Abstract
Mobile Crowd Sensing (MCS) is widely used in large-scale complex social sensing tasks even though it cannot offer reliable sensing quality yet due to the mobility restrictions. In order to solve the inadequate sensing opportunities provided by an MCS system, we focus on building a Hybrid Crowd Sensing (HCS) network by organizing both static and uncontrolled mobile nodes. We use the static node central opportunistic coverage to measure the sensing quality of HCS by analyzing the different features of coverage in the three regions and forming definitions. Our proposed approach can enable the static nodes to be deployed in the traditional hexagonal lattice, and mobile nodes to be located by smaller hexagonal lattices. Moreover, the analysis results demonstrate that the hexagonal lattice is more economical in both the number of mobile nodes needed by the seamless coverage SSA and network connectivity with the square grid. Finally, we make further analysis of the stream successful transmission probability, and find out that there are many complex influence factors of the static node central opportunistic coverage, such as the size of the time window T, the relative position of the start location and the end location, the number of mobile nodes participates stream transmission, mobile strategy of mobile nodes, opportunistic delegation mechanism, opportunistic routing mechanism, and so on. We modelize the lower limitation of it by a discrete Markov chain, and the simulation results show both the feasibility and rationality of using the static node central opportunistic coverage as the sensing quality metric.
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