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Articles 451 - 480 of 919
Full-Text Articles in Computer Sciences
Mixed-Criticality Scheduling To Minimize Makespan, Sanjoy K. Baruah, Arvind Easwaran, Zhishan Guo
Mixed-Criticality Scheduling To Minimize Makespan, Sanjoy K. Baruah, Arvind Easwaran, Zhishan Guo
Computer Science Faculty Research & Creative Works
In the mixed-criticality job model, each job is characterized by two execution time parameters, representing a smaller (less conservative) estimate and a larger (more conservative) estimate on its actual, unknown, execution time. Each job is further classified as being either less critical or more critical. The desired execution semantics are that all jobs should execute correctly provided all jobs complete upon being allowed to execute for up to the smaller of their execution time estimates, whereas if some jobs need to execute beyond their smaller execution time estimates (but not beyond their larger execution time estimates), then only the jobs …
On Selective Activation In Dense Femtocell Networks, Michael Lin, Simone Silvestri, Novella Bartolini, Thomas F. La Porta
On Selective Activation In Dense Femtocell Networks, Michael Lin, Simone Silvestri, Novella Bartolini, Thomas F. La Porta
Computer Science Faculty Research & Creative Works
Over-provisioned femtocell networks can be used to serve indoor locations that see high peak loads, such as airports or train stations. However, networks designed for high peak loads are mostly under-utilized, which is wasteful from an energy-use perspective. This paper introduces a femtocell selective activation problem. We motivate the use of selective activation in femtocell networks using real femtocell power measurements. We formally define the selective activation problem, and introduce GreenFemto, a distributed femtocell selective activation algorithm. We prove that GreenFemto converges to a locally Pareto optimal solution. Detailed simulations of an LTE wireless system are used to demonstrate the …
Data Analytics For Fault Localization In Complex Networks, Maggie X. Cheng, Wei Biao Wu
Data Analytics For Fault Localization In Complex Networks, Maggie X. Cheng, Wei Biao Wu
Computer Science Faculty Research & Creative Works
We consider the problem of identifying the source of failure in a network after receiving alarms or having observed symptoms. To locate the root cause accurately and timely in a large communication system is challenging because a single fault can often result in a large number of alarms, and multiple faults can occur concurrently. In this paper, we present a new fault localization method using a machine-learning approach. We propose to use logistic regression to study the correlation among network events based on end-to-end measurements. Then based on the regression model, we develop fault hypothesis that best explains the observed …
Network Recovery After Massive Failures, Novella Bartolini, Stefano Ciavarella, Thomas F.La Porta, Simone Silvestri
Network Recovery After Massive Failures, Novella Bartolini, Stefano Ciavarella, Thomas F.La Porta, Simone Silvestri
Computer Science Faculty Research & Creative Works
This paper addresses the problem of efficiently restoring sufficient resources in a communications network to support the demand of mission critical services after a large-scale disruption. We give a formulation of the problem as a MILP and show that it is NP-hard. We propose a polynomial time heuristic, called Iterative Split and Prune (ISP) that decomposes the original problem recursively into smaller problems, until it determines the set of network components to be restored. We performed extensive simulations by varying the topologies, the demand intensity, the number of critical services, and the disruption model. Compared to several greedy approaches ISPper …
Secure Multiset Intersection Cardinality And Its Application To Jaccard Coefficient, Bharath K. Samanthula, Wei Jiang
Secure Multiset Intersection Cardinality And Its Application To Jaccard Coefficient, Bharath K. Samanthula, Wei Jiang
Computer Science Faculty Research & Creative Works
The Jaccard Coefficient, as an information similarity measure, has wide variety of applications, such as cluster analysis and image segmentation. Due to the concerns of personal privacy, the Jaccard Coefficient cannot be computed directly between two independently owned datasets. The problem, secure computation of the Jaccard Coefficient for multisets (SJCM), considers the situation where two parties want to securely compute the random shares of the Jaccard Coefficient between their multisets. During the process, the content of each party's multiset is not disclosed to the other party and also the value of Jaccard Coefficient should be hidden from both parties. Secure …
Hyper-Heuristics, Daniel R. Tauritz, John Woodward
Hyper-Heuristics, Daniel R. Tauritz, John Woodward
Computer Science Faculty Research & Creative Works
No abstract provided.
Bic-Lsu: Big Data Research Integration With Cyberinfrastructure For Lsu, Chui Hui Chiu, Nathan Lewis, Dipak Kumar Singh, Arghya Kusum Das, Mohammad M. Jalazai, Richard Platania, Sayan Goswami, Kisung Lee, Seung Jong Park
Bic-Lsu: Big Data Research Integration With Cyberinfrastructure For Lsu, Chui Hui Chiu, Nathan Lewis, Dipak Kumar Singh, Arghya Kusum Das, Mohammad M. Jalazai, Richard Platania, Sayan Goswami, Kisung Lee, Seung Jong Park
Computer Science Faculty Research & Creative Works
In recent years, big data analysis has been widely applied to many research fields including biology, physics, transportation, and material science. Even though the demands for big data migration and big data analysis are dramatically increasing in campus IT infrastructures, there are several technical challenges that need to be addressed. First of all, frequent big data transmission between storage systems in different research groups imposes heavy burdens on a regular campus network. Second, the current campus IT infrastructure is not designed to fully utilize the hardware capacity for big data migration and analysis. Last but not the least, running big …
A Model-Free Localization Method For Sensor Networks With Sparse Anchors, Maggie Xiaoyan Cheng, Wei Biao Wu
A Model-Free Localization Method For Sensor Networks With Sparse Anchors, Maggie Xiaoyan Cheng, Wei Biao Wu
Computer Science Faculty Research & Creative Works
This paper considers the problem of sensor node localization, where a total of an anchor nodes is used to determine the locations of other nodes based on the received signal strengths. Challenges arise when anchor nodes are sparse and locations of them are not at grid positions. A range-based machine learning algorithm is developed to tackle the challenges. Instead of using samples to calibrate the parameters of a chosen signal model, we use machine learning to estimate the signal propagation function and its parameters at the same time. It overcomes the model dependency issue of existing range-based algorithms and avoids …
Maximizing Coding Gain In Wireless Networks With Decodable Network Coding, Maggie Cheng, Quanmin Ye, Xiaochun Cheng, Lin Cai
Maximizing Coding Gain In Wireless Networks With Decodable Network Coding, Maggie Cheng, Quanmin Ye, Xiaochun Cheng, Lin Cai
Computer Science Faculty Research & Creative Works
Network coding improves transmission efficiency by combining packets at relay nodes and thus reduces the number of packets sent to the network. It is a network layer solution to improve network throughput and transmission efficiency. However, a coded packet must be decodable by the destination, otherwise it is a waste of resource to combine them together and to deliver the coded packet. This paper addresses how to find the coding solution that guarantees decodability at the destination. We first quantify the coding gain as the number of transmissions reduced and then provide a method for runtime check whether a coding …
In-Band Wormhole Detection In Wireless Ad Hoc Networks Using Change Point Detection Method, Maggie Xiaoyan Cheng, Yi Ling, Wei Biao Wu
In-Band Wormhole Detection In Wireless Ad Hoc Networks Using Change Point Detection Method, Maggie Xiaoyan Cheng, Yi Ling, Wei Biao Wu
Computer Science Faculty Research & Creative Works
This paper addresses detecting in-band wormholes in wireless ad hoc networks. The detection scheme requires collecting the end-to-end delay of packets at the receiver and then applying a sequential change point detection algorithm to detect abrupt changes in the delay time series. A new change point detection algorithm, named SW-CLT, is proposed. The algorithm is based on the Central Limit Theorem (CLT) and does not involve using a preset detecting threshold. The algorithm is compared with the non-parametric cumulative sum (NP-CUSUM) because the non-parametric version is believed to be more robust to highly dynamic data than the parametric version. SW-CLT …
Sorting Under Forbidden Comparisons, Avah Banerjee, Dana Richards
Sorting Under Forbidden Comparisons, Avah Banerjee, Dana Richards
Computer Science Faculty Research & Creative Works
In this paper we study the problem of sorting under forbidden comparisons where some pairs of elements may not be compared (forbidden pairs). Along with the set of elements V the input to our problem is a graph G(V, E), whose edges represents the pairs that we can compare in constant time. Given a graph with n vertices and m =(n2) - q edges we propose the first non-trivial deterministic algorithm which makes O((q + n) log n) comparisons with a total complexity of O(n2 + qω/2), where ω is the …
Big Data Management And Analytics For Mobile Crowd Sensing, Tingting Chen, Fan Wu, Tony Tie Luo, Mea Wang, Qirong Ho
Big Data Management And Analytics For Mobile Crowd Sensing, Tingting Chen, Fan Wu, Tony Tie Luo, Mea Wang, Qirong Ho
Computer Science Faculty Research & Creative Works
No abstract provided.
Towards Practical Algorithm Based Fault Tolerance In Dense Linear Algebra, Panruo Wu, Qiang Guan, Nathan Debardeleben, Sean Blanchard, Dingwen Tao, Xin Liang, For Full List Of Authors, See Publisher's Website.
Towards Practical Algorithm Based Fault Tolerance In Dense Linear Algebra, Panruo Wu, Qiang Guan, Nathan Debardeleben, Sean Blanchard, Dingwen Tao, Xin Liang, For Full List Of Authors, See Publisher's Website.
Computer Science Faculty Research & Creative Works
Algorithm based fault tolerance (ABFT) attracts renewed interest for its extremely low overhead and good scalability. However the fault model used to design ABFT has been either abstract, simplistic, or both, leaving a gap between what occurs at the architecture level and what the algorithm expects. As the fault model is the deciding factor in choosing an effective checksum scheme, the resulting ABFT techniques have seen limited impact in practice. In this paper we seek to close the gap by directly using a comprehensive architectural fault model and devise a comprehensive ABFT scheme that can tolerate multiple architectural faults of …
New-Sum: A Novel Online Abft Scheme For General Iterative Methods, Dingwen Tao, Shuaiwen Leon Song, Sriram Krishnamoorthy, Panruo Wu, Xin Liang, Eddy Z. Zhang, For Full List Of Authors, See Publisher's Website.
New-Sum: A Novel Online Abft Scheme For General Iterative Methods, Dingwen Tao, Shuaiwen Leon Song, Sriram Krishnamoorthy, Panruo Wu, Xin Liang, Eddy Z. Zhang, For Full List Of Authors, See Publisher's Website.
Computer Science Faculty Research & Creative Works
Emerging high-performance computing platforms, with large component counts and lower power margins, are anticipated to be more susceptible to soft errors in both logic circuits and memory subsystems. We present an online algorithm-based fault tolerance (ABFT) approach to efficiently detect and recover soft errors for general iterative methods. We design a novel checksum-based encoding scheme for matrix-vector multiplication that is resilient to both arithmetic and memory errors. Our design decouples the checksum updating process from the actual computation, and allows adaptive checksum overhead control. Building on this new encoding mechanism, we propose two online ABFT designs that can effectively recover …
Toward Dmd Illuminated Spatial-Temporal Modulated Thermography, Joshua D. Pribe, Srinivas Chakravarthi Thandu, Zhaozheng Yin, Edward C. Kinzel
Toward Dmd Illuminated Spatial-Temporal Modulated Thermography, Joshua D. Pribe, Srinivas Chakravarthi Thandu, Zhaozheng Yin, Edward C. Kinzel
Computer Science Faculty Research & Creative Works
This paper reports on a system using a Digital Micromirror Device (DMD) to modulate a near-infrared laser source spatially and temporally. The DMD can produce an arbitrary heat source varying both spatially and temporally over the target. When the thermal response of the target surface is recorded using a thermal imager, this provides new possibilities in subsurface defect detection, partially with regard to features whose orientation does not allow them to be resolved using conventional thermographic inspection techniques. In this respect it is similar to conventional focused spot detection approaches; however, the DMD allows the signal to be frequency/phase multiplexed …
Distributed Attribute Based Access Control Of Aggregated Data In Sensor Clouds, Vimal Kumar, Sanjay Kumar Madria
Distributed Attribute Based Access Control Of Aggregated Data In Sensor Clouds, Vimal Kumar, Sanjay Kumar Madria
Computer Science Faculty Research & Creative Works
Sensor clouds are large scale wireless sensor networks (WSNs), built by connecting a number of smaller WSNs together. Each of these smaller individual WSNs may be owned by different owners. Sensor clouds are dynamic in nature, where wireless sensors can be provisioned and de-provisioned for the users on demand. In such a multi-user, multi-owner system, user access control is a significant problem. Previous user access control schemes have been centralized and designed for standalone sensors or smaller networks and do not take large networks into consideration. In large networks, data is generally aggregated in-network during data collection. In this paper, …
Lazer: Distributed Memory-Efficient Assembly Of Large-Scale Genomes, Sayan Goswami, Arghya Kusum Das, Richard Platania, Kisung Lee, Seung Jong Park
Lazer: Distributed Memory-Efficient Assembly Of Large-Scale Genomes, Sayan Goswami, Arghya Kusum Das, Richard Platania, Kisung Lee, Seung Jong Park
Computer Science Faculty Research & Creative Works
Genome sequencing technology has witnessed tremendous progress in terms of throughput as well as cost per base pair, resulting in an explosion in the size of data. Consequently, typical sequence assembly tools demand a lot of processing power and memory and are unable to assemble big datasets unless run on hundreds of nodes. In this paper, we present a distributed assembler that achieves both scalability and memory efficiency by using partitioned de Bruijn graphs. By enhancing the memory-to-disk swapping and reducing the network communication in the cluster, we can assemble large sequences such as human genomes (452 GB) on just …
Mobile Computing, Internet Of Things, And Big Data For Urban Informatics, Anirban Mondal, Praveen Rao, Sanjay Kumar Madria
Mobile Computing, Internet Of Things, And Big Data For Urban Informatics, Anirban Mondal, Praveen Rao, Sanjay Kumar Madria
Computer Science Faculty Research & Creative Works
Urban informatics is emerging as a new discipline for cities and governments to improve the lives of citizens using information technology. In this advanced seminar, we introduce the key challenges and opportunities in urban informatics, discuss topics in mobile computing, Internet of Things (IoT) and big data analytics, to advance the state-of-the-art in urban informatics and provide interesting use cases. This seminar is designed for academicians, researchers, city administrators/planners, application developers, and research students with background in mobile computing and database systems.
Estimating Freeway Travel Times Using The General Motors Model, Shu Yang, Yaojan Wu, Zhaozheng Yin, Yiheng Feng
Estimating Freeway Travel Times Using The General Motors Model, Shu Yang, Yaojan Wu, Zhaozheng Yin, Yiheng Feng
Computer Science Faculty Research & Creative Works
Travel time is a key transportation performance measure because of its diverse applications. Various modeling approaches to estimating freeway travel time have been well developed due to widespread installation of intelligent transportation system sensors. However, estimating accurate travel time using existing freeway travel time models is still challenging under congested conditions. Therefore, this study aimed to develop an innovative freeway travel time estimation model based on the General Motors (GM) car-following model. Since the GM model is usually used in a microsimulation environment, the concepts of virtual leading and virtual following vehicles are proposed to allow the GM model to …
Energy-Efficient Selective Activation In Femtocell Networks, Michael Lin, Simone Silvestri, Novella Bartolini, Thomas La Porta
Energy-Efficient Selective Activation In Femtocell Networks, Michael Lin, Simone Silvestri, Novella Bartolini, Thomas La Porta
Computer Science Faculty Research & Creative Works
Provisioning the capacity of wireless networks is difficult when peak load is significantly higher than average load, for example, in public spaces like airports or train stations. Service providers can use femtocells and small cells to increase local capacity, but deploying enough femtocells to serve peak loads requires a large number of femtocells that will remain idle most of the time, which wastes a significant amount of power. To reduce the energy consumption of over-provisioned femtocell networks, we formulate a femtocell selective activation problem, which we formalize as an integer nonlinear optimization problem. Then we introduce Green Femto, a distributed …
Evaluating Different Distributed-Cyber-Infrastructure For Data And Compute Intensive Scientific Application, Arghya Kusum Das, Seung Jong Park, Jaeki Hong, Wooseok Chang
Evaluating Different Distributed-Cyber-Infrastructure For Data And Compute Intensive Scientific Application, Arghya Kusum Das, Seung Jong Park, Jaeki Hong, Wooseok Chang
Computer Science Faculty Research & Creative Works
Scientists are increasingly using the current state of the art big data analytic software (e.g., Hadoop, Giraph, etc.) for their data-intensive applications over HPC environment. However, understanding and designing the hardware environment that these data- and compute-intensive applications require for good performance is challenging. With this motivation, we evaluated the performance of big data software over three different distributed-cyber-infrastructures, including a traditional HPC-cluster called SuperMikeII, a regular datacenter called SwatIII, and a novel MicroBrick-based hyperscale system called CeresII, using our own benchmark Parallel Genome Assembler (PGA). PGA is developed atop Hadoop and Giraph and serves as a good real-world example …
Mixed-Criticality Job Models: A Comparison, Sanjoy K. Baruah, Zhishan Guo
Mixed-Criticality Job Models: A Comparison, Sanjoy K. Baruah, Zhishan Guo
Computer Science Faculty Research & Creative Works
The Vestal model in widely used in the real-time scheduling community for representing mixed-criticality real-time workloads. This model requires that multiple WCET estimates -- one for each criticality level in a system -- be obtained for each task. Burns suggests that being required to obtain too many WCET estimates may place an undue burden on system developers, and proposes a simplification to the Vestal model that makes do with just two WCET estimates per task. Burns makes a convincing case in favor of adopting this simplified model; here, we report on our attempts at comparing the two models -- Vestal’s …
Systems And Methods For Emergency Situation Communications, Sriram Chellappan, Srinivas Thandu, Patrick Sullivan, Levi Malott
Systems And Methods For Emergency Situation Communications, Sriram Chellappan, Srinivas Thandu, Patrick Sullivan, Levi Malott
Computer Science Faculty Research & Creative Works
A system for enabling communications during an emergency situation is described. A system may be configured to generate graphical user interfaces including a map displaying a location and a status of the one or more users located at the scene of an emergency situation. The graphical user interfaces may be displayed on a user's portable computing device. The graphical user interfaces may be displayed at a computing device located at a dispatcher site.
Efficient Aerial Data Collection With Uav In Large-Scale Wireless Sensor Networks, Chengliang Wang, Fei Ma, Junhui Yan, Debraj De, Sajal K. Das
Efficient Aerial Data Collection With Uav In Large-Scale Wireless Sensor Networks, Chengliang Wang, Fei Ma, Junhui Yan, Debraj De, Sajal K. Das
Computer Science Faculty Research & Creative Works
Data collection from deployed sensor networks can be with static sink, ground-based mobile sink, or Unmanned Aerial Vehicle (UAV) based mobile aerial data collector. Considering the large-scale sensor networks and peculiarity of the deployed environments, aerial data collection based on controllable UAV has more advantages. In this paper, we have designed a basic framework for aerial data collection, which includes the following five components: deployment of networks, nodes positioning, anchor points searching, fast path planning for UAV, and data collection from network. We have identified the key challenges in each of them and have proposed efficient solutions. This includes proposal …
Special Issue: Modeling & Simulation For Cyber Security Of Autonomous Vehicle Systems, Dariusz Mikulski, Greg Hudas, Sajal Das, Frank Lewis
Special Issue: Modeling & Simulation For Cyber Security Of Autonomous Vehicle Systems, Dariusz Mikulski, Greg Hudas, Sajal Das, Frank Lewis
Computer Science Faculty Research & Creative Works
No abstract provided.
On The Feasibility Of Leveraging Smartphone Accelerometers To Detect Explosion Events, Srinivas Chakravarthi Thandu, Pratool Bharti, Levi Malott, Sriram Chellappan
On The Feasibility Of Leveraging Smartphone Accelerometers To Detect Explosion Events, Srinivas Chakravarthi Thandu, Pratool Bharti, Levi Malott, Sriram Chellappan
Computer Science Faculty Research & Creative Works
In this paper, we investigate the feasibility of leveraging the accelerometer in modern smartphones to detect the triggering of explosion events. By emplacing a static smartphone and a state-of-the-art seismometer in the vicinity of real explosion blasts (conducted at an Explosives Research Lab in a university setting), and comparing their detected event readings, we make several insightful contributions. We find that readings from events in the smartphone and the seismometer are highly correlated in the temporal and frequency domain. We then demonstrate the feasibility of designing an algorithm in the smartphone (executing as an app) to detect the triggering of …
A Risk Assessment Framework For Wireless Sensor Networks In A Sensor Cloud, Amartya Sen, Sanjay Madria
A Risk Assessment Framework For Wireless Sensor Networks In A Sensor Cloud, Amartya Sen, Sanjay Madria
Computer Science Faculty Research & Creative Works
A Sensor cloud framework is composed of various heterogeneous wireless sensor networks (WSNs) integrated with the cloud platform. Integration with the cloud platform, in addition to the inherent resource and power constrained nature of the sensor nodes makes these WSNs belonging to a sensor cloud susceptible to security attacks. As such there is a need to formulate effective and efficient security measures for such an environment. But in doing so, requires an understanding of the likelihood and impact of different attacks feasible on the WSNs. In this paper, we propose a risk assessment framework for the WSNs belonging to a …
Network Coding And Coding-Aware Scheduling For Multicast In Wireless Networks, Maggie Xiaoyan Cheng, Quanmin Ye, Xiaochun Cheng, Robert F. Erbacher
Network Coding And Coding-Aware Scheduling For Multicast In Wireless Networks, Maggie Xiaoyan Cheng, Quanmin Ye, Xiaochun Cheng, Robert F. Erbacher
Computer Science Faculty Research & Creative Works
Network coding is a network layer technique to 06mprove transmission efficiency. Coding packets is especially ben07ficial in a wireless environment where the dem08nd for radio spectrum is high. However, to fully rea09ize the benefits of network coding two challenging iss10es that must be addressed are: (1) Guaranteeing sep11ration of coded packets at the destination, and (2) Mit12gating the extra coding/decoding delay. If the destination has13all the needed packets to decode a coded pac14et, then separation failure can be averted. If the sch15duling algorithm considers the arrival time of coding pai16s, then the extra delay can be mitigated. In this paper, …
Sinr-Based Connectivity Enhancement In Wireless Ad Hoc Networks, Maggie Xiaoyan Cheng, Yi Ling, Brian M. Sadler
Sinr-Based Connectivity Enhancement In Wireless Ad Hoc Networks, Maggie Xiaoyan Cheng, Yi Ling, Brian M. Sadler
Computer Science Faculty Research & Creative Works
We address the issue of wireless ad hoc network connectivity by using a tail model that is derived from the signal to interference and noise ratio (SINR). The SINR model more accurately describes link connectivity than the traditionally used disk model in the real-world. We first assess the network connectivity by measuring the conductance of the network and find the bottleneck location of the network, and then deploy a relay node to improve the connectivity at the bottleneck. A partition algorithm is proposed to address the first problem, and an optimization problem is proposed to address the relay node deployment …
Network Topology Inference With Partial Information, Brett Holbert, Srikar Tati, Simone Silvestri, Thomas F. La Porta, Ananthram Swami
Network Topology Inference With Partial Information, Brett Holbert, Srikar Tati, Simone Silvestri, Thomas F. La Porta, Ananthram Swami
Computer Science Faculty Research & Creative Works
Full knowledge of the routing topology of the Internet is useful for a multitude of network management tasks. However, the full topology is often not known and is instead estimated using topology inference algorithms. Many of these algorithms use Traceroute to probe paths and then use the collected information to infer the topology. We perform real experiments and show that, in practice, routers may severely disrupt the operation of Traceroute and cause it to only provide partial information. We propose iTop, an algorithm for inferring the network topology when only partial information is available. iTop constructs a virtual topology, which …