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Distributed Perimeter Firewall Policy Management Framework
(University of Missouri--Kansas City, 2017)
A perimeter firewall is the first line of defense that stops unwanted packets (based on
defined firewall policies) entering the organization that deploys it. In the real world, every
organization maintains a perimeter ...
Achieving Optimal Schedule by Network Flow Techniques
(2015-08-11)
Scheduling plays an important role in protocol design and performance optimizations for
wireless or wired networks. This dissertation studies how to achieve optimal performance
for two fundamental scheduling problems ...
A New Approach for Fast Processing of SPARQL Queries on RDF Quadruples
(2015-06-19)
The Resource Description Framework (RDF) is a standard model for representing
data on the Web. It enables the interchange and machine processing of
data by considering its semantics. While RDF was first proposed with the ...
High Availability and Scalability Schemes for Software- Defined Networks (SDN)
(2015)
A proliferation of network-enabled devices and network-intensive applications require
the underlying networks not only to be agile despite of complex and heterogeneous
environments, but also to be highly available and ...
A Graph Analytics Framework for Knowledge Discovery
(2016)
In the current data movement, numerous efforts have been made to convert and normalize
a large number of traditionally structured and unstructured data to semi-structured data
(e.g., RDF, OWL). With the increasing number ...
Application-Aware Network Design Using Software Defined Networking for Application Performance Optimization for Big Data and Video Streaming
(University of Missouri--Kansas City, 2017)
This dissertation investigates improvement in application performance. For applications, we consider two classes: Hadoop MapReduce and video streaming. The Hadoop
MapReduce (M/R) framework has become the de facto standard ...
Volatility-Aware Query Processing in Peer-to-Peer Systems
(University of Missouri--Kansas City, 2010)
Peer-to-Peer (P2P) paradigm has been recognized as a disruptive technology that can aggregate enormous storage and processing resources for information sharing and distributed computing. This paradigm has received significant ...
Semantic Frameworks for Document and Ontology Clustering
(University of Missouri--Kansas City, 2011-01-20)
The Internet has made it possible, in principle, for scientists to quickly find research papers of interest. In practice, the overwhelming volume of publications makes this a time consuming task. It is, therefore, important ...
Data center resource management with temporal data center resource management with temporal dynamic workload
(University of Missouri--Kansas City, 2012-06-19)
The proliferation of Internet services drives the data center expansion in both size
and the number. More importantly, the energy consumption (as part of total cost of ownership
(TCO)) has become a social concern. When ...
DBHAaaS – Database High Availability As A Service For Cloud Computing
(University of Missouri–Kansas City, 2016)
On conventional database systems, the recovery manager applies transaction Undo or Redo
operation or a combination of them to recover the last consistent state of the database from a
system failure. Transaction redo, ...
Energy Efficient Resource Allocation for Virtual Network Services with Dynamic Workload in Cloud Data Centers
(2015)
With the rapid proliferation of cloud computing, more and more network services and
applications are deployed on cloud data centers. Their energy consumption and green
house gas emissions have significantly increased. ...
A semantic framework for event-driven service composition
(University of Missouri--Kansas City, 2011-09-14)
Service Oriented Architecture (SOA) has become a popular paradigm for designing
distributed systems where loosely coupled services (i.e. computational entities) can be
integrated seamlessly to provide complex composite ...
Deep Open Representative Learning for Image and Text Classification
(2020)
An essential goal of artificial intelligence is to support the knowledge discovery process from data to the knowledge that is useful in decision making. The challenges in the knowledge discovery process are typically due ...
Lightweight cryptographic protocols for mobile devices
(2020)
In recent years, a wide range of resource-constrained devices have been built and integrated into many networked systems. These devices collect and transfer data over the Internet in order for users to access the data or ...
Internet of Things (IoT) Applications With Diverse Direct Communication Methods
(University of Missouri--Kansas City, 2016)
Internet of Things (IoT) is a network of physical objects or things that are
embedded with electronics, software, sensors, and network connectivity - which enable
the object to collect and exchange data. Rapid proliferation ...
An Approach For Scalable First-Order Rule Learning On Twitter Data
(2021)
Scalable Rule Learning (SRLearn) is a scalable divide-and-conquer approach with graph-based modeling of social media data, to scale up first-order rule learning through Markov Logic Networks on a commodity cluster on large ...
Security Management of Smart Home Internet-Of-Things: A Framework, Finite-State Attack Modeling, And Worst Attack Vulnerability Analysis
(2023)
Smart Home Internet of Things (SHIoT) provides a rich compendium of innovative, ubiquitous, and interactive services to users using a variety of smart sensors, devices and applications. However, owing to the strongly ...
Scalable Acceleration of The Characteristic Mode Analysis Computational Toolbox Using Big Data Techniques
(2021)
Characteristic Mode Analysis (CMA) is used in the design and analysis of a wide range of electromagnetic devices such as antennas and nano-structures. CMA provides physical insight into a target's electromagnetic response ...
Ice-Mocha: Intelligent crowd engineering using mobile internet of things characterization and analytics
(2019)
Human casualties at entertaining, religious, or political crowd events often occur due to the lack of proper crowd safety management. Notably, for a moving crowd, a minor accident can create a panic for the people to start ...
ICE-MILK: Intelligent Crowd Engineering using Machine-based Internet of Things Learning and Knowledge Building
(2022)
The lack of proper crowd safety control and management often leads to spreading human casualties and infectious diseases (e.g., COVID-19). Many Machine Learning (ML) technologies inspired by computer vision and video ...