Final answer:
The cross-platform data exchange issue in distributed systems is often handled through data serialization, such as using XML or JSON formats. Data serialization involves converting complex data structures into a standardized format that can be easily transmitted and understood by different platforms.
Step-by-step explanation:
In distributed systems, where computing nodes are often heterogeneous and have different data representations, the issue of cross-platform data exchange is handled through a process called data serialization. Data serialization involves converting complex data structures, such as objects or arrays, into a standardized format that can be easily transmitted and understood by different platforms. One commonly used method for data serialization is using the eXtensible Markup Language (XML) or JavaScript Object Notation (JSON). These formats provide a platform-independent way to represent data, allowing it to be exchanged between different systems and applications.
For example, let's say we have a distributed system with two nodes: Node A running on a Windows machine and Node B running on a Linux machine. Node A wants to send a complex data structure to Node B. To handle the cross-platform data exchange, Node A can serialize the data into a JSON format. JSON provides a standardized way to represent data as a collection of key-value pairs, which can be easily understood by both Windows and Linux systems. Once the data is serialized, Node A can transmit it to Node B over the network. On the receiving end, Node B can deserialize the JSON data and convert it back into its original complex data structure.
In summary, the cross-platform data exchange issue in distributed systems is often handled through data serialization, which involves converting complex data structures into a standardized format that can be easily transmitted and understood by different platforms. XML and JSON are commonly used formats for data serialization in distributed systems.