Allocation Of Computer Time Research Articles

Energy-Efficient Mobile Edge Computing in RIS-Aided OFDM-NOMA Relay Networks

In this paper, the design of task offloading and computing strategy in a mobile edge computing (MEC) system deployed over a reconfigurable intelligent surface (RIS)-aided orthogonal frequency division multiplexing based non-orthogonal multiple access (OFDM-NOMA) relay network is studied, where both a relay node and an MEC server located at an access point help a user terminal accomplish task computing. Our objective is to minimize energy consumption for communication and computation at the user terminal and the relay subject to a given task executing delay constraint. To this end, a novel protocol is first proposed to enable the user terminal and the relay to fully utilize the high passive beamforming gain provided by RIS and the high spectral efficiency offered by OFDM and NOMA techniques for task offloading. Then, under the newly proposed protocol, a resource allocation optimization problem is formulated, where RIS reflection coefficients, task offloading and computing time allocation, subcarrier and power allocation, task partition, and CPU frequency of the MEC server are jointly optimized. Because the numerous optimization variables are coupled with each other and integer programming is involved for subcarrier allocation optimization, the formulated problem is a mixed integer programming and highly non-convex problem that is hard to tackle. To address this problem, an efficient algorithm is devised to achieve its solution by employing alternating optimization, layer optimization, big-M formulation and successive convex approximation techniques. Simulation results validate that substantial energy savings can be achieved by employing RIS and OFDM-NOMA techniques in wireless relaying-based MEC systems.

Satisfaction-driven cooperative trajectory optimisation for multi-UAV-assisted mobile edge computing

This paper investigates an unmanned aerial vehicle (UAV)-assisted mobile edge computing scenario, where multiple UAVs provide computational services for user devices (UDs) with different service priorities. Taking into account UDs' different service priorities as well as diverse computation-offloading demands, a satisfaction-model is proposed, which gives consideration to UDs' satisfaction degree toward the offloading services as well as the fairness of their offloading amount. We aim to maximise UDs' sum satisfaction by jointly optimising the offloading time allocation, computing time allocation, users' transmit power, as well as UAV trajectory. A non-convex optimisation problem is formulated and an effective solution framework is proposed, where the problem is decomposed into three sub-problems that are solved alternately and iteratively by applying successive convex approximation (SCA) technique. Numerical results show that the proposed scheme achieves higher satisfaction with lower standard deviation as compared to benchmark schemes.

Computation Bits Maximization in UAV-Enabled Mobile-Edge Computing System

In recent years, unmanned aerial vehicles (UAVs) have been widely used in various industries (e.g., search and rescue, express delivery, etc.) due to their high flexibility. In addition, the deployment of UAVs equipped with mobile-edge computing (MEC) servers to provide computing services at the edges of networks has become an emerging method. Under complex and limited resource constraints, increasing the total number of computation bits in the system becomes a challenging problem. Motivated by this, in this article, we propose an optimization framework to maximize the computation bits of the whole system by jointly optimizing the bandwidth allocation, the task offloading time allocation, and the trajectory of the UAV under the energy constraints of ground devices (GDs) and the maximal battery energy of the UAV. The formulated problem is a nonconvex and nonconcave problem that is very difficult to solve. To this end, we decompose the objective function into three suboptimization problems and adopt successive convex optimization techniques to solve them. Then, we utilize the block coordinate descent (BCD) algorithm to address the overall optimization problem. By doing so, the bandwidth allocation of GDs, task offloading time and local computing time allocation in each time slot, and the trajectory of the UAV are optimized alternately during each iteration. We conduct extensive simulations, and the results verify that the proposed solution achieves a better performance than those of other benchmark schemes.

Reinforcement learning of adaptive online rescheduling timing and computing time allocation

Mathematical optimization methods have been developed to a vast variety of complex problems in the field of process systems engineering (e.g., the scheduling of chemical batch processes). However, the use of these methods in online scheduling is hindered by the stochastic nature of the processes and prohibitively long solution times when optimized over long time horizons. The following questions are raised: When to trigger a rescheduling, how much computing resources to allocate, what optimization strategy to use, and how far ahead to schedule? We propose an approach where a reinforcement learning agent is trained to make the first two decisions (i.e., rescheduling timing and computing time allocation). Using neuroevolution of augmenting topologies (NEAT) as the reinforcement learning algorithm, the approach yields, on average, better closed-loop solutions than conventional rescheduling methods on three out of four studied routing problems. We also reflect on expanding the agent’s decision-making to all four decisions.

Offloading Optimization and Time Allocation for Multiuser Wireless Energy Transfer Based Mobile Edge Computing System

This paper considers a wireless energy transfer based mobile edge computing system, where wireless devices can be charged by the radio-frequency signals broadcast by hybrid access point. With Mobile Edge Computing (MEC), wireless devices can execute their computation tasks locally or offload them to the MEC server by time division multiple access protocol. Based on this system, this paper studies the problem of system energy efficiency maximization by joint optimization of computing time allocation, energy consumption, capacity of local computing and task offloading. A Tabu search based system energy efficiency maximization algorithm is proposed for solving the optimization problems. Finally, the performance of the proposed algorithm is valued by extensive simulation experiments. Simulation results verify the effectiveness of the proposed algorithm.

Offloading and system resource allocation optimization in TDMA based wireless powered mobile edge computing

• A WP-MEC system with N WDs and one HAP is considered, where WDs and HAP are single antenna devices. • The goal is to maximize the weighted sum computation rate by joint optimization of system resources management and task computing time allocation. • An alternating direction multiplier method (ADMM) based distributed optimization method is proposed. • Experimental results show that the proposed method greatly increases the weighted sum computation rate while keeping the energy consumption at a low level. In this paper, a wireless powered mobile edge computing (WP-MEC) system is considered, in which a hybrid access point integrated with MEC servers can charge N wireless devices (WDs) by broadcasting radio-frequency signals, and the time division multiple access (TDMA) protocol is used for task offloading of WDs. The goal of this paper is to maximize the weighted sum computation rate by joint optimization of system resources management and task computing time allocation. To solve this optimization problem, an alternating direction multiplier method (ADMM) based distributed optimization method is proposed. The proposed method can decompose the optimization problem into N sub-problems, which are solved by N WDs. Experimental results show that the proposed method outperforms the benchmarks and greatly increases the weighted sum computation rate while keeping the energy consumption at a low level under the premise of time complexity O ( N ).

Energy- and angle-resolved ionization ofH2+interacting with xuv subfemtosecond laser pulses

We gratefully acknowledge fruitful discussions with Dr. A. Palacios. This work was accomplished with an allocation of computer time from Mare Nostrum BSC and CCCUAM and was partially supported by European Research Council Advanced Grant No. XCHEM 290853, MINECO Project No. FIS2013-42002-R, ERA-Chemistry Project No. PIM2010EEC-00751, European Grant No. MC-ITN CORINF, European COST Action XLIC CM1204, and the CAM project NANOFRONTMAG. H.B. acknowledges support for mobility from ITN CORINF and is grateful for the hospitality of the Universidad Autonoma de Madrid. R.E.F.S. acknowledges FCT - Fundacao para a Ciencia e Tecnologia, Portugal, Grant No. SFRH/BD/84053/2012

GPCR Activation on the Microsecond Timescale in MD Simulations

G-protein coupled receptors (GPCRs) play a central role in signal transduction and consequently represent a major drug target. Structural similarities suggest a common working mechanism, which is typically deduced from crystal structures of activation intermediates. The latter have become available recently, in particular for the light sensing GPCR rhodopsin and other members of the rhodopsin-like GPCR family. These crystal structures provide snapshots along the activation pathway, however, the transitions between those remain speculative.Time resolved spectroscopy is able to provide crucial insights into dynamic details. However, another promising route to study receptor dynamics was opened by the recent occurrence of special purpose computers for molecular dynamics (MD) simulations, which allow to observe conformational transitions related to receptor activation/deactivation directly in unbiased MD simulations on timescales of tens of microseconds.The activation kinetics for GPCRs, such as rhodopsin, typically feature time constants on the order of milliseconds, which is still beyond reach for direct simulation. However, here we present microsecond simulations for a special case, squid rhodopsin from Todarodes pacificus. While it shares many structural features with its bovine counterpart, activation occurs with a time constant of 12.5 microseconds at room temperature. We analyze simulations of the light activated receptor spanning up to 20 microseconds, allowing us to identify activation events and focus specifically on the interactions between the retinal ligand and the receptor, that trigger the activation process.This work was supported by the German Academy of Sciences Leopoldina (fellowship to M.H.) and the NSF (grant CHE-0750175). We are grateful for an allocation of computer time on Anton at the Pittsburgh Supercomputing Center (supported by the NIH).

Long Distance Lipid: Protein Coupling in the Protein Translocon

The SecY/Sec61 protein translocon is the central component of the sophisticated translocase machinery essential for the biosynthesis of membrane and secreted proteins in all branches of life. To incorporate newly synthesized transmembrane (TM) proteins into the lipid membrane, SecY opens a helical gate formed by TM helices 2 and 7 towards the bilayer. Opening of a lateral helical gate to release TM proteins requires close communication between the translocon and the lipid membrane.Here we report prolonged molecular dynamics computations on wild-type and mutant translocons with perturbed lipid interactions. We find a remarkable long-distance coupling between the translocon and the surrounding lipid membrane. Mutating amino acids that in the wild type interact with lipids affects the shape of the lipid membrane surrounding the translocon. Importantly, the status of the lipid:translocon interactions is rapidly communicated to the plug - a structural element whose displacement is thought to be part of the translocon opening. The rapid propagation of structural perturbations throughout the translocon is likely facilitated by the extensive hydrogen-bonding network of the translocon. The tight coupling between the translocon and the lipid membrane demonstrated here could explain the experimental observations that the lipid membrane composition affects the proper assembly and functioning of the translocase machinery.Research supported in part by the National Institute of General Medical Sciences (GM-74637 and GM-86685 to S.H.W), the NSF (CHE-0750175 to D.J.T), and an allocation of computer time from the NSF through the TeraGrid resources at TACC (Ranger). A.-N.B is supported in part by Marie Curie International Reintegration Award FP7-PEOPLE-2010-RG 276920.

Lipid-Coupled Docking of Transmembrane Substrate by the GlpG Rhomboid Protease from Escherichia Coli

Intramembrane proteases cleave transmembrane (TM) substrates within the plane of the lipid membrane. The GlpG rhomboid protease appears to dock its TM substrates by opening laterally towards the membrane a gate formed by helix 5. A crystal structure thought to represent GlpG in a closed state indicates a lipid headgroup bound to the catalytic site. Since the lipid must unbind for the substrate to dock, the questions arise as to how fast does lipid unbinding occur, and whether there is coupling between the incoming TM substrate and the lipid bound to the active site. To address these questions we performed systematic molecular dynamics (MD) simulations of GlpG in the absence of a TM substrate, and with TM substrate at various locations relative to GlpG. We find that, indeed, the presence of the substrate causes the lipid:active site interactions to weaken rapidly, in several tens of nanoseconds. That is, the incoming substrate prepares the enzyme for docking by inducing the displacement of the active-site lipid. The structure and dynamics of the substrate docking region of GlpG depend not only on whether or not a lipid molecule is bound to the active site, but also on the presence of the TM substrate. Our results on the lipid-coupled docking of the substrate to GlpG reveal an unsuspected complexity of the lipid interactions of intramembrane proteases.This research was supported in part by the National Institute of General Medical Sciences (GM-74637 and GM-86685 to S.H.W) and an allocation of computer time from the National Science Foundation through the TeraGrid resources at TACC (Ranger).

Opening the Protein Translocon

The protein translocon (SecY in prokaryotes/Sec61 in eukaryotes) is essential for the biosynthesis of many proteins in all organisms. Opening of the translocon is thought to involve displacement of the plug helix that helps seal the translocon in its closed state; incorporation of transmembrane helices into the lipid membrane apparently involves opening of the lateral gate formed by transmembrane (TM) helices TM2 and TM7.Our investigation of the molecular dynamics (MD) of the M. janaaschii SecYEG translocon indicated that the closed state of the translocon is stabilized by an exquisite network of inter-helical hydrogen bonds; this network also ensures that perturbations are rapidly relayed throughout the translocon, and cause displacement of the plug (1). Bioinformatics analyses and MD computations suggest an important functional role of the central cluster of hydrogen bonds that interconnect the gate helices and TM3.Targeting of secreted proteins to the translocon is generally encoded in the signal peptide, a ∼20 amino acids extension of the N-terminus of the nascent protein. MD simulations of translocons with bound proOmpA signal peptide reveal that inside the translocon the signal peptide interacts both with protein amino acid residues and water molecules. Hydrogen bonding between conserved SecY amino acids and the backbone of the signal peptide stabilizes the location of the signal peptide inside the translocon, and may explain the observation from our computations that mutating the translocon affects the structure and dynamics of the signal peptide.Research supported in part by the National Institute of General Medical Sciences (GM-74637 and GM-86685 to S.H.W) and the National Science Foundation.(CHE-0750175 to D.J.T.), and an allocation of computer time from the National Science Foundation through the TeraGrid resources at TACC (Ranger).(1) Bondar A.-N., del Val C., Freites J.A., Tobias D.J., White S.H. Structure 18: 847-857, 2010.

Lipid-Mediated Helix Gating in the GlpG Rhomboid Protease from Escherichia Coli

Intramembrane proteases cleave transmembrane substrates to liberate molecules that participate in essential cellular processes, such as cell signaling and gene regulation. Understanding how intramembrane proteases work requires knowledge of how substrates are docked and cleaved within the membrane plane. We find that lipid interactions and the presence of the substrate affect significantly the structure and dynamics of the helical gate and of the cap loop that control access to the active site of the GlpG rhomboid protease from E. coli.In the absence of the substrate, the 1-palmytoyl-2-oleoyl-sn-glycero-3-phosphatidyethanolamine (POPE) lipid molecule bound to the protease active site remains closely associated with the protease on the ∼90ns timescale of the molecular dynamics (MD) simulation. Presence of the Spitz transmembrane substrate perturbs the interactions between the protease and the active-site lipid molecule. The substrate and whether or not a lipid headgroup is bound to the active site affect the orientation of the lateral gate helix 5 relative to the rest of the protein, the structure and dynamics of the cap loop, and the interaction between the catalytic serine and water. This suggests that lipid molecules may be involved in controlling the access to the active site of intramembrane proteases.This research was supported in part by the National Institute of General Medical Sciences (GM-74637 and GM-86685 to S.H.W) and an allocation of computer time from the National Science Foundation through the TeraGrid resources at TACC (Ranger).

Lipid Membrane Composition has A Dramatic Effect on the Dynamics of the GlpG Rhomboid Protease from Escherichia Coli

Intramembrane proteases cleave transmembrane substrates to liberate physiologically important molecules. The proteolytic activity of these enzymes can be significantly influenced by the composition of the lipid membrane. Here, we find that the composition of the lipid membrane has a dramatic effect on the motions of the GlpG rhomboid serine protease from Escherichia coli.In a 1-palmytoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC) lipid bilayer, conformational changes of two critical structural elements of the protease, the cap loop close to the active site and the regulatory loop L1, occur within 40ns of unconstrained molecular dynamics simulations. In contrast, in a 1-palmytoyl-2-oleoyl-sn-glycero-3-phosphatidylethanolamine (POPE) lipid bilayer, a conformational transition of the cap loop is observed only after ∼80ns, ∼20ns after that of loop L1. This sensitivity of the enzyme motions on the lipid membrane composition is explained by differences in how POPC and POPE lipid headgroups hydrogen bond among themselves, and with protein amino acids. Tight interactions between a lipid headgroup and the active site restrict the dynamics of the cap loop.An atomistic description of the structure and dynamics of the protease:substrate complex is a critical first step towards understanding how the protease works. Molecular dynamics simulations of GlpG together with the Spitz model substrate reveal that docking of the substrate to the enzyme involves a complex interplay of changes in the structure and dynamics of the substrate, the protease, and the surrounding lipid molecules.This research was supported in part by the National Institute of General Medical Sciences (GM-74637 to S.H.W) and an allocation of computer time from the National Science Foundation through the TeraGrid resources at TACC (Ranger).

Down-State Model of the KvAP Full Channel

Voltage-gated potassium (Kv) channels have at least two distinct conformations, an “up” state, corresponding to the open/activated state of the channel, and a “down” state, corresponding to the resting state of the channel. Kv channels are tetramers that consist of a central pore domain (PD) and four peripheral voltage-sensing domains (VSDs) that respond to changes in the transmembrane (TM) potential. The PD opens and closes via mechanical coupling to the VSDs, which undergo large conformational changes as the TM potential changes. The molecular mechanism of these changes is poorly understood, because the Kv crystal structures reported to date are exclusively in the up state. We have recently reported a down-state model of the isolated VSD of KvAP that is consistent with existing experimental data. Based on this down-state model, we have now generated a down-state model for the KvAP full channel using targeted molecular dynamics. We used the end point of an equilibrated simulation of the KvAP full channel in the up state as a starting point and four symmetrically arranged down-state VSDs as targets. The PD was unconstrained during the simulation. Preliminary results suggest that, as expected, steric interactions between the S4-S5 linker and the intracellular half of S6 result in a measurable narrowing of the pore. We compare our model to the closed-state structure of the KcSA channel (2001, Science 280: 69), which consists of a Kv-homologous PD but no VSD, and to the Kv1.2 mammalian channel down-state model of Pathak et al (2007, Neuron 56: 124). This work is supported by NIH grants GM74637 and GM86685 and NSF grant CHE-0750175, and we are grateful for the allocation of computer time on the NSF-supported Teragrid resources provided by the Texas Advanced Computing Center.

A general framework on the simulation-based optimization under fixed computing budget

In many real world problems, the design space is huge and the estimation of performance measure has to rely on simulation which is time-consuming. Hence, to find the optimal design in the design space based on the simulation output is not trivial. It is important to have a computing time allocation rule to decide how much effort to spend in sampling the design space, how many designs to sample, and how long to run for each design alternative within a given computing budget. In this paper, we propose a framework for making these allocation decisions. We use the problem of assemble-to-order (ATO) systems to demonstrate how this framework can be applied. The sample average approximation (SAA) method is chosen as the sampling method used in this application example. The numerical results show that this framework provides a good basis for allocation decisions.

Crystallographic water sites from a theoretical perspective.

We thank the Robert A Welch Foundation, the Texas Coordinating Board and the National Institutes of Health for partial support of this research. Gillian C Lynch is thanked for valuable discussions and suggestions. The Metacenter is acknowledged for a generous allocation of computer time at Pittsburgh Supercomputing Center. Molecular Simulations Inc. is acknowledged for providing graphics software support.

Managing Test-Procedures to Achieve Reliable Software

Quantitative decision-making procedures are proposed to aid software project managers to manage effectively the testing stage during software project development. The module and integration testing phases are thoroughly investigated. Decision procedures which maximize the reliability and/or minimize some cost-benefit objective subject to a time and/or budget constraint are suggested. These procedures optimally allocate test time to the modules for module testing and select the optimal data mixture for integration testing. Testing of computer software is a major component of the software development effort. An efficient allocation of computer time among various modules during testing can appreciably improve reliability and shorten the testing stage. Using decision models presented in this paper, a project manager can effectively allocate test time during module testing and select the best data mixture for integration testing. The models are based upon software failure data that are collected during testing. These decision models can be valuable not only for the project manager but for the group responsible for generating the appropriate test data.

Optimal allocation of computer time in monte carlo studies of interval procedures

This paper describes three way of designing Monte Carle studies to estimate the meiusion probability of a prediction interval procedure. It diseusses the problem of computer time allocation during these Monte Carlo Studies. develops the relationships between variances of the estimates and computer times required to obtain any given variance, and gives guidelines for choosing the optimal allocation of time for specific problems.

Erratum

Correction for the author's paper “The Allocation of Computer Time in Comparing Simulation Experiments,” Operations Research, Vol. 16, 280–295 (1968).

The Allocation of Computer Time in Comparing Simulation Experiments

This paper investigates the problem of efficiently allocating computer time between two simulation experiments when the objective is to make a statistical comparison of means. For a given level of accuracy our results show that significantly less computer time is required when the sample sizes are determined according to a certain rule than when the sample sizes are equal. A graphical analysis suggests that small errors in estimating the population parameters of the allocation rule do not significantly affect the efficient allocation of time. The influence that the degree of autocorrelation has on the time allocation is also investigated; results show that small differences in the autocorrelation functions are important when each process is highly autocorrelated. Positively correlated samples for the two experiments are examined and incorporated into the efficient allocation rule. It is shown that their use leads to a saving in computer time. A two-stage procedure is described wherein initial estimates of the population parameters are computed which permit the experimenter to estimate how many more observations to collect on each experiment. The procedure is simple and straightforward to implement and should be of practical value. When the computer time requirements turn out to be prohibitive, we suggest using negatively correlated replications on each experiment. This may be accomplished by using antithetic variates. The two-stage procedure also applies in this case.