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Nodes in a wireless sensor network are normally constrained by hardware and environmental conditions and face challenges of reduced computing capabilities and system security vulnerabilities. This fact calls for special requirements for network protocol design, security assessment models, and energy-efficient algorithms. Data aggregation is an effective energy conservation technique, which removes redundant information from the data aggregated from neighbor sensor nodes. How to further improve the effectiveness of data aggregation plays an important role in improving data collection accuracy and reducing the overall network energy consumption. Unfortunately, sensor nodes are normally deployed in an open environment and thus are subject to various attacks conducted by adversaries. Consequently, data aggregation brings new challenges to wireless sensor network security. In this article, we propose a novel secure data aggregation solution based on autoregressive integrated moving average model, a time series analysis technique, to prevent private data from being learned by adversaries. We leverage the autoregressive integrated moving average model to predict the data volume in sensor nodes, and update and synchronize the model as needed. The experimental results demonstrate that our model provides accurate predictions and that, compared with competing methods, our solution achieves better security, lower computation and communication costs, and better flexibility. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks are a key element of the Internet of Things since they are one of the most interesting pervasive systems. However, they are battery-powered, so energy efficiency represents one of the primary design challenges to address. This goal can be primarily achieved through an optimization of the communication procedure, which is the most power-consuming component of a WSN node. Nevertheless, the poor resources of the embedded devices usually limit the complexity of protocol solutions, which thus are not sufficient to reach satisfactory results. For this reason, the current trend aims at integrating both hardware and software solutions. In this work, a cross-layer solution, based on the combined use of a duty-cycling MAC protocol and a reconfigurable beam-steering antenna, is presented and validated. It significantly reduces the nodes’ power consumption by exploiting scheduling techniques and directional communications. Specifically, a MAC scheduler manages the activation of the antenna sectors based on information coming from both MAC and network layers. This way, node awakenings occur only when an actual communication has to take place and only the interested antenna sector is activated. The effectiveness of the proposed cross-layer approach has been evaluated through OMNeT++ simulation tool. [ABSTRACT FROM AUTHOR]