Qualification: 
M.Tech, B-Tech
simisurendran@am.amrita.edu

Simi S. currently serves as an Assistant Professor (Sr.Gr.) at the Department of Computer Science Engineering at Amrita School of Engineering, Amritapuri. She pursued her M. Tech in Wireless Networks and Applications, Amrita Vishwa Vidyapeetham. She has 10 years of academic experience. She has published 3 journal paper and 15 conference papers.

Awards/Achievements

  • 'Best Poster Award' in Sensys 13, Italy

Publications

Publication Type: Conference Paper

Year of Publication Title

2016

Balaji Hariharan, P. Venkat Rangan, Simi Surendran, Rekha, P., Arya Devi R. D., and Dr. Maneesha V. Ramesh, “Delay and energy optimization in multilevel balanced WSNs for landslide monitoring”, in 2016 IEEE Global Humanitarian Technology Conference (GHTC), 2016.[Abstract]


In most of the real world wireless sensor network deployments, the energy utilization is a critical factor as the nodes are battery powered. In most of the real-world deployments it is observed that the sensing subsystem consumes higher power. In order to extend the lifetime of such systems it is required to reduce the sensing energy than communication energy. We have deployed a system for monitoring Landslides in India consists of 150 geo-physical sensors and used solar panels to power these sensor nodes. The decision making in favor of Landslide occurrence is based on the maximum values obtained from the high priority sensors. As this maximum value is not frequently changing in the deployment, locating the sensor node with maximum value allows us to switch off the other sensors for a predetermined period of time. This work proposes an optimal balanced network topology for delay minimization by parallelizing data aggregation operation in each sub-network. The sensor node switch off schemes on the top of delay minimized topology enables the optimal utilization of the available solar power. The analysis of these mechanisms shows that, more number of nodes can be powered with the available source of energy and can increase the network life time.

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PDF iconDelay-and-energy-optimization-in-multilevel-balanced-WSNs-for-landslide-monitoring.pdf

2014

J. Shanavas and Simi Surendran, “An Energy Efficient and Reliable Topology Control Scheme with Connectivity Learning in Wireless Networks”, in International Conference on Emerging Research in Computing, Information, Communication and Applications 2014, 2014.

2014

J. Shanavas and Simi Surendran, “An energy efficient topology control scheme with connectivity learning in wireless networks”, in Proceedings of the 2014 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2014, 2014.[Abstract]


In wireless networks, due to the variation in environmental and link characteristics, the network topology will change over time. The foremost feature that affects the connectivity and lifetime of a network is the distributed topology control. Nodes in a wireless network are resource constrained. Topology control algorithms should be helpful to improve the energy utilization, reduce interference between nodes and extend lifetime of the networks operating on battery power. This paper proposes a topology control and maintenance scheme while learning the network link characteristics. The system learns the varying network link characteristics using reinforcement learning technique and gives an optimal choice of paths to be followed for packet forwarding. The algorithm calculates the number of neighbors a node can have, which helps to reduce power consumption and interference effects. The algorithm also ensures strong connectivity in the network so that reachability between any two nodes in the network is guaranteed. Analysis and simulation results illustrate the correctness and effectiveness of our proposed algorithm.

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2013

Dr. Maneesha V. Ramesh, Rekha, P., P., D., and Simi Surendran, “An Adaptive Energy Management Scheme for Real-time Landslide Detection”, in Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems, New York, NY, USA, 2013.[Abstract]


Sensor nodes in wireless sensor network are powered by batteries and thus the utilization of effective energy management techniques becomes one of the most important challenges in realistic design of WSN. This paper deals with an optimal energy management scheme in Landslide detection system deployed in Kerala. Based on the meteorological, hydrological and soil parameters, sensors will be dynamically prioritized, scheduled and selects appropriate sensors for event handling. The results of this research work shows that the life time of the network has been improved due to the implementation of this adaptive energy management scheme.

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PDF iconAn-Adaptive-Energy-Management-Scheme-for-Real-time-Landslide-Detection.pdf

Publication Type: Conference Proceedings

Year of Publication Title

2015

Simi Surendran and Varghese, S. Ann, “Enhance QoS by Learning Data flow rates in Wireless Networks Using Hierarchical Docition”, 4th International Conference on Eco-friendly Computing and Communication Systems, ICECCS 2015, Procedia Computer Science, vol. 70. Elsevier, pp. 708 - 714, 2015.[Abstract]


Wireless Wireless network finds application in military environments, emergency, rescue operations and medical monitoring due to its self-configuring nature. As the availability of resources such as processing power, buffer capacity and energy are limited in wireless networks; it is required to devise efficient algorithms for packet forwarding. Due to the dynamic nature of the wireless environment, the traditional packet forwarding strategies cannot guarantee good network performance every time. This paper proposes a method for learning data flow rates in wireless network to improve quality of service in the network. Each node in the network learns the environment using reinforcement learning approach and selects appropriate neighbours for packet forwarding. In order to improve the learning capacity of nodes, the hierarchical docition technique is employed. Docition applied to each layer of network, which selects a set of special nodes which has more information about the environment and share this information with less informative nodes. The algorithm is tested in a geographical routing protocol and the results indicate improved network performance.

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2015

Simi Surendran and Vijayan, S., “Distributed Computation of Connected Dominating Set for Multi-Hop Wireless Networks”, Procedia Computer Science, Seventh International Symposium on Applications of Ad hoc and Sensor Networks, vol. 63. Elsevier, Berlin, pp. 482 - 487, 2015.[Abstract]


In large wireless multi-hop networks, routing is a main issue as they include many nodes that span over relatively a large area. In such a scenario, finding smallest set of dominant nodes for forwarding packets would be a good approach for better communication. Connected dominating set (CDS) computation is one of the method to find important nodes in the network. As CDS computation is an NP problem, several approximation algorithms are available but these algorithms have high message complexity. This paper discusses the design and implementation of a distributed algorithm to compute connected dominating sets in a wireless network with the help of network spectral properties. Based on local neighborhood, each node in the network finds its ego centric network. To identify dominant nodes, it uses bridge centrality value of ego centric network. A distributed algorithm is proposed to find nodes to connect dominant nodes which approximates CDS. The algorithm has been applied on networks with different network sizes and varying edge probability distributions. The algorithm outputs 40% important nodes in the network to form back haul communication links with an approximation ratio ≤ 0.04 * ∂ + 1, where ∂ is the maximum node degree. The results confirm that the algorithm contributes to a better performance with reduced message complexity.

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