Congestion in wireless sensor networks (WSNs) is an unavoidable issue in today’s scenario, where data traffic increased to its aggregated capacity of the channel. The consequence of this turns in to overflowing of the buffer at each receiving sensor nodes which ultimately drops the packets, reduces the packet delivery ratio, and degrades throughput of the network, since retransmission of every unacknowledged packet is not an optimized solution in terms of energy for resource-restricted sensor nodes. Routing is one of the most preferred approaches for minimizing the energy consumption of nodes and enhancing the throughput in WSNs, since the routing problem has been proved to be an NP-hard and it has been realized that a heuristic-based approach provides better performance than their traditional counterparts. To tackle all the mentioned issues, this paper proposes an efficient congestion avoidance approach using Huffman coding algorithm and ant colony optimization (ECA-HA) to improve the network performance. This approach is a combination of traffic-oriented and resource-oriented optimization. Specially, ant colony optimization has been employed to find multiple congestion-free alternate paths. The forward ant constructs multiple congestion-free paths from source to sink node, and backward ant ensures about the successful creation of paths moving from sink to source node, considering energy of the link, packet loss rate, and congestion level. Huffman coding considers the packet loss rate on different alternate paths discovered by ant colony optimization for selection of an optimal path. Finally, the simulation result presents that the proposed approach outperforms the state of the art approaches in terms of average energy consumption, delay, and throughput and packet delivery ratio.

中文翻译：

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下一代无线传感器网络拥塞控制的流量和能量感知优化

在当今的场景中，无线传感器网络 (WSN) 中的拥塞是一个不可避免的问题，其中数据流量增加到其信道的聚合容量。这样做的后果是每个接收传感器节点的缓冲区溢出，最终丢弃数据包，降低数据包交付率，并降低网络的吞吐量，因为重传每个未确认的数据包在能量方面并不是优化的解决方案用于资源受限的传感器节点。路由是最小化节点能量消耗和提高 WSN 吞吐量的最优选方法之一，因为路由问题已被证明是 NP-hard 并且已经意识到基于启发式的方法比他们的传统同行。为了解决所有提到的问题，本文提出了一种使用霍夫曼编码算法和蚁群优化（ECA-HA）的有效拥塞避免方法来提高网络性能。这种方式是面向流量和面向资源的优化相结合。特别地，蚁群优化已被用于寻找多个无拥塞的替代路径。前向蚂蚁构造多条从源节点到宿节点的无拥塞路径，后向蚂蚁考虑链路能量、丢包率和拥塞程度，确保成功创建从宿节点到源节点的路径。霍夫曼编码考虑了蚁群优化发现的不同替代路径上的丢包率，以选择最佳路径。最后，