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Shivkumar Kalyanaraman

Researcher at IBM

Publications -  289
Citations -  6866

Shivkumar Kalyanaraman is an academic researcher from IBM. The author has contributed to research in topics: Network packet & Network congestion. The author has an hindex of 42, co-authored 287 publications receiving 6677 citations. Previous affiliations of Shivkumar Kalyanaraman include Ohio State University & Rensselaer Polytechnic Institute.

Papers
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Patent

Optimisation framework for wireless analytics

TL;DR: In this paper, a radio network controller extracts a common structure by collaborative filtering data associated with a plurality of user devices and the plurality of received objects and analyzes the common structure to infer usage patterns within a time slot.
Patent

Monitoring and evaluating performance and aging of solar photovoltaic generation systems and power inverters

TL;DR: In this paper, a method for monitoring and evaluation of individual subsystems within solar photovoltaic power generation systems is presented, which includes the steps of: obtaining sensor data from the photiovoltaic system, computing an efficiency of the panels and an efficiency for the inverter system using the sensor data; computing an aging parameter for the panels using the efficiency of panels; determining whether the aging parameters for the panel or inverter for the system exceeds a predetermined threshold level; and taking action if either the aging parameter or for the array or for a system exceeds the threshold level
Proceedings ArticleDOI

Macro-scheduling of base stations for video-on-demand flows in WiMAX networks

TL;DR: A simulation-based evaluation shows that the overall macro scheduling scheme can improve the number of satisfied users by up to 35% in comparison to other approaches, while only minimally sacrificing on throughput.
Patent

Internet of things-enabled solar photovoltaic health monitoring and advising related thereto

TL;DR: In this article, a computer-implemented method includes obtaining current-voltage samples corresponding to solar photovoltaic modules by triggering switch circuitry between an inverter attributed to the solar PV modules and a currentvoltage tracer, detecting one or more anomalies in the obtained current voltages, automatically performing a root cause analysis on the detected anomalies, and automatically generating and outputting a suggestion for remedial action based on the identified pre-determined anomaly class.