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Data aggregation is an essential operation for the sink to obtain summary information in a Wireless Sensor Network (WSN). The problem of Minimum Latency Aggregation Schedule (MLAS) which seeks a fastest and collision-free aggregation schedule has been well studied when nodes are always awake. However, in duty-cycle WSNs, nodes can only receive data in active state. In such networks, it is of great...
WSNs are often besieged with issues related to interference when transmissions of two or more closely located sensor nodes interfere with each other. This forces the data aggregating nodes to receive distorted, faulty or interference ridden signals, which severely affects the fidelity of data being aggregated. If such faults are not arrested at the source, interference laden transmissions or Interference-Faults...
Data aggregation is a key, yet time-consuming functionality introduced to conserve energy in wireless sensor networks (WSNs). In this paper, to minimize time latency, we focus on aggregation scheduling problem and propose an efficient distributed algorithm that generates a collision-free schedule with the least number of time slots. In contrast to others, our approach named FAST mainly contributes...
We consider a wireless sensor network in which a routing tree has been established to transmit the information from a set of source nodes to a data sink. The existing algorithms to schedule the transmission slots in a way that allows the data to be compressed as it moves towards the data sink are centralized or rely on interference models that fail occasionally. We propose a distributed TDMA scheduling...
In-network aggregation has become a promising technique for improving the energy efficiency of wireless sensor networks. Aggregating data at various nodes in the network results in a reduction in the amount of bits transmitted over the network, and hence, saves energy. In this paper, we focus on another important aspect of aggregation, i.e., delay performance. In conjunction with link scheduling,...
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