In　order　to　prolong　the　lifetime,　reduce　the　energy　consumption,　and　balance　the　network　load　effectively,　a　dynamic　alliance　model　and　its　corresponding　algorithm　of　task　allocation　in　wireless　sensor　network　(WSN)　were　proposed.　This　method　described　a　cost　function　according　to　the　execution　time,　energy　consumption　and　load　balance.　Particle　swarm　optimization　was　used　to　optimize　task　allocation.　Meanwhile,　a　mutation　operator　that　could　effectively　improve　the　algorithm＇s　ability　on　global　search　and　maintained　population　diversity　was　also　introduced.　Simulation　results　show　that　the　proposed　algorithm　provides　a　good　balance　of　local　solutions　and　global　exploration,　which　results　in　a　great　decrease　of　execution　time　and　a　steady　balance　of　network　load.