# An Untraceable Data Sharing Scheme in Wireless Sensor Networks
## 6 Performance Evaluation
### Theoretical Analysis  
In existing cloud-based source-location privacy protection schemes, the cloud is constructed based on the original message \(X\). In this paper, we assumed that the description data, \(X\), of a panda is \(l\) bits and the head of a package is always \(l^{\prime}\) bits, i.e., the total length of the package is \(l^{\prime}+l\) bits. In existing cloud-based schemes, all the nodes periodically send packages that have the same of \(l^{\prime}+l\) bits and the dummy messages are employed to hide message \(X\). In a cloud with \(m\) nodes, the cloud needs to totally transmit and receive \(m*(l^{\prime}+l)\) bits data in a period. If the packages walk \(k\) steps in average, \(m*(l^{\prime}+l)*k\) bits data are transmitted because of message \(X\). In our scheme, we design a \((t,n)\)-secret sharing scheme and employ the shares to construct the cloud. It can be calculated that the length of the shares is \(l/t\) bits. The head of a package contains the basic geographic information about the destination and is necessary for all the packages. Therefore, the total length of the packages in our cloud is \(l^{\prime}+l/t\). In the same cloud with existing schemes, the cloud needs to totally transmit and receive \(m*(l^{\prime}+l/t)\) bits data in a period. Similarly, \(m*(l^{\prime}+l/t)*k\) bits data are transmitted because of message \(X\) in our scheme.  
Except for constructing the cloud, some extra energy is consumed in the process of delivering the packages from the source node to the sink node. We assumed that the distance between the fake source node and the sink node is \(k^{\prime}\) hops. In the existing scheme, the data transmission amount is \((l^{\prime}+l)*k^{\prime}\) bits. In our scheme, the data transmission amount can be calculated as \((l^{\prime}+l/t)*n*k^{\prime}\).  
By combining the above two phases, the total data transmission amount is \(m*(l^{\prime}+l)*k+(l^{\prime}+l)*k^{\prime}\) in the existing cloud-based scheme. In our scheme, the total data transmission amount is \(m*(l^{\prime}+l/t)*k+(l^{\prime}+l/t)*n*k^{\prime}\). For convenience sake, we set \(m=100\), \(l^{\prime}=128\), \(k=5\), \(k^{\prime}=10\), \(n=7\) and the simulation results are presented in Figure 7.  
It can be observed that with the increasing of \(l\), the data transmission amount of both cloud-based scheme and our scheme increases. This is consistent with the analysis result. In our scheme, various records of the panda are hidden in message \(X\) and, without the specific statement, the length of \(X\) is assumed as 1024 bits in the following.  
Except for total data transmission amount, the balance of nodes' workload also affects the performances of these schemes. As discussed in Section 5.4, the nodes around the sink node in our network have a similar data transmission workload with that of nodes in typical WSNs. For each network, an interesting observation is that the nodes near to the sink node consume more energy than the nodes far from the sink node. This is reasonable considering that all the data need to be delivered to the sink node and the hence the nodes near to the sink node need to deliver more data. A proper solution to balance the workload of all the nodes in the network is that we can scatter slightly more nodes around the sink node.