In wireless sensor networks data, which get generated, is not always same; some data may be more important than others and having different priorities. As deployment sizes and data rates grow, congestion becomes a major problem in these networks. The congestion results in arbitrary dropping of data packets that reduce the overall network throughput. In this paper, we discuss the various parameters (root causes of congestion), which help us to avoid and control the congestion in the wireless sensor network. The parameters consider in this paper are input/output flow rate, node density, non-linear or unbalanced distribution of load, processing / service time of node and reliability of network.

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The internet of things-integrated sensor nodes (IoT-WSN) is widely adopted in variety of applications such as fire detection, gas leakage detection in industry, earthquake detection, vibrating locations on flyover, weather monitoring, and many more wherein highest value is required in time to serve the abnormal areas with highest priority. The query-based information extraction has increased attention of many researchers working on increasing the network lifetime of the IoT-WSN. In resource-constraint IoT-WSN, executing the requests (in the form of queries) in time with minimum energy consumption is the main requirement and focus. The query processing at sink node in collaboration with neighboring nodes and then finding the top-k values for data aggregation is the most challenging job in IoT-WSN. This chapter investigates the various query-based approaches and improvements in the query data availability. The chapter also presents a comparative analysis that gives an idea of different aspects and applications of query-based schemes.