This research focus on conducting a detailed performance analysis of three commonly used link-quality metrics in wireless sensor networks: ETX, 4Bit, and RNP. We study the interplay between these metrics and CTP, a tree-based routing protocol provided by TinyOS. The goal of the project is to provide extensive evaluation of ETX, 4Bit and RNP with insights on their performance under different criteria.
Due to the dynamic and asymmetric nature of the wireless links, various link quality estimation metrics have been proposed in literature to cope with the vagaries of the communication channel. In previous research, link reliability estimation metrics such as ETX and RNP have been proved to perform superior as compared to conventional metrics like shortest path or minimum latency in wireless sensor networks.
The question being asked In this research project is simple: which metric can deliver the best performance? To answer this question, we extensively evaluated some of the most commonly used link estimation techniques based on link reliability and compared the performance of these metrics with different but realistic network conditions.
In Additional, blacklisting policy is used in default link estimator of TinyOS as a part of multihop routing stack, but the actual effects of blacklisting in realistic network configurations have not been extensively studied. To answer this question, we studied the the impact of the presence or absence of a blacklisting policy when using these link quality estimation metrics.
Testbed: We conducted our experiments using a testbed located on one floor of a office building, with the nodes placed along the ceiling of a long corridor. There are 33 nodes in total, organized into 11 groups of 3 motes. Each group of motes are mounted on a bar with one foot separation. The location of these 11 bars are depicted in Figure 1.
Experiment Settings: We experimented with four different network configurations: 11 nodes with 0dBm and -10dBm transmission power; 33 nodes with 0dBm and -10dBm transmission power. To increase the diameter of the network, the root node was set at one end of the corridor. In 11-node experiments, the nodes are evenly separated within 250 feet distance. In 33-node experiments, the nodes are divided into 11 groups, each group contains 3 nodes.
Both ETX and 4Bit use the ETX metric for link estimation. 4B combines information from physical and network layer to provide more efficient link estimation to the upper layer. The other metric, RNP accounts for the distribution of packet losses of a link when estimating link quality. it represents the number of transmissions attempts including retransmissions to deliver a packet whereas ETX represents the number of transmissions required to deliver a packet without retransmission.
In our results, ETX and 4Bit exhibit the same preference in choosing paths with near perfect links. As a result, the average path length for ETX and 4B is almost the same. Since ETX selects parent nodes based solely on the quality of its neighbors, it has much better path quality and is more adaptive to changes in link quality.
By definition, RNP gives higher estimation to links with consecutive losses comparing to delivery rate based ETX. From the routing perspective, RNP tends to use links with less perfect quality that span long distance, therefore often selects paths with less hops to constitute an end-to-end route. Although packet losses occurs more often in longer links, the retransmission mechanism in the routing protocol can still ensure a high delivery rate with a few retransmissions. This is reflected in our experiments at low network densities where RNP chooses paths with less hops than the other two metrics. This leads to a smaller cost for delivering a packet, while maintaining a high end to end delivery rate that is comparable to that of ETX and 4Bit.
We also compared the effect of the presence and absence of blacklisting policy on the routing performance of ETX, RNP and 4Bit. ETX and RNP exhibit better performance without blacklisting with better path quality, higher delivery rates and less overhead. On the other hand, 4B performs much worse without blacklisting, especially in high network density configuration. This counter- intuitive result can be explained by the design of the link estimator: Regardless of the metric, the link estimator maintains records for its 10 best neighbors by link quality. In case of 4B, with blacklisting absent, the link estimator will consult the routing protocol when a new neighbor is discovered. If this neighbor is located closer to the sink, the routing protocol will instruct the link estimator to include this node in the neighbor table. As the link quality to this node could be lower than the node evicted from the neighbor table, the neighbor table will be polluted by such entries. In high power- high network density networks, the number of such nodes will be big enough to affect the routing choices made in 4Bit, resulting in poor delivery rate.