Infrastructure　in　distributed　cloud　computing　systems　(DC2Ss)　is　concurrently　shared　by　multiple　different　applications　to　flexibly　and　cost-effectively　provide　various　services.　It　becomes　a　challenge　to　maximize　the　profit　of　DC2Ss　due　to　the　fact　that　Internet　service　provider　(ISP)　bandwidth　price,　availability　of　green　energy,　electricity　price,　and　revenue　brought　by　tasks　differ　from　multiple　sites.　To　solve　it,　this　work　designs　a　Location-Sensitive　Resource　Optimization　approach　by　considering　spatial　variations　in　DC2Ss　to　achieve　profit　maximization　for　DC2Ss　by　optimizing　ISP　and　server　resources.　This　work　formulates　the　profit　maximization　problem　as　convex　optimization　and　solved　with　the　interior　point　method.　Realistic　data-based　simulations　prove　that　higher　profit　and　throughput　are　achieved　than　two　widely　used　approaches.