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Data collection is a common operation of Wireless Sensor Networks (WSNs). The performance of data collection can be measured by its achievable network capacity. However, most existing works focus on the network capacity of unicast, multicast or/and broadcast, which are different communication modes from data collection, especially continuous data collection. In this paper, we study the Snapshot/Continuous Data Collection (SDC/CDC) problem under the Physical Interference Model (PhIM) for randomly deployed dense WSNs. For SDC, we propose a Cell-Based Path Scheduling (CBPS) algorithm based on network partitioning. Theoretical analysis shows that its achievable network capacity is Ω(W) (W is the data transmitting rate, i.e. bandwidth, over a channel), which is order-optimal. For CDC, we propose a novel Segment-Based Pipeline Scheduling (SBPS) algorithm that significantly speeds up the CDC process, and achieves a surprising network capacity, which is at least √(n/ log n) or n/log n times better than the current best result.