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The Internet of Things (IoT) has become a transformative technological infrastructure, serving as a benchmark for automating and standardizing various activities across different domains to reduce human effort, especially in hazardous environments. In these networks, devices with embedded sensors capture valuable information about activities and report it to the nearest server. Although IoT networks are exceptionally useful in solving real-life problems, managing duplicate data values, often captured by neighboring devices, remains a challenging issue. Despite various methodologies reported in the literature to minimize the occurrence of duplicate data, it continues to be an open research problem. This paper presents a sophisticated data aggregation approach designed to minimize the ratio of duplicate data values in the refined set with the least possible information loss in IoT networks. First, at the device level, a local data aggregation process filters out outliers and duplicates data before transmission. Second, at the server level, a dynamic programming-based non-metric method identifies the longest common subsequence (LCS) among data from neighboring devices, which is then shared with the edge module. Simulation results confirm the approach’s exceptional performance in optimizing the bandwidth, energy consumption, and response time while maintaining high accuracy and precision, thus significantly reducing overall network congestion.

Wireless Sensor Networks (WSNs) inherently are resource-constrained in terms of available energy, bandwidth, processing power and memory space. In these networks, congestion occurs when the incoming traffic load surpasses the available capacity of the network. There are various factors that lead to congestion in WSNs such as buffer overflow, varying rates of transmission, a many-to-one communication paradigm, channel contention and interference. Congestion leads to depletion of the nodes energy, deterioration of network performance and an increase in network latency and packet loss. As a result, energy-efficient and reliable state-of-the art congestion control protocols need to be designed to detect, notify and control congestion effectively. In this paper, we present a review of the latest state-of-the-art congestion control protocols. We analyze these protocols from various perspectives such as, their deployed environments, internal operational mechanisms, their advantages and disadvantages. Depending on their inherent nature of control mechanisms, these protocols are classified either as traffic-based congestion control or resource-based congestion control. Based on our analysis, we further subdivided these protocols based on their hop-by-hop and end-to-end delivery modes.

In these days embedded system have an important role in different Fields and applications like Network embedded system , Real-time embedded systems which supports the mission-critical domains, mostly having the time constraints, Stand-alone systems which includes the network router etc. A great deployment in the processors made for completing the demanding needs of the users. There is also a large-scale deployment occurs in sensor networks for providing the advance facilities, for handled such type of embedded systems a specific operating system must provide. This paper presents some software infrastructures that have the ability of supporting such types of embedded systems.