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Abstract Wireless Sensor Networks (WSNs) are increasingly used in data-intensive applications such as microclimate monitoring,precision agriculture, and audio/video surveillance. A key challenge faced by data-intensive WSNs is to transmit all the data generatedwithin an application’s lifetime to the base station despite the fact that sensor nodes have limited power supplies. We propose using low costdisposable mobile relays to reduce the energy consumption of data-intensive WSNs. Our approach differs from previous work intwo main aspects. First, it does not require complex motion planning of mobile nodes, so it can be implemented on a number of low-costmobile sensor platforms. Second, we integrate the energy consumption due to both mobility and wireless transmissions into a holisticoptimization framework. Our framework consists of three main algorithms. The first algorithm computes an optimal routing treeassuming no nodes can move.
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Mobile Relay Configuration in Data-Intensive Wireless Sensor Networks
Abstract
Wireless Sensor Networks (WSNs) are increasingly used in data-intensive
applications such as microclimate monitoring, precision agriculture, and audio/video
surveillance. A key challenge faced by data-intensive WSNs is to transmit all the data
generated within an application’s lifetime to the base station despite the fact that sensor
nodes have limited power supplies. We propose using low cost disposable mobile
relays to reduce the energy consumption of data-intensive WSNs. Our approach differs
from previous work in two main aspects. First, it does not require complex motion
planning of mobile nodes, so it can be implemented on a number of low-cost mobile
sensor platforms. Second, we integrate the energy consumption due to both mobility
and wireless transmissions into a holistic optimization framework. Our framework
consists of three main algorithms. The first algorithm computes an optimal routing tree
assuming no nodes can move. The second algorithm improves the topology of the
routing tree by greedily adding new nodes exploiting mobility of the newly added
nodes. The third algorithm improves the routing tree by relocating its nodes without
changing its topology. This iterative algorithm converges on the optimal position for
each node given the constraint that the routing tree topology does not change. We
present efficient distributed implementations for each algorithm that require only
limited, localized synchronization. Because we do not necessarily compute an optimal
topology, our final routing tree is not necessarily optimal. However, our simulation
results show that our algorithms significantly outperform the best existing solutions.
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Abstract Existing System Disadvantages Proposed System Advantages Objective System Requirements System Architecture
Literature Survey Module List Module Description Data Flow Diagram Level DFD Module Wise DFD Problem Definition Review Document Explanation
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