A software-hardware hybrid steering mechanism for clustered microarchitectures

Clustered microarchitectures provide a promising paradigm to solve or alleviate the problems of increasing microprocessor complexity and wire delays. High- performance out-of-order processors rely on hardware-only steering mechanisms to achieve balanced workload distribution among clusters. However, the additional steering logic results in a significant increase on complexity, which actually decreases the benefits of the clustered design. In this paper, we address this complexity issue and present a novel software-hardware hybrid steering mechanism for out-of-order processors. The proposed software- hardware cooperative scheme makes use of the concept of virtual clusters. Instructions are distributed to virtual clusters at compile time using static properties of the program such as data dependences. Then, at runtime, virtual clusters are mapped into physical clusters by considering workload information. Experiments using SPEC CPU2000 benchmarks show that our hybrid approach can achieve almost the same performance as a state-of-the-art hardware-only steering scheme, while requiring low hardware complexity. In addition, the proposed mechanism outperforms state-of-the-art software-only steering mechanisms by 5% and 10% on average for 2-cluster and 4-cluster machines, respectively.Peer ReviewedPostprint (published version

Energy-efficient data acquisition for accurate signal estimation in wireless sensor networks

Long-term monitoring of an environment is a fundamental requirement for most wireless sensor networks. Owing to the fact that the sensor nodes have limited energy budget, prolonging their lifetime is essential in order to permit long-term monitoring. Furthermore, many applications require sensor nodes to obtain an accurate estimation of a point-source signal (for example, an animal call or seismic activity). Commonly, multiple sensor nodes simultaneously sample and then cooperate to estimate the event signal. The selection of cooperation nodes is important to reduce the estimation error while conserving the network’s energy. In this paper, we present a novel method for sensor data acquisition and signal estimation, which considers estimation accuracy, energy conservation, and energy balance. The method, using a concept of ‘virtual clusters,’ forms groups of sensor nodes with the same spatial and temporal properties. Two algorithms are used to provide functionality. The ‘distributed formation’ algorithm automatically forms and classifies the virtual clusters. The ‘round robin sample scheme’ schedules the virtual clusters to sample the event signals in turn. The estimation error and the energy consumption of the method, when used with a generalized sensing model, are evaluated through analysis and simulation. The results show that this method can achieve an improved signal estimation while reducing and balancing energy consumption

Resource Allocation using Virtual Clusters

In this report we demonstrate the utility of resource allocations that use virtual machine technology for sharing parallel computing resources among competing users. We formalize the resource allocation problem with a number of underlying assumptions, determine its complexity, propose several heuristic algorithms to find near-optimal solutions, and evaluate these algorithms in simulation. We find that among our algorithms one is very efficient and also leads to the best resource allocations. We then describe how our approach can be made more general by removing several of the underlying assumptions

Система моделювання роботи GRID систем з застосуванням ієрархічного планувальника та методу віртуальних кластерів

У даній статті розглянуті алгоритми планування у Grid-системах, серед них метод віртуальних кластерів. В основу планувальника було покладено ієрархічний спосіб планування. Описана розроблена програма моделювання Grid системи, яка дозволяє використовувати вищезгадані та інші популярні алгоритми. Досліджено отримані результати алгоритмів їх недоліки та переваги у порівнянні з іншими методами планування, описано принципи реалізації моделювання за допомогою віртуальних кластерів.This article describes the scheduling algorithms for Grid-systems including the method of virtual clusters. Hierarchical scheduling method was chosen as the basic method of scheduling. The Grid system simulation program, which allows the use of the mentioned and other popular algorithms, is described. The article includes received results and the comparison of the scheduling algorithms and describes the principles of the simulation using virtual clusters

Towards migratable elastic virtual clusters on hybrid clouds

© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper describes the research work in the context of the CLUVIEM project towards achieving migrat- able, self-managed virtual elastic clusters on hybrid Cloud infrastructures. These virtual clusters can span across on- premises and public Cloud infrastructures thus leveraging hybrid Cloud platforms. They are elastic since working nodes are automatically provisioned and relinquished to dynamically adapt the capacity of the virtual cluster (in terms of number of nodes) according to the current workload. They are self- managed since the elasticity rules are managed via the head node without requiring any external software entity for mon- itoring and deciding when to scale in and out. Finally, they are migratable since they consider both application migration, via application checkpointing, and infrastructure migration, by cloning infrastructures across multi-Clouds. These features introduce unprecedented flexibility for cost-effective cluster- based computing with minimal impact for cluster users. The paper summarises the current state of developments and future roads to achieve this vision.AC would like to thank the program “Ayudas para la contratacion de personal investigador en formaci ´ on´ de carcter predoctoral, programa VALi+d”, grant number ACIF/2013/003, from the Conselleria d’Educacio of the ´ Generalitat Valenciana. Also, the authors would like to thank the Spanish ”Ministerio de Econom´ıa y Competitividad” for the CLUVIEM project with reference TIN2013-44390-RCalatrava Arroyo, A.; Moltó, G.; Romero Alcalde, E.; Caballer Fernández, M.; Alfonso Laguna, CD. (2015). Towards migratable elastic virtual clusters on hybrid clouds. IEEE. https://doi.org/10.1109/CLOUD.2015.139

Energy-Efficient Data Acquisition in Wireless Sensor Networks through Spatial Correlation

The application of Wireless Sensor Networks (WSNs) is restrained by their often-limited lifetime. A sensor node's lifetime is fundamentally linked to the volume of data that it senses, processes and reports. Spatial correlation between sensor nodes is an inherent phenomenon to WSNs, induced by redundant nodes which report duplicated information. In this paper, we report on the design of a distributed sampling scheme referred to as the 'Virtual Sampling Scheme' (VSS). This scheme is formed from two components: an algorithm for forming virtual clusters, and a distributed sampling method. VSS primarily utilizes redundancy of sensor nodes to get only a subset to sense the environment at any one time. Sensor nodes that are not sensing the environment are in a low-power sleep state, thus conserving energy. Furthermore, VSS balances the energy consumption amongst nodes by using a round robin method

CernVM Online and Cloud Gateway: a uniform interface for CernVM contextualization and deployment

In a virtualized environment, contextualization is the process of configuring a VM instance for the needs of various deployment use cases. Contextualization in CernVM can be done by passing a handwritten context to the user data field of cloud APIs, when running CernVM on the cloud, or by using CernVM web interface when running the VM locally. CernVM Online is a publicly accessible web interface that unifies these two procedures. A user is able to define, store and share CernVM contexts using CernVM Online and then apply them either in a cloud by using CernVM Cloud Gateway or on a local VM with the single-step pairing mechanism. CernVM Cloud Gateway is a distributed system that provides a single interface to use multiple and different clouds (by location or type, private or public). Cloud gateway has been so far integrated with OpenNebula, CloudStack and EC2 tools interfaces. A user, with access to a number of clouds, can run CernVM cloud agents that will communicate with these clouds using their interfaces, and then use one single interface to deploy and scale CernVM clusters. CernVM clusters are defined in CernVM Online and consist of a set of CernVM instances that are contextualized and can communicate with each other.Comment: Conference paper at the 2013 Computing in High Energy Physics (CHEP) Conference, Amsterda

Dependability in hybrid grid systems: a virtual clusters approach

With the rapid evolution of mobile and ubiquitous computing, small-scale devices like personal digital assistants, smart "converged" phones and laptops now dominate the market. Despite the parallel emergence of the grid as the new distributed computing infrastructure, an integrated hybrid grid system that consists of both traditional fixed nodes but mobile and limited devices as well, has only recently gained some popularity. One of the main challenges in realizing this integration is the very low levels of reliability and availability of small scale and mobile devices - a characteristic that could compromise the overall dependability and performance of the whole grid system. In this paper we try to identify the main dependability requirements for such a hybrid grid system. We then present our own approach to an efficient integration using our virtual clusters platform, and explain how we manage to meet the dependability requirements as set by our research