Tj Watson Research Center

Yorktown Heights, NY, United States

Tj Watson Research Center

Yorktown Heights, NY, United States
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Meyer P.,Tj Watson Research Center | Cokelaer T.,European Bioinformatics Institute | Chandran D.,Autodesk | Kim K.H.,University of Washington | And 13 more authors.
BMC Systems Biology | Year: 2014

Background: Accurate estimation of parameters of biochemical models is required to characterize the dynamics of molecular processes. This problem is intimately linked to identifying the most informative experiments for accomplishing such tasks. While significant progress has been made, effective experimental strategies for parameter identification and for distinguishing among alternative network topologies remain unclear. We approached these questions in an unbiased manner using a unique community-based approach in the context of the DREAM initiative (Dialogue for Reverse Engineering Assessment of Methods). We created an in silico test framework under which participants could probe a network with hidden parameters by requesting a range of experimental assays; results of these experiments were simulated according to a model of network dynamics only partially revealed to participants. Results: We proposed two challenges; in the first, participants were given the topology and underlying biochemical structure of a 9-gene regulatory network and were asked to determine its parameter values. In the second challenge, participants were given an incomplete topology with 11 genes and asked to find three missing links in the model. In both challenges, a budget was provided to buy experimental data generated in silico with the model and mimicking the features of different common experimental techniques, such as microarrays and fluorescence microscopy. Data could be bought at any stage, allowing participants to implement an iterative loop of experiments and computation. Conclusions: A total of 19 teams participated in this competition. The results suggest that the combination of state-of-the-art parameter estimation and a varied set of experimental methods using a few datasets, mostly fluorescence imaging data, can accurately determine parameters of biochemical models of gene regulation. However, the task is considerably more difficult if the gene network topology is not completely defined, as in challenge 2. Importantly, we found that aggregating independent parameter predictions and network topology across submissions creates a solution that can be better than the one from the best-performing submission. © 2014 Meyer et al.; licensee BioMed Central Ltd.

Ardagna D.,Polytechnic of Milan | Tanelli M.,Polytechnic of Milan | Lovera M.,Polytechnic of Milan | Zhang L.,Tj Watson Research Center
WOSP/SIPEW'10 - Proceedings of the 1st Joint WOSP/SIPEW International Conference on Performance Engineering | Year: 2010

In order to reduce the operating costs of IT systems, nowadays service applications are executed in virtualized infrastructures and a time varying fraction of the physical servers' capacity is shared among running applications. The performance modelling of a virtualized server is very challenging as the impact of the choice of the Virtual Machine Monitor (VMM) scheduler, its parameters and I/O management overhead is still only partially understood. In this paper, black-box models based on the Linear Parameter Varying (LPV) framework are proposed for the run-time modelling and performance control of Web services in virtualized hosting environments. As the behavior of the application response time is highly time varying and the workload conditions substantially change within the same business day, LPV models seem very promising for predicting the performance of such systems. Specifically, the suitability of subspace LPV identification methods for multi-variable systems is investigated and their performance assessed on experimental data gathered on Xen environments. © 2009 ACM.

Gao W.,University of Tennessee at Knoxville | Cao G.,Pennsylvania State University | Iyengar A.,Tj Watson Research Center | Srivatsa M.,Tj Watson Research Center
IEEE Transactions on Mobile Computing | Year: 2014

Disruption tolerant networks (DTNs) are characterized by low node density, unpredictable node mobility, and lack of global network information. Most of current research efforts in DTNs focus on data forwarding, but only limited work has been done on providing efficient data access to mobile users. In this paper, we propose a novel approach to support cooperative caching in DTNs, which enables the sharing and coordination of cached data among multiple nodes and reduces data access delay. Our basic idea is to intentionally cache data at a set of network central locations (NCLs), which can be easily accessed by other nodes in the network. We propose an efficient scheme that ensures appropriate NCL selection based on a probabilistic selection metric and coordinates multiple caching nodes to optimize the tradeoff between data accessibility and caching overhead. Extensive trace-driven simulations show that our approach significantly improves data access performance compared to existing schemes. © 2014 IEEE.

Zhang D.,Rutgers University | He T.,University of Minnesota | Ye F.,State University of New York at Stony Brook | Ganti R.,Tj Watson Research Center | Lei H.,Rutgers University
IEEE Transactions on Mobile Computing | Year: 2016

In many mobile sensing applications devices need to discover new neighbors and maintain the rendezvous with known neighbors continuously. Due to the limited energy supply, these devices have to duty cycle their radios to conserve the energy and bandwidth, making neighbor discovery and rendezvous maintenance even more challenging. To date, the main mechanism for device discover and rendezvous maintenance in existing solutions is pairwise, direct one-hop communication. We argue that such pairwise direct communication is sufficient but not necessary: there exist unnecessary active slots that can be eliminated, without affecting discovery and rendezvous. In this work, we propose a novel concept of extended quorum system, which leverages indirect discovery to further conserve energy. Specifically, we use quorum graph to capture all possible information flow paths where knowledge about known-neighbors can propagate among devices. By eliminating redundant paths, we can reduce the number of active slots significantly. Since a quorum graph can characterize arbitrary active schedules of mobile devices, our work can be broadly used to improve many existing quorum-based discovery and rendezvous solutions. We comprehensively evaluate EQS in three different scales of networks, and the results show that EQS reduces as much as 55% energy consumption with a maximal 5% increase in latency for existing solutions. To test the real-world values of EQS, we further propose a taxicab dispatching application called EQS-dispatch to navigate taxicab drivers to the area with less competition based on the discovery results of nearby taxicabs. © 2016 IEEE.

Bacon D.F.,Tj Watson Research Center | Rabbah R.,Tj Watson Research Center | Shukla S.,Tj Watson Research Center
Queue | Year: 2013

The programmability of FPGAs must improve if they are to be part of mainstream computing. © 2013 ACM.

Zhang R.,Smarter Energy Research Institute | Kumar T.,Smarter Energy Research Institute | Wang H.,Tj Watson Research Center
Proceedings - Winter Simulation Conference | Year: 2016

Power transformer is one of the most expensive equipments in the electrical power grid. Transformer outages may lead to substantial economical losses. One of the most important parameters governing a transformer's life expectancy and reliability is transformer aging condition and loading condition. At the same time, it is found that electric consumption is highly correlated with weather condition, therefore, in this study, we present a solution that firstly, predict the probability that a transformer Accelerated Aging Event (AAE) happens under the given weather condition; secondly, to predict the severity of the AAE, i.e., the scale of the accelerated aging factor for the event. Finally, we computed the expected life expectancy of the transformer under possible weather conditions trajectories during transformer's remaining life span using Monte Carlo simulation. © 2015 IEEE.

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