## 5 Simulation Results  
We expect that the proposed energy-efficient relaying mechanism can be employed to save energy in real-world wireless image sensor networks, bringing valuable contributions in this area. As the sensing relevancies of source nodes are exploited to assign relaying priorities to data packets, the network will preserve packets with higher impact to the applications overall quality, potentially performing better than optimization approaches based only on packets' payloads. In order to assess the proposed approaches in what concerns energy consumption, we conducted a series of simulations where source nodes with different sensing relevancies are deployed. The standard relaying functionality in the framework Castalia [37] was adapted to execute our packet selection algorithms. Basically, they read the SR\({}_{(s)}\) included in each data packet to decide if it will be forwarded to the next hop or silently dropped, according to the current energy level and predefined energy thresholds. Castalia is a C\(++\) discrete event simulator based on the OMNet\(++\) platform [37]. Two different communication scenarios were considered for the simulations, as presented in Figure 6. Those networks are composed of few nodes for simplicity, which are improbable for real-world wireless sensor networks, but are useful to verify packet relaying in braided-paths since they follow the same principles of large networks. The first scenario is composed of two source nodes (s1 and s2) and one intermediate node that implements the proposed approaches (n1), while the Scenario 2 is composed of 5 source nodes (s1, s2, s3, s4 and s5) and 5 intermediate nodes, where the proposed approaches are implemented only in node n2. The maximum distance between neighbor nodes is established in 20 meters. For the experiments, we considered source nodes transmitting a single generic 64 \(\times\) 64 uncompressed grayscale image snapshot every 10 s. For an effective payload size of 104 bytes, 40 data packets are transmitted by source nodes for a single snapshot. The visual sensor nodes will be transmitting data packets in a maximum transmission rate of 250 kbps and with a transmission power of \(-5\) dBm. A simple interference model is assumed (interferences are res  
Figure 5: Different reconstructed images according to the considered 1-level 2D DWT subbands. from neighbor nodes), where packet collisions are handled by MAC-layer protocols. In [37], the packet reception probabilities are calculated based on the transmission power of the transmitting nodes, keeping some level of similarity with real-world communications. The MAC functionalities are supported by T-MAC [25], a duty-cycle protocol that dynamically adjusts the sleeping time for higher efficiency (better adapting to higher transmission rates), also performing retransmission of corrupted packets. Default T-MAC parameters were considered for the experiments, according to the definitions in Castalia WSN discrete-event simulator (version 3.2). We defined different configurations different configurations of sensing relevancies, as depicted in Table 5. The SR-based(1) and SR-based(2) configurations are intended for simulations over the Scenario 1, while the remaining configurations are aimed at simulations over Scenario 2. The SR-based relaying is concerned only with the SR in each packet (Section 4.1), while the SR-DWT-based approaches also exploits DWT subbands relevancies (Section 4.2). We initially conducted simulations comparing the SR-based relaying approach with a traditional SR-unaware relaying mechanism (every incoming packet is forwarded) and a standard Data-relevance approach where only the payloads' relevancies (DWT subbands) are considered for energy-efficient relaying, in a similar way as expressed in [9]. In the latter, the original images are encoded by a 1-level 2D DWT and packets are prioritized using only the value of DR, as defined in Table 6.