diff --git a/README.md b/README.md
index 6cad1eb4..38a72106 100644
--- a/README.md
+++ b/README.md
@@ -70,12 +70,18 @@ You can also refer [K8S cluster application and kubectl installation](./paddle_f
 ## Benchmark task
 
 Gru4Rec [9] introduces recurrent neural network model in session-based recommendation. PaddlePaddle's Gru4Rec implementation is in https://github.com/PaddlePaddle/models/tree/develop/PaddleRec/gru4rec. An example is given in [Gru4Rec in Federated Learning](https://paddlefl.readthedocs.io/en/latest/examples/gru4rec_examples.html)
+## Release note
 
-## On Going and Future Work
-
-- Experimental benchmark with public datasets in federated learning settings.
+- v0.2.0 released 
+    - Support Kubernetes easy deployment 
+    - Add api for [LEAF](https://arxiv.org/abs/1812.01097) dataset which is in federated settings, supporting benchmark experiments. 
+    - Add FL-scheduler, acting as a central controller during the training phase. 
+    - Add FL-Submitter to support cluster task submission
+    - Add secure aggregation algorithm
+    - Support more optimizers in PaddleFL such as Adam
+    - More examples available
 
-- Federated Learning Systems deployment methods in Kubernetes.
+## On Going and Future Work
 
 - Vertical Federated Learning Strategies and more horizontal federated learning strategies will be open sourced.
 
diff --git a/README_cn.md b/README_cn.md
index e5e0a2db..aa0bf2c5 100644
--- a/README_cn.md
+++ b/README_cn.md
@@ -69,13 +69,17 @@ kubectl apply -f ./paddle_fl/examples/k8s_deployment/master.yaml
 
 Gru4Rec [9] 在基于会话的推荐中引入了递归神经网络模型。PaddlePaddle的GRU4RC实现代码在 https://github.com/PaddlePaddle/models/tree/develop/PaddleRec/gru4rec. 一个基于联邦学习训练Gru4Rec模型的示例请参考[Gru4Rec in Federated Learning](https://paddlefl.readthedocs.io/en/latest/examples/gru4rec_examples.html)
 
-
+## 版本更新
+- v0.2.0 发布
+    - 支持 Kubernetes 简易部署
+    - 添加在联邦学习设定下的[LEAF](https://arxiv.org/abs/1812.01097) 公开数据集接口，支持基准的设定 
+    - 添加 FL-scheduler, 在训练过程中充当中心控制器的角色 
+    - 添加 FL-Submitter 功能，支持集群任务部署
+    - 添加 secure aggregation 算法
+    - 支持更多的机器学习优化器，例如：Adam
+    - 增加更多的实际应用例子
 ## 正在进行的工作
 
-- 联邦学习在公共数据集上的实验基准。
-
-- kubernetes中联邦学习系统的部署方法。
-
 - 垂直联合学习策略和更多的水平联合学习策略将是开源的。
 
 ## 参考文献
diff --git a/paddle_fl/examples/submitter_demo/conf.txt b/paddle_fl/examples/submitter_demo/conf.txt
index f2f0d48d..ec3fdc87 100644
--- a/paddle_fl/examples/submitter_demo/conf.txt
+++ b/paddle_fl/examples/submitter_demo/conf.txt
@@ -7,7 +7,7 @@ monitor_cmd=
 #train_cmd=python test_hadoop.py
 
 hdfs_path=afs://xingtian.afs.baidu.com:9902
-ugi=mlarch,Fv1M87
+ugi=your_fs_name, your_ugi
 hdfs_output=/user/feed/mlarch/sequence_generator/dongdaxiang/job_44
 worker_nodes=2
 server_nodes=1
diff --git a/paddle_fl/version.py b/paddle_fl/version.py
index 2c95b454..8540fde4 100644
--- a/paddle_fl/version.py
+++ b/paddle_fl/version.py
@@ -12,5 +12,5 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 """ PaddleFL version string """
-fl_version = "0.1.11"
-module_proto_version = "0.1.11"
+fl_version = "0.2.0"
+module_proto_version = "0.2.0"