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Data aggregation, gathering and gossiping are all vital communication tasks in wireless sensor networks (WSNs). When all networking devices are always active, scheduling algorithms for these communication tasks have been extensively investigated under both the protocol and physical interference models. However, wireless devices usually switch between the sleep state and the active state for the…

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis.…

Researchers have associated agriculture and food processing with adverse environmental impacts like; falls in the underground freshwater table, energy consumption, and high carbon emission. These factors have the worst effect on developing countries. Therefore, there is a need for on-demand food production techniques that require minimum resource utilization. For these reasons, scientists are now focusing…

Over the last decades, numerous distributed consensus-based algorithms have found a wide application as a complementary mechanism for data aggregation in wireless sensor networks. In this paper, we provide an analysis of the generalized Metropolis-Hastings algorithm for data aggregation with a fully-distributed stopping criterion. The goal of the implemented stopping criterion is to effectively bound…

Many real-life applications based on the wireless sensor networks are equipped with data aggregation mechanisms for suppressing or even overcoming negative environmental effects and data redundancy. In this paper, we present an extended analysis of the linear average consensus algorithm for distributed summing with bounded execution over wireless sensor networks. We compare a centralized and…

With the advancement in the field of Internet-of-Things (IoT), event monitoring applications have rapidly evolved from a simple event data acquisition towards predictive event analytics involving multi-sensory data aggregation in a distributed environment. Existing event monitoring schemes are mainly relying on ine_cient centralized processing mechanism, which may lead to the common single-point of failure for…