Studies of marine physical, chemical and microbiological processes benefit from observing in a La... more Studies of marine physical, chemical and microbiological processes benefit from observing in a Lagrangian frame of reference. Some of these processes are related to specific density or temperature ranges. We have developed a method for a Tethys-class long-range autonomous underwater vehicle (LRAUV) (which has a propeller and a buoyancy engine) to track a targeted isothermal layer (within a narrow temperature range) in a stratified water column when operating in buoyancy-controlled drift mode. In this mode, the vehicle shuts off its propeller and autonomously detects the isotherm and stays with it by actively controlling the vehicle's buoyancy. The LRAUV starts on an initial descent to search for the target temperature. Once the temperature falls in the target center bracket, the vehicle records the corresponding depth and adjusts buoyancy to hold that depth. As long as the temperature stays within a tolerance range, the vehicle continues to hold that depth. If the temperature falls out of the tolerance range, the vehicle will increase or decrease buoyancy to reacquire the target temperature and track it. In a June 2015 experiment in Monterey Bay, California, an LRAUV ran the presented algorithm to successfully track a target isotherm for 13 hours. Over the isotherm tracking duration, the LRAUV mostly remained in the 0.5 • C (peak-to-peak) tolerance range as designed, even though the water column's stratification kept changing. This work paves the way to coupling an LRAUV's complimentary modes of flight and drift-searching for an oceanographic feature in flight mode, and then switching to drift mode to track the feature in a Lagrangian frame of reference.
Proceedings of the National Academy of Sciences, 2015
Significance Microbes drive biogeochemical cycles across the globe, collectively playing a centra... more Significance Microbes drive biogeochemical cycles across the globe, collectively playing a central role in shaping the biosphere. Despite their immense importance, the in situ activities of communities of microbes, in particular uncultivated lineages of “microbial dark matter,” remain poorly elucidated. In this study, we report that common temporal and ecological dynamics underpin disparate marine microbial communities, providing the first evidence that trans-Pacific diurnal transcriptional patterns in these communities may regulate ecological and biogeochemical processes across the ocean. In total, our findings indicate a remarkable regularity in the timing of community-wide activity in the ocean, and suggest that global patterns of a variety of biogeochemical transformations may be temporally predictable and governed by structured ecological determinants.
The document offers texts of papers presented at a multi-disciplinary and multi-audience transpor... more The document offers texts of papers presented at a multi-disciplinary and multi-audience transportation seminar conducted by the Department of Transportation and Logistics of the University of Northern Florida. An understanding of transportation career opportunities and manpower requirements was sought by those attend'.ng: career counselors, curriculum planners, students, industry representatives, and faculty. Papers are presented under the following categories: (1) The Economic; Social, and Political Significance of Transportation, with five apers discussing transportation and distribution, prices, economic development, urbanization, and political aspects; (2) Trarsportation Services, with four papers discussing intermodal actiiities, airline careers, United Parcel Service, and warehousing; (3) Government and Transportation, with four papers discussing government roles as promotor and regulator regarding Amtrak, aviation, and the Florida Public Service Commission; (4) Transportation Issues and Answers, with four papers discussing urban movement, safety, enviornmental and ecological considerations, and State transportation; (5) Transportation Career Opportunities, with six papers discussing railroad, carrier employment, service firms, industrial traffic management, public services, and education; (6) Transportation and the Curriculum, with six papers discussing historical considerations, economic development, government, social and environemental considerations, a curriculum development program, and a summary of findings and recommendations of a curriculum planning group at the seminar. (LH) Documents acquied by ERIC include many informal unpublished materials not available from other sources. ERIC makes every effort to obtain the best copy available. Nevertheless, items of marginal reproducibility are often encountered and this affects -the quality of the microfiche and hardcopy reproductions ERIC makes available via the ERIC Document Reproduction Service (EDRS). EDRS is not responsible for the quality of the original document. Reproductions supplied by EDRS are the best that can be made from the original.
The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, 2012
In the contemporary military environment, making decisions on how to best utilize resources to ac... more In the contemporary military environment, making decisions on how to best utilize resources to accomplish a mission with a set of specified constraints is difficult. A Cordon and Search of a village (a.k.a. village search) is an example of such a mission. Leaders must plan the mission, assigning assets (e.g. soldiers, robots, unmanned aerial vehicles, military working dogs) to accomplish the given task in accordance with orders from higher headquarters. Computer tools can assist these leaders in making decisions, and do so in a manner that will ensure the chosen solution is within mission constraints and is robust against uncertainty in environmental parameters. Currently, no such tools exist at the tactical or operational level to assist decision makers in their planning process and, as a result, individual experience and simplistic data tables are the only tools available. Using robustness concepts, this paper proposes a methodology, a mathematical model, and resource allocation h...
The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, 2014
On the modern battlefield cordon and search missions (also known as village searches) are conduct... more On the modern battlefield cordon and search missions (also known as village searches) are conducted daily. Creating resource allocations that link search teams (e.g. soldiers, robots, unmanned aerial vehicles, military working dogs) to target buildings is difficult and time consuming in the static planning environment and is even more challenging in a time-constrained dynamic environment. Conducting dynamic resource allocation during the execution of a military village search mission is beneficial especially when the time to develop a static plan is limited and hence the quality of the plan is relatively poor. Dynamic heuristics can help improve the static plan because they are able to incorporate current state information that is unavailable prior to mission execution and thus produce more accurate results than static heuristics alone can achieve. There are currently no automated means to create these dynamic resource allocations for military use. Using robustness concepts, this pa...
2006 International Conference on Parallel Processing (ICPP'06)
Often, parallel and distributed computing systems must operate in an environment replete with unc... more Often, parallel and distributed computing systems must operate in an environment replete with uncertainty. Determining a resource allocation that accounts for this uncertainty in a way that can provide a probabilistic guarantee that a given level of quality of service (QoS) is achieved is an important research problem. This paper defines a stochastic methodology for quantifiably determining a resource allocation's ability to satisfy QoS constraints in the midst of uncertainty in system parameters. Uncertainty in system parameters and its impact on system performance are modeled stochastically. This stochastic model is then used to derive a quantitative expression for the robustness of a resource allocation. The paper investigates the utility of the proposed stochastic robustness metric by applying the metric to resource allocations in a simulated distributed system. The simulation results are then compared with deterministically defined metrics from the literature.
2008 IEEE International Symposium on Parallel and Distributed Processing, 2008
This paper summarizes some of our research in the area of robust static resource allocation for d... more This paper summarizes some of our research in the area of robust static resource allocation for distributed computing systems operating under imposed Quality of Service (QoS) constraints. Often, these systems are expected to function in a physical environment replete with uncertainty, which causes the amount of processing required over time to fluctuate substantially. Determining a resource allocation that accounts for this uncertainty in a way that can provide a probabilistic guarantee that a given level of QoS is achieved is an important research problem. The stochastic robustness metric described in this research is based on a mathematical model where the relationship between uncertainty in system parameters and its impact on system performance are described stochastically.
IEEE Transactions on Parallel and Distributed Systems, 2015
Today's data centers face the issue of balancing electricity use and completion times of their wo... more Today's data centers face the issue of balancing electricity use and completion times of their workloads. Rising electricity costs are forcing data center operators to either operate within an electricity budget or to reduce electricity use as much as possible while still maintaining service agreements. Energy-aware resource allocation is one technique a system administrator can employ to address both problems: optimizing the workload completion time (makespan) when given an energy budget, or to minimize energy consumption subject to service guarantees (such as adhering to deadlines). In this paper, we study the problem of energy-aware static resource allocation in an environment where a collection of independent (non-communicating) tasks ("bag-of-tasks") is assigned to a heterogeneous computing system. Computing systems often operate in environments where task execution times vary (e.g., due to cache misses or data dependent execution times). We model these execution times stochastically, using probability density functions. We want our resource allocations to be robust against these variations, where we define energy-robustness as the probability that the energy budget is not violated, and makespan-robustness as the probability a makespan deadline is not violated. We develop and analyze several heuristics for energy-aware resource allocation for both energy-constrained and deadline-constrained problems.
Proceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM, 2007
Heterogeneous distributed computing systems often must operate in an environment where system par... more Heterogeneous distributed computing systems often must operate in an environment where system parameters are subject to uncertainty. Robustness can be defined as the degree to which a system can function correctly in the presence of parameter values different from those assumed. We present a methodology for quantifying the robustness of resource allocations in a dynamic environment where task execution times are stochastic. The methodology is evaluated through measuring the robustness of three different resource allocation heuristics within the context of a stochastic dynamic environment. A Bayesian regression model is fit to the combined results of the three heuristics to demonstrate the correlation between the stochastic robustness metric and the presented performance metric. The correlation results demonstrated the significant potential of the stochastic robustness metric to predict the relative performance of the three heuristics given a common objective function.
2009 International Conference on Parallel Processing, 2009
This research investigates the problem of robust dynamic resource allocation for heterogeneous di... more This research investigates the problem of robust dynamic resource allocation for heterogeneous distributed computing systems operating under imposed constraints. Often, such systems are expected to function in an environment where uncertainty in system parameters is common. In such an environment, the amount of processing required to complete an application may fluctuate substantially. Determining a resource allocation that accounts for this uncertainty-in a way that can provide a probability that a given level of service is achieved-is an important area of research. We define a mathematical model of stochastic robustness appropriate for a dynamic environment that can be used during resource allocation to aid heuristic decision making. In addition, we design a novel technique for maximizing stochastic robustness in this environment. Our performance results for this technique are compared with several well known resource allocation techniques in a simulated environment that models a heterogeneous distributed computing system.
2011 40th International Conference on Parallel Processing Workshops, 2011
Energy-efficient resource allocation within clusters and data centers is important because of the... more Energy-efficient resource allocation within clusters and data centers is important because of the growing cost of energy. We study the problem of energyconstrained dynamic allocation of tasks to a heterogeneous cluster computing environment. Our goal is to complete as many tasks by their individual deadlines and within the system energy constraint as possible given that task execution times are uncertain and the system is oversubscribed at times. We use Dynamic Voltage and Frequency Scaling (DVFS) to balance the energy consumption and execution time of each task. We design and evaluate (via simulation) a set of heuristics and filtering mechanisms for making allocations in our system. We show that the appropriate choice of filtering mechanisms improves performance more than the choice of heuristic (among the heuristics we tested).
An ad hoc grid is a heterogeneous computing system composed of mobile devices. Each computing res... more An ad hoc grid is a heterogeneous computing system composed of mobile devices. Each computing resource is constrained in battery energy. The problem being studied is to assign statically computing resources to the subtasks of an application that has an execution time constraint, when the resources are oversubscribed. All subtasks must be executed; to accommodate this in an oversubscribed environment, each subtask has two versions: the primary or
Energy-efficient resource allocation within clusters and data centers is important because of the... more Energy-efficient resource allocation within clusters and data centers is important because of the growing cost of energy. We study the problem of energyconstrained dynamic allocation of tasks to a heterogeneous cluster computing environment. Our goal is to complete as many tasks by their individual deadlines and within the system energy constraint as possible given that task execution times are uncertain and the system is oversubscribed at times. We use Dynamic Voltage and Frequency Scaling (DVFS) to balance the energy consumption and execution time of each task. We design and evaluate (via simulation) a set of heuristics and filtering mechanisms for making allocations in our system. We show that the appropriate choice of filtering mechanisms improves performance more than the choice of heuristic (among the heuristics we tested).
We study heterogeneous computing (HC) systems that consist of a set of different machines that ha... more We study heterogeneous computing (HC) systems that consist of a set of different machines that have varying capabilities. These machines are used to execute a set of heterogeneous tasks that vary in their computational complexity. Finding the optimal mapping of tasks to machines in an HC system has been shown to be, in general, an NP-complete problem. Therefore, heuristics have been used to find nearoptimal mappings. The performance of allocation heuristics can be affected significantly by factors such as task and machine heterogeneities. In this paper, we identify different statistical measures used to quantify the heterogeneity of HC systems, and show the correlation between the performance of the heuristics and these measures
Heterogeneous parallel and distributed computing systems may operate in an environment where cert... more Heterogeneous parallel and distributed computing systems may operate in an environment where certain system performance features degrade due to unpredictable circumstances. Robustness can be defined as the degree to which a system can function correctly in the presence of parameter values different from those assumed. This work develops a model for quantifying robustness in a dynamic heterogeneous computing environment where task execution time estimates are known to contain errors. This mathematical expression of robustness is then applied to two different problem environments. Several heuristic solutions to both problem variations are presented that utilize this expression of robustness to influence mapping decisions.
Journal of Parallel and Distributed Computing, 2008
This article appeared in a journal published by Elsevier. The attached copy is furnished to the a... more This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit:
This research investigates the problem of robust static resource allocation for distributed compu... more This research investigates the problem of robust static resource allocation for distributed computing systems operating under imposed Quality of Service (QoS) constraints. Often, such systems are expected to function in an environment where uncertainties in system parameters is common. In such an environment, the amount of processing required to complete a task may fluctuate substantially. Determining a resource allocation that accounts for this uncertainty-in a way that can provide a probability that a given level of QoS is achieved-is an important area of research. We present two techniques for maximizing the probability that a given level of QoS is achieved. The performance results for our techniques are presented for a simulated environment that models a heterogeneous clusterbased radar data processing center.
One type of heterogeneous computing (HC) systems consists of machines with diverse capabilities h... more One type of heterogeneous computing (HC) systems consists of machines with diverse capabilities harnessed together to execute a set of tasks that vary in their computational complexity. An HC system can be characterized using an Estimated Time to Compute (ETC) matrix. Each value in this matrix represents the ETC of a specific task on a specific machine when executed exclusively. Heuristics use the values in the ETC matrix to allocate tasks to machines in the HC system. The performance of resource allocation heuristics can be affected significantly by factors such as task and machine heterogeneities. Therefore, quantifying heterogeneity will allow a system to select a heuristic appropriate for the given heterogeneous environment. In this paper, we identify different central moments used to quantify the heterogeneity of ETC matrices obtained from real world systems and benchmark data, and show the effect of these moments on the performance of heuristics both through simple examples and simulations.
h i g h l i g h t s • Novel methodology for creating robust resource allocations given a tight de... more h i g h l i g h t s • Novel methodology for creating robust resource allocations given a tight deadline. • Resource allocation heuristics that maximize robustness. • Local search operator for a Genetic Algorithm including search space analysis. • Local search based path relinking crossover operator for a Genetic Algorithm.
Studies of marine physical, chemical and microbiological processes benefit from observing in a La... more Studies of marine physical, chemical and microbiological processes benefit from observing in a Lagrangian frame of reference. Some of these processes are related to specific density or temperature ranges. We have developed a method for a Tethys-class long-range autonomous underwater vehicle (LRAUV) (which has a propeller and a buoyancy engine) to track a targeted isothermal layer (within a narrow temperature range) in a stratified water column when operating in buoyancy-controlled drift mode. In this mode, the vehicle shuts off its propeller and autonomously detects the isotherm and stays with it by actively controlling the vehicle's buoyancy. The LRAUV starts on an initial descent to search for the target temperature. Once the temperature falls in the target center bracket, the vehicle records the corresponding depth and adjusts buoyancy to hold that depth. As long as the temperature stays within a tolerance range, the vehicle continues to hold that depth. If the temperature falls out of the tolerance range, the vehicle will increase or decrease buoyancy to reacquire the target temperature and track it. In a June 2015 experiment in Monterey Bay, California, an LRAUV ran the presented algorithm to successfully track a target isotherm for 13 hours. Over the isotherm tracking duration, the LRAUV mostly remained in the 0.5 • C (peak-to-peak) tolerance range as designed, even though the water column's stratification kept changing. This work paves the way to coupling an LRAUV's complimentary modes of flight and drift-searching for an oceanographic feature in flight mode, and then switching to drift mode to track the feature in a Lagrangian frame of reference.
Proceedings of the National Academy of Sciences, 2015
Significance Microbes drive biogeochemical cycles across the globe, collectively playing a centra... more Significance Microbes drive biogeochemical cycles across the globe, collectively playing a central role in shaping the biosphere. Despite their immense importance, the in situ activities of communities of microbes, in particular uncultivated lineages of “microbial dark matter,” remain poorly elucidated. In this study, we report that common temporal and ecological dynamics underpin disparate marine microbial communities, providing the first evidence that trans-Pacific diurnal transcriptional patterns in these communities may regulate ecological and biogeochemical processes across the ocean. In total, our findings indicate a remarkable regularity in the timing of community-wide activity in the ocean, and suggest that global patterns of a variety of biogeochemical transformations may be temporally predictable and governed by structured ecological determinants.
The document offers texts of papers presented at a multi-disciplinary and multi-audience transpor... more The document offers texts of papers presented at a multi-disciplinary and multi-audience transportation seminar conducted by the Department of Transportation and Logistics of the University of Northern Florida. An understanding of transportation career opportunities and manpower requirements was sought by those attend'.ng: career counselors, curriculum planners, students, industry representatives, and faculty. Papers are presented under the following categories: (1) The Economic; Social, and Political Significance of Transportation, with five apers discussing transportation and distribution, prices, economic development, urbanization, and political aspects; (2) Trarsportation Services, with four papers discussing intermodal actiiities, airline careers, United Parcel Service, and warehousing; (3) Government and Transportation, with four papers discussing government roles as promotor and regulator regarding Amtrak, aviation, and the Florida Public Service Commission; (4) Transportation Issues and Answers, with four papers discussing urban movement, safety, enviornmental and ecological considerations, and State transportation; (5) Transportation Career Opportunities, with six papers discussing railroad, carrier employment, service firms, industrial traffic management, public services, and education; (6) Transportation and the Curriculum, with six papers discussing historical considerations, economic development, government, social and environemental considerations, a curriculum development program, and a summary of findings and recommendations of a curriculum planning group at the seminar. (LH) Documents acquied by ERIC include many informal unpublished materials not available from other sources. ERIC makes every effort to obtain the best copy available. Nevertheless, items of marginal reproducibility are often encountered and this affects -the quality of the microfiche and hardcopy reproductions ERIC makes available via the ERIC Document Reproduction Service (EDRS). EDRS is not responsible for the quality of the original document. Reproductions supplied by EDRS are the best that can be made from the original.
The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, 2012
In the contemporary military environment, making decisions on how to best utilize resources to ac... more In the contemporary military environment, making decisions on how to best utilize resources to accomplish a mission with a set of specified constraints is difficult. A Cordon and Search of a village (a.k.a. village search) is an example of such a mission. Leaders must plan the mission, assigning assets (e.g. soldiers, robots, unmanned aerial vehicles, military working dogs) to accomplish the given task in accordance with orders from higher headquarters. Computer tools can assist these leaders in making decisions, and do so in a manner that will ensure the chosen solution is within mission constraints and is robust against uncertainty in environmental parameters. Currently, no such tools exist at the tactical or operational level to assist decision makers in their planning process and, as a result, individual experience and simplistic data tables are the only tools available. Using robustness concepts, this paper proposes a methodology, a mathematical model, and resource allocation h...
The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, 2014
On the modern battlefield cordon and search missions (also known as village searches) are conduct... more On the modern battlefield cordon and search missions (also known as village searches) are conducted daily. Creating resource allocations that link search teams (e.g. soldiers, robots, unmanned aerial vehicles, military working dogs) to target buildings is difficult and time consuming in the static planning environment and is even more challenging in a time-constrained dynamic environment. Conducting dynamic resource allocation during the execution of a military village search mission is beneficial especially when the time to develop a static plan is limited and hence the quality of the plan is relatively poor. Dynamic heuristics can help improve the static plan because they are able to incorporate current state information that is unavailable prior to mission execution and thus produce more accurate results than static heuristics alone can achieve. There are currently no automated means to create these dynamic resource allocations for military use. Using robustness concepts, this pa...
2006 International Conference on Parallel Processing (ICPP'06)
Often, parallel and distributed computing systems must operate in an environment replete with unc... more Often, parallel and distributed computing systems must operate in an environment replete with uncertainty. Determining a resource allocation that accounts for this uncertainty in a way that can provide a probabilistic guarantee that a given level of quality of service (QoS) is achieved is an important research problem. This paper defines a stochastic methodology for quantifiably determining a resource allocation's ability to satisfy QoS constraints in the midst of uncertainty in system parameters. Uncertainty in system parameters and its impact on system performance are modeled stochastically. This stochastic model is then used to derive a quantitative expression for the robustness of a resource allocation. The paper investigates the utility of the proposed stochastic robustness metric by applying the metric to resource allocations in a simulated distributed system. The simulation results are then compared with deterministically defined metrics from the literature.
2008 IEEE International Symposium on Parallel and Distributed Processing, 2008
This paper summarizes some of our research in the area of robust static resource allocation for d... more This paper summarizes some of our research in the area of robust static resource allocation for distributed computing systems operating under imposed Quality of Service (QoS) constraints. Often, these systems are expected to function in a physical environment replete with uncertainty, which causes the amount of processing required over time to fluctuate substantially. Determining a resource allocation that accounts for this uncertainty in a way that can provide a probabilistic guarantee that a given level of QoS is achieved is an important research problem. The stochastic robustness metric described in this research is based on a mathematical model where the relationship between uncertainty in system parameters and its impact on system performance are described stochastically.
IEEE Transactions on Parallel and Distributed Systems, 2015
Today's data centers face the issue of balancing electricity use and completion times of their wo... more Today's data centers face the issue of balancing electricity use and completion times of their workloads. Rising electricity costs are forcing data center operators to either operate within an electricity budget or to reduce electricity use as much as possible while still maintaining service agreements. Energy-aware resource allocation is one technique a system administrator can employ to address both problems: optimizing the workload completion time (makespan) when given an energy budget, or to minimize energy consumption subject to service guarantees (such as adhering to deadlines). In this paper, we study the problem of energy-aware static resource allocation in an environment where a collection of independent (non-communicating) tasks ("bag-of-tasks") is assigned to a heterogeneous computing system. Computing systems often operate in environments where task execution times vary (e.g., due to cache misses or data dependent execution times). We model these execution times stochastically, using probability density functions. We want our resource allocations to be robust against these variations, where we define energy-robustness as the probability that the energy budget is not violated, and makespan-robustness as the probability a makespan deadline is not violated. We develop and analyze several heuristics for energy-aware resource allocation for both energy-constrained and deadline-constrained problems.
Proceedings - 21st International Parallel and Distributed Processing Symposium, IPDPS 2007; Abstracts and CD-ROM, 2007
Heterogeneous distributed computing systems often must operate in an environment where system par... more Heterogeneous distributed computing systems often must operate in an environment where system parameters are subject to uncertainty. Robustness can be defined as the degree to which a system can function correctly in the presence of parameter values different from those assumed. We present a methodology for quantifying the robustness of resource allocations in a dynamic environment where task execution times are stochastic. The methodology is evaluated through measuring the robustness of three different resource allocation heuristics within the context of a stochastic dynamic environment. A Bayesian regression model is fit to the combined results of the three heuristics to demonstrate the correlation between the stochastic robustness metric and the presented performance metric. The correlation results demonstrated the significant potential of the stochastic robustness metric to predict the relative performance of the three heuristics given a common objective function.
2009 International Conference on Parallel Processing, 2009
This research investigates the problem of robust dynamic resource allocation for heterogeneous di... more This research investigates the problem of robust dynamic resource allocation for heterogeneous distributed computing systems operating under imposed constraints. Often, such systems are expected to function in an environment where uncertainty in system parameters is common. In such an environment, the amount of processing required to complete an application may fluctuate substantially. Determining a resource allocation that accounts for this uncertainty-in a way that can provide a probability that a given level of service is achieved-is an important area of research. We define a mathematical model of stochastic robustness appropriate for a dynamic environment that can be used during resource allocation to aid heuristic decision making. In addition, we design a novel technique for maximizing stochastic robustness in this environment. Our performance results for this technique are compared with several well known resource allocation techniques in a simulated environment that models a heterogeneous distributed computing system.
2011 40th International Conference on Parallel Processing Workshops, 2011
Energy-efficient resource allocation within clusters and data centers is important because of the... more Energy-efficient resource allocation within clusters and data centers is important because of the growing cost of energy. We study the problem of energyconstrained dynamic allocation of tasks to a heterogeneous cluster computing environment. Our goal is to complete as many tasks by their individual deadlines and within the system energy constraint as possible given that task execution times are uncertain and the system is oversubscribed at times. We use Dynamic Voltage and Frequency Scaling (DVFS) to balance the energy consumption and execution time of each task. We design and evaluate (via simulation) a set of heuristics and filtering mechanisms for making allocations in our system. We show that the appropriate choice of filtering mechanisms improves performance more than the choice of heuristic (among the heuristics we tested).
An ad hoc grid is a heterogeneous computing system composed of mobile devices. Each computing res... more An ad hoc grid is a heterogeneous computing system composed of mobile devices. Each computing resource is constrained in battery energy. The problem being studied is to assign statically computing resources to the subtasks of an application that has an execution time constraint, when the resources are oversubscribed. All subtasks must be executed; to accommodate this in an oversubscribed environment, each subtask has two versions: the primary or
Energy-efficient resource allocation within clusters and data centers is important because of the... more Energy-efficient resource allocation within clusters and data centers is important because of the growing cost of energy. We study the problem of energyconstrained dynamic allocation of tasks to a heterogeneous cluster computing environment. Our goal is to complete as many tasks by their individual deadlines and within the system energy constraint as possible given that task execution times are uncertain and the system is oversubscribed at times. We use Dynamic Voltage and Frequency Scaling (DVFS) to balance the energy consumption and execution time of each task. We design and evaluate (via simulation) a set of heuristics and filtering mechanisms for making allocations in our system. We show that the appropriate choice of filtering mechanisms improves performance more than the choice of heuristic (among the heuristics we tested).
We study heterogeneous computing (HC) systems that consist of a set of different machines that ha... more We study heterogeneous computing (HC) systems that consist of a set of different machines that have varying capabilities. These machines are used to execute a set of heterogeneous tasks that vary in their computational complexity. Finding the optimal mapping of tasks to machines in an HC system has been shown to be, in general, an NP-complete problem. Therefore, heuristics have been used to find nearoptimal mappings. The performance of allocation heuristics can be affected significantly by factors such as task and machine heterogeneities. In this paper, we identify different statistical measures used to quantify the heterogeneity of HC systems, and show the correlation between the performance of the heuristics and these measures
Heterogeneous parallel and distributed computing systems may operate in an environment where cert... more Heterogeneous parallel and distributed computing systems may operate in an environment where certain system performance features degrade due to unpredictable circumstances. Robustness can be defined as the degree to which a system can function correctly in the presence of parameter values different from those assumed. This work develops a model for quantifying robustness in a dynamic heterogeneous computing environment where task execution time estimates are known to contain errors. This mathematical expression of robustness is then applied to two different problem environments. Several heuristic solutions to both problem variations are presented that utilize this expression of robustness to influence mapping decisions.
Journal of Parallel and Distributed Computing, 2008
This article appeared in a journal published by Elsevier. The attached copy is furnished to the a... more This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit:
This research investigates the problem of robust static resource allocation for distributed compu... more This research investigates the problem of robust static resource allocation for distributed computing systems operating under imposed Quality of Service (QoS) constraints. Often, such systems are expected to function in an environment where uncertainties in system parameters is common. In such an environment, the amount of processing required to complete a task may fluctuate substantially. Determining a resource allocation that accounts for this uncertainty-in a way that can provide a probability that a given level of QoS is achieved-is an important area of research. We present two techniques for maximizing the probability that a given level of QoS is achieved. The performance results for our techniques are presented for a simulated environment that models a heterogeneous clusterbased radar data processing center.
One type of heterogeneous computing (HC) systems consists of machines with diverse capabilities h... more One type of heterogeneous computing (HC) systems consists of machines with diverse capabilities harnessed together to execute a set of tasks that vary in their computational complexity. An HC system can be characterized using an Estimated Time to Compute (ETC) matrix. Each value in this matrix represents the ETC of a specific task on a specific machine when executed exclusively. Heuristics use the values in the ETC matrix to allocate tasks to machines in the HC system. The performance of resource allocation heuristics can be affected significantly by factors such as task and machine heterogeneities. Therefore, quantifying heterogeneity will allow a system to select a heuristic appropriate for the given heterogeneous environment. In this paper, we identify different central moments used to quantify the heterogeneity of ETC matrices obtained from real world systems and benchmark data, and show the effect of these moments on the performance of heuristics both through simple examples and simulations.
h i g h l i g h t s • Novel methodology for creating robust resource allocations given a tight de... more h i g h l i g h t s • Novel methodology for creating robust resource allocations given a tight deadline. • Resource allocation heuristics that maximize robustness. • Local search operator for a Genetic Algorithm including search space analysis. • Local search based path relinking crossover operator for a Genetic Algorithm.
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Papers by Jay Smith