2,349 research outputs found

    Adaptive data synchronization algorithm for IoT-oriented low-power wide-area networks

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    The Internet of Things (IoT) is by now very close to be realized, leading the world towards a new technological era where people’s lives and habits will be definitively revolutionized. Furthermore, the incoming 5G technology promises significant enhancements concerning the Quality of Service (QoS) in mobile communications. Having billions of devices simultaneously connected has opened new challenges about network management and data exchange rules that need to be tailored to the characteristics of the considered scenario. A large part of the IoT market is pointing to Low-Power Wide-Area Networks (LPWANs) representing the infrastructure for several applications having energy saving as a mandatory goal besides other aspects of QoS. In this context, we propose a low-power IoT-oriented file synchronization protocol that, by dynamically optimizing the amount of data to be transferred, limits the device level of interaction within the network, therefore extending the battery life. This protocol can be adopted with different Layer 2 technologies and provides energy savings at the IoT device level that can be exploited by different applications

    Optimal Error Rates for Interactive Coding II: Efficiency and List Decoding

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    We study coding schemes for error correction in interactive communications. Such interactive coding schemes simulate any nn-round interactive protocol using NN rounds over an adversarial channel that corrupts up to ρN\rho N transmissions. Important performance measures for a coding scheme are its maximum tolerable error rate ρ\rho, communication complexity NN, and computational complexity. We give the first coding scheme for the standard setting which performs optimally in all three measures: Our randomized non-adaptive coding scheme has a near-linear computational complexity and tolerates any error rate δ<1/4\delta < 1/4 with a linear N=Θ(n)N = \Theta(n) communication complexity. This improves over prior results which each performed well in two of these measures. We also give results for other settings of interest, namely, the first computationally and communication efficient schemes that tolerate ρ<27\rho < \frac{2}{7} adaptively, ρ<13\rho < \frac{1}{3} if only one party is required to decode, and ρ<12\rho < \frac{1}{2} if list decoding is allowed. These are the optimal tolerable error rates for the respective settings. These coding schemes also have near linear computational and communication complexity. These results are obtained via two techniques: We give a general black-box reduction which reduces unique decoding, in various settings, to list decoding. We also show how to boost the computational and communication efficiency of any list decoder to become near linear.Comment: preliminary versio
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