Aditya Kumar Mishra

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The goal of the Smart* project is to optimize home energy consumption. As part of the project, we have designed and deployed a “live” system that continuously gathers a wide variety of environmental and operational data in three real homes. In contrast to prior work, our focus has been on sensing depth, i.e., collecting as much data as possible from each(More)
Flattening household electricity demand reduces generation costs, since costs are disproportionately affected by peak demands. While the vast majority of household electrical loads are interactive and have little scheduling flexibility (TVs, microwaves, etc.), a substantial fraction of home energy use derives from background loads with some, albeit limited,(More)
Market-based electricity pricing provides consumers an opportunity to lower their electric bill by shifting consumption to low price periods. In this paper, we explore how to lower electric bills without requiring consumer involvement using an intelligent charging system, called SmartCharge, and an on-site battery array to store low-cost energy for use(More)
Distributed generation (DG) uses many small on-site energy sources deployed at individual buildings to generate electricity. DG has the potential to make generation more efficient by reducing transmission and distribution losses, carbon emissions, and demand peaks. However, since renewables are intermittent and uncontrollable, buildings must still rely, in(More)
Renewable energy harvested from the environment is an attractive option for providing green energy to homes. Unfortunately, the intermittent nature of renewable energy results in a mismatch between when these sources generate energy and when homes demand it. This mismatch reduces the efficiency of using harvested energy by either i) requiring batteries to(More)
In an entity classification task, topic or concept hierarchies are often incomplete. Previous work by Dalvi et al. [12] has showed that in non-hierarchical semi-supervised classification tasks, the presence of such unanticipated classes can cause semantic drift for seeded classes. The Exploratory learning [12] method was proposed to solve this problem;(More)
Distributed generation (DG) uses many small onsite energy harvesting deployments at individual buildings to generate electricity. DG has the potential to make generation more efficient by reducing transmission and distribution losses, carbon emissions, and demand peaks. However, since renewables are intermittent and uncontrollable, buildings must still(More)
In this work, we revisit the traffic engineering (TE) problem focusing on user-perceived application performance, an aspect that has largely been ignored in prior work. Using real traffic matrices and topologies from three ISPs, we conduct very large-scale experiments simulating ISP traffic as an aggregate of a large number of TCP flows. Our(More)
Reducing peak demand is an important part of ongoing smart grid research efforts. To reduce peak demand, utilities are introducing variable rate electricity prices. Recent efforts have shown how variable rate pricing can incentivize consumers to use energy storage to cut their electricity bill, by storing energy during inexpensive off-peak periods and using(More)
Open Shortest Path First (OSPF) is one of the most widely used intra-domain routing protocol. It is well known that OSPF protocol does not provide flexibility in terms of packet forwarding to achieve any network optimization objective. Because of the high cost of network assets and commercial and competitive nature of Internet service provisioning, service(More)