Wireless sensor networks (WSNs) and mobile crowdsensing (MCS) are two important paradigms in urban dynamic sensing. In both sensing paradigms, task allocation is a significant problem, which may affect the completion quality of sensing tasks. In this paper, we give a survey of task allocation in WSNs and MCS from the contrastive perspectives in terms of data quality and sensing cost, which help to better understand related objectives and strategies. We first analyze the different characteristics of two sensing paradigms, which may lead to difference in task allocation issues or strategies. Then, we present some common issues in task allocation with objectives in data quality and sensing cost. Furthermore, we provide reviews of unique task allocation issues in MCS according to its new characteristics. Finally, we identify some potential opportunities for the future research.