In　the　past　decades,　Dynamic　Internet　of　Things　(D-IoT)　networks　have　played　a　conspicuously　more　important　role　in　many　real-life　areas,　including　disaster　relief,　environment　monitoring,　public　safety,　and　so　on,　to　rapidly　collect　information　from　the　environment　and　help　people　to　make　the　decision.　Meanwhile,　due　to　the　widespread　implementation　of　dynamic　IoT　networks,　there　exists　an　enormous　demand　on　designing　suitable　models　and　efficient　algorithms　for　fundamental　operations　in　dynamic　IoT　networks,　to　achieve　the　high　throughput　and　reliable　low-latency　communication　demands　in　6G　networks.　In　this　article,　we　first　present　a　general　dynamic　model　to　comprehensively　depict　most　of　the　dynamic　phenomena　in　IoT　networks.　Then,　based　on　the　proposed　dynamic　model,　a　distributed　scheduling　algorithm　is　proposed　to　competitively　optimize　the　Age-of-Information　(AoI)　problem　in　the　context　of　a　D-IoT　network.　We　say　our　scheduling　algorithm　is　competitive:　the　throughput　of　the　base　station　approximates　the　optimal　solution　with　constant　competitive　ratio;　and,　the　latency　for　a　packet　received　by　the　base　station　is　only　constant　times　larger　than　the　optimal　latency.　Rigorous　theoretical　analysis　and　extensive　simulations　are　presented　to　verify　the　high　throughput　and　reliable　low-latency　communications　in　our　proposed　algorithm.