In an agent-based WSN, the main technical challenges include data fusion and energy efficiency, as well as energy and load balancing [15].
Then, the effect of multi-attribute-based data fusion regarding energy consumption is analyzed.
To realize the efficient data collection, the effect of data fusion on energy consumption should be fully considered.
The agent technology has drawn much attention in wireless sensor networks (WSNs) to perform data fusion and energy balancing.
It can be deduced that the condition of intra-grid data fusion can save energy is E 2 - E 1 = D ( s i ) e t ( a ) + D ( s i ) e r + [ D ( s i ) + D ( s j ) ] e f - min ( D ( s i ), D ( s j ) ) σ e t ( 2 a ) < 0 ⇒ σ > D ( s i ) [ e t ( a ) + e r + e f ] + D ( s j ) e f min ( D ( s i ), D ( s j ) ) e t ( 2 a ).
In addition, although data fusion can reduce the energy consumption, it still introduces the extra energy consumption, where each fusion for 1 bit data is denoted by e f.
In Section 4.2, we have proved the condition of intra-grid data fusion that can save energy.
The effective data fusion can reduce the energy consumption, while the reduced data amount is determined by the data coefficient relativity.
Theorem 1: ∀s i, s j ∈ g u (x,y), the condition of intra-grid data fusion that can save energy is: σ > D ( s i ) [ e t ( a ) + e r + e f ] + D ( s j ) e f min ( D ( s i ), D ( s j ) ) e t ( 2 a ).
Theorem 2: ∀s i ∈ g u (x,y), s j ∈ g u (x', y'), the condition of inter-grid data fusion that can save energy is σ > [ D ( s i ) + D ( s j ) ] e f min ( D ( s i ), D ( s j ) ) ( e t ( 2 a ) + e r ) ( ∣ x 0 ��� + ∣ y 0 ∣ ).
