A Comparison of Eleven Static Heuristics for Mapping a Class of Independent Tasks onto Heterogeneous Distributed Computing Systems

By Tracy D. Braun, H. J. Siegel, Noah Beck, Ladislau Bölöni, Muthucumaru Maheswaran, A. Reuther, J. Robertson, M. Theys, Bin Yao, D. Hensgen and 1 more. J. Parallel Distributed Comput., 2001

1,933 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Hardware and Architecture, Information Systems

View Paper: https://www.semanticscholar.org/paper/77ffb473344575b11a4e8d94ed883466074b572b

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Citations in the corpus

Scheduling Algorithms for Grid Computing: State of the Art and Open Problems (2006, background): “For example, static scheduling algorithms are studied in [17] [23] and [118], and in [68] [106] [28] and [79], dynamic scheduling algorithms are presented.”
An Ant Colony Optimization Approach to a Grid Workflow Scheduling Problem With Various QoS Requirements (2009, background): “The most popular approaches are the static or dynamic list scheduling algorithms based on different heuristics, such as opportunistic load balancing (OLB), minimum execution time (MET), minimum completion time (MCT) [8], min–min [8]–[12], max– min [8]–[12], duplex [8], sufferage [10], [11], random [”
A review of metaheuristic scheduling techniques in cloud computing (2015, background): “Former is dependent scheduling or more commonly known as work-ﬂow scheduling [2] and the latter is known as independent scheduling [4].”
A market-oriented hierarchical scheduling strategy in cloud workflow systems (2011, methodology): “For conventional applications with independent tasks, resource managers usually employ scheduling strategies with relatively simple heuristics such as FCFS (first come, first served), Min-Min and Max-Min [39] [50] to satisfy the QoS constraints such as on time and/or cost.”
A CyberGIS Framework for the Synthesis of Cyberinfrastructure, GIS, and Spatial Analysis (2010, methodology): “Task scheduling heuristics are often developed to balance the computing loads of subdomains based on both static and dynamic strategies (Braun et al. 2001; Beaumont, Legrand, and Robert 2003).”
WorkflowSim: A toolkit for simulating scientific workflows in distributed environments (2012, methodology): “• MaxMin : Similar to MinMin, but MaxMin [2] picks up the job with the maximum completion time and assigns it to its best available resource.”
Computational models and heuristic methods for Grid scheduling problems (2010, neutral): “For instance, if in each iteration the best neighboring solution is accepted, we have the steepest descent version in the minimization case. this method is based on the process of Short Hop [48].”
A hybrid heuristic for DAG scheduling on heterogeneous systems (2004, methodology): “Although there exist many heuristics to schedule a number of independent tasks onto heterogeneous machines [3] — which could be used for the corresponding phase of the hybrid heuristic presented above — we propose here a novel heuristic.”
New Grid Scheduling and Rescheduling Methods in the GrADS Project (2004, methodology): “heuristics that we apply are the min-min, the max-min, and the sufferage heuristics [3, 19 ].”
Towards a Load Balancing in a three-level cloud computing network (2010, background): “MET tries to find good job-node pairings, but because it does not consider the current load on a node it will often cause load imbalance between the nodes and not adapt application in the heterogeneity computer system [1] [3].”
User-priority guided Min-Min scheduling algorithm for load balancing in cloud computing (2013, methodology): “The traditional Min-Min algorithm is a simple, efficient algorithm that produces a better schedule that minimizes the total completion time of tasks than other algorithms in the literature [7].”
Scheduling distributed applications: the SimGrid simulation framework (2003, background): “scheduling task graphs [27], scheduling independent tasks [6]).”