A5019688465- Cognitive Radio Networks and Spectrum Sensing
- Parallel Computing and Optimization Techniques
- Cloud Computing and Resource Management
- Software System Performance and Reliability
- Green IT and Sustainability
- Advanced MIMO Systems Optimization
- Bacterial Identification and Susceptibility Testing
- Privacy-Preserving Technologies in Data
- Cooperative Communication and Network Coding
- Advanced Bandit Algorithms Research
- Distributed systems and fault tolerance
- Stochastic Gradient Optimization Techniques
- Algorithms and Data Compression
- Advanced Research in Systems and Signal Processing
- Advanced Memory and Neural Computing
- Security in Wireless Sensor Networks
- Antimicrobial Resistance in Staphylococcus
- Full-Duplex Wireless Communications
- Target Tracking and Data Fusion in Sensor Networks
- Data Management and Algorithms
- Stochastic processes and financial applications
- Solar Thermal and Photovoltaic Systems
- Wireless Communication Security Techniques
- Web Data Mining and Analysis
- Advanced Data Storage Technologies
Manipal University Jaipur
2019-2024
National Institute of Technology Raipur
2023
Manipal Academy of Higher Education
2020-2021
University of Chicago
2014-2019
University of Cincinnati
2019
University of Illinois Chicago
2015-2018
Indian Institute of Technology Kharagpur
2011
In many deployments, computer systems are underutilized -- meaning that applications have performance requirements demand less than full system capacity. Ideally, we would take advantage of this under-utilization by allocating resources so the met and energy is minimized. This optimization problem complicated fact power consumption various configurations often application or even input dependent. Thus, practically, minimizing for a constraint requires fast, accurate estimations...
Many modern computing systems must provide reliable latency with minimal energy. Two central challenges arise when allocating system resources to meet these conflicting goals: (1) complexity hardware exposes diverse complicated interactions and (2) dynamics be maintained despite unpredictable changes in operating environment or input. Machine learning accurately models the of complex, interacting resources, but does not address dynamics; control theory adjusts dynamic changes, struggles...
Independent applications co-scheduled on the same hardware will interfere with one another, affecting performance in complicated ways. Predicting this interference is key to efficiently scheduling shared hardware, but forming accurate predictions difficult because there are many features that could lead interference. In paper we investigate machine learning approaches (specifically, regularization) understand relation between those and application We propose ESP, a highly fast regularization...
We introduce an unsupervised query segmentation scheme that uses logs as the only resource and can effectively capture structural units in queries. believe Web search queries have a unique syntactic structure which is distinct from of English or bag-of-words model. The segments discovered by our help understand this underlying grammatical structure. apply statistical model based on Hoeffding's Inequality to mine significant word n-grams subsequently use them for segmenting Evaluation against...
Machine learning and artificial intelligence are invaluable for computer systems optimization: as expose more resources management, ML/AI is necessary modeling these resources' complex interactions. The standard way to incorporate into a system first train learner accurately predict the system's behavior function of resource usage---e.g., energy efficiency core usage---and then deploy learned model part system---e.g., scheduler. In this paper, we show that (1) continued improvement accuracy...
Non-volatile memories (NVMs) have attracted significant interest recently due to their high-density, low static power, and persistence. There are, however, several challenges associated with building practical systems from NVMs, including limited write endurance long latencies. Researchers proposed a variety of architectural techniques which can achieve different tradeoffs between lifetime, performance energy efficiency; no individual technique satisfy requirements for all applications...
Many modern computing systems must provide reliable latency with minimal energy. Two central challenges arise when allocating system resources to meet these conflicting goals: (1) complexity hardware exposes diverse complicated interactions and (2) dynamics be maintained despite unpredictable changes in operating environment or input. Machine learning accurately models the of complex, interacting resources, but does not address dynamics; control theory adjusts dynamic changes, struggles...
In many deployments, computer systems are underutilized -- meaning that applications have performance requirements demand less than full system capacity. Ideally, we would take advantage of this under-utilization by allocating resources so the met and energy is minimized. This optimization problem complicated fact power consumption various configurations often application or even input dependent. Thus, practically, minimizing for a constraint requires fast, accurate estimations...
Our software framework, Proteus, treats adaptation as a first-class object, enabling rapid development of robust, adaptive applications. Proteus developers specify their programs' intent and adaptable components (or knobs). A control-theoretic runtime continually monitors the running application, adjusting knobs so that specified is met.
In many deployments, computer systems are underutilized -- meaning that applications have performance requirements demand less than full system capacity. Ideally, we would take advantage of this under-utilization by allocating resources so the met and energy is minimized. This optimization problem complicated fact power consumption various configurations often application or even input dependent. Thus, practically, minimizing for a constraint requires fast, accurate estimations...
Various quality assessment parameters for multimedia traffic in the wireless network depends on reckoning Quality of Experience (QoE) from Service (QoS). Mean Opinion Score (MOS) is extensively used metric integrated (data and video) management resource allocation. This work mainly studies an uplink underlay Dynamic Spectrum Access (DSA) optimization problem that utilizes Deep Reinforcement Learning (DRL) algorithm simultaneous QoE enhancement interference within a tolerable limit. A...
In this paper, we develop a method to estimate the relative position and heading of an Unmanned Aerial Vehicle (UAV) attempting land on moving platform using range-only measurements under GPS-denied conditions. Landing problems typically require precise estimation heading, proposed solution estimates pose between (in case ship deck) landing multirotor. Vision-based techniques although accurate will fail hostile weather conditions with lack Global Positioning System (GPS). This formulation...
Current distribution scenario reveals that the spectrum is allocated to individual service providers who have authority control access frequency traded by governing of region and provider. As a consequence, has now become scarce resource. However, with use Cognitive Radio, it becomes possible observe spectrum, so as find which frequencies are free ultimately implementing best communication shape. The aim this paper equalize total radio resources amongst devices work within same geographical...
In this paper a generalized scheme for attaining the two significant objectives in Photo-voltaic (PV) integrated system i.e., Maximum Power Point Tracking (MPPT) and Voltage regulation has been proposed under different environmental operating scenarios. A single converter- based control to extract maximum power varying degree of solar irradiance voltage dynamic loading conditions. The controller is tuned execute desired objective as per requirement application. extensively validated real...