Task-resource scheduling problem

Gorbenko, Anna; Popov, Vladimir

doi:10.1007/s11633-012-0664-y

Cited by 64 publications

(52 citation statements)

References 31 publications

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“…Other cloud system optimization frameworks that also operate on a similar task graph based workload model include: Nephele [12], Pegasus [14], VGrADS [15], Particle Swarm Optimization (PSO) based frameworks [16,17], Surfer [13], DisNet [18], Dryad [11] and BC/Azure [19]. (2) The cloud platform is modeled as a weighted graph, which is capable of representing heterogeneous servers with varied resource capacities, power efficiencies and communication bottlenecks.…”

Section:  Acceptable Complexitymentioning

confidence: 99%

An energy and deadline aware resource provisioning, scheduling and optimization framework for cloud systems

Gao

Wang

Gupta

et al. 2013

2013 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS)

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Abstract-Cloud computing has attracted significant attention due to the increasing demand for low-cost, high performance, and energy-efficient computing. In this large-scale, heterogeneous, multi-user environment of a cloud system, profit maximization for the cloud service provider (CSP) is a key objective. In this paper, the problem of global optimization of the cloud system operation (in the sense of lowering operation costs by maximizing energy efficiency, while satisfying user deadlines defined in the Service Level Agreements) is addressed from the perspective of the CSP.The modeling of the workload dictates viable approaches toward cloud operation optimization. Of the two current models: independent batch requests and task graphs with dependencies, we adopt the later. This fine-grained treatment of workloads provides many opportunities for energy and performance optimizations, thus enabling the CSP to meet user deadlines at lower operation costs. However, these optimizations require additional efforts in terms of resource provisioning, virtual machine placement, and task scheduling. Such issues are addressed in a holistic fashion in the proposed framework.In this cloud environment, users can construct their own services and applications based on the available set of virtual machines, but are relieved from the burden of resource provisioning and task scheduling. The CSP will then capitalize on the data parallelisms in each user workload, effectively manage the collective user requests, and apply custom optimizations to create a global energy cost and deadline-aware cloud platform.

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Section:  Acceptable Complexitymentioning

confidence: 99%

An energy and deadline aware resource provisioning, scheduling and optimization framework for cloud systems

Gao

Wang

Gupta

et al. 2013

2013 International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS)

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“…Clearly, ζ gives us an explicit reduction from HP to 3SAT. We consider our genetic algorithm which was proposed in [17]. We have used heterogeneous cluster for our computational experiments.…”

Section: G(a[n] B[n]) Is a Hamilton Path In G Now Let G(a[1]mentioning

confidence: 99%

On Hamilton paths in grid graphs

Gorbenko¹,

Popov²

2013

astp

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In this paper we consider an approach to solve the Hamilton path problem for grid graphs. This approach is based on an explicit reduction from the problem to the satisfiability problem. Gridworlds are extensively used for design of experiments as models of real world. In particular, grid graphs are popular testbeds for different hard problems. In particular, grid graphs used for investigation of robotic planning problems (see e.g. [1]). For instance, grid graph can be considered as a map of some indoor environment. Vacuum cleaning robot needs cover the environment. The robot must visit each vertex only once to prevent a damage of the floor. It is clear that we can consider the Hamilton path problem (HP) for grid graphs as a model for this robotic problem. In this paper we consider an approach to solve HP. Note that HP is NP-complete [2]. Encoding different hard problems as instances of SAT has caused considerable interest (see e.g. PACS[3] - [15]). We consider an explicit reduction from HP to the satisfiability problem.

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“…Note that different satisfiability problems and applications of these problems for investigations of methods of solution of other problems received a lot of attention recently (see e.g. [4] - [9]). In this paper we use the satisfiability problem as a testbed for a genetic algorithm with exons and introns.…”

mentioning

confidence: 99%