title: A search strategy of Level-Based Flooding for the Internet of Things.
abstract: This paper deals with the query problem in the Internet of Things (IoT). Flooding is an important query strategy. However, original flooding is prone to cause heavy network loads. To address this problem, we propose a variant of flooding, called Level-Based Flooding (LBF). With LBF, the whole network is divided into several levels according to the distances (i.e., hops) between the sensor nodes and the sink node. The sink node knows the level information of each node. Query packets are broadcast in the network according to the levels of nodes. Upon receiving a query packet, sensor nodes decide how to process it according to the percentage of neighbors that have processed it. When the target node receives the query packet, it sends its data back to the sink node via random walk. We show by extensive simulations that the performance of LBF in terms of cost and latency is much better than that of original flooding, and LBF can be used in IoT of different scales.
authors.affiliation: School of Software, Dalian University of Technology, Dalian 116620, China. qiutie@dlut.edu.cn
authors.forename: Tie
authors.initials: T
authors.lastname: Qiu
authors.forename: Yanhong
authors.initials: Y
authors.lastname: Ding
authors.forename: Feng
authors.initials: F
authors.lastname: Xia
authors.forename: Honglian
authors.initials: H
authors.lastname: Ma
keywords: Internet of Things; energy efficiency; flooding; query processing; search