Jan 28, 2020 · Then based on their submodular property, two task allocation methods are proposed, namely double greedy (dGreedy) and submodular optimisation ( ...
Oct 22, 2024 · Task allocation for crowdsensing based on submodular optimisation ; of loc(j) can also be expressed as the total number of ; 1 ≤ j ≤ hl that are ...
Then based on their submodular property, two task allocation methods are proposed, namely double greedy (dGreedy) and submodular optimisation (SMO). The two ...
In crowdsensing, task allocation is a primary issue which determines the data quality and the cost of sensing tasks. In this paper, on the basis of the sweep ...
Sep 23, 2024 · The problem stated is a combinatorial optimization that aims to maximize a submodular function (see Appendix A for the proof). Finding such an ...
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Bibliographic details on Task allocation for crowdsensing based on submodular optimisation.
Since workers select tasks based on their own preference or goals (e.g., nearby, easy, or high payment), the overall performance may not be globally optimized.
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Task allocation is a significant issue in crowd sensing, which trades off the data quality and sensing cost. Existing task allocation works are based on the ...
An ordered submodularity-based budget-feasible mechanism for opportunistic mobile crowdsensing task allocation and pricing. IEEE Trans. Mob. Comput. 2024 ...
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Oct 14, 2020 · We prove that the task allocation problem is an NP-hard and submodular problem and then propose a native greedy selection (NGS) algorithm, which ...
Missing: optimisation. | Show results with:optimisation.