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Aman Kansal
Researcher at Microsoft
Publications - 160
Citations - 15209
Aman Kansal is an academic researcher from Microsoft. The author has contributed to research in topics: Wireless sensor network & Data center. The author has an hindex of 54, co-authored 159 publications receiving 14790 citations. Previous affiliations of Aman Kansal include University of California, Los Angeles & Carnegie Mellon University.
Papers
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Proceedings ArticleDOI
Controlled mobility for sustainable wireless sensor networks
TL;DR: It is argued that a new design dimension to enhance sustainability in sensor networks - the use of controlled mobility can alleviate resource limitations and improve system performance by adapting to deployment demands.
Patent
Scheduling execution of complementary jobs based on resource usage
Aman Kansal,Weiwei Xiong,Jie Liu +2 more
TL;DR: In this paper, a plurality of jobs is received and one or more jobs are mapped to other jobs based on which resources are fully utilized or overloaded, and the resources may be partitioned equally or proportionally based on the resource usage or priorities.
Patent
Virtual machine power consumption measurement and management
TL;DR: In this paper, the authors proposed a virtual machine power metering system and method to measure the power consumption of individual virtual machines, which can also be used to obtain power consumption for a specific activity (such as a service, request, or search query).
Patent
Context-based device action prediction
TL;DR: In this paper, a decision engine is used to decide whether to perform an action on a computing device based on the contextual value of a contextor, and the implementation can also update the decision engine using feedback related to the action.
Proceedings ArticleDOI
Improving energy efficiency of personal sensing applications with heterogeneous multi-processors
TL;DR: This paper experimentally and analytically investigate the design considerations that arise in the efficient use of the low power processor and provides a thorough understanding of the problem space.