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Missouri University of Science and Technology

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Articles 391 - 420 of 1938

Full-Text Articles in Computer Sciences

A Survey On Mobile Charging Techniques In Wireless Rechargeable Sensor Networks, Amar Kaswan, Prasanta K. Jana, Sajal K. Das Sep 2022

A Survey On Mobile Charging Techniques In Wireless Rechargeable Sensor Networks, Amar Kaswan, Prasanta K. Jana, Sajal K. Das

Computer Science Faculty Research & Creative Works

The recent breakthrough in wireless power transfer (WPT) technology has empowered wireless rechargeable sensor networks (WRSNs) by facilitating stable and continuous energy supply to sensors through mobile chargers (MCs). A plethora of studies have been carried out over the last decade in this regard. However, no comprehensive survey exists to compile the state-of-the-art literature and provide insight into future research directions. To fill this gap, we put forward a detailed survey on mobile charging techniques (MCTs) in WRSNs. In particular, we first describe the network model, various WPT techniques with empirical models, system design issues and performance metrics concerning the …

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Guest Editorial: Special Section On Distributed Intelligence Over Internet Of Things, Honglong Chen, Joel Rodrigues, Feng Xia, Sajal K. Das Sep 2022

Guest Editorial: Special Section On Distributed Intelligence Over Internet Of Things, Honglong Chen, Joel Rodrigues, Feng Xia, Sajal K. Das

Computer Science Faculty Research & Creative Works

No abstract provided.

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Compressed Sensing Based Low-Power Multi-View Video Coding And Transmission In Wireless Multi-Path Multi-Hop Networks, Nan Cen, Zhangyu Guan, Tommaso Melodia Sep 2022

Compressed Sensing Based Low-Power Multi-View Video Coding And Transmission In Wireless Multi-Path Multi-Hop Networks, Nan Cen, Zhangyu Guan, Tommaso Melodia

Computer Science Faculty Research & Creative Works

Wireless Multimedia Sensor Network (WMSN) is increasingly being deployed for surveillance, monitoring and Internet-of-Things (IoT) sensing applications where a set of cameras capture and compress local images and then transmit the data to a remote controller. Such captured local images may also be compressed in a multi-view fashion to reduce the redundancy among overlapping views. In this paper, we present a novel paradigm for compressed-sensing-enabled multi-view coding and streaming in WMSN. We first propose a new encoding and decoding architecture for multi-view video systems based on Compressed Sensing (CS) principles, composed of cooperative sparsity-aware block-level rate-adaptive encoders, feedback channels and …

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Be Smart, Save I/O: A Probabilistic Approach To Avoid Uncorrectable Errors In Storage Systems, Md Arifuzzaman, Masudul Bhuiyan, Mehmet Gumus, Engin Arslan Sep 2022

Be Smart, Save I/O: A Probabilistic Approach To Avoid Uncorrectable Errors In Storage Systems, Md Arifuzzaman, Masudul Bhuiyan, Mehmet Gumus, Engin Arslan

Computer Science Faculty Research & Creative Works

Silent data corruption poses a significant risk to the integrity of data in storage systems. Although error correction codes (ECC) can recover the majority of such errors, a nonnegligible portion of them escape ECC, referred as uncorrectable errors (UEs). Despite being rare in nature, increasing scale of storage systems and fast-growing I/O rates decreased the mean time between UEs from months to hours. Yet, unlike disk failures, UEs are hard to predict with high precision, making it difficult to adopt proactive measures. In this paper, we introduce a probabilistic approach to deploy UE mitigation strategies that can capture significant portion …

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Products Pricing And Return Strategies For The Dual Channel Retailers, Jian Liu, Xinyue Sun, Yanyan Liu Sep 2022

Products Pricing And Return Strategies For The Dual Channel Retailers, Jian Liu, Xinyue Sun, Yanyan Liu

Electrical and Computer Engineering Faculty Research & Creative Works

This paper analyzed how different return strategies and return rates affect dual-channel retailers' profits and channel pricings. Return can stimulate sales; however, the return has presented significant challenges to retailers. The return has long been studied to maximize profit and pricing; however, the different return strategies for dual-channel retailers affect channel both. This paper aimed to study whether or not dual-channel retailers should allow customers to return items in two channels and whether or not the retailer should contract with the manufacturers and pay extra fees to return products. This study indicated when the retailer should allow customers' returns to …

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Dynamic Path Planning For Unmanned Aerial Vehicles Under Deadline And Sector Capacity Constraints, Sudharsan Vaidhun, Zhishan Guo, Jiang Bian, Haoyi Xiong, Sajal K. Das Aug 2022

Dynamic Path Planning For Unmanned Aerial Vehicles Under Deadline And Sector Capacity Constraints, Sudharsan Vaidhun, Zhishan Guo, Jiang Bian, Haoyi Xiong, Sajal K. Das

Computer Science Faculty Research & Creative Works

The US National Airspace System is currently operating at a level close to its maximum potential. The limitation comes from the workload demand on the air traffic controllers. Currently, the air traffic flow management is based on the flight path requests by the airline operators, whereas the minimum separation assurance between flights is handled strategically by air traffic control personnel. In this paper, we propose a scalable framework that allows path planning for a large number of unmanned aerial vehicles (UAVs) taking into account the deadline and weather constraints. Our proposed solution has a polynomial-time computational complexity that is also …

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Maximising Social Welfare In Selfish Multi-Modal Routing Using Strategic Information Design For Quantal Response Travelers, Sainath Sanga Aug 2022

Maximising Social Welfare In Selfish Multi-Modal Routing Using Strategic Information Design For Quantal Response Travelers, Sainath Sanga

Masters Theses

"Traditional selfish routing literature quantifies inefficiency in transportation systems with single-attribute costs using price-of-anarchy (PoA), and provides various technical approaches (e.g. marginal cost pricing) to improve PoA of the overall network. Unfortunately, practical transportation systems have dynamic, multi-attribute costs and the state-of-the-art technical approaches proposed in the literature are infeasible for practical deployment. In this paper, we offer a paradigm shift to selfish routing via characterizing idiosyncratic, multiattribute costs at boundedly-rational travelers, as well as improving network efficiency using strategic information design. Specifically, we model the interaction between the system and travelers as a Stackelberg game, where travelers adopt multi-attribute …

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Social Media Analytics With Applications In Disaster Management And Covid-19 Events, Md Yasin Kabir Aug 2022

Social Media Analytics With Applications In Disaster Management And Covid-19 Events, Md Yasin Kabir

Doctoral Dissertations

"Social media such as Twitter offers a tremendous amount of data throughout an event or a disastrous situation. Leveraging social media data during a disaster is beneficial for effective and efficient disaster management. Information extraction, trend identification, and determining public reactions might help in the future disaster or even avert such an event. However, during a disaster situation, a robust system is required that can be deployed faster and process relevant information with satisfactory performance in real-time. This work outlines the research contributions toward developing such an effective system for disaster management, where it is paramount to develop automated machine-enabled …

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Secured Information Dissemination And Misbehavior Detection In Vanets, Ayan Roy Aug 2022

Secured Information Dissemination And Misbehavior Detection In Vanets, Ayan Roy

Doctoral Dissertations

"In a connected vehicle environment, the vehicles in a region can form a distributed network (Vehicular Ad-hoc Network or VANETs) where they can share traffic-related information such as congestion or no-congestion with other vehicles within its proximity, or with a centralized entity via. the roadside units (RSUs). However, false or fabricated information injected by an attacker (or a malicious vehicle) within the network can disrupt the decision-making process of surrounding vehicles or any traffic-monitoring system. Since in VANETs the size of the distributed network constituting the vehicles can be small, it is not difficult for an attacker to propagate an …

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Drone-Truck Cooperated Delivery Under Time Varying Dynamics, Arindam Khanda, Federico Corò, Sajal K. Das Jul 2022

Drone-Truck Cooperated Delivery Under Time Varying Dynamics, Arindam Khanda, Federico Corò, Sajal K. Das

Computer Science Faculty Research & Creative Works

Rapid technological developments in autonomous unmanned aerial vehicles (or drones) could soon lead to their large-scale implementation in the last-mile delivery of products. However, drones have a number of problems such as limited energy budget, limited carrying capacity, etc. On the other hand, trucks have a larger carrying capacity, but they cannot reach all the places easily. Intriguingly, last-mile delivery cooperation between drones and trucks can synergistically improve delivery efficiency. In this paper, we present a drone-truck co-operated delivery framework under time-varying dynamics. Our framework minimizes the total delivery time while considering low energy consumption as the secondary objective. The …

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Region-Adaptive, Error-Controlled Scientific Data Compression Using Multilevel Decomposition, Qian Gong, Ben Whitney, Chengzhu Zhang, Xin Liang, Anand Rangarajan, Jieyang Chen, Lipeng Wan, Paul Ullrich, Qing Liu, Robert Jacob, Sanjay Ranka, Scott Klasky Jul 2022

Region-Adaptive, Error-Controlled Scientific Data Compression Using Multilevel Decomposition, Qian Gong, Ben Whitney, Chengzhu Zhang, Xin Liang, Anand Rangarajan, Jieyang Chen, Lipeng Wan, Paul Ullrich, Qing Liu, Robert Jacob, Sanjay Ranka, Scott Klasky

Computer Science Faculty Research & Creative Works

The increase of computer processing speed is significantly outpacing improvements in network and storage bandwidth, leading to the big data challenge in modern science, where scientific applications can quickly generate much more data than that can be transferred and stored. As a result, big scientific data must be reduced by a few orders of magnitude while the accuracy of the reduced data needs to be guaranteed for further scientific explorations. Moreover, scientists are often interested in some specific spatial/temporal regions in their data, where higher accuracy is required. The locations of the regions requiring high accuracy can sometimes be prescribed …

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Wikimarks: Harvesting Relevance Benchmarks From Wikipedia, Laura Dietz, Shubham Chatterjee, Connor Lennox, Sumanta Kashyapi, Pooja Oza, Ben Gamari Jul 2022

Wikimarks: Harvesting Relevance Benchmarks From Wikipedia, Laura Dietz, Shubham Chatterjee, Connor Lennox, Sumanta Kashyapi, Pooja Oza, Ben Gamari

Computer Science Faculty Research & Creative Works

We provide a resource for automatically harvesting relevance benchmarks from Wikipedia - which we refer to as "Wikimarks"to differentiate them from manually created benchmarks. Unlike simulated benchmarks, they are based on manual annotations of Wikipedia authors. Studies on the TREC Complex Answer Retrieval track demonstrated that leaderboards under Wikimarks and manually annotated benchmarks are very similar. Because of their availability, Wikimarks can fill an important need for Information Retrieval research. We provide a meta-resource to harvest Wikimarks for several information retrieval tasks across different languages: paragraph retrieval, entity ranking, query-specific clustering, outline prediction, and relevant entity linking and many more. …

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Bert-Er: Query-Specific Bert Entity Representations For Entity Ranking, Shubham Chatterjee, Laura Dietz Jul 2022

Bert-Er: Query-Specific Bert Entity Representations For Entity Ranking, Shubham Chatterjee, Laura Dietz

Computer Science Faculty Research & Creative Works

Entity-oriented search systems often learn vector representations of entities via the introductory paragraph from the Wikipedia page of the entity. As such representations are the same for every query, our hypothesis is that the representations are not ideal for IR tasks. In this work, we present BERT Entity Representations (BERT-ER) which are query-specific vector representations of entities obtained from text that describes how an entity is relevant for a query. Using BERT-ER in a downstream entity ranking system, we achieve a performance improvement of 13-42% (Mean Average Precision) over a system that uses the BERT embedding of the introductory paragraph …

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Mgard+: Optimizing Multilevel Methods For Error-Bounded Scientific Data Reduction, Xin Liang, Ben Whitney, Jieyang Chen, Lipeng Wan, Qing Liu, Dingwen Tao, James Kress, David Pugmire, Matthew Wolf, Norbert Podhorszki, Scott Klasky Jul 2022

Mgard+: Optimizing Multilevel Methods For Error-Bounded Scientific Data Reduction, Xin Liang, Ben Whitney, Jieyang Chen, Lipeng Wan, Qing Liu, Dingwen Tao, James Kress, David Pugmire, Matthew Wolf, Norbert Podhorszki, Scott Klasky

Computer Science Faculty Research & Creative Works

Nowadays, data reduction is becoming increasingly important in dealing with the large amounts of scientific data. Existing multilevel compression algorithms offer a promising way to manage scientific data at scale but may suffer from relatively low performance and reduction quality. In this paper, we propose MGARD+, a multilevel data reduction and refactoring framework drawing on previous multilevel methods, to achieve high-performance data decomposition and high-quality error-bounded lossy compression. Our contributions are four-fold: 1) We propose to leverage a level-wise coefficient quantization method, which uses different error tolerances to quantize the multilevel coefficients. 2) We propose an adaptive decomposition method which …

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Classification Of Alzheimer's Disease Via Vision Transformer: Classification Of Alzheimer's Disease Via Vision Transformer, Yanjun Lyu, Xiaowei Yu, Dajiang Zhu, Lu Zhang Jun 2022

Classification Of Alzheimer's Disease Via Vision Transformer: Classification Of Alzheimer's Disease Via Vision Transformer, Yanjun Lyu, Xiaowei Yu, Dajiang Zhu, Lu Zhang

Computer Science Faculty Research & Creative Works

Deep models are powerful in capturing the complex and non-linear relationship buried in brain imaging data. However, the huge number of parameters in deep models can easily overfit given limited imaging data samples. In this work, we proposed a cross-domain transfer learning method to solve the insufficient data problem in brain imaging domain by leveraging the knowledge learned in natural image domain. Specifically, we employed ViT as the backbone and firstly pretrained it using ImageNet-21K dataset and then transferred to the brain imaging dataset. A slice-wise convolution embedding method was developed to improve the standard patch operation in vanilla ViT. …

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Ultrafast Error-Bounded Lossy Compression For Scientific Datasets, Xiaodong Yu, Sheng Di, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, Franck Cappello Jun 2022

Ultrafast Error-Bounded Lossy Compression For Scientific Datasets, Xiaodong Yu, Sheng Di, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, Franck Cappello

Computer Science Faculty Research & Creative Works

Today's scientific high-performance computing applications and advanced instruments are producing vast volumes of data across a wide range of domains, which impose a serious burden on data transfer and storage. Error-bounded lossy compression has been developed and widely used in the scientific community because it not only can significantly reduce the data volumes but also can strictly control the data distortion based on the user-specified error bound. Existing lossy compressors, however, cannot offer ultrafast compression speed, which is highly demanded by numerous applications or use cases (such as in-memory compression and online instrument data compression). In this paper, we propose …

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Analysis Of Federated Scheduling For Integer-Valued Workloads, Marion Sudvarg, Chris Gill Jun 2022

Analysis Of Federated Scheduling For Integer-Valued Workloads, Marion Sudvarg, Chris Gill

Computer Science Faculty Research & Creative Works

In federated scheduling of parallel real-time tasks on multiprocessor systems, high-utilization tasks are allocated dedicated processors on which they execute exclusively. Several methods exist for allocating a sufficient number of processors to guarantee that each task meets its deadline. In this paper, we propose two new strategies for allocating unit-speed cores to tasks with integer workload and deadline values. The first method can be performed in constant time for each high-utilization task, given the task's total workload, critical-path length, and deadline. The second method exploits the DAG structure of high-utilization tasks, providing a potentially better schedule in pseudo-polynomial time. We …

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Accelerating Serverless Computing By Harvesting Idle Resources, Hanfei Yu, Hao Wang, Jian Li, Xu Yuan, Seung Jong Park Apr 2022

Accelerating Serverless Computing By Harvesting Idle Resources, Hanfei Yu, Hao Wang, Jian Li, Xu Yuan, Seung Jong Park

Computer Science Faculty Research & Creative Works

Serverless computing automates fine-grained resource scaling and simplifies the development and deployment of online services with stateless functions. However, it is still non-trivial for users to allocate appropriate resources due to various function types, dependencies, and input sizes. Misconfiguration of resource allocations leaves functions either under-provisioned or over-provisioned and leads to continuous low resource utilization. This paper presents Freyr, a new resource manager (RM) for serverless platforms that maximizes resource efficiency by dynamically harvesting idle resources from over-provisioned functions to under-provisioned functions. Freyr monitors each function's resource utilization in real-time, detects over-provisioning and under-provisioning, and learns to harvest idle resources …

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A Parallel Algorithm Template For Updating Single-Source Shortest Paths In Large-Scale Dynamic Networks, Arindam Khanda, Sriram Srinivasan, Sanjukta Bhowmick, Boyana Norris, Sajal K. Das Apr 2022

A Parallel Algorithm Template For Updating Single-Source Shortest Paths In Large-Scale Dynamic Networks, Arindam Khanda, Sriram Srinivasan, Sanjukta Bhowmick, Boyana Norris, Sajal K. Das

Computer Science Faculty Research & Creative Works

The Single Source Shortest Path (SSSP) problem is a classic graph theory problem that arises frequently in various practical scenarios; hence, many parallel algorithms have been developed to solve it. However, these algorithms operate on static graphs, whereas many real-world problems are best modeled as dynamic networks, where the structure of the network changes with time. This gap between the dynamic graph modeling and the assumed static graph model in the conventional SSSP algorithms motivates this work. We present a novel parallel algorithmic framework for updating the SSSP in large-scale dynamic networks and implement it on the shared-memory and GPU …

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Improving I/O Performance For Exascale Applications Through Online Data Layout Reorganization, Lipeng Wan, Axel Huebl, Junmin Gu, Franz Poeschel, Ana Gainaru, Ruonan Wang, Jieyang Chen, Xin Liang, Dmitry Ganyushin, Todd Munson, Ian Foster, Jean Luc Vay, Norbert Podhorszki, Kesheng Wu Apr 2022

Improving I/O Performance For Exascale Applications Through Online Data Layout Reorganization, Lipeng Wan, Axel Huebl, Junmin Gu, Franz Poeschel, Ana Gainaru, Ruonan Wang, Jieyang Chen, Xin Liang, Dmitry Ganyushin, Todd Munson, Ian Foster, Jean Luc Vay, Norbert Podhorszki, Kesheng Wu

Computer Science Faculty Research & Creative Works

The applications being developed within the U.S. Exascale Computing Project (ECP) to run on imminent Exascale computers will generate scientific results with unprecedented fidelity and record turn-around time. Many of these codes are based on particle-mesh methods and use advanced algorithms, especially dynamic load-balancing and mesh-refinement, to achieve high performance on Exascale machines. Yet, as such algorithms improve parallel application efficiency, they raise new challenges for I/O logic due to their irregular and dynamic data distributions. Thus, while the enormous data rates of Exascale simulations already challenge existing file system write strategies, the need for efficient read and processing of …

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Measurement Errors In Range-Based Localization Algorithms For Uavs: Analysis And Experimentation, Francesco Betti Sorbelli, Cristina M. Pinotti, Simone Silvestri, Sajal K. Das Apr 2022

Measurement Errors In Range-Based Localization Algorithms For Uavs: Analysis And Experimentation, Francesco Betti Sorbelli, Cristina M. Pinotti, Simone Silvestri, Sajal K. Das

Computer Science Faculty Research & Creative Works

Localizing Ground Devices (GDs) is an Important Requirement for a Wide Variety of Applications, Such as Infrastructure Monitoring, Precision Agriculture, Search and Rescue Operations, to Name a Few. to This End, Unmanned Aerial Vehicles (UAVs) or Drones Offer a Promising Technology Due to their Flexibility. However, the Distance Measurements Performed using a Drone, an Integral Part of a Localization Procedure, Incur Several Errors that Affect the Localization Accuracy. in This Paper, We Provide Analytical Expressions for the Impact of Different Kinds of Measurement Errors on the Ground Distance between the UAV and GDs. We Review Three Range-Based and Three Range-Free …

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Minimizing The Deployment Cost Of Uavs For Delay-Sensitive Data Collection In Iot Networks, Wenzheng Xu, Tao Xiao, Junqi Zhang, Weifa Liang, Zichuan Xu, Xuxun Liu, Xiaohua Jia, Sajal K. Das Apr 2022

Minimizing The Deployment Cost Of Uavs For Delay-Sensitive Data Collection In Iot Networks, Wenzheng Xu, Tao Xiao, Junqi Zhang, Weifa Liang, Zichuan Xu, Xuxun Liu, Xiaohua Jia, Sajal K. Das

Computer Science Faculty Research & Creative Works

In this paper, we study the deployment of Unmanned Aerial Vehicles (UAVs) to collect data from IoT devices, by finding a data collection tour for each UAV. To ensure the 'freshness' of the collected data, the total time spent in the tour of each UAV that consists of the UAV flying time and data collection time must be no greater than a given delay B, e.g., 20 minutes. In this paper, we consider a problem of deploying the minimum number of UAVs and finding their data collection tours, subject to the constraint that the total time spent in each tour …

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Netchain: A Blockchain-Enabled Privacy-Preserving Multi-Domain Network Slice Orchestration Architecture, Guobiao He, Wei Su, Shuai Gao, Ningchun Liu, Sajal K. Das Mar 2022

Netchain: A Blockchain-Enabled Privacy-Preserving Multi-Domain Network Slice Orchestration Architecture, Guobiao He, Wei Su, Shuai Gao, Ningchun Liu, Sajal K. Das

Computer Science Faculty Research & Creative Works

Multi-domain networking slice orchestration is an essential technology for the programmable and cloud-native 5G network. However, existing research solutions are either based on the impractical assumption that operators will reveal all the private network information or time-consuming secure multi-party computation which is only applicable to limited computation scenarios. To provide agile and privacy-preserving end-to-end network slice orchestration services, this paper proposes NetChain, a multi-domain network slice orchestration architecture based on blockchain and trusted execution environment. Correspondingly, we design a novel consensus algorithm CoNet to ensure the strong security, scalability, and information consistency of NetChain. In addition, a bilateral evaluation mechanism …

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Perceptions Of Violations By Artificial And Human Actors Across Moral Foundations, Timothy Maninger, Daniel Burton Shank Mar 2022

Perceptions Of Violations By Artificial And Human Actors Across Moral Foundations, Timothy Maninger, Daniel Burton Shank

Psychological Science Faculty Research & Creative Works

Artificial agents such as robots, chatbots, and artificial intelligence systems can be the perpetrators of a range of moral violations traditionally limited to human actors. This paper explores how people perceive the same moral violations differently for artificial agent and human perpetrators by addressing three research questions: How wrong are moral foundation violations by artificial agents compared to human perpetrators? Which moral foundations do artificial agents violate compared to human perpetrators? What leads to increased blame for moral foundation violations by artificial agents compared to human perpetrators? We adapt 18 human-perpetrated moral violation scenarios that differ by the moral foundation …

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Speeding Up Routing Schedules On Aisle Graphs With Single Access, Francesco Betti Sorbelli, Stefano Carpin, Federico Coro, Sajal K. Das, Alfredo Navarra, Cristina M. Pinotti Feb 2022

Speeding Up Routing Schedules On Aisle Graphs With Single Access, Francesco Betti Sorbelli, Stefano Carpin, Federico Coro, Sajal K. Das, Alfredo Navarra, Cristina M. Pinotti

Computer Science Faculty Research & Creative Works

In this article, we study the orienteering aisle-graph single-access problem (OASP), a variant of the orienteering problem for a robot moving in a so-called single-access aisle graph, i.e., a graph consisting of a set of rows that can be accessed from one side only. Aisle graphs model, among others, vineyards or warehouses. Each aisle-graph vertex is associated with a reward that a robot obtains when it visits the vertex itself. As the energy of the robot is limited, only a subset of vertices can be visited with a fully charged battery. The objective is to maximize the total reward collected …

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Fedvcp: A Federated-Learning-Based Cooperative Positioning Scheme For Social Internet Of Vehicles, Xiangjie Kong, Haoran Gao, Guojiang Shen, Gaohui Duan, Sajal K. Das Feb 2022

Fedvcp: A Federated-Learning-Based Cooperative Positioning Scheme For Social Internet Of Vehicles, Xiangjie Kong, Haoran Gao, Guojiang Shen, Gaohui Duan, Sajal K. Das

Computer Science Faculty Research & Creative Works

Intelligent vehicle applications, such as autonomous driving and collision avoidance, put forward a higher demand for precise positioning of vehicles. The current widely used global navigation satellite systems (GNSS) cannot meet the precision requirements of the submeter level. Due to the development of sensing techniques and vehicle-to-infrastructure (V2I) communications, some vehicles can interact with surrounding landmarks to achieve precise positioning. Existing work aims to realize the positioning correction of common vehicles by sharing the positioning data of sensor-rich vehicles. However, the privacy of trajectory data makes it difficult to collect and train data centrally. Moreover, uploading vehicle location data wastes …

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Joint Bidding Decision Of Wind Farms And Energy Storage Based On Newsvendor Model, Xinyue Sun, Jian Liu, Meng Ou, Yanyan Liu Feb 2022

Joint Bidding Decision Of Wind Farms And Energy Storage Based On Newsvendor Model, Xinyue Sun, Jian Liu, Meng Ou, Yanyan Liu

Electrical and Computer Engineering Faculty Research & Creative Works

Currently, renewable energy generation has received more and more attention. This article focuses on wind energy generation, one of the renewable energy sources. Aiming at the intermittent and unpredictable wind power problems, according to the day ahead bidding mechanism in the power market, this paper introduces the energy storage system to maximize wind power merchants profit based on the newsvendor model. First, this paper focuses on the wind farms combined with storage system to put forward the optimal bidding decision of selling or buying electricity to the market one day in advance and the optimal bidding amount. Then, we analyze …

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Distributed Matrix Tiling Using A Hypergraph Labeling Formulation, Avah Banerjee, Maxwell Reeser, Guoli Ding Jan 2022

Distributed Matrix Tiling Using A Hypergraph Labeling Formulation, Avah Banerjee, Maxwell Reeser, Guoli Ding

Computer Science Faculty Research & Creative Works

Partitioning large matrices is an important problem in distributed linear algebra computing, used in ML among others. Briefly, our goal is to perform a sequence of matrix algebra operations in a distributed manner on these large matrices. However, not all partitioning schemes work well with different matrix algebra operations and their implementations (algorithms). This is a type of data tiling problem. In this paper we consider a data tiling problem using hypergraphs. We prove some hardness results and give a theoretical characterization of its complexity on random instances. Additionally, we develop a greedy algorithm and experimentally show its efficacy.

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Greedy Algorithms For Scheduling Package Delivery With Multiple Drones, Francesco Betti Sorbelli, Federico Corò, Sajal K. Das, Lorenzo Palazzetti, Cristina M. Pinotti Jan 2022

Greedy Algorithms For Scheduling Package Delivery With Multiple Drones, Francesco Betti Sorbelli, Federico Corò, Sajal K. Das, Lorenzo Palazzetti, Cristina M. Pinotti

Computer Science Faculty Research & Creative Works

Unmanned Aerial Vehicles (or drones) can be used for a myriad of civil applications, such as search and rescue, precision agriculture, or last-mile package delivery. Interestingly, the cooperation between drones and ground vehicles (trucks) can even enhance the quality of service. In this paper, we investigate the symbiosis among a truck and multiple drones in a last-mile package delivery scenario, introducing the Multiple Drone-Delivery Scheduling Problem (MDSP). From the main depot, a truck takes care of transporting a team of drones that will be used to deliver packages to customers. Each delivery is associated with a drone's energy cost, a …

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Cansafe: An Mtd Based Approach For Providing Resiliency Against Dos Attack Within In-Vehicle Networks, Ayan Roy, Sanjay Kumar Madria Jan 2022

Cansafe: An Mtd Based Approach For Providing Resiliency Against Dos Attack Within In-Vehicle Networks, Ayan Roy, Sanjay Kumar Madria

Computer Science Faculty Research & Creative Works

Trending towards autonomous transportation systems, modern vehicles are equipped with hundreds of sensors and actuators that increase the intelligence of the vehicles with a higher level of autonomy, as well as facilitate increased communication with entities outside the in-vehicle network. However, increase in a contact point with the outside world has exposed the controller area network (CAN) of a vehicle to remote security vulnerabilities. In particular, an attacker can inject fake high priority messages within the CAN through the contact points, while preventing legitimate messages from controlling the CAN (Denial-of-Service (DoS) attack). In this paper, we propose a Moving Target …

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