الفهرس 
AbstractOnly 14 pages are availabe for public view
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Abstract
Prolonged network lifetime is a major challenge in the wide-range deployment of Wireless Sensor Networks (WSNs) sensor nodes hare limited energy supplies. Spatially distributed WSN support applications ranging from monitor physical and environmental to battlefield surveillance and traffic control. The majority of these applications need sensors to have a long lifetime without human intervention and battery replacement. Consequently, energy conservation is one of the basic goals when designing WSNs. To maximize network lifetime, approaches like duty cycling, low power consumption profiles, and listening modes have been proposed. In this thesis, we explore the energy saving possibilities through embedded analysis patterns in the network. We propose a scheme to perform in-network analytics which increases the lifetime of the network and reduces the random flooding of the messages, thus improving the bandwidth of the entire network. The results obtained through simulations are carried on open source network simulator (CupCarbon) which is a popular simulator for the wireless network and is based on IEEE 802.15.4. The results obtained from the simulations where EEIAS operations altogether expand the system lifetime in comparison with the other schemes. The cause is on account of EEIAS operations mitigate the heavy traffic phenomenon and allow the sender sensor to precisely know when its planned recipient starts its Activate Duration (AD). Regarding the receiver, the sender in EEIAS can stay in an idle state until the recipient awakens, consequently saving power. But, in the Asynchronous Energy Saving (ASES) method, all the sender nodes should stay an active mode after Tidle (Idle time) of waiting for the gathering of the Wakeup Notification (WN) from its expected recipient, which may bring about the sender to expend a lot of power for each transmission endeavor.