. Most sensors available in the market operate with discrete power levels. So in this paper we consider the sensor nodes with only two possible power levels assigned to them. Our aim is to minimize the total power consumption while maintaining the strong connectivity between the sensor nodes in the network. We present a nearly optimal heuristic algorithm and also the experimental results. Our SCDPA algorithm gives an average approximation of 1.51. We also present a heuristic algorithm to minimize total power using 3 power levels. © 2015 IEEE.