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Spatial crowdsourcing, a human-centric compelling paradigm in performing spatial tasks, has drawn rising attention. Task assignment is of paramount importance in spatial crowdsourcing. Existing studies often use heuristics of various kinds to solve task assignment problems. These schemes usually only apply some specific cases, once the environment changes, the efficiency of the algorithms is significantly reduced. In this paper, we first introduce a taxonomy of task assignment in spatial crowdsourcing. Next, we design an approximation algorithm and get an efficient solution for the important problem, namely, Bounded and Heterogeneous Task Assignment (BHTA), such that the sum of the rewards of workers is maximized subject to multiple constraints. We prove that the BHTA problem is NP-hard. Subsequently, we propose a constant-ratio approximation algorithm based on partition and shifting method to achieve the assignment solution. To meet with the workers’ dynamism, we further devise a greedy algorithm and provide theoretical guarantee. Experiments on synthetic and real datasets demonstrate the efficiency of our strategy over previous methods. So far as we know, this paper is the first attempt to give a constant-ratio approximation for such task assignment problems in spatial crowdsourcing. [ABSTRACT FROM AUTHOR]

Measurements of impulsive noise in a 400/275/132-kV electricity substation are presented. The measurements are made with three antennas having overlapping bands covering the range 100 MHz–6 GHz. This range includes those bands relevant to modern wireless local area network and wireless personal area network technologies (e.g., IEEE 802.11a/b/g and IEEE 802.15.1/4), which, if proved to be sufficiently robust in the presence of impulsive noise, could play a useful role in substation monitoring and control. Impulsive events are extracted from the measured data using the wavelet packet transform, and the statistical distributions of pulse rate, pulse amplitude, pulse duration, and pulse rise time are presented. An unexpected quasi-periodic component of the noise is observed. [ABSTRACT FROM PUBLISHER]