ENERGY-EFFICIENT SCHEDULING IN GRID COMPUTING AND RESOURCE ALLOCATION IN OPPORTUNISTIC CLOUD COMPUTING: MODELS AND ALGORITHMS

Doctoral thesis (2014)

Resource allocation among Heterogenous Computing Systems (HCS) components, such as cluster, grid, or cloud computing can be considered as a service. These systems manage millions of computational ... [more ▼]

Resource allocation among Heterogenous Computing Systems (HCS) components, such as cluster, grid, or cloud computing can be considered as a service. These systems manage millions of computational resources to solve several difficult com- putational problems. Resource allocation and scheduling among these systems are still a hot topic for research purposes. A goal of this research is to find an effi- cient use of these resources proposing a resource allocation and efficient scheduling techniques. Firstly, the relevance of energy consumption in processing elements as well as techniques and policies to support it are presented. It emphasizes in resource allocation algorithms in opportunistic environments and low complexity scheduling heuristics in grid computing environment. In particular, a series of low complexity, scalable, and energy-efficient algorithms for scheduling in grid computing and a resource allocation technique for opportunistic environment are presented. The latest aforementioned technique was evaluated in an opportunistic cloud environment. Three fast and energy-efficient batch mode scheduling novel heuristics were designed, developed, and evaluated to produce fast tasks mapping in HCS. To fully understand their capabilities and limitations, these aforemen- tioned heuristics were studied and compared with a variety of system parameters for their performance and scalability. [less ▲]

Energy Savings on a Cloud-based Opportunistic Infrastructure

in Service Oriented Computing ICSOC 2013 Workshops (2014)

In this paper, we address energy savings on a Cloud-based opportunistic infrastructure. The infrastructure implements opportunis- tic design concepts to provide basic services, such as virtual CPUs, RAM ... [more ▼]

In this paper, we address energy savings on a Cloud-based opportunistic infrastructure. The infrastructure implements opportunis- tic design concepts to provide basic services, such as virtual CPUs, RAM and Disk while profiting from unused capabilities of desktop computer laboratories in a non-intrusive way. We consider the problem of virtual machines consolidation on the oppor- tunistic cloud computing resources. We investigate four workload packing algorithms that place a set of virtual machines on the least number of physical machines to increase resource utilization and to transition parts of the unused resources into a lower power states or switching off. We em- pirically evaluate these heuristics on real workload traces collected from our experimental opportunistic cloud, called UnaCloud. The final aim is to implement the best strategy on UnaCoud. The results show that a consolidation algorithm implementing a policy taking into account fea- tures and constraints of the opportunistic cloud saves energy more than 40% than related consolidation heuristics, over the percentage earned by the opportunistic environment. [less ▲]

GFOG: Green and Flexible Opportunistic Grids.

in Khan, Samee; Zomaya, Albert; Lizhe, Wang (Eds.) Scalable Computing and Communications. Theory and Practice (2013)

Energy efficiency and high performance computing are the basic design consider- ations across modern-day computing solutions due to different concerns, such as system functioning, operational cost, and ... [more ▼]

Energy efficiency and high performance computing are the basic design consider- ations across modern-day computing solutions due to different concerns, such as system functioning, operational cost, and environmental issues. Opportunistic grid infrastructures offer computational power at low cost focused on harvesting idle computing cycles of existing commodity computing resources. Other than allow- ing the customization of execution environments, virtualization is considered as one key technique to reduce energy consumption in large-scale systems and contributes to the scalability of the system. This work presented an energy efficient approach for opportunistic grids based on virtualization. The experimental results showed that depending on the strategy used to deploy virtual machines on desktop machines, virtu- alization significantly improves the energy efficiency of opportunistic grids compared with dedicated computing systems, without disturbing the owner-user. [less ▲]

Energy-aware VM allocation on An Opportunistic Cloud Infrastructure

in Proceedings of the 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (2013)

UnaCloud is an opportunistic based cloud infras- tructure (IaaS) that allows to access on-demand computing capabilities using commodity desktops. Although UnaCloud maximizes the use of idle resources to ... [more ▼]

UnaCloud is an opportunistic based cloud infras- tructure (IaaS) that allows to access on-demand computing capabilities using commodity desktops. Although UnaCloud maximizes the use of idle resources to deploy virtual machines, it does not use energy-efficient resource allocation algorithms. In this paper, we design and develop different energy-aware algorithms to operate in an energy-efficient way and at the same time to guarantee the performance of the UnaCloud users. Performance tests with different algorithms and scenarios using real trace workloads from UnaCloud, show how different policies can change the energy consumption patterns and reduce the energy consumption in the opportunistic cloud infrastructure. The results show that some algorithms can reduce the energy-consumption power up to 30% over the percentage earned by the opportunistic environment [less ▲]

Impact of Voltage Levels Number for Energy-aware Bi-objective DAG Scheduling for Multi-processors Systems

in Advances in Information Technology: 5th International Conference, IAIT 2012, Bangkok, Thailand, December 6-7, 2012, Proceedings (2012)

Energy-Aware Fast Scheduling Heuristics in Heterogeneous Computing Systems

in High Performance Computing and Simulation (HPCS), 2011 International Conference on (2011)

In heterogeneous computing systems it is crucial to sched- ule tasks in a manner that exploits the heterogeneity of the resources and applications to optimize systems perfor- mance. Moreover, the energy ... [more ▼]

In heterogeneous computing systems it is crucial to sched- ule tasks in a manner that exploits the heterogeneity of the resources and applications to optimize systems perfor- mance. Moreover, the energy efficiency in these systems is of a great interest due to different concerns such as opera- tional costs and environmental issues associated to carbon emissions. In this paper, we present a series of original low complexity energy efficient algorithms for scheduling. The main idea is to map a task to the machine that executes it fastest while the energy consumption is minimum. On the practical side, the set of experimental results showed that the proposed heuristics perform as efficiently as related ap- proaches, demonstrating their applicability for the consid- ered problem and its good scalability. [less ▲]