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Scheduling Tasks to Maximize Usage of Aggregate Variables in Place [chapter]

Samah Abu-Mahmeed, Cheryl McCosh, Zoran Budimlić, Ken Kennedy, Kaushik Ravindran, Kevin Hogan, Paul Austin, Steve Rogers, Jacob Kornerup
2009 Lecture Notes in Computer Science  
In this paper, we present a greedy algorithm for in-place computation of aggregate (array and structure) variables.  ...  Our algorithm greedily picks the most profitable opportunities for in-place computation, then updates the scheduling and in-place constraints in the program graph.  ...  We would also like to thank Keith Cooper and Tim Harvey for their insights and discussions concerning relevant register allocation topics, and Vivek Sarkar for his assistance in understanding copy elimination  ... 
doi:10.1007/978-3-642-00722-4_15 fatcat:pxp2fropdva7vjj6nz24nftoam

Network Lifetime Maximization in Wireless Mesh Networks for Machine-to-Machine Communication

Emma Fitzgerald, Michał Pióro, Artur Tomaszewski
2019 Ad hoc networks  
In this paper we present new optimization formulations for maximizing the network lifetime in wireless mesh networks performing data aggregation and dissemination for machine-tomachine communication in  ...  the Internet of Things.  ...  Acknowledgements The presented work was supported by the National Science Centre, Poland, under the grant no. 2017/25/B/ST7/02313, "Packet routing and transmission scheduling optimization  ... 
doi:10.1016/j.adhoc.2019.101987 fatcat:xfdrg7t7pba7djgszst5prhsam

Resource coordination in Wireless Sensor Networks by combinatorial auction based method

Muhidul Islam Khan, Bernhard Rinner, Carlo S. Regazzoni
2012 2012 IEEE 3rd International Conference on Networked Embedded Systems for Every Application (NESEA)  
Scheduling of these tasks is very important aspect for WSN in order to coordinate the resources. In this paper, an effective market based method is proposed for resource coordination in WSN.  ...  These application needs to perform some tasks like sensing, transmitting, sleeping, receiving etc. At each time step, the sensor nodes need to perform one task based on its application demand.  ...  ACKNOWLEDGMENT This work was supported in part by the Erasmus Mundus Joint Doctorate in Interactive and Cognitive Environments, which is funded by the EACEA Agency of the European Commission under EMJD  ... 
doi:10.1109/nesea.2012.6474012 dblp:conf/nesea/KhanRR12 fatcat:v73wsmn4wne7xgbjsenjc7zpqe


Won Wook Song, Myeongjae Jeon, Byung-Gon Chun
2022 Proceedings of the 13th ACM SIGOPS Asia-Pacific Workshop on Systems  
Stream analytics desirable under a WAN setup requires the consideration of path diversity and the associated bandwidth from data source to sink when performing operator task placement for the query execution  ...  However, timely processing of such data streams is challenging because wide-area network (WAN) bandwidth is scarce and varies widely across both different geo-locations (i.e., spatially) and points of  ...  In our example, we can observe that NY has the best network conditions among the three sites, and our scheduling algorithm places a total of 8 tasks on NY, while placing 4 tasks each in Paris and Seoul  ... 
doi:10.1145/3546591.3547524 fatcat:wduedc4xljhg3bpiqw7pxd6iba

Allocating Jobs with Periodic Demand Variations [chapter]

Olivier Beaumont, Ikbel Belaid, Lionel Eyraud-Dubois, Juan-Angel Lorenzo-del-Castillo
2015 Lecture Notes in Computer Science  
In the context of service hosting in large-scale datacenters, we consider the problem faced by a provider for allocating services to machines.  ...  In this paper, we provide a mathematical framework to analyze the packing of services exhibiting daily patterns and whose peaks occur at different times.  ...  In this case, it seems reasonable to place those services on different physical machines to avoid machine starvation.  ... 
doi:10.1007/978-3-662-48096-0_12 fatcat:pz6dan6ko5h2tkighmc267gq7a

Scheduling of Time-Varying Workloads Using Reinforcement Learning

Shanka Subhra Mondal, Nikhil Sheoran, Subrata Mitra
2021 AAAI Conference on Artificial Intelligence  
Due to the variety of time-varying workloads and their complex resource usage characteristics, it is challenging to design well-defined heuristics for scheduling them optimally across different machines  ...  In this paper, we propose a Deep Reinforcement Learning (DRL) based approach to exploit various temporal resource usage patterns of timevarying workloads as well as a technique for creating equivalence  ...  We design high penalty to the cases where any of the machines were not able to meet the aggregate resource requirement of TVWs scheduled in that machine, during any period of time.  ... 
dblp:conf/aaai/MondalSM21 fatcat:6y7kawcwirfavcwu6aeivuwczq

Continuous refinement of agent resource estimates

David N. Morley, Karen L. Myers, Neil Yorke-Smith
2006 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems - AAMAS '06  
The challenge we address is to reason about projected resource usage within a hierarchical task execution framework in order to improve agent effectiveness.  ...  Specifically, we seek to define and maintain maximally informative guaranteed bounds on projected resource requirements, in order to enable an agent to take full advantage of available resources while  ...  This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA), through the Department of the Interior, NBC, Acquisition Services Division, under Contract No.  ... 
doi:10.1145/1160633.1160787 dblp:conf/atal/MorleyMY06 fatcat:kidelw5rvfhgrfdh3cormflbi4

Scheduling Live Migration of Virtual Machines

Vincent Kherbache, Eric Madelaine, Fabien Hermenier
2017 IEEE Transactions on Cloud Computing  
To provide schedules with minimal completion times, mVM parallelizes and sequentializes the migrations with regards to the memory workload and the network topology. mVM is implemented as a plugin of BtrPlace  ...  By computing schedules involving thousands of migrations performed over various fat-tree network topologies, we observed that the mVM solving time accounts for about 1% of the schedule execution time.  ...  Each consists in placing a set of tasks on a bounded resource. A task aggregates three variables: a height, a duration, and a starting time.  ... 
doi:10.1109/tcc.2017.2754279 fatcat:uxmhp4ewgvfgrbkdr6jnruyyuy

Production scheduling of a large-scale industrial continuous plant: Short-term and medium-term scheduling

Munawar A. Shaik, Christodoulos A. Floudas, Josef Kallrath, Hans-Joachim Pitz
2009 Computers and Chemical Engineering  
An upper-level model is used to find the optimal number of products, and length of the time horizon to be considered for solving the lower level short-term scheduling problem.  ...  In this work, we describe short-term and medium-term scheduling for a largescale industrial continuous plant.  ...  of each task, in order to satisfy the market requirements while maximizing/minimizing some objective function.  ... 
doi:10.1016/j.compchemeng.2008.08.013 fatcat:pkfrr4ieqbfxpj7jjowpj3qfve

Electricity Consumption Constraints for Smart-home Automation: An Overview of Models and Applications

Gulnar Mehdi, Mikhal Roshchin
2015 Energy Procedia  
The realization of this smart architecture necessitates the agents need to know their decision space, in order to schedule different devices according to their individual constraints.  ...  The global energy consumption challenge can largely be addressed by adoption of smart-home autonomous agents, allowing adaptive scheduling of electronic devicesfor household and businesses alike.  ...  His valuable feedback sessions were important in development of models and study structure.  ... 
doi:10.1016/j.egypro.2015.12.196 fatcat:6q4rpqnfbzhzzougjdzvgxdkha

Enabling Distributed Energy Storage by Incentivizing Small Load Shifts

David Irwin, Srinivasan Iyengar, Stephen Lee, Aditya Mishra, Prashant Shenoy, Ye Xu
2017 ACM Transactions on Cyber-Physical Systems  
In addition, unlike variable rate pricing, we also show that flat-power pricing incentivizes the scheduling of elastic background loads, such as air conditioners and heaters, to reduce peak demand.  ...  power usage as possible to low-price, off-peak periods.  ...  Of course, schedulers cannot arbitrarily stretch a load, as the average power usage and duration of a task affects its operation.  ... 
doi:10.1145/3015663 fatcat:s6xtz2h4sjgzniqwq73moniig4

Optimized Task Group Aggregation-Based Overflow Handling on Fog Computing Environment Using Neural Computing

Harwant Singh Arri, Ramandeep Singh Khosa, Sudan Jha, Deepak Prashar, Gyanendra Prasad Joshi, Ill Chul Doo
2021 Mathematics  
In terms of virtual machine efficiency for resource scheduling, average success rate, average task completion success rate, and virtual machine response time are improved.  ...  As a result of TGA usage in conjunction with an Artificial Neural Network (ANN), we may assess the model's QoS characteristics to detect an overloaded server and then move the model's data to virtual machines  ...  Load Balancing: In order to maximize time efficiency and make optimal use of resources, it distributes jobs or loads among multiple system nodes.  ... 
doi:10.3390/math9192522 fatcat:qfwgbpwbfrg2ristcmpvmzpkde

Optimizing Task Placement and Online Scheduling for Distributed GNN Training Acceleration [article]

Ziyue Luo, Yixin Bao, Chuan Wu
2022 arXiv   pre-print
The potentials of strategical task placement and optimal scheduling of data transmission and task execution have not been well explored.  ...  Our framework consists of two modules: (i) an online scheduling algorithm that schedules the execution of training tasks, and the data transmission plan; and (ii) an exploratory task placement scheme that  ...  Let binary variable x t j,n indicate the start time of task j in iteration n: x t j,n is 1 if task j in iteration n starts at time t, and 0, otherwise.  ... 
arXiv:2204.11224v1 fatcat:sv5dsh77fjg6rawwzbtoqfzr2q

Mutable Protection Domains: Towards a Component-Based System for Dependable and Predictable Computing

Gabriel Parmer, Richard West
2007 28th IEEE International Real-Time Systems Symposium (RTSS 2007)  
In this way, a system can be dynamically reconfigured to maximize software fault isolation, increasing dependability, while guaranteeing various tasks are executed according to specific time constraints  ...  system, to ensure resource constraints while simultaneously maximizing isolation benefit.  ...  A schedule is then constructed assuming this WCET, and the implicit requirement placed on the system is that the task must complete execution within its allotted CPU share.  ... 
doi:10.1109/rtss.2007.27 dblp:conf/rtss/ParmerW07 fatcat:dn6dqpckd5cjtk23yncf7o4tvq

Towards energy-aware scheduling in data centers using machine learning

Josep Ll. Berral, Íñigo Goiri, Ramón Nou, Ferran Julià, Jordi Guitart, Ricard Gavaldà, Jordi Torres
2010 Proceedings of the 1st International Conference on Energy-Efficient Computing and Networking - e-Energy '10  
There is a growing interest in "Green" IT and there is still a big gap in this area to be covered.  ...  As energy-related costs have become a major economical factor for IT infrastructures and data-centers, companies and the research community are being challenged to find better and more efficient power-aware  ...  Our approach applies some scheduling policies that reduce the number of unused machines according to the workload needs in each moment, and decide task placing and reallocation in order to compact jobs  ... 
doi:10.1145/1791314.1791349 dblp:conf/eenergy/BerralGNJGGT10 fatcat:wb65jkzg4fhejh3ljqcpcvmj4u
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