Example Scenario

(b) Abstract view of the net-work.

Figure 6.12: Network topology used in the simulation

In order to allow a comparison between WASP and CICADA, we have taken the same example scenario. Figure 6.12(a) shows the example network where some sensors are placed on a human body. Figure 6.12(b) shows the generic tree view of this network. Thirteen nodes are each sending a CBR-stream to one sink with radios capable of transmitting up to 1Mbps. When configuring CICADA with control slots of 0.5 ms and data slots of 5 ms, the tree was set up after 192 ms.

S A B C D E F G H I J K L M

Figure 6.13: Time usage in the nodes. The sink has number 1, node A is number 2 and so on.

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In the first evaluation, the duty cycle was set to 100% and all sensor data was sent to the sink. Each node sent a data packet of 500 bytes every 150 ms. When data was being generated at each node, the cycle length stabilized to 124.5 ms or 9 control slots and 24 data slots. For this example, the packet inter arrival time was set to be higher than the cycle length, ensuring that at most 1 packet was sent during each cycle. Doing so, no packet loss was obtained. As in WASP, nodes only have to operate their radio when they are sending or receiving data. The time usage of the nodes in CICADA is depicted in Figure 6.13. The sink can turn its radio off when it has sent its SCHEME-message in the control cycle (8 control slots) and in the waiting period in the data cycle (10 data slots). Thus, each cycle the radio can be turned off during 54 ms or 43.7% of the time. The same holds for the other nodes. The sleep ratios in this figure correspond to sleep ratios calculated with (6.4) and with the understanding that the radio is turned off when it has sent its control scheme. If we compare the energy usage of CICADA with WASP, Figure 5.9, it can be seen that for all nodes the sleep ratio is larger for CICADA.

This is in line with the conclusions of Figure 6.7 where for low ζ the sleep ratio is higher for CICADA. In this scenario ζ corresponds to 4.

We have also calculated the overhead associated with CICADA, i.e. both the control packets as the headers of the data packets. The overhead for each node can be found in Table 6.5. Overall, the overhead is very limited, only a few percent.

This was expected as the header length is limited (7 bytes for a data packet, see Section 6.1.11) and the control packets for sending the schemes are small. We also have to take in mind that in this example the size of the payload is 500 bytes. The overhead of the sink is 100% as the sink only sends control packets.

Node Total bytes sent Overhead (bytes) Ratio

S 1674 1674 100.00%

A 47800 1800 3.85%

B 94640 2640 2.85%

C 24231 1231 5.19%

D 141499 3499 2.53%

E 24180 1180 4.99%

F 71157 2157 3.10%

G 71157 2157 4.62%

H 70741 1741 2.50%

I 47741 1741 3.73%

J 24180 1180 4.99%

K 24180 1180 4.99%

L 24180 1180 4.99%

M 24180 1180 4.99%

Table 6.5: Overhead induced by CICADA for the example network of Figure 6.12(b)

152 CICADA: ENERGYEFFICIENT ANDRELIABLENETWORKING

The example network was also used to evaluate the sleep ratio and packet loss for varying packet inter arrival time (t_arrival) and for different duty cycles. The packet inter arrival time is defined as the time between two packets received from the application layer. CICADA is also compared with S-MAC [7], a much used CSMA-style protocol for sensor networks. Nodes synchronize on time by build-ing virtual clusters and employ a fixed duty cycle to reduce idle listenbuild-ing overhead.

S-MAC includes carrier sense, collision avoidance (RTS/CTS signaling), and over-hearing avoidance. We have used the implementation of S-MAC available in NS-2 with the default parameters (a duty cycle of 10%) and with fixed (optimal) rout-ing. Doing so, the overhead and delay caused by the routing protocol is avoided.

In Figure 6.14, it can be seen that CICADA has a packet loss of 0% as long as the packet inter arrival time is lower than the length of the duty cycle. The main reason for this problem is that the node is not aware of the application’s traffic pattern (i.e. the sensor rate). The node can only reserve slots (by changing its αi) for data already queued. For example, when the nodes start transmitting packets, two packets will be reserved in the first cycle. The cycle lenght will increase and in the next cycle three packets need to be reserved. This will again lenghten the duration of the cycle, and the following cycle four slots will be reserved. This mechanism creates an avalanche effect in the length of the duty cycle. Currently, CICADA does not take this problem into account. A possible solution is to im-plement a traffic predictor who can more precisely predict the packet inter arrival time. Compared with S-MAC, CICADA performs a lot better.

10⁻¹ 10⁰ 10¹

Figure 6.14: Packet loss for the network of Figure 6.12(b). The duty cycle ∆ and the packet inter arrival time tarrivalis varied.

The sleep ratio is shown in Figure 6.15. The sleep ratio drops for small packet inter arrival times, which is expected as more traffic is sent in the network.

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ever, when the packet inter arrival time is too low, the sleep ratio rises again. More packets are lost due to buffer overflows, thus less packets are actually sent. This effect further scales with the packet loss of Figure 6.14. For lower duty cycles, the sleep ratio rises up to 95%. Compared with S-MAC (duty cycle of 10%) CICADA performs better when the duty cycle is set to 20% or lower.

10⁻¹ 10⁰ 10¹

0 10 20 30 40 50 60 70 80 90 100

Packet Inter Arrival Time (s)

Sleep ratio (%) ∆ = 100%

∆ = 50%

∆ = 20%

∆ = 10%

S−MAC

Figure 6.15: Sleep ratio for the network of Figure 6.12(b). The duty cycle ∆ and the packet inter arrival time is varied.

The results above show that CICADA has a high sleep ratio, especially when the duty cycle is reduced to 50% or lower. Longer duty cycles however lead to packet loss when packet inter arrival times are too low. When deploying a WBAN using CICADA, one thus has to balance the desired throughput and the energy efficiency against each other.