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Singh, Karandeep
- Implementing Modified Cluster Head Selection in Existing TEEN Routing Protocol
Abstract Views :171 |
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Authors
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1 Department of Computer Engineering, Punjabi University, Patiala, Punjab, IN
1 Department of Computer Engineering, Punjabi University, Patiala, Punjab, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 22 (2016), Pagination: 49-55Abstract
The study of various protocols in wireless sensor networks shows that energy is the key concern in WSN due to the limited irreplaceable power sources of sensor nodes. The main reason for that is large amount of energy used in data transmission. Various researches take place to improve the energy efficiency and lifetime of WSN by developing routing algorithms. In this paper, Modified cluster head selection implemented in existing TEEN routing protocol to enhance the energy efficiency of the existing protocol in wireless sensor networks. A variable value of threshold energy is used for the nodes to aggregate data and transmit it to further nodes, which leads to increase the residual energy of each node and hence the performance. We evaluated the results after implementing the modified cluster head selection in existing TEEN routing protocol and observed that it performs better than existing TEEN routing protocol.Keywords
Cluster Head Selection, TEEN, Residual Energy, Dead Nodes, ELF, Energy Efficiency, Lifetime.Full Text
- Big Data Study-Basics,Techniques and Tools
Abstract Views :148 |
PDF Views:5
Authors
Affiliations
1 Department of Computer Engineering, Punjabi University, Patiala, IN
1 Department of Computer Engineering, Punjabi University, Patiala, IN
Source
Research Cell: An International Journal of Engineering Sciences, Vol 22 (2016), Pagination: 795-800Abstract
A lot of technologies revolution are driving rapid increase in data generation and data gathering. This is why big data is today's buzzword in every science and engineering domain. Big Data is similar to small data but bigger in size. Big data is not being greater than certain number of petabytes or terabytes. This can be assumed technology expands over time and data set size which is assumed as Big Data will also increases. Data is increasing day by day exponentially so today data is increased beyond the storage capacity of traditional databases. To process and analyze such datasets which cannot be stored in traditional databases Big Data tool like Hadoop is used. This paper will discuss the introduction, characteristics and various tools used to process and analyze big data.Keywords
Big Data, Data Types, Volume, Velocity, Traditional Data, Sources, Hadoop, MapReduce, HDFS, Tools.Full Text