# A Novel Approach for Improving XML Querying over Wireless Broadcast Channels
## 5 Comparative Study
### Comparison of Access Time of the Proposed Scheme with Various Data Placement Schemes
\begin{table}
\begin{tabular}{l l l l l} \hline \hline
**Metric** & **Proposed Scheme** & **Broadcast Disk** & **Index-Based** & **Sequential** \\  & **Scheme** & **Method**[20] & **Method[21] & **Broadcast[22]** \\ \hline Query Response Time & & & & \\ (seconds) & 5.4 & 5 & 5 & 17 \\ \hline Network Traffic (MB) & 10 & 10 & 11 & 10 \\ \hline CPU Utilization (\%) & 50 & 30 & 60 & 70 \\ \hline Memory Utilization (\%) & 40 & 30 & 50 & 60 \\ \hline Bandwidth Utilization (\%) & 60 & 50 & 50 & 80 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison of various performance metrics of the proposed scheme against existing XML data placement techniques. Comparison of Various Performance Metrics of the Proposed Scheme with Centralized Querying and Unpartitioned Broadcasting XML Data Placement Schemes  
In this section, we compare the proposed scheme for improving XML querying over wireless broadcast channels to two other algorithms: centralized querying and unpartitioned broadcasting XML data placement schemes. Centralized querying stores XML data in a central database and sends the query to a server for processing. The server processes the query and sends the results to the mobile device. Unpartitioned broadcasting sends the entire XML data stream over the wireless channel while the query is processed on the mobile device. We evaluated the following performance metrics:  
1. **Query Response Time (QRT):** Time taken from issuing a query to receiving the results. 2. **Network Traffic (NT):** Amount of data transmitted over the network during the query process. 3. **Resource Utilization (RU):** Utilization of system resources (CPU, memory, bandwidth) during the query process. The comparison of various performance metrics of the proposed scheme against centralized querying and unpartitioned broadcasting techniques is tabulated in Table 5 and depicted in Figure 6. Our proposed scheme provides the best balance between low query response time and moderate network traffic and resource utilization. Due to the need to transmit data to and from the central server, centralized querying has the highest response time and network traffic. These factors result in high resource utilization. In terms of query response time and network traffic, unpartitioned broadcasting outperforms centralized querying, but it still consumes a lot of resources and takes longer to respond than the proposed scheme. The proposed scheme significantly reduces query response time when compared to centralized querying and unpartitioned broadcasting. The scheme reduces latency when accessing large XML documents by partitioning the data stream and distributing it across multiple wireless broadcast channels. The query routing mechanism ensures that queries are routed to the appropriate partitions, thereby improving response times. Figure 5: Comparison of the various performance metrics of the proposed scheme against centralized querying [23] and unpartitioned [24] broadcasting techniques. Our proposed scheme efficiently distributes the load across multiple channels, reducing overall network traffic congestion. Centralized querying frequently results in bottlenecks because all data queries are routed through a single point. While unpartitioned broadcasting may overload the network with redundant data transmissions. The proposed scheme addresses these issues through intelligent partitioning and load balancing, resulting in more efficient network utilization. The proposed scheme optimizes resource utilization by distributing data and query processing across multiple channels. This distribution avoids overloading any single channel while making better use of the available bandwidth. In contrast, centralized querying can put a strain on server resources, and unpartitioned broadcasting fails to capitalize on the potential of parallel processing.