Task allocation in group of nodes in the IoT: A consensus approach

The realization of the Internet of Things (IoT) paradigm relies on the implementation of systems of cooperative intelligent objects with key interoperability capabilities. In order for objects to dynamically cooperate to IoT applications' execution, they need to make their resources available in a flexible way. However, available resources such as electrical energy, memory, processing, and object capability to perform a given task, are often limited. Therefore, resource allocation that ensures the fulfilment of network requirements is a critical challenge. In this paper, we propose a distributed optimization protocol based on consensus algorithm, to solve the problem of resource allocation and management in IoT heterogeneous networks. The proposed protocol is robust against links or nodes failures, so it's adaptive in dynamic scenarios where the network topology changes in runtime. We consider an IoT scenario where nodes involved in the same IoT task need to adjust their task frequency and buffer occupancy. We demonstrate that, using the proposed protocol, the network converges to a solution where resources are homogeneously allocated among nodes. Performance evaluation of experiments in simulation mode and in real scenarios show that the algorithm converges with a percentage error of about±5% with respect to the optimal allocation obtainable with a centralized approach

Energy consumption management in Smart Homes: An M-Bus communication system

Energy consumption management in Smart Home environments relies on the implementation of systems of cooperative intelligent objects named Smart Meters. In order for devices to cooperate to smart metering applications' execution, they need to make their information available. In this paper we propose a framework that aims at managing energy consumption of controllable appliances in groups of Smart Homes belonging to the same neighbourhood or condominium. We consider not only electric power distribution, but also alternative energy sources such as solar panels. We define a communication paradigm based on M-Bus for the acquisition of relevant data by managing nodes. We also provide a lightweight algorithm for the distribution of the available alternative power among houses. Performance evaluation of experiments in simulation mode prove that the proposed framework does not jeopardise the lifetime of Smart Meters, particularly in typical situations where managed devices do not continuously turn on and off

Objects that agree on task frequency in the IoT: A lifetime-oriented consensus based approach

Some key features of the end-systems impact on the way communications happen within the IoT: available objects' resources are limited, different objects may provide the same information (e. g. sense the same physical measure), the number of nodes in the IoT is quickly overcoming the number of Internet hosts with greater reliability issues. This entails for a new paradigm of communication with respect to those characterizing the traditional Internet. Before providing the required information about the physical world, objects coordinate with the other objects in groups and provide a unified service to the external world (the application that requires the service), with the intent to distribute the load of the requested services according to specific community defined rules, which could be: lifetime extension, QoS (Quality of Service) maximization, reward maximization, or others. In this paper other than describing the characteristics of this new communication paradigm and challenges it is called to address, we also propose a first solution for its implementation that relies on a distributed optimization protocol based on the consensus algorithm. Results of simulations and real experiments are also presented that show the viability in implementing the new communication model in a distributed way

Estimation of physical layer performance in WSNs exploiting the method of indirect observations

Wireless Sensor Networks (WSNs) are used in many industrial and consumer applications that are increasingly gaining impact in our day to day lives. Still great efforts are needed towards the definition of methodologies for their effective management. One big issue is themonitoring of the network status, which requires the definition of the performance indicators and methodologies and should be accurate and not intrusive at the same time. In this paper, we present a new process for the monitoring of the physical layer in WSNs making use of a completely passive methodology. From data sniffed by external nodes, we first estimate the position of the nodes by applying the Weighted Least Squares (WLS) to the method of indirect observations. The resulting node positions are then used to estimate the status of the communication links using the most appropriate propagation model. We performed a significant number of measurements on the field in both indoor and outdoor environments. From the experiments, we were able to achieve an accurate estimation of the channel links status with an average error lower than 1 dB, which is around 5 dB lower than the error introduced without the application of the proposed method

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Golden ratio and self-similarity in swimming: breast-stroke and the back-stroke

Introduction: Dynamics-on-graph concepts and generalized finite-length Fibonacci sequences have been used to characterize, from a temporal point of view, both human walking & running at a comfortable speed and front-crawl & butterfly swimming strokes at a middle/long distance pace. Such sequences, in which the golden ratio plays a crucial role to describe self-similar patterns, have been found to be subtly experimentally exhibited by healthy (but not pathological) walking subjects and elite swimmers, in terms of durations of gait/stroke-subphases with a clear physical meaning. Corresponding quantitative indices have been able to unveil the resulting hidden time-harmonic and self-similar structures. Results: In this study, we meaningfully extend such latest findings to the remaining two swimming strokes, namely, the breast-stroke and the back-stroke: breast-stroke, just like butterfly swimming, is highly technical and involves the complex coordination of the arm and leg actions, while back-stroke is definitely similar to front-crawl swimming. An experimental validation with reference to international-level swimmers is included