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Anna Scaglione
Arizona State University
430Publications
45H-index
10.5kCitations
Publications 430
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#1Shammya Shananda Saha (ASU: Arizona State University)H-Index: 2
#2Eran SchweitzerH-Index: 1
Last.Nathan G. JohnsonH-Index: 7
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This work proposes a framework to generate synthetic distribution feeders mapped to real geo-spatial topologies using available OpenStreetMap data. The synthetic power networks can facilitate power systems research and development by providing thousands of realistic use cases. The location of substations is taken from recent efforts to develop synthetic transmission test cases, with underlying real and reactive power in the distribution network assigned using population information gathered from...
#2Nurullah KarakocH-Index: 1
Last.Anna ScaglioneH-Index: 45
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With the emergence of small cell networks and fifth-generation (5G) wireless networks, the backhaul becomes increasingly complex. This study addresses the problem of how a central SDN orchestrator can flexibly share the total backhaul capacity of the various wireless operators among their gateways and radio nodes (e.g., LTE enhanced Node Bs or Wi-Fi access points). In order to address this backhaul resource allocation problem, we introduce a novel backhaul optimization methodology in the context...
#1Or Shalom (BIU: Bar-Ilan University)
#2Amir Leshem (BIU: Bar-Ilan University)H-Index: 24
Last.Anna Scaglione (ASU: Arizona State University)H-Index: 45
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This paper describes a distributed statistical estimation problem, corresponding to a network of agents. The network may be vulnerable to data injection attacks, in which attackers control legitimate nodes in the network and use them to inject false data. We have previously shown [1] that the detection metric by Wu et. al in [2], is vulnerable to sophisticated attacks where the attacker mixes normal behaviour and false data injection. In this paper we propose a novel metric that can be computed ...
#1Raksha Ramakrishna (ASU: Arizona State University)H-Index: 1
#2Anna Scaglione (ASU: Arizona State University)H-Index: 45
While the graph theoretic properties pertaining to the electrical grid are well known, the field of graph signal processing offers new insights and understanding about the measurements from the electrical grid. In this paper we establish that voltage measurements are the result of a low-rank excitation to a low-pass graph filter. Then, we illustrate the identification of community structure in the electrical grid since the excitations are low-rank in nature. Proposed algorithm for community dete...
May 1, 2019 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Hoi-To Wai (CUHK: The Chinese University of Hong Kong)H-Index: 8
#2Yonina C. Eldar (Stanford University)H-Index: 68
Last.Anna Scaglione (ASU: Arizona State University)H-Index: 45
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Many recent works on inference of graph structure assume that the graph signals are fully observable. For large graphs with thousands or millions of nodes, this entails high complexity on the data collection and processing steps. Here, we study a community inference problem on partially observed (sub-sampled) graph signals which sidesteps topology inference, while revealing the coarse structure of the graph directly. Two variants of the inference task are studied: (i) a blind method that infers ...
May 1, 2019 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Raksha Ramakrishna (ASU: Arizona State University)H-Index: 1
#2Anna Scaglione (ASU: Arizona State University)H-Index: 45
Last.Cihan Tepedelenlioglu (ASU: Arizona State University)H-Index: 26
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In this paper, we present a distributed array processing algorithm to analyze the power output of solar photo-voltaic (PV) installations, leveraging the low-rank structure inherent in the data to estimate possible faults. Our multi-agent algorithm requires near-neighbor communications only and is also capable of jointly estimating the common low rank cloud profile and local shading of panels. To illustrate the workings of our algorithm, we perform experiments to detect shading faults in solar PV...
May 1, 2019 in ICASSP (International Conference on Acoustics, Speech, and Signal Processing)
#1Nikhil Ravi (ASU: Arizona State University)
#2Anna Scaglione (ASU: Arizona State University)H-Index: 45
Last.Angelia Nedic (ASU: Arizona State University)H-Index: 38
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In this paper, we consider the problem of solving a distributed (consensus-based) optimization problem in a network that contains regular and malicious nodes (agents). The regular nodes are performing a distributed iterative algorithm to solve their associated optimization problem, while the malicious nodes inject false data with a goal to steer the iterates to a point that serves their own interest. The problem consists of detecting and isolating the malicious agents, thus allowing the regular ...
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