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Articles 1 - 4 of 4
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Multicellular Models Bridging Intracellular Signaling And Gene Transcription To Population Dynamics, Mohammad Aminul Islam, Satyaki Roy, Sajal K. Das, Dipak Barua
Multicellular Models Bridging Intracellular Signaling And Gene Transcription To Population Dynamics, Mohammad Aminul Islam, Satyaki Roy, Sajal K. Das, Dipak Barua
Computer Science Faculty Research & Creative Works
Cell signaling and gene transcription occur at faster time scales compared to cellular death, division, and evolution. Bridging these multiscale events in a model is computationally challenging. We introduce a framework for the systematic development of multiscale cell population models. Using message passing interface (MPI) parallelism, the framework creates a population model from a single-cell biochemical network model. It launches parallel simulations on a single-cell model and treats each stand-alone parallel process as a cell object. MPI mediates cell-to-cell and cell-to-environment communications in a server-client fashion. In the framework, model-specific higher level rules link the intracellular molecular events to cellular …
Energy Constrained Dominating Set For Clustering In Wireless Sensor Networks, Julia Albath, Mayur Thakur, Sanjay Kumar Madria
Energy Constrained Dominating Set For Clustering In Wireless Sensor Networks, Julia Albath, Mayur Thakur, Sanjay Kumar Madria
Computer Science Faculty Research & Creative Works
Using partitioning in wireless sensor networks to create clusters for routing, data management, and other protocols has been proven as a way to ensure scalability and to deal with sensor network shortcomings such as limited communication ranges and energy. Choosing a cluster head within each cluster is important because cluster heads use additional energy for their responsibilities and that burden needs to be carefully passed around. Many existing protocols either choose cluster heads randomly or use nodes with the highest remaining energy. We introduce the energy constrained minimum dominating set (ECDS) to model the problem of optimally choosing cluster heads …
Incentive Based Routing Protocol For Mobile Peer To Peer Networks, Anil Jade, Sanjay Kumar Madria, Mark Linderman
Incentive Based Routing Protocol For Mobile Peer To Peer Networks, Anil Jade, Sanjay Kumar Madria, Mark Linderman
Computer Science Faculty Research & Creative Works
Incentive models are becoming increasingly popular in Mobile Peer to Peer Networks (M-P2P) as these models entice node participation in return for a virtual currency to combat free riding and to effectively manage constraint resources in the network. Many routing protocols proposed are based on best effort data traffic policy, such as the shortest route selection (hop minimization). Using virtual currency to find a cost effective optimal route from the source to the destination, while considering Quality of Service (QoS) aspects such as bandwidth and service capacity constraints for data delivery, remains a challenging task due to the presence of …
An Efficient Multicomputer Algorithm For The Solution Of Chemical Process Flowsheeting Equations, Fikret Ercal, Neil L. Book, S. Pait, J. J. Fielding
An Efficient Multicomputer Algorithm For The Solution Of Chemical Process Flowsheeting Equations, Fikret Ercal, Neil L. Book, S. Pait, J. J. Fielding
Computer Science Faculty Research & Creative Works
This paper presents a parallel solution method of large sparse systems of linear equations arising in the context of a chemical process flowsheeting application on a message passing multicomputer. To maximize the performance, the algorithm uses a novel matrix decomposition and solution method, called parallel two-phased LU decomposition, which schedules the concurrent tasks in a maximally overlapping manner, and at the same time, tries to minimize the interprocessor data dependencies and obtain optimal load balancing. The forward elimination step is performed concurrently with the parallel two-phased LU decomposition step and backward substitution is parallelized in a piecewise manner. Implementation results …