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.