We propose a number of selective-splitting and cache-maintenance algorithms to reduce the computational complexity of associative-client caches and network load. Our selective-splitting algorithms selectively split query-intersected semantic regions based on the relative region access-latency or relative region size in a semantic data caching and replacement model. Our cache-maintenance algorithms are set up for studying a variety of design issues in synchronizing associative-client caches. We analyzed the performance of our proposed algorithms in a network environment. Results from our study show that the selective-splitting algorithms reduce the number of splitting operations by 80% in most cases, and the avoidance-based maintenance algorithms outperform the detection-based maintenance algorithms not only in reducing the network traffic but also in rendering consistent performance under various experimental variances.