With　the　growing　prominence　of　the　Internet　of　Vehicles　(IoV),　there　is　an　unprecedented　generation　of　vehicular　data,　which　harbors　immense　potential　for　diverse　applications.　Considering　the　convergence　of　blockchain　technology　and　IoV,　blockchain　can　be　used　as　a　distributed　ledger　to　establish　a　decentralised　and　autonomous　trading　platform　for　IoV　networks.　However,　the　limitations　in　the　power　and　computational　capacities　of　IoV　devices　hinder　their　direct　involvement　in　the　Proof-of-Work　(PoW)　process.　Addressing　this　challenge,　offloading　the　computational　demands　of　PoW　to　Mobile　Edge　Computing　(MEC)　servers　emerges　as　a　feasible　solution.　This　scenario　has　prompted　us　to　conceptualize　the　computational　resource　management　in　blockchain　consensus　as　a　two-layered　resource　game,　aimed　at　optimizing　both　the　profits　of　computing　power　providers　and　the　utility　for　vehicles.　In　the　Blockchain　Market　Layer　subgame,　we　employ　a　game-theoretic　framework　to　analyze　the　interactions　between　MEC　servers　and　vehicles　within　a　PoW-based　blockchain　network.　To　optimize　the　system　utility,　we　introduce　a　centralized　evolutionary　game-based　pool　selection　algorithm.　Simultaneously,　in　the　Edge　Cloud　Network　Layer　subgame,　a　reverse　auction　algorithm　is　implemented　to　align　the　computing　power　supply　with　the　demand　within　the　blockchain　market.　Here,　the　cloud　data　center　functions　as　the　seller　of　computing　power,　while　the　edge　servers　aggregate　the　computing　demand　from　IoV　devices.　A　broker　is　then　tasked　with　the　allocation　and　pricing　of　computing　resources,　in　accordance　with　the　bids,　ensuring　adherence　to　economic　principles　of　authenticity　and　individual　rationality.　Simulation　results　demonstrate　that　our　mechanism　enhances　system　efficiency　while　ensuring　revenue,　thereby　enabling　an　effective　distribution　of　computing　resources　between　vehicles　and　cloud　data　centers.　IEEE