Utility Optimization of Federated Learning with Differential Privacy

Algorithm 2

Client choose.

	Input:, number of participant selected ,
	Output: Clients chosen
(1)	for client in client list do
(2)	score = evaluate client(D)
(3)	score list.add(score)
(4)	end
(5)	p_list = calculate_p(score list)
(6)	sort(p_list)
(7)	calculate p_threshold()
(8)	for p in p_list do
(9)	ifthen
(10)
(11)	end
(12)	end
(13)	return