V. Prasanna

V. Prasanna
University of Southern California | USC · Department of Electrical Engineering

About

762
Publications
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15,654
Citations

Publications

Publications (762)
Article
In developing countries, reliable electricity access is often undermined by the absence of supply from the national power grid and/or load shedding. To alleviate this problem, smart micro-grid (SMG) networks that are small scale distributed electricity provision networks composed of individual electricity providers and consumers, are being increasi...
Chapter
Enormous amount of data from physical objects, such as devices comprising Internet of Things (IoT), is being made available through Web APIs on a daily basis. Manual discovery and integration of relevant data sources can be cumbersome. A unified view of relevant data sources is desirable for creating applications for monitoring and decision making....
Article
The combination of data, semantics, and the Web has led to an ever growing and increasingly complex body of semantic data. Accessing such structured data requires learning formal query languages, such as SPARQL, which poses significant difficulties for non-expert users. To date, many interfaces for querying Ontologies have been developed. However,...
Article
Sketch, a highly accurate data stream summarization technique, has gained much interest in the research community in recent years. Because of its sub-linear memory complexity, Sketch-based techniques consume significantly less memory than the traditional per-item-state techniques for processing high throughput data streams. One of the major applica...
Article
Full-text available
PageRank is a fundamental link analysis algorithm and a key representative of the performance of other graph algorithms and Sparse Matrix Vector (SpMV) multiplication. Calculating PageRank on sparse graphs generates large amount of random memory accesses resulting in low cache line utilization and poor use of memory bandwidth. In this paper, we pre...
Conference Paper
Full-text available
The k-truss of a graph is a subgraph such that each edge is tightly connected to the remaining elements in the k-truss. The k-truss of a graph can also represent an important community in the graph. Finding the k-truss of a graph can be done in a polynomial amount of time, in contrast finding other subgraphs such as cliques. While there are numerou...
Article
Full-text available
Mitigating Supply-Demand mismatch is critical for smooth power grid operation. Traditionally, load curtailment techniques such as Demand Response (DR) have been used for this purpose. However, these cannot be the only component of a net-load balancing framework for Smart Grids with high PV penetration. These grids can sometimes exhibit supply surpl...
Conference Paper
In this paper, we develop novel parallel circuit designs for calculating the bit reversal. To perform bit reversal on 2n data words, the designs take 2k (k <n) words as input each cycle. The circuits consist of concatenated single-port buffers and 2-to-1 multiplexers and use minimum number of registers for control. The designs consume minimum numbe...
Article
Machine learning (ML) algorithms have been shown to be effective in classifying a broad range of applications in the internet traffic. In this paper, we propose algorithms and architectures to realize online traffic classification using flow level features. First, we develop a traffic classifier based on C4.5 decision tree algorithm and Entropy-MDL...
Conference Paper
Accurate crime forecasting can allow law enforcement to more effectively plan their resource allocation such as patrol routes and placements. We study the effectiveness of traditional regression approaches in forecasting crime occurrences in Portland, Oregon. We divide the area of interest into equally spaced cells and investigate the spatial autoc...
Article
A summary of contributions made by significant papers from the first 25 years of the Field-Programmable Logic and Applications conference (FPL) is presented. The 27 papers chosen represent those which have most strongly influenced theory and practice in the field.
Conference Paper
Choosing the most profitable wells for steam jobs is of high value given the cost and resources required for the procedure. To find the best candidates, we develop a system with two parts: i) An autoencoder to reduce the dimensionality of input data, ii) A kernel regression to predict the production gain. We show the benefit of application of autoe...
Article
Full-text available
Demand Response (DR) is a widely used technique to minimize the peak to average consumption ratio during high demand periods. We consider the DR problem of achieving a given curtailment target for a set of consumers equipped with a set of discrete curtailment strategies over a given duration. An effective DR scheduling algorithm should minimize the...
Article
Full-text available
The accurate estimation of system state variables at buses in the power-grid is crucial for determining the operational state of the power system. Spoofing attacks on meters at buses can bypass bad data detectors in Supervisory Control and Data Acquisition (SCADA) systems and undetectably manipulate state estimates. Existing methods for protection...
Article
Prosumers or proactive consumers are steadily on the rise in emerging Smart Grid systems. These consumers, apart from their traditonal role of using energy from the grid, also are actively involved in individually transferring stored energy from renewable sources such as wind and solar, to the grid. The large-scale integration of renewable generati...
Article
Full-text available
Often in marketing, political campaigns and social media, two competing products or opinions propagate over a social network. Studying social influence in such competing cascade scenarios enables building effective strategies for maximizing the propagation of one process by targeting the most “influential” nodes in the network. The majority of prio...
Conference Paper
Accurate estimation of complex voltage phase angles at buses in the power-grid is crucial for determining the operational state of the power system. Existing methods for protection of the state estimate of critical buses against data injection attacks focus on design time assuming a static set of critical buses. We formulate a set of optimal protec...
Article
Detecting and responding to real-world events is an integral part of any enterprise or organization, but Semantic Computing has been largely underutilized for complex event processing (CEP) applications. A primary reason for this gap is the difference in the level of abstraction between the high-level semantic models for events and the low-level ra...
Conference Paper
Subgraph isomorphism is a fundamental graph problem with many applications. Due to its NP-Hard nature, subgraph isomorphism in large dynamic graphs is considered as a challenging problem. In this paper, we present a distributed graph pruning algorithm (D-IDS) for dynamic graphs to enable efficient subgraph isomorphism. D-IDS continuously maintains...
Article
The widespread monitoring of electricity consumption due to increasingly pervasive deployment of networked sensors in urban environments has resulted in an unprecedentedly large volume of data being collected. Particularly, with the emerging Smart Grid technologies becoming more ubiquitous, real-time and online analytics for discovering the underly...
Article
Full-text available
Emerging applications in Internet of Things (IoT) and Cyber-Physical Systems (CPS) present novel challenges to Big Data platforms for performing online analytics. Ubiquitous sensors from IoT deployments are able to generate data streams at high velocity, that include information from a variety of domains, and accumulate to large volumes on disk. Co...
Article
Online set intersection operations have been widely used in network processing tasks, such as Quality of Service differentiation, firewall processing, and packet/traffic classification. The major challenge for online set intersection is to sustain line-rate processing speed; accelerating set intersection using state-of-the-art hardware devices is o...
Conference Paper
We introduce intervention optimization as a new area of exploration for data mining research. Interventions are events designed to impact a corresponding time series. The task is to maximize the impact of such events by training a model on historical data. We propose PRIMER as a new regression-rule learning system for identifying sets of event feat...
Article
Full-text available
FPGAs have been widely used for accelerating various applications. For many data intensive applications, the memory bandwidth limits the performance. 3D memories with through-silicon-via connections provide potential solutions to the latency and bandwidth limitations. In this paper, we revisit the classic 2D FFT problem to evaluate the performance...
Article
In the context of networking, a heavy hitter is an entity in a data stream whose amount of activity (such as bandwidth consumption or number of connections) is higher than a given threshold. Detecting heavy hitters is a critical task for network management and security in the Internet and data centers. Data streams in modern network usually contain...
Conference Paper
Full-text available
Several applications including community detection in social networks and discovering correlated genes involve finding large subgraphs of high density. We propose the problem of finding the largest subgraph of a given density. The problem is a generalization of the Max-Clique problem which seeks the largest subgraph that has an edge density of 1. W...
Conference Paper
String and regular expression pattern matching is an integral part of intrusion detection systems to detect potential threats. YARA is a pattern matching framework to identify malicious content by defining complex patterns and signatures. Software implementations of YARA on CPU do not meet the throughput requirements of core networks. We present a...
Conference Paper
Gas compressor failures are frequently caused by breakdown of valves. Since production is dependent on rotating equipment, it is useful to minimize downtime caused by such valve failures, and try to predict them in advance. This is a challenging problem, which we address using Big Data analysis of the data gathered by a large number of sensors depl...
Article
Cyber-physical systems (CPSs) integrate computation, communication, and physical capabilities to interact with the physical world and humans. In this paper, we develop a novel strategic resource availability management (STREAM) system to improve information integrity and availability in an energy constrained CPS environment under the presence of ma...
Conference Paper
Determining voltage phase angles of buses in a Smart Grid is a critical operation in the power system state estimation process. Invalid state estimate of strategic buses can cause a severe socioeconomic impact. In this paper, we present an optimal protection scheme to protect the voltage phase angle estimation of strategic buses in a Smart Grid aga...
Article
As a kernel function in network routers, packet classification requires the incoming packet headers to be checked against a set of predefined rules. There are two trends for packet classification: (1) to examine a large number of packet header fields, and (2) to use software-based solutions on multi-core general purpose processors and virtual machi...
Article
Full-text available
The study of information dissemination on a social network has gained significant importance with the rise of social media. Since the true dynamics are hidden, various diffusion models have been exposed to explain the cascading behavior. Such models require extensive simulation for estimating the dissemination over time. In an earlier work, we prop...
Article
Decision-trees have been widely used in scientific computing. It is challenging to sustain high performance for large decision-trees. In this paper, we present a conversion technique translating a generic decision-tree into multiple compact hash tables; the conversion technique does not depend on the depth or shape of the decision-tree. All the com...
Conference Paper
Full-text available
As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction...
Conference Paper
The chief challenge in identifying similar individuals across multiple ontologies is the high computational cost of evaluating similarity between every pair of entities. We present an approach to querying for similar individuals across multiple ontologies that makes use of the correspondences discovered during ontology alignment in order to reduce...
Conference Paper
We extend a bootstrapping method that was initially developed for extracting relations from webpages to the problem of extracting content from large collections of short unstructured text. Such data appear as field notes in enterprise applications and as messages in social media services. The method iteratively learns sentence patterns that match a...
Conference Paper
FPGAs have been widely used for accelerating various applications. For many data intensive applications, the memory bandwidth can limit the performance. 3D memories with through-silicon-via connections provide potential solutions to the latency and bandwidth issues. In this paper, we revisit the classic 2D FFT problem to evaluate the performance of...
Conference Paper
Often in marketing, political campaigns and social media, two competing products or opinions propagate over a social network. Studying social influence in such competing cascades scenarios enables building effective strategies for maximizing the propagation of one process by targeting the most "influential" nodes in the network. The majority of pri...
Data
Supplement to our IEEE BigData 2014 paper. http://www-scf.usc.edu/~patri/bigdata14.html
Conference Paper
Full-text available
Accurate estimation and evaluation of consumption reduction achieved by participants during Demand Response is critical to Smart Grids. We perform an in-depth study of popular estimation methods used to determine the extent of consumption shedding during DR, using a real-world Smart Grid dataset from the University of Southern California campus mic...
Conference Paper
Full-text available
Demand response (DR) is a technique used in smart grids to shape customer load during peak hours. Automated DR offers utilities a fine grained control and a high degree of confidence in the outcome. However the impact on the customer's comfort means this technique is more suited for industrial and commercial settings than for residential homes. In...
Conference Paper
Full-text available
The use of AMI in Smart Grids has resulted in huge volumes of energy consumption data being collected. We design a provably efficient online clustering technique based on algorithmic theory to analyze high volume, high dimensional energy consumption data at scale, and on the fly. Unlike prior work, we study the consumption properties of the whole p...
Conference Paper
The advent of smart meters and advanced communication infrastructures catalyzes numerous smart grid applications such as dynamic demand response, and paves the way to solve challenging research problems in sustainable energy consumption. The space of solution possibilities are restricted primarily by the huge amount of generated data requiring cons...
Conference Paper
Full-text available
The MapReduce programming model, due to its simplicity and scalability, has become an essential tool for processing large data volumes in distributed environments. Recent Stream Processing Systems (SPS) extend this model to provide low-latency analysis of high-velocity continuous data streams. However, integrating MapReduce with streaming poses cha...
Conference Paper
Full-text available
Graphs are a key form of Big Data, and performing scalable analytics over them is invaluable to many domains. There is an emerging class of inter-connected data which accumulates or varies over time, and on which novel algorithms both over the network structure and across the time-variant attribute values is necessary. We formalize the notion of ti...
Conference Paper
Interestingness measures stand as proxy for “real human interest,” but their effectiveness is rarely studied empirically due to the difficulty of obtaining ground-truth data. We propose a method based on learning-to-rank algorithms that enables pairwise rankings collected from domain community members to be used to learn a domain-specific measure....
Article
Due to the rapid growth of Internet, there is an increasing need for efficiently classifying packets with many header fields in large rule sets. For example, in Software Defined Networking (SDN), the OpenFlow table lookup can require 15 packet header fields to be examined. In this paper, we present several decomposition-based packet classiffication...
Conference Paper
Full-text available
Existing Big Data streams coming from social and other connected sensor networks exhibit intrinsic interdependency enabling unique challenges to scalable graph analytics. Data from these graphs is usually collected on various geographically distributed data servers making it suitable for distributed processing on clouds. While numerous solutions fo...
Conference Paper
An increasing number of applications in environmental monitoring and location-based services make use of large-scale distributed sensing provided by wireless sensor networks. In such applications, a large number of sensor devices are deployed to collect useful information such as temperature readings and vehicle positions. However, these distribute...
Conference Paper
Recent advances in three dimensional integrated circuits have enabled large amounts of memory to be stacked in layers and accessed by a logic unit using high bandwidth vertical interconnects. Several 3D architectures have been proposed with different organizations of memory and logic layers. In particular, 3D stacks of memory dies can be interfaced...
Conference Paper
FPGA-based systems consisting external memory have been extensively employed in data intensive applications such as signal, image, and network processing. Memory energy is a dominating factor in the overall system energy dissipation. In particular, when performing non-sequential memory access patterns, significant amount of energy is dissipated due...
Article
Internet routers perform packet classification on incoming packets for various network services such as network security and Quality of Service (QoS) routing. All the incoming packets need to be examined against predefined rules in the router; packets are filtered out for security reasons or forwarded to specific ports during this process. Another...
Article
In this chapter we discuss two aspects of network virtualization in modern data centers: (1) network link virtualization and (2) network node virtualization. By virtualizing physical network links, each virtual network may obtain a slice of network links and build its own logical topology out of the shared physical topology. In network node virtual...
Conference Paper
Analysis of trade-offs between energy efficiency and latency is essential to generate designs complying with a given set of constraints. Improvements in FPGA technologies offer a myriad choices for power and performance optimizations. Various algorithm intrinsic parameters also affect these objectives. The design space is compounded by the availabl...
Conference Paper
Full-text available
The smart grid changes the way energy is produced and distributed. In addition both, energy and information is exchanged bidirectionally among participating parties. Therefore heterogeneous systems have to cooperate effectively in order to achieve a common high-level use case, such as smart metering for billing or demand response for load curtailme...
Article
Multi-field packet classification is a network kernel function where packets are classified and routed based on a predefined rule set. Recently, there has been a new trend in exploring Graphics Processing Unit (GPU) for network applications. These applications typically do not perform floating point operations and it is challenging to obtain speedu...