A Distributed Approach for the Optimal Power Flow Problem Based on ADMM and Sequential Convex Approximations

The optimal power flow (OPF) problem, which plays a central role in operating electrical networks is considered. The problem is nonconvex and is in fact NP hard. Therefore, designing efficient algorithms of practical relevance is crucial, though their global optimality is not guaranteed. Existing semi-definite programming relaxation based approaches are restricted to OPF problems where zero duality holds. In this paper, an efficient novel method to address the general nonconvex OPF problem is investigated. The proposed method is based on alternating direction method of multipliers combined with sequential convex approximations. The global OPF problem is decomposed into smaller problems associated to each bus of the network, the solutions of which are coordinated via a light communication protocol. Therefore, the proposed method is highly scalable. The convergence properties of the proposed algorithm are mathematically substantiated. Finally, the proposed algorithm is evaluated on a number of test examples, where the convergence properties of the proposed algorithm are numerically substantiated and the performance is compared with a global optimal method.Comment: 14 page

Distributed Fault Detection with Sensor Networks using Pareto-Optimal Dynamic Estimation Method

In this paper, a distributed method for fault detection using sensor networks is proposed. Each sensor communicates only with neighboring nodes to compute locally an estimate of the state of the system to monitor. A residual is defined and suitable stochastic thresholds are designed, allowing to set the parameters so to guarantee a maximum false alarms probability. The main novelty and challenge of the proposed approach consists in addressing the individual correlations between the state, the measurements, and the noise components, thus significantly generalising the estimation methodology compared to previous results. No assumptions on the probability distribution family are needed for the noise variables. Simulation results show the effectiveness of the proposed method, including an extensive sensitivity analysis with respect to fault magnitude and measurement noise

Performances of the UNDERground SEISmic array for the analysis of seismicity in Central Italy

This paper presents the first results from the operation of a dense seismic array deployed in the underground Physics Laboratories at Gran Sasso (Central Italy). The array consists of 13 short-period, three-component seismometers with an aperture of about 550 m and average sensor spacing of 90 m. The reduced sensor spacing, joined to the spatially-white character of the background noise allows for quick and reliable detection of coherent wavefront arrivals even under very poor SNR conditions. We apply high-resolution frequency-slowness and polarization analyses to a set of 27 earthquakes recorded between November, 2002, and September, 2003, at epicentral distances spanning the 20-140 km interval. We locate these events using inversion of P- and S-wave backazimuths and S-P delay times, and compare the results with data from the Centralized National Seismic Network catalog. For the case of S-wave, the discrepancies among the two set of locations never exceed 10 km; the largest errors are instead observed for the case of P-waves. This observation may be due to the fact that the small array aperture does not allow for robust assessment of waves propagating at high apparent velocities. This information is discussed with special reference to the directions of future studies aimed at elucidating the location of seismogenetic structures in Central Italy from extended analysis of the micro-seismicity

Low complexity content replication through clustering in Content-Delivery Networks

Contemporary Content Delivery Networks (CDN) handle a vast number of content items. At such a scale, the replication schemes require a significant amount of time to calculate and realize cache updates, and hence they are impractical in highly-dynamic environments. This paper introduces cluster-based replication, whereby content items are organized in clusters according to a set of features, given by the cache/network management entity. Each cluster is treated as a single item with certain attributes, e.g., size, popularity, etc. and it is then altogether replicated in network caches so as to minimize overall network traffic. Clustering items reduces replication complexity; hence it enables faster and more frequent caches updates, and it facilitates more accurate tracking of content popularity. However, clustering introduces some performance loss because replication of clusters is more coarse-grained compared to replication of individual items. This tradeoff can be addressed through proper selection of the number and composition of clusters. Due to the fact that the exact optimal number of clusters cannot be derived analytically, an efficient approximation method is proposed. Extensive numerical evaluations of time-varying content popularity scenarios allow to argue that the proposed approach reduces core network traffic, while being robust to errors in popularity estimation

Slow earthquakes and low frequency tremor along the Apennines, Italy

This paper reviews the main observations on slow earthquakes and low frequency tremor made along the Apennines, the main seismic active zone of Italy. These observations have been made using a geodetic interferometer system operating since 1994 in the underground tunnel of Gran Sasso, central Italy, and an underground seismic array (UNDERSEIS) operating since 2002 in the same environment. The observations made in recent years indicate that both phenomena are quite rare and apparently uncorrelated. Slow earthquakes, mainly recorded in 1997 and occasionally later, have probably been caused by the activity of a shallow fault system located near the interferometers. Until now only one tremor episode characterized by low frequency content and duration of several hours has been detected in January 2004, without any correlations with the occurrence of slow or regular earthquakes. The signal to noise ratio of this event is very low, but the results of our detailed analysis show that its frequency contents and wave field characteristics are compatible with a low frequency non volcanic tremor

Improving TCP performance during the intra LTE handover

Abstract-Ensuring a seamless connection when users are moving across radio cells is essential to guarantee a high communication quality. In this paper, performance of TCP during the handover in a Long Term Evolution (LTE) network is investigated. Specifically, mobile users with high bit rates TCP services are considered, and the impacts of the intra LTE handover over their perceived throughput are studied. Due to the mobility of the users across radio cells, the high bandwidth required, and possible network congestions, it is shown that the handover may cause sudden degradation of the quality of the communication if the process is not correctly controlled. To alleviate these problems, three solutions are proposed: fast path switch, handover prediction, and active queue management. The first two solutions avoids excessive delay in the packet delivery during the handover, whereas the second solution acts at the transport network with an active queue management. Simulation results, obtained by an extension of the ns-2 simulator, show that the proposed solutions present advantages, and that the handover prediction used with the active queue management increases TCP performance significantly

Performances of the UNDERground SEISmic array for the analysis of seismicity in Central Italy

This paper presents the first results from the operation of a dense seismic array deployed in the underground Physics Laboratories at Gran Sasso (Central Italy). The array consists of 13 short-period, three-component seis- mometers with an aperture of about 550 m and average sensor spacing of 90 m. The reduced sensor spacing, joined to the spatially-white character of the background noise allows for quick and reliable detection of coher- ent wavefront arrivals even under very poor SNR conditions. We apply high-resolution frequency-slowness and polarization analyses to a set of 27 earthquakes recorded between November, 2002, and September, 2003, at epi- central distances spanning the 20-140 km interval. We locate these events using inversion of P- and S-wave back- azimuths and S-P delay times, and compare the results with data from the Centralized National Seismic Network catalog. For the case of S-wave, the discrepancies among the two set of locations never exceed 10 km; the largest errors are instead observed for the case of P-waves. This observation may be due to the fact that the small array aperture does not allow for robust assessment of waves propagating at high apparent velocities. This informa- tion is discussed with special reference to the directions of future studies aimed at elucidating the location of seismogenetic structures in Central Italy from extended analysis of the micro-seismicity

Non-adenine based purines accelerate wound healing

Wound healing is a complex sequence of cellular and molecular processes that involves multiple cell types and biochemical mediators. Several growth factors have been identified that regulate tissue repair, including the neurotrophin nerve growth factor (NGF). As non-adenine based purines (NABPs) are known to promote cell proliferation and the release of growth factors, we investigated whether NABPs had an effect on wound healing. Full-thickness, excisional wound healing in healthy BALB/c mice was significantly accelerated by daily topical application of NABPs such as guanosine (50% closure by days 2.5′.8). Co-treatment of wounds with guanosine plus anti-NGF reversed the guanosine-promoted acceleration of wound healing, indicating that this effect of guanosine is mediated, at least in part, by NGF. Selective inhibitors of the NGF-inducible serine/threonine protein kinase (protein kinase N), such as 6-methylmercaptopurine riboside abolished the acceleration of wound healing caused by guanosine, confirming that activation of this enzyme is required for this effect of guanosine. Treatment of genetically diabetic BKS.Cg-m+/+lepr db mice, which display impaired wound healing, with guanosine led to accelerated healing of skin wounds (25% closure by days 2.8′.0). These results provide further confirmation that the NABP-mediated acceleration of cutaneous wound healing is mediated via an NGF-dependent mechanism. Thus, NABPs may offer an alternative and viable approach for the treatment of wounds in a clinical setting

A distributed pareto-optimal dynamic estimation method

In this paper, a novel distributed model-based prediction method is proposed using sensor networks. Each sensor communicates with the neighboring nodes for state estimation based on a consensus protocol without centralized coordination. The proposed distributed estimator consists of a consensus-filtering scheme, which uses a weighted combination of sensors information, and a model-based predictor. Both the consensus-filtering weights and the model-based prediction parameter for all the state components are jointly optimized to minimize the variance and bias of the prediction error in a Pareto framework. It is assumed that the weights of the consensus-filtering phase are unequal for the different state components, unlike consensus-based approaches from literature. The state, the measurements, and the noise components are assumed to be individually correlated, but no probability distribution knowledge is assumed for the noise variables. The optimal weights are derived and it is established that the consensus-filtering weights and the model-based prediction parameters cannot be designed separately in an optimal way. The asymptotic convergence of the mean of the prediction error is demonstrated. Simulation results show the performance of the proposed method, obtaining better results than distributed Kalman filtering