mapper/batcher: serialize per-node work to prevent out-of-order delivery

processBatchedChanges queued each pending change for a node as a
separate work item. Since multiple workers pull from the same channel,
two changes for the same node could be processed concurrently by
different workers. This caused two problems:

1. MapResponses delivered out of order — a later change could finish
   generating before an earlier one, so the client sees stale state.
2. updateSentPeers and computePeerDiff race against each other —
   updateSentPeers does Clear() + Store() which is not atomic relative
   to a concurrent Range() in computePeerDiff.

Bundle all pending changes for a node into a single work item so one
worker processes them sequentially. Add a per-node workMu that
serializes processing across consecutive batch ticks, preventing a
second worker from starting tick N+1 while tick N is still in progress.

Fixes #3140

hscontrol/mapper/batcher_concurrency_test.go

@@ -660,33 +660,6 @@ func TestBatcher_CloseMultipleTimes_DoubleClosePanic(t *testing.T) {
 			"Fix: add sync.Once or atomic.Bool to close()", panics)
 }
 
-// TestBatcher_QueueWorkDuringShutdown verifies that queueWork doesn't block
-// when the batcher is shutting down.
-func TestBatcher_QueueWorkDuringShutdown(t *testing.T) {
-	lb := setupLightweightBatcher(t, 3, 10)
-
-	// Close the done channel to simulate shutdown
-	close(lb.b.done)
-
-	// queueWork should not block (it selects on done channel)
-	done := make(chan struct{})
-
-	go func() {
-		lb.b.queueWork(work{
-			changes: []change.Change{change.DERPMap()},
-			nodeID:  types.NodeID(1),
-		})
-		close(done)
-	}()
-
-	select {
-	case <-done:
-		// Success - didn't block
-	case <-time.After(1 * time.Second):
-		t.Fatal("queueWork blocked during shutdown")
-	}
-}
-
 // TestBatcher_MapResponseDuringShutdown verifies that MapResponseFromChange
 // returns ErrBatcherShuttingDown when the batcher is closed.
 func TestBatcher_MapResponseDuringShutdown(t *testing.T) {