Work place: Manav Rachna International University, Faculty of Engineering and Technology, Faridabad, 121004, India
E-mail: kaebeh@gmail.com
Website:
Research Interests: Computer systems and computational processes, Computer Architecture and Organization, Data Structures and Algorithms
Biography
Kaebeh Yaeghoobi S.B. received her B.S.C. in Information Technology in 2009, and her M.C.S. degree in Computer Science & Engineering from Hamdard University, New Delhi, India in 2011. Currently, she is a PhD scholar of Department of Computer Science and Engineering at Manav Rachna International University, Faridabad, India. Her research interests include algorithms and wireless sensor network.
By Kaebeh Yaeghoobi S.B. M.K.Soni S.S. Tyagi
DOI: https://doi.org/10.5815/ijcnis.2016.01.02, Pub. Date: 8 Jan. 2016
Wireless Sensor Networks are emerging technologies that are diverse on energy consumption from different aspects. In the task mode, energy consumption of sensor nodes is categorized in, data packet transmitting, data processing and idle mode. Fundamentally, higher power is required and utilized at the time of data trans-receive as comparing to idle mode. However, power consumption of sensor in idle mode is necessarily important. To conserve energy, the network must provide quality of service sleep schedule, and use a mechanism to turn off the radio receiver periodically in coordinating method. Moreover, through dynamically round task management of sensors, significant energy saving can be achieved. Based on tasks and sleep schedules, nodes can form their clusters. It is necessary for real-time wireless applications to cogitate data transmit at the actual and response time based on the queries or tasks. This paper proposes Dynamic Immediate Data Report (DIDR) for real-time communication to schedule sleep mode of sensors in the network. Furthermore, to minimize the network energy consumption, Dynamic Schedule Data Report (DSDR) method is proposed. This method shows its efficiency by reducing the active time of nodes in the network. The performance analysis of the proposed works, illustrate effectively more energy efficiency as compared to existing methods.
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