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Digital Communications and Networking Commons™
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Articles 1 - 6 of 6
Full-Text Articles in Digital Communications and Networking
Intelligent Networks For High Performance Computing, William Whitney Schonbein
Intelligent Networks For High Performance Computing, William Whitney Schonbein
Computer Science ETDs
There exists a resurgence of interest in `smart' network interfaces that can operate on data as it flows through a network. However, while smart capabilities have been expanding, what they can do for high-performance computing (HPC) is not well-understood. In this work, we advance our understanding of the capabilities and contributions of smart network interfaces to HPC. First, we show current offloaded message demultiplexing can mitigate (but not eliminate) overheads incurred by multithreaded communication. Second, we demonstrate current offloaded capabilities can be leveraged to provide Turing complete program execution on the interface. We elaborate with a framework for offloading arbitrary …
Blockchain Based Communication Architectures With Applications To Private Security Networks, Ashley N. Mayle
Blockchain Based Communication Architectures With Applications To Private Security Networks, Ashley N. Mayle
Computer Science ETDs
Existing communication protocols in security networks are highly centralized. While this naively makes the controls easier to physically secure, external actors require fewer resources to disrupt the system because there are fewer points in the system can be interrupted without the entire system failing. We present a solution to this problem using a proof-of-work-based blockchain implementation built on MultiChain. We construct a test-bed network containing visual imagers and microwave sensor information. These data types are ubiquitous in perimeter security systems and allow a realistic representation of a real-world network architecture. The cameras in this system use an object detection algorithm …
Incentivization In Mobile Edge Computing Using A Full Bayesian Approach, Sean Lebien
Incentivization In Mobile Edge Computing Using A Full Bayesian Approach, Sean Lebien
Electrical and Computer Engineering ETDs
The advances of multi-access edge computing (MEC) have paved the way for the integration of the MEC servers, as intelligent entities into the Internet of Things (IoT) environment as well as into the 5G radio access networks. In this thesis, a novel artificial intelligence-based MEC servers’ activation mechanism is proposed, by adopting the principles of Reinforcement Learning (RL) and Bayesian Reasoning. The considered problem enables the MEC servers’ activation decision-making, aiming at enhancing the reputation of the overall MEC system, as well as considering the total computing costs to serve efficiently the users’ computing demands, guaranteeing at the same time …
A Novel Framework Using Neutrosophy For Integrated Speech And Text Sentiment Analysis, Florentin Smarandache, Kritika Mishra, Ilanthenral Kandasamy, Vasantha Kandasamy W.B.
A Novel Framework Using Neutrosophy For Integrated Speech And Text Sentiment Analysis, Florentin Smarandache, Kritika Mishra, Ilanthenral Kandasamy, Vasantha Kandasamy W.B.
Branch Mathematics and Statistics Faculty and Staff Publications
With increasing data on the Internet, it is becoming difficult to analyze every bit and make sure it can be used efficiently for all the businesses. One useful technique using Natural Language Processing (NLP) is sentiment analysis. Various algorithms can be used to classify textual data based on various scales ranging from just positive-negative, positive-neutral-negative to a wide spectrum of emotions. While a lot of work has been done on text, only a lesser amount of research has been done on audio datasets. An audio file contains more features that can be extracted from its amplitude and frequency than a …
Intelligent Algorithm For Trapezoidal Interval Valued Neutrosophic Network Analysis, Florentin Smarandache, Said Broumi, Deivanayagampillai Nagarajan, Malayalan Lathamaheswari, Mohamed Talea, Assia Bakali
Intelligent Algorithm For Trapezoidal Interval Valued Neutrosophic Network Analysis, Florentin Smarandache, Said Broumi, Deivanayagampillai Nagarajan, Malayalan Lathamaheswari, Mohamed Talea, Assia Bakali
Branch Mathematics and Statistics Faculty and Staff Publications
The shortest path problem has been one of the most fundamental practical problems in network analysis. One of the good algorithms is Bellman-Ford, which has been applied in network, for the last some years. Due to complexity in the decision-making process, the decision makers face complications to express their view and judgment with an exact number for single valued membership degrees under neutrosophic environment. Though the interval number is a special situation of the neutrosophic, it did not solve the shortest path problems in an absolute manner. Hence, in this work, the authors have introduced the score function and accuracy …
Nonlinear Least Squares 3-D Geolocation Solutions Using Time Differences Of Arrival, Michael V. Bredemann
Nonlinear Least Squares 3-D Geolocation Solutions Using Time Differences Of Arrival, Michael V. Bredemann
Mathematics & Statistics ETDs
This thesis uses a geometric approach to derive and solve nonlinear least squares minimization problems to geolocate a signal source in three dimensions using time differences of arrival at multiple sensor locations. There is no restriction on the maximum number of sensors used. Residual errors reach the numerical limits of machine precision. Symmetric sensor orientations are found that prevent closed form solutions of source locations lying within the null space. Maximum uncertainties in relative sensor positions and time difference of arrivals, required to locate a source within a maximum specified error, are found from these results. Examples illustrate potential requirements …