# A Novel Approach for Improving XML Querying over Wireless Broadcast Channels
## 2 Related Work  
The authors introduced a wireless XML streaming method that provides energy-efficient access to a wireless stream. To represent XML data and index information, the authors created two hierarchical structures: the XML data tree and the XML index tree. The wireless XML stream is created by traversing these two structures with specific duplications [9].  
This study presented a novel XML stream structure for distributing XML data over a broadcast channel. The structure consisted of grouping and summarizing the structural information of XML nodes. It is possible to reduce the size of the XML stream by summarizing the information, thus resulting in a faster retrieval of the desired XML data via a wireless broadcast channel. The suggested XML stream structure includes indexes that allow you to skip unimportant parts of the XML stream. As a result, it can reduce the energy consumption of mobile devices when receiving XML query results [10].  
Path Stream Group Level (PSGL) nodes are introduced as new frameworks for processing streaming XML data. The framework takes advantage of the hierarchical structure of XML documents. Mobile clients can selectively download XML data using various tiny indices, such as level, child, sibling, attribute, and text. The data were organized using the XML document tree's hierarchy, and XML items with the same XML path prefix were grouped to save battery life on mobile clients [11].  
This paper described two novel XML data placement strategies for distributing XML data over multiple wireless broadcast channels. The XML data stream was divided into several sections and assigned to various wireless broadcast channels. The goal of both was to reduce access time when running XML queries across broadcast channels. Based on the experimental results, the proposed XML data placement strategies achieved the goal of further reducing access time, especially when dealing with large XML documents [12].  
Between the beginning of human civilization and the year 2000, humanity produced a total of five exabytes of data. The writers were, however, producing five exabytes of data every day. It loses its usefulness if no query operation is run on the data.  
Any organization that analyses these data may become more resilient and nimbler, enabling it to handle a range of business issues.  
The query-processing system is an important component of big data because it manages queries. This study distinguished between several query optimization procedures and their algorithms, which are used in large datasets to avoid query optimization problems. This review assisted researchers in identifying alternative methods for processing data and improving query processing and optimization in a variety of applications [13] by employing different query processing strategies.  
This paper investigated the use of wireless network connectivity to store Wushu Historical Archives' XML metadata database. The study focused on metadata storage in XML databases, specifically document size, document loading, and document query. This is achieved by using data load-balancing algorithms and two-way path constraint algorithms [14].  
The authors of this research study proposed a hybrid indexing approach for data transmission. This method distributes the indexing using a hash table and employs Huffman-tree index coding. The authors of the proposed work conducted a thorough analysis to provide a theoretical explanation for the current indexing scheme's performance. The outcomes of different strategies were then compared.  
The authors used an indexing method to retrieve geographic information in a wire-free environment [15] in their proposed solution.