Energy-efficient Data Replication in Cloud Computing Datacenters

in Cluster Computing (2015), 18(1), 385-402

Cloud computing is an emerging paradigm that provides computing, communication and storage resources as a service over a network. Communication resources often become a bottleneck in service provisioning ... [more ▼]

Cloud computing is an emerging paradigm that provides computing, communication and storage resources as a service over a network. Communication resources often become a bottleneck in service provisioning for many cloud applications. Therefore, data replication which brings data (e.g., databases) closer to data consumers (e.g., cloud applications) is seen as a promising solution. It allows minimizing network delays and bandwidth usage. In this paper we study data replication in cloud computing data centers. Unlike other approaches available in the literature, we consider both energy efficiency and bandwidth consumption of the system. This is in addition to the improved quality of service QoS obtained as a result of the reduced communication delays. The evaluation results, obtained from both mathematical model and extensive simulations, help to unveil performance and energy efficiency tradeoffs as well as guide the design of future data replication solutions. [less ▲]

The sandpile scheduler: How self-organized criticality may lead to dynamic load-balancing

in Cluster Computing (2014)

This paper studies a self-organized criticality model called sandpile for dynamically load-balancing tasks arriving in the form of Bag-of-Tasks in large-scale decentralized system. The sandpile is ... [more ▼]

This paper studies a self-organized criticality model called sandpile for dynamically load-balancing tasks arriving in the form of Bag-of-Tasks in large-scale decentralized system. The sandpile is designed as a decentralized agent system characterizing a cellular automaton, which works in a critical state at the edge of chaos. Depending on the state of the cellular automaton, different responses may occur when a new task is assigned to a resource: it may change nothing or generate avalanches that reconfigure the state of the system. The abundance of such avalanches is in power-law relation with their sizes, a scale-invariant behavior that emerges without requiring tuning or control parameters. That means that large—catastrophic—avalanches are very rare but small ones occur very often. Such emergent pattern can be efficiently adapted for non-clairvoyant scheduling, where tasks are load balanced in computing resources trying to maximize the performance but without assuming any knowledge on the tasks features. The algorithm design is experimentally validated showing that the sandpile is able to find near-optimal schedules by reacting differently to different conditions of workloads and architectures. [less ▲]

Green Flexible Opportunistic Computing with task consolidation and virtualization

in Cluster Computing (2012)

Energy efficiency and high computing power are basic design considerations across modern-day computing solutions due to different concerns such as system perfor- mance, operational cost, and environmental ... [more ▼]

Energy efficiency and high computing power are basic design considerations across modern-day computing solutions due to different concerns such as system perfor- mance, operational cost, and environmental issues. Desktop Grid and Volunteer Computing System (DGVCS) so called opportunistic infrastructures offer computational power at low cost focused on harvesting idle computing cycles of ex- isting commodity computing resources. Other than allow- ing to customize the end user offer, virtualization is consid- ered as one key techniques to reduce energy consumption in large-scale systems and contributes to the scalability of the system. This paper presents an energy efficient approach for opportunistic infrastructures based on task consolidation and customization of virtual machines. The experimental re- sults with single desktops and complete computer rooms show that virtualization significantly improves the energy-efficiency of opportunistic grids compared with dedicated computing systems without disturbing the end-user. [less ▲]

A two-phase heuristic for the energy-efficient scheduling of independent tasks on computational grids

in Cluster Computing (2012)