Abstract
In wireless sensor networks (WSNs), there are numerous factors that may cause network congestion problems, such as the many-to-one communication modes, mutual interference of wireless links, dynamic changes of network topology and the memory-restrained characteristics of nodes. All these factors result in a network being more vulnerable to congestion. In this paper, a cross-layer active predictive congestion control scheme (CL-APCC) for improving the performance of networks is proposed. Queuing theory is applied in the CL-APCC to analyze data flows of a single-node according to its memory status, combined with the analysis of the average occupied memory size of local networks. It also analyzes the current data change trends of local networks to forecast and actively adjust the sending rate of the node in the next period. In order to ensure the fairness and timeliness of the network, the IEEE 802.11 protocol is revised based on waiting time, the number of the node's neighbors and the original priority of data packets, which dynamically adjusts the sending priority of the node. The performance of CL-APCC, which is evaluated by extensive simulation experiments. is more efficient in solving the congestion in WSNs. Furthermore, it is clear that the proposed scheme has an outstanding advantage in terms of improving the fairness and lifetime of networks.
Highlights
Recent technology development in the fields of wireless communication and MEMS has made extensive distribution of wireless sensor networks (WSNs) become possible
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, as well as combined with network conditions and node rate within period t
Congestion has a severe influence on network performance, which results in a large number of missing packets, unfair status of network and significant wasted energy due to the repeated sending packets
Summary
Recent technology development in the fields of wireless communication and MEMS has made extensive distribution of wireless sensor networks (WSNs) become possible. The above characteristics 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. 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 period t + 1 in order to avoid the congestion.
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