SyncStream employs strategically placed edge processing nodes that act as intermediary data caches closer to the end-user.

These nodes use machine learning algorithms to predict which data is likely to be needed next based on past access patterns and pre-fetch it.

The system utilizes parallel processing and custom communication protocols to ensure fast synchronization with the main blockchain network, reducing data retrieval times significantly.

Furthermore, SyncStream regularly evaluates the performance of caches and dynamically adjusts their location and capacity to align with usage patterns, enhancing responsiveness without compromising the security or shared state of the blockchain.

SyncStream provides a swift, secure and scalable solution to latency issues in blockchain networks by leveraging edge computing and ML-driven predictive caching.

This solution dramatically enhances the viability of blockchain for real-time applications without compromising security or data integrity, meeting both efficiency and security demands.

This solution requires an integration of edge computing nodes that are feasible given current technologies, but challenges include ensuring consistency with the main blockchain and safeguarding against security risks inherent in pre-fetching and caching.

Initial infrastructure costs are considerable given the need for robust edge networks and ML capability, but manageable through partnerships and phased deployment.