## 1 Introduction  
Recent technology development in the fields of wireless communication and MEMS has made extensive distribution of wireless sensor networks (WSNs) become possible. It is obvious that WSNs are reliable, accurate, flexible, inexpensive, easy to deploy and have other excellent features. As such, they have potential applications in many areas. For instance, monitoring is one of the most important applications of WSNs, such as the monitoring of agricultural crops, buildings, water quality, etc. These types of sensor networks have the characteristics of centralized data collection, multi-hop data transmission, many-to-one flow patterns, as well as increased data flow brought about by contingency. The above characteristics easily lead to the part or overall congestion of WSNs, which seriously influences the quality of the service of networks [1]. This can include increased delays in transmitting information and the loss of data packets. It also leads to repeated data sending that further increases the flow of the network, which wastes valuable energy, bandwidth and other network resources.  
A traditional wired network [2] merely affords a transmission platform for data. It adheres to the end-to-end design concept and the intermediate nodes are only responsible for retransmitting data. However, WSNs are different from wired networks in that they are data-centered networks and the intermediate nodes also process data packet; in addition, the physical equipment of the nodes is often subject to destruction and has limited energy. Also, the wireless channel is vulnerable to be interfered with by other transmission signals. All the characteristics mentioned above increase the difficulty of controlling the congestion of WSNs. Therefore, the traditional network congestion control schemes, such as TCP, UDP, etc. cannot meet the requirements of WSNs, which makes the research work on congestion for WSNs more significant and challenging.  
Consequently, it is necessary to efficiently control the data transmission of WSNs, which aims at avoiding or properly relieving the occurrence of network's congestion. To be integrated with network congestion and fairness, a cross-layer active predictive congestion control scheme is proposed, which is based on the occupied node memory and data flow trends of local network (grid), as well as combined with network conditions and node rate within period \(t\). It aims at predicting the inputting and outputting rates of node within the next period \(t+1\) in order to avoid the congestion. The fairness of network and the timeliness of data packets are also taken into account by the design of cross-layer scheme.  
The remainder of this paper is organized as follows. Section 2 introduces the related work including typical congestion control protocols. Section 3 provides system architecture and basic models of WSN for later analysis. In Section 4, the proposed scheme is presented in detail, which includes control methods of congestion in node-level and system-level, as well as the revised IEEE 802.11 protocol. Section 5 does the specific analysis based on each performance of CL-APCC. The performance of CL-APCC is mainly evaluated in Section 6. Finally, in Section 7, we make some concluding remarks and outline some future work.