Network　infrastructure　and　connectivity　in　the　Internet　of　Things　(IoT)　applications　are　becoming　increasingly　complex　and　heterogeneous,　opening　up　many　challenges　including　reliability.　Many　real-world　networks　exhibit　community　structure,　where　the　networked　devices　can　be　easily　grouped　into　sets　with　dense　internal　connections　but　sparse　connections　between　different　sets.　Examples　of　such　community-structured　networks　can　be　found　in　diverse　IoT　applications　such　as　smart　grids,　smart　cities,　and　military　systems.　Due　to　these　critical　applications,　reliability　analysis　is　of　great　significance　for　robust　and　safe　design　and　operation　of　IoT　networks.　In　this　paper,　we　present　an　efficient　binary　decision　diagram　(BDD)-based　approach　to　analyze　the　reliability　of　an　IoT　network　with　community　structure　and　subject　to　random　link　failures.　As　efficiency　of　the　BDD-based　approach　heavily　depends　on　the　ordering　of　input　variables,　we　make　novel　contributions　by　proposing　efficient　ordering　heuristics　for　individual　communities　and　the　whole　IoT　network　composed　of　multiple　communities.　Performance　of　the　proposed　ordering　heuristics　for　IoT　networks　with　either　linear　interconnection　pattern　or　random　interconnection　pattern　is　investigated.　As　demonstrated　through　comprehensive　experiments,　the　proposed　ordering　heuristics　provide　significantly　better　performance　in　model　complexity　than　the　traditional　ordering　heuristics.