TY - JOUR
T1 - Static Node Center Opportunistic Coverage and Hexagonal Deployment in Hybrid Crowd Sensing
AU - Ding, Shuang
AU - He, Xin
AU - Wang, Jicheng
AU - Qiao, Baojun
AU - Gai, Keke
N1 - Publisher Copyright:
© 2016, Springer Science+Business Media New York.
PY - 2017/3/1
Y1 - 2017/3/1
N2 - 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.
AB - 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.
KW - Hexagonal deployment
KW - Markov chain
KW - hybrid crowd sensing
KW - static node center opportunistic coverage
KW - stream successful transmission probability
UR - http://www.scopus.com/inward/record.url?scp=84960379621&partnerID=8YFLogxK
U2 - 10.1007/s11265-016-1120-y
DO - 10.1007/s11265-016-1120-y
M3 - Article
AN - SCOPUS:84960379621
SN - 1939-8018
VL - 86
SP - 251
EP - 267
JO - Journal of Signal Processing Systems
JF - Journal of Signal Processing Systems
IS - 2-3
ER -