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Ȩ Ȩ > ¿¬±¸¹®Çå > ±¹³» ³í¹®Áö > Çѱ¹Á¤º¸°úÇÐȸ ³í¹®Áö > Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)

Á¤º¸°úÇÐȸ³í¹®Áö (Journal of KIISE)

Current Result Document :

ÇѱÛÁ¦¸ñ(Korean Title) ¹«¼± ¼¾¼­ ³×Æ®¿öÅ©¿¡¼­ÀÇ ºÐ»ê ÄÄÇ»Æà ¸ðµ¨
¿µ¹®Á¦¸ñ(English Title) Distributed Computing Models for Wireless Sensor Networks
ÀúÀÚ(Author) ¹ÚÃÑ¸í   ÀÌÃæ»ê   Á¶¿µÅ   Á¤Àιü   Chongmyung Park   Chungsan Lee   Youngtae Jo   Inbum  
¿ø¹®¼ö·Ïó(Citation) VOL 41 NO. 11 PP. 0958 ~ 0966 (2014. 11)
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(Korean Abstract)
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(English Abstract)
Wireless sensor networks offer a distributed processing environment. Many sensor
nodes are deployed in fields that have limited resources such as computing power, network bandwidth, and electric power. The sensor nodes construct their own networks automatically, and the collected data are sent to the sink node. In these traditional wireless sensor networks, network congestion due to packet flooding through the networks shortens the network life time. Clustering or in-network technologies help reduce packet flooding in the networks. Many studies have been focused on saving energy in the sensor nodes because the limited available power leads to an important problem of extending the operation of sensor networks as long as possible. However, we focus on the execution time because clustering and local distributed processing already contribute to saving energy by local decision-making. In this paper, we present a cooperative processing model based on the processing timeline. Our processing model includes validation of the processing, prediction of the total execution time, and determination of the optimal number of processing nodes for distributed processing in wireless sensor networks. The experiments demonstrate the accuracy of the proposed model, and a case study shows that our model can be used for the distributed application.
Å°¿öµå(Keyword) cooperative processing model   clustering   execution time   in-network processing   Çù·Â ó¸® ¸ðµ¨   Ŭ·¯½ºÅ͸µ   ½ÇÇà ½Ã°£   ³×Æ®¿öÅ© ³»ºÎ󸮠 
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