alexa Mobile Sink based Data Gathering and Forwarding in WSN
ISSN ONLINE(2320-9801) PRINT (2320-9798)

International Journal of Innovative Research in Computer and Communication Engineering
Open Access

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Special Issue Article

Mobile Sink based Data Gathering and Forwarding in WSN

C. Kanimozhi1, Prof. M.Mohamed Musthafa, M.Tech., (Ph.D).,2
  1. II ME (CSE), Dept. of CSE, Al-Ameen Engineering College, Erode, Tamilnadu, India
  2. Head of the Department, Dept. of CSE, Al-Ameen Engineering College, Erode, Tamilnadu, India
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Abstract

Environment monitoring is performed using the sensor devices. Wireless Sensor Network (WSN) is constructed with a set of data collection units. Base station, sinks and sensor devices are used in the WSN. Power resources, bandwidth and storages are the limitations of the sensor devices. Sink nodes are used to collect data from a group of sensor devices. Many to one traffic pattern based data collection model increases the transmission load to a set of nodes. The traffic pattern based network load problem is referred as hotspot problem. Energy efficient communication protocols and multi-sink systems are used to handle hotspot problems. Static and mobility based sink placement schemes are used to handle data collection process. Mobile sinks are used to increase the network lifetime with delay constraints. Random mobility and controlled mobility models are used in the mobile sinks. In random mobility the sinks are moved randomly within the network. The sinks are deterministically moved across the network is referred as controlled mobility. The network lifetime is managed with the number of nodes and delay values. The Delay bounded Sink Mobility problem is initiated under sensor node allocation to sinks. A polynomial-time optimal algorithm is used for the origin problem. Extended Sink Scheduling Data Routing algorithm is used to schedule sink nodes. The mobile sink scheduling scheme is enhanced to support large size networks. Distributed scheduling algorithm is applied to schedule nodes with high scalability. The scheduling scheme is tuned for multiple sink based environment. Delay and energy parameters are integrated in the sink scheduling process. The decentralized scheduling mechanism achieves high data collection efficiency with low latency values. Region based sink movement is used to manage data collection risk levels.

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