The　rise　of　emerging　services　has　brought　a　rapid　growth　in　bulk　data　transfers　across　inter-datacenter　(DC)　wide　area　networks　(WANs).　To　accommodate　the　demands　of　such　services,　DC　storage　is　introduced　into　the　data-plane　path　so　that　delay-tolerant　bulk　data　can　be　temporarily　stored　and　forwarded　(SnF)　when　network　is　less　busy.　However,　the　use　of　storage　transforms　a　conventional　routing　problem　into　a　scheduling　problem,　where　spatial　routing　and　temporal　scheduling　must　be　jointly　performed.　Moreover,　the　complexity　of　the　problem　increases　exponentially　with　the　scale　of　the　network　as　well　as　the　number　of　storage　sites.　While　prior　SnF　scheduling　methods　are　effective　for　small　networks　or　for　static　traffic,　they　are　either　too　complex　or　insufficient　for　large　networks　with　dynamic　traffic.　In　this　paper,　we　study　the　performance-complexity　tradeoff　in　SnF　scheduling.　Studies　show　that　desirable　performance　can　be　attained　by　considering　a　few　alternate　routes　rather　than　dynamically　routing　over　the　entire　network　topology.　Thus,　our　proposed　SnF　scheduling　method　aims　to　decouple　the　problem　into　its　spatial　and　temporal　components,　and　then　solve　these　components　separately.　The　proposed　method　hence　has　low　complexity　while　still　achieving　high　performance.　Simulations　demonstrate　that　when　the　traffic　load　is　medium　or　higher,　the　conventional　joint　method　may　suffer　from　the　detour　issue.　In　this　case,　the　proposed　method　has　the　potential　to　outperform　the　conventional　joint　method　even　with　only　three　alternate　routes　considered　in　SnF　scheduling.