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Optimizing MapReduce for Highly Distributed Environments
[article]
2012
arXiv
pre-print
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We propose a model-driven optimization that has two key features: (i) it is end-to-end as opposed to myopic optimizations that may only make locally optimal but globally suboptimal decisions, and (ii) ...
In this paper, we develop a modeling framework to capture MapReduce execution in a highly distributed environment comprising distributed data sources and distributed computational resources. ...
Our results also show that as the network becomes more distributed and heterogeneous, our optimization provides higher benefits (82% for globally distributed sites vs. 37% for a single local cluster over ...
arXiv:1207.7055v1
fatcat:bou3twbytvgh5ldwvvavju4c5a
Progressive optimization in a shared-nothing parallel database
2007
Proceedings of the 2007 ACM SIGMOD international conference on Management of data - SIGMOD '07
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In this paper, we present a comprehensive and practical solution to this problem, including several novel voting schemes whether to trigger re-optimization, a mechanism to reuse local intermediate results ...
Extending the serial POP to a parallel environment is a challenging problem since we need to determine when and how we can trigger re-optimization based on cardinalities collected from multiple independent ...
CHECKPOINT OPERATOR PLACEMENT STRATEGIES FOR PARALLEL QUERY EXECUTION PLANS The main metrics concerning the placement of PCHECK operators are the risk and opportunity of re-optimization. ...
doi:10.1145/1247480.1247569
dblp:conf/sigmod/HanNMKK07
fatcat:rtweo2qkezhrbfym3dys3ik3de
Optimizing Cloud-Service Performance: Efficient Resource Provisioning via Optimal Workload Allocation
2017
IEEE Transactions on Parallel and Distributed Systems
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However, finding the optimal workloadallocation algorithm in a heterogeneous computing environment is in general an NPhard problem [30, 31] . ...
Chapter 4 Optimal workload allocation Workload allocation (or task scheduling) is a critical issue in heterogeneous computing environments such as cloud computing. ...
doi:10.1109/tpds.2016.2628370
fatcat:hqqv6m6akva2rhnjkuilauvvhu
Optimized load balance scheduling algorithm
2022
TELKOMNIKA (Telecommunication Computing Electronics and Control)
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In this work a combination of two inspired metaheuristic algorithms BAT and cuckoo search was proposed; the first algorithm can utilize fast exploration using global search, the latter algorithm can avoid ...
trapping into BAT local optimum problem using levy flight with a far random walk. ...
This strategy is used in the global BAT search. ...
doi:10.12928/telkomnika.v20i1.22464
fatcat:ppdg6bowvfbtjhlfx26u2a65xa
Hybrid Whale Optimization Algorithm for Resource Optimization in Cloud E-Healthcare Applications
2022
Computers Materials & Continua
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To overcome this issue many resource optimization meta-heuristic models are been proposed but these models cannot find a global best solution to complete the task in the least time and manage utilization ...
In the next generation of computing environment e-health care services depend on cloud services. ...
The search agents provide the solution space which includes multiple local optimal search agents and may include global optimal search agents. ...
doi:10.32604/cmc.2022.023056
fatcat:foyrh4bil5gbjk3m3oimfnwqxa
Optimal cache allocation for Content-Centric Networking
2013
2013 21st IEEE International Conference on Network Protocols (ICNP)
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We formulate this problem as a content placement problem and obtain the exact optimal solution by a two-step method. ...
Through simulations, we use this algorithm to investigate the factors that affect the optimal cache allocation in CCN, such as the network topology and the popularity of content. ...
Homogeneous allocation strategies do substantially worse, while the performance of the optimal allocation decreases in an approximately logarithmic manner. • The benefits of heterogeneous optimal cache ...
doi:10.1109/icnp.2013.6733577
dblp:conf/icnp/WangLTUX13
fatcat:jblpnsivkng6tnjpowoujrx6vu
Multi-factorial Optimization for Large-scale Virtual Machine Placement in Cloud Computing
[article]
2020
arXiv
pre-print
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The results show that compared with various heuristic methods, our method could shorten optimization time significantly and offer a competitive placement solution for the LVMP problem in heterogeneous ...
This paper aims to apply the MFO technology to the LVMP problem in heterogeneous environment. Firstly, we formulate a deployment cost based VMP problem in the form of the MFO problem. ...
The choice of virtual machine placement (VMP) strategy is vital to lower operational cost for cloud service providers. ...
arXiv:2001.06585v2
fatcat:k2jleyrm6rg6fokbxd5qqx6hui
Swarm Tetris: Applying particle swarm optimization to tetris
2010
IEEE Congress on Evolutionary Computation
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In this paper it is aimed to retrieve the cost of query plans as well as cost of particles of swarm in multiple query processing environments by applying particle swarm optimization techniques. ...
Major tasks in multiple query processing are common operation or expression identification and global execution plan construction. ...
the following sequence: (1) query decomposition, (2) data localization, (3)global optimization, (4) local optimization. ...
doi:10.1109/cec.2010.5586033
dblp:conf/cec/LangenhovenHE10
fatcat:4t3f3j7i4fc5zihylvap4w5c2q
AI-aided Traffic Differentiated QoS Routing and Dynamic Offloading in Distributed Fragmentation Optimized SDN-IoT
2020
International journal of engineering research and technology
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Quality of Service provisioning is an on-going demand in software-defined IoT (SD-IoT), particularly for large scale environments. ...
In this paper, we address this issue by proposing a seamless model of AI-aided Traffic Differentiated QoS Routing and Dynamic Offloading in distributed fragmentation optimized SDN-IoT. ...
The global controller has a global view of the local controller's management and control. ...
doi:10.37624/ijert/13.8.2020.1880-1895
fatcat:lhfkqfb6f5fepll2pqq22uqhwe
Generic cloud platform multi-objective optimization leveraging models@run.time
2014
Proceedings of the 29th Annual ACM Symposium on Applied Computing - SAC '14
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Optimization Problem (CMOP). ...
We validate our approach based on a case study that we define with our cloud provider partner EBRC 1 as representative of a dynamic management problem of heterogeneous distributed cloud nodes. ...
This research is supported by the Fonds National de la Recherche, Luxembourg C12/IS/4011170 in the context of TOOM Core project. ...
doi:10.1145/2554850.2555044
dblp:conf/sac/KatebFNMAT14
fatcat:nw3yzr2sh5bc5bu63fgxk4xm24
Automatic and transparent I/O optimization with storage integrated application runtime support
2015
Proceedings of the 10th Parallel Data Storage Workshop on - PDSW '15
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As a result, programming models, languages, and storage systems are limited in the optimizations they can perform for I/O operations, as the semantics of the I/O library is typically at the level of transfers ...
For many HPC applications where I/O operations for analyzing and checkpointing large data sets are a non-negligible portion of the overall execution time, such a "know nothing" I/O design has negative ...
N-1 vs N-M), and in terms of I/O scheduling (global barrier vs. asynchronous I/O). ...
doi:10.1145/2834976.2834983
dblp:conf/sc/WatkinsJSMAM15
fatcat:vllpjh5oz5acxdsgqicugvuoty
Seeking for the Optimal Energy Modelisation Accuracy to Allow Efficient Datacenter Optimizations
2016
2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid)
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Do we need a detailed and fine-grained energy model to perform good optimizations in the datacenter? ...
Through experiments, our results show that we don't get energy savings compared to classical bin-packing strategies but there are some gains in using precise modeling: better utilization of the network ...
Whereas LrMu stands for CloudSim placement algorithm with Local Regression allocation policy and Maximum Utilization. Note that the energy consumption unit is the kWh.
B. ...
doi:10.1109/ccgrid.2016.67
dblp:conf/ccgrid/OutinDBP16
fatcat:3dbn3i637jb2bbtxqs5allxaxm
A Taxonomy of Cooperative Particle Swarm Optimizers
2008
International Journal of Computational Intelligence Research
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Particle Swarm Optimization (PSO) is one of the most effective optimization tools, which emerged in the last decade. ...
Finally, two different versions of the PSO algorithm are applied in the FPGA placement problem. ...
Nearby swarms interacted through an exclusion strategy similar to what was used in [28] . Another interaction also occurs globally among all the swarms through an anti-convergence operator. ...
doi:10.5019/j.ijcir.2008.133
fatcat:ptdnzvqjs5gvpj62wdrtndiahm
Query optimization in compressed database systems
2001
Proceedings of the 2001 ACM SIGMOD international conference on Management of data - SIGMOD '01
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We show that eager and lazy decompression strategies produce suboptimal plans for queries involving compressed string attributes. ...
We propose a Hierarchical Dictionary Encoding strategy that intelligently selects the most effective compression method for string-valued attributes. ...
Hence, the choice of K is crucial: If K = 2, optimal plans for both cases are kept, while if K = 1, only the local minimum is kept, allowing globally suboptimal results. ...
doi:10.1145/375663.375692
dblp:conf/sigmod/ChenGK01
fatcat:xtfvacb2rfbbhbuxcivbkn3tia
Query optimization in compressed database systems
2001
SIGMOD record
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2003; you can also visit the original URL.
The file type is application/pdf.
We show that eager and lazy decompression strategies produce suboptimal plans for queries involving compressed string attributes. ...
We propose a Hierarchical Dictionary Encoding strategy that intelligently selects the most effective compression method for string-valued attributes. ...
Hence, the choice of K is crucial: If K = 2, optimal plans for both cases are kept, while if K = 1, only the local minimum is kept, allowing globally suboptimal results. ...
doi:10.1145/376284.375692
fatcat:ywafbjusfbhglgpydevo2pdzly
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