Edge　computing　has　emerged　as　a　killer　technology　for　a　hyper-connected　world　due　to　its　distributed　architecture　and　customer-proximity　property.　Combined　edge　nodes　with　the　cloud　data　center,　a　cloud-edge　computing　paradigm　is　formed,　whose　resource　ecosystem　calls　for　competitive　pricing　and　optimal　resource　allocation.　However,　it　is　not　feasible　to　realize　global　information-based　optimization　since　some　information　is　kept　private　to　their　owners.　To　solve　this　challenge,　this　paper　develops　the　user-independent　hierarchical　reverse　game　and　the　user-assisted　hierarchical　reverse　game　to　depict　the　relationship　among　the　resource　provider,　the　resource　tenant,　and　the　resource　user.　The　aim　is　to　seek　the　optimal　strategies　for　players　without　revealing　any　private　information.　The　common　trait　of　both　games　is　to　force　the　players　to　report　the　optimal　strategies　based　on　their　actual　private　information.　This　salient　trait　can　produce　privacy-preservation　optimization　since　there　is　no　requirement　for　the　players　to　release　their　individual　information　directly,　and　the　optimal　strategies　of　other　players　can　be　deduced　naturally.　The　difference　between　the　user-independent　hierarchical　reverse　game　and　the　user-assisted　one　is　that　the　game　rules　are　stipulated　entirely　by　the　provider　and　the　tenants　(edge　nodes)　in　the　former,　while　some　game　rules　can　be　customized　according　to　the　advice　of　users　in　the　latter.　This　leads　the　user-independent　hierarchical　reverse　game　is　more　concise　and　easy　to　guarantee　the　incentive　compatibility　constraint,　while　the　user-assisted　hierarchical　reverse　game　can　attract　more　users　since　the　game　rules　can　adapt　to　their　economic　status,　requirements,　and　preferences.　©　1975-2011　IEEE.