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Real world data aggregation and delivery in Internet of Things (IoT) technology are essential to predict and retrieve target data in short time so that the end user feels no delay but ensures a high quality of information. In addition to habitat monitoring and disaster management, these networks have a wide range of other uses, including security and military operations. The processing capabilities of sensor nodes are restricted due to the fact that they have a limited battery life and hence a modest size and processing capacity. WSNs are also susceptible to failure as a result of the limited battery power available. In WSNs, data aggregation is practiced as an energy efficient strategy to reduce computing and transmission latency. It is because of sensor node distribution density that shares the same data at a time data redundancy comes to exist. It is possible to reduce redundancy by adopting a suitable machine learning algorithm while executing the data aggregation process. Researchers are still chasing behind algorithms and modeling strategies effectively to ease the process of developing an effective and acceptable data aggregation strategy from existing wireless sensor network (WSN) models. A three stage framework is proposed for an efficient data aggregation mechanism, and the stages are Modified LEACH, extreme learning machines (ELM), adaptive Kalman filter, and Bi-LSTM. This experiment result shows better performance than the existing methods. [ABSTRACT FROM AUTHOR]

3G network is a widely employed technology in today's world. 3G network efficiently supports wireless traffic in static as well as mobile topology. This network is used in transmitting various types of traffic such data, audio, video, etc. Nowadays, video transmission has become a major part of the overall traffic due to its higher demands. Video streaming is used in several applications and resource allocation for this purpose is critical as the channel conditions in 3G network are highly varying. In this paper, we propose to develop a Resource Allocation technique for Video Streaming Using Channel Condition Prediction in 3G networks. In this technique, the channel conditions are predicted and then the video services are provided. To reduce the load on the system, an optimization model is employed. [ABSTRACT FROM AUTHOR]

Many methods have been introduced to establish a secure multicast communication between different nodes in the network, but these methods have not achieved the secured data transfer. This article explains the most significant way for the key distribution among the nodes, so that any outside infringement won't be able to access the data as well as the key. It uses different algorithms for secure data transfer. Self-healing technique is being used so that when the key is lost, the group members can recover the key by themselves and unnecessary interactions with the group manager can be avoided, which saves additional cost and reduces traffic. [ABSTRACT FROM PUBLISHER]

In wireless sensor networks the Nodes are mobility enabled, since the communication among nodes fully depend on the distance between nodes and time taken to transmit the data packets. Any routing protocols suggesting the shortest path based route formation is the best concept for fast and safe transmission and it improves the QoS of the WSN in terms of speed and accuracy. Without locating the nodes and the accurate distance, the shortest path finding is inefficient. In this paper a novel Localization approach is introduced to localize the nodes accurately with the help of Beacon Nodes in the network. The simulation results produced better performance than the existing systems. [ABSTRACT FROM AUTHOR]