In wireless sensor networks (WSNs), due to dense deployment, sensory data gathered by sensor nodes in close proximity tend to exhibit high correlation and therefore redundant. Transmitting such redundant data is not practical in the energy-constrained WSNs. Data aggregation offers a key solution to reduce such redundancy by allowing intermediate nodes to aggregate raw data streams before routing them toward a sink node. This in turn reduces transmission energy consumption. Prior work in data aggregation often rely on node�s location for selecting an aggregator node, a fusion point. In this work, we propose two data aggregation mechanisms where aggregator nodes are determined opportunistically without dependency on global knowledge of data flow, network topology and nodes� geographical location. These mechanisms aggregate and route data packets based on Received Signal Strength Indicator (RSSI). An aggregation identification (AggID) is associated with each data packet generated by a sensor node. The RSSI and AggID are used in the RSSI-Based Fowarding for favoring nodes closer to sink to be an aggregator and also a relay node. We show via simulation the performance of the proposed mechanisms in terms of normalized number of transmissions, total number of packets transmissions and receptions, average energy consumed per data packet, network lifetime, end-to-end delay and packet loss probability. © 2014, Springer Science+Business Media New York.