We investigate the impact of multiple, mobile sinks on efficient data collection in wireless sensor networks. To improve performance, our protocol design focuses on minimizing overlaps of sink trajectories and balancing the service load among the sinks. To cope with high network dynamics, placement irregularities and limited network knowledge we propose three different protocols: a) a centralized one, that explicitly equalizes spatial coverage; this protocol assumes strong modeling assumptions, and also serves as a kind of performance lower bound in uniform networks of low dynamics b) a distributed protocol based on mutual avoidance of sinks c) a clustering protocol that distributively groups service areas towards balancing the load per sink. Our simulation findings demonstrate significant gains in latency, while keeping the success rate and the energy dissipation at very satisfactory levels even under high network dynamics and deployment heterogeneity.