Simulation Results – Routing metric performance

Routing Metrics

All routing metrics have already been discussed in Section 3.4.1. The routing metrics are used in the two different modes of P-NLB: S-SPM and LBM.

• Free space in receive buffers

• Number of child nodes

• Number of upstream nodes

• Energy level of nodes

Two different network structures

While previously simulations are only run on the random network topology the simulations of the routing metric performance are also done on another network type: a network with two clusters with different sizes:

• Network consisting of two connected clusters of unequal size. One cluster has 25 nodes, the other has 40 nodes, both clusters contain one sink – the difference is thus 15 nodes. Test setup should prove a load balanced network is an efficient network. This network type is hereafter called asymmetric clusters.

Figure 25 – Symmetric cluster topology

4.4.1 Routing metric performance: Random topology

When looking at the performance of all algorithms in random topologies in Figure 1, LBM is still better in distributing the load over the sinks. All routing metrics have more or less the same load for each routing mode.

NCLB results in the lowest latency in the random topology, 50% lower than SPR. Latency is in general higher in LBM than in S-SPM. Latency is lowest when using routing metrics Buffer, in both routing modes. In S-SPM mode the latency comes close to the latency of NCLB. In LBM the latency with using routing metric Buffer is lower than three routing metrics of S-SPM.

PDR is highest when using Buffer as metric in S-SPM. NCLB has a higher PDR than all other algorithms, although the results do not differ very much. LBM stays behind, with a PDR equal to that of SPR.

The throughput of SPR is lowest of all algorithms, NCLB and routing metric Network lifetime in S-SPM results in the highest throughput. The throughput of LBM is up to 10% worse than that of S-S-SPM.

Logically, routing metric Network lifetime results in the highest network life, in S-SPM up to 10%

higher than SPR and NCLB. The energy efficiency shows no great differences.

The standard deviation of these graphs can be found in Appendix I, Figure 30. Again these standard deviations are very high.

In general latency varies most among the different routing metrics, where routing metric Buffer performs clearly the best in both routing modes. By using this routing metric, nodes are best in avoiding congestion and consequently this results in the lowest latency and highest PDR. The results of the other performance metrics show more or less equal results for all routing metrics, although routing metric Network lifetime achieves a better throughput and network lifetime. Looking at all results; NCLB performs in general the best, with lowest latency and highest PDR. In almost all cases SPR performs worse than all other algorithms and LBM worse than S-SPM.

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Standard deviation of sink loads, normalized

Standard

a) Standard deviation of load per sink b) Latency

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Packet delivery ratio (% delivered of total send)

Standard NCLB

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e) Network lifetime f) Energy efficiency

Figure 26 – Simulation results random topology

4.4.2 Routing metric performance: Asymmetric clusters topology

The asymmetric clusters topology shows again that LBM is able to distribute the load uniformly over the sinks. This results in a much lower latency for the routing metrics Child nodes, Buffer and Descendants using LBM compared with using S-SPM, and even lower than NCLB. The decrease in latency compared with SPR is more than 50%. Routing metric Energy level has in both S-SPM and LBM a higher latency, probably caused by the long routing path in order to avoid nearly depleted nodes around the sink. The lowest latency of all algorithms is achieved by using routing metrics Buffer and Descendants in LBM.

If routing mode LBM is used, PDR is up to 10% higher than all other algorithms. The highest PDR is also achieved by using routing metrics Buffer and Descendants in LBM. Throughput is showing other results than the PDR. This can be explained by the fact that traffic load on the top-level neighbours of the sinks is more important for the throughput than up to those nodes. Therefore, it is no surprise the routing metrics Buffer, Descendants and Energy Level, which can best route around congested top-level neighbours to less congested top-level neighbours, have the highest throughput. Of course, NCLB has the highest throughput, since that protocol makes the best use of the top-level neighbours of the sinks.

As expected, the network lifetime, is highest when using the routing metric Network lifetime. NCLB also results in a high network lifetime, because it distributes the load over all neighbours of the sinks.

Since these neighbours are likely to run out of energy first, this approach extends the lifetime of those nodes. The lifetime of the whole network is increased up to 10%, in comparison with SPR.

The energy efficiency performance metrics show that the long routing paths of routing metric Network lifetime result in relatively much energy is used to deliver the packets at the sinks.

The standard deviations of these graphs, which can be found in Appendix I, Figure 31, are quite low.

In general it is obvious that routing metric Child nodes performs worst of all routing metrics in this regular network type, since most nodes have an equal degree. Therefore, this metric cannot gain any advantage. Routing metric Buffer is most suitable if a low latency or high PDR are needed. Routing metric Network lifetime can best be used if a high network lifetime or throughput is required. In this network type, P-NLB is able to outperform the centralized algorithm of NCLB in performance metrics

latency in PDR and achieve the same performance in performance metrics network lifetime and

Standard deviation of sink loads, normalized

Standard NCLB

a) Standard deviation of load per sink b) Latency

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Packet delivery ratio (% delivered of total send)

Standard NCLB

e) Network lifetime f) Energy efficiency

Figure 27 – Simulation results two non-uniform clusters topology