Nowadays, Quantum Key Distribution (QKD) has garnered widespread attention due to its ability to provide symmetric secret keys with information-theoretic security in point-to-point communication. Additionally, key relay technology has been introduced to complete end-to-end key distribution between remote parties by consuming keys in the intermediate links. The routing problem of selecting paths for key relay technology becomes crucial as it directly impacts the network's performance. In this paper, we focus on addressing the routing problem for a specific scenario to serve applications with real-time requirements. Real-time is a critical necessity for supporting various applications, such as video chatting and calling. To satisfy real-time requirements and achieve Quality of Service (QoS) provision to guarantee the completion time, we introduce a distributed routing protocol called Distributed Routing Protocol Based on Key Reservation (Q-RoKR). It reserves keys in advance along the selected path, thereby satisfying real-time requirements. We also propose a priority-awareness mechanism to address resource competition and make efficient use of keys in links. Extensive experiments demonstrate that our protocol effectively meets the real-time requirements and significantly improves throughput. Furthermore, our key efficiency approaches the optimal bound when compared to other comparison schemes.

Searchable Symmetric Encryption (SSE) is a valuable cryptographic tool that allows a client to retrieve its outsourced data from an untrusted server via keyword search. Initially, SSE research primarily focused on the efficiency-security trade-off. However, in recent years, attention has shifted towards range queries instead of exact keyword searches, resulting in significant developments in the SSE field. Despite the advancements in SSE schemes supporting range queries, many are susceptible to leakage-abuse attacks due to volumetric profile leakage. Although several schemes exist to prevent volume leakage, these solutions prove inefficient when dealing with large-scale datasets. In this paper, we highlight the efficiency-security trade-off for range queries in SSE. Subsequently, we propose a volume-hiding range SSE scheme that ensures efficient operations on extensive datasets. Leveraging the order-weighted inverted index and bitmap structure, our scheme achieves high search efficiency while maintaining the confidentiality of the volumetric profile. To facilitate searching within large-scale datasets, we introduce a partitioning strategy that divides a broad range into disjoint partitions and stores the information in a local binary tree. Through an analysis of the leakage function, we demonstrate the security of our proposed scheme within the ideal/real model simulation paradigm. Our experimental results further validate the practicality of our scheme with real-life large-scale datasets.