TY - GEN
T1 - A sybil-proof and time-sensitive incentive tree mechanism for crowdsourcing
AU - Zhang, Xiang
AU - Xue, Guoliang
AU - Yang, Dejun
AU - Yu, Ruozhou
N1 - Funding Information:
by NSF grants 1217611, 1420881, 1421685, and 1461886. The information reported here does not reflect the position or the policy of the federal government.
Publisher Copyright:
© 2015 IEEE.
PY - 2015
Y1 - 2015
N2 - Crowdsourcing incentive mechanism design has raised numerous interests from research communities in recent years. While most research focuses on contribution-based payment allocation, a solid crowdsourcing incentive mechanism should encourage users to both devote efforts to complete the task and refer other users to join into participation. In this paper, we adopt a data structure called incentive tree which has a unique advantage in incentivizing participants for solicitation. Furthermore, we consider the crowdsourcing scenario where the contribution model is submodular and time-sensitive, which is more realistic compared to the linear summation model adopted by previous works. Under this model, we design a reward mechanism based on the incentive tree, and prove that this mechanism satisfies several economic properties such as continuing contribution incentive, continuing solicitation incentive, θ-reward proportional to contribution, early contribution incentive, and sybil-proofness. We implemented our incentive mechanism and conducted extensive performance evaluations. The evaluation results confirm our theoretical analysis.
AB - Crowdsourcing incentive mechanism design has raised numerous interests from research communities in recent years. While most research focuses on contribution-based payment allocation, a solid crowdsourcing incentive mechanism should encourage users to both devote efforts to complete the task and refer other users to join into participation. In this paper, we adopt a data structure called incentive tree which has a unique advantage in incentivizing participants for solicitation. Furthermore, we consider the crowdsourcing scenario where the contribution model is submodular and time-sensitive, which is more realistic compared to the linear summation model adopted by previous works. Under this model, we design a reward mechanism based on the incentive tree, and prove that this mechanism satisfies several economic properties such as continuing contribution incentive, continuing solicitation incentive, θ-reward proportional to contribution, early contribution incentive, and sybil-proofness. We implemented our incentive mechanism and conducted extensive performance evaluations. The evaluation results confirm our theoretical analysis.
KW - Crowdsourcing
KW - Submodular Contribution
KW - Sybil-proofness
KW - Timesensitivity
UR - http://www.scopus.com/inward/record.url?scp=84964918180&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84964918180&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2014.7417272
DO - 10.1109/GLOCOM.2014.7417272
M3 - Conference contribution
AN - SCOPUS:84964918180
T3 - 2015 IEEE Global Communications Conference, GLOBECOM 2015
BT - 2015 IEEE Global Communications Conference, GLOBECOM 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 58th IEEE Global Communications Conference, GLOBECOM 2015
Y2 - 6 December 2015 through 10 December 2015
ER -