DVFS governor for HPC: Higher, Faster, Greener

International audienceIn High Performance Computing, being respectful of the environment is usually secondary compared to performance: The faster, the better. As Exascale computing is in the spotlight, electric power concerns arise as current exascale projects might need too much power to even boot. A recent incentive (Exascale at maximum 20MW) shows that reality is catching up with HPC center designers. Beyond classical works on hardware infrastructure or at the middleware level, we do believe that system-level solutions have great potential for energy reduction. Moreover energy-reduction has often been neglected by the HPC community that focus mainly on raw computing performance. In the literature, energy savings is achieved mainly by two means: Either processor load is the only metric taken into account to reduce processors frequency and to ensure no impact on raw performances, Or processor frequency is managed only at task level outside the critical path. In this article we show that designing and implementing a DVFS (Dynamic Voltage and Frequency Scaling) mechanism based on instantaneous system values (here network activity) can save up to 25% of energy consumption while reducing marginally performance. In several cases, reducing energy consumption also leads to an increase in performances because of the thermal budget of recent processors. This work is validated with real experiments on a Linux cluster using the NAS Parallel Benchmark (NPB)

T2D: A Peer to Peer trust management system based on Disposition to Trust

International audienceWhile the trust paradigm is essential to broadly extend the communication between the environment's actors, the evaluation of trust becomes a challenge when confronted with initializing the trust relationship and validating the transi- tive propriety of trust. Whether between users or between organizations, existing solutions work to create for peer to peer networks, flexible and decentralized security mecha- nisms with trust approach. However, we have noticed that the trust management systems do not make the most of the subjectivity, more specifically, the notion of Disposition to Trust although this aspect of subjectivity has a strong influence on how to assess direct and a transitive trust. For this reason in our study, we tackle this problem by introducing a new distributed trust model called T2D (Trust to Distrust) which is designed to incorporate the follow- ing contributions : (i) A behavior model which represents the Disposition to Trust ; (ii) Initialization of trust relation- ship (direct and transitive) according to the defined behavior model

Energy aware clouds scheduling using anti-load balancing algorithm : EACAB

International audienceCloud computing is a highly scalable and cost-effective infrastructure for running HPC, enterprise and Web applications. However rapid growth of the demand for computational power by scientific, business and web- applications has led to the creation of large-scale data centers consuming enormous amounts of electrical power. Hence, energy-efficient solutions are required to minimize their energy consumption. The objective of our approach is to reduce data center’s total energy consumption by controlling cloud applications’ overall resource usage while guarantying service level agreement. This article presents Energy aware clouds scheduling using anti-load balancing algorithm (EACAB). The proposed algorithm works by associating a credit value with each node. The credit of a node depends on its affinity to its jobs, its current workload and its communication behavior. Energy savings are achieved by continuous consolidation of VMs according to current utilization of resources, virtual network topologies established between VMs and thermal state of computing nodes. The experiment results show that the cloud application energy consumption and energy efficiency is being improved effectively

A Balanced Battery Usage Routing Protocol to Maximize Network Lifetime of MANET Based on AODV

International audienceEnergy efficiency is a critical issue for battery-powered mobile devices in ad hoc networks. Failure of node or link allows re-routing and establishing a new path from source to destination which creates extra energy consumption of nodes, sparse network connectivity and a more likelihood occurrences of network partition. Routing based on energy related parameters is one of the important solutions to extend the lifetime of the network. In this paper, we are designing and evaluating a novel energy aware routing protocol called a balanced battery usage routing protocol (BBU) which uses residual energy, hop count and energy threshold as a cost metric to maximize network life time and distribute energy consumption of Mobile Ad hoc Network (MANET) based on Ad hoc on-demand Distance Vector (AODV).The new protocol is simulated using Network Simulator-2.34 and comparisons are made to analyze its performance based on network lifetime, delivery ratio, normalized routing overhead, standard deviation of residual energy of all Nodes and average end to end delay for different network scenarios. The results show that the new energy aware algorithm makes the network active for longer interval of time once it is established and fairly distribute energy consumption across nodes on the network

Accélération du traitement de données avioniques : Hadoop@PireCloud

International audienc

Energy Consumption Library

International audienceThe energy consumption of a computing system depends not only on its architecture, but also on its usage. This paper describes the Energy Consumption Library (libec), a modular library of sensors and power estimators, which do not depend on wattmeter to measure the power dissipated by a machine and/or the applications that it executes, etc. In addition, four use cases are used to demonstrate some of the library's capabilities

Range-free selective anchor node center of the smallest communication overlap polygon localization algorithm in wireless networks

International audienceThis paper presents a range-free selective anchor node center of the smallest communication overlap polygon localization algorithm in wireless networks. The algorithm is range-free which does not require ranging devices. To estimate the location of unknown (location unaware) nodes it uses node connectivity based on selected anchor (location aware) nodes. The algorithm first selects appropriate anchor nodes. Then, the True Intersection Points (TIPs) constituting the vertices of the smallest communication overlap polygon (SCOP) of these selected anchor nodes' communication ranges are found. Finally, the location of the unknown node is estimated at the center of the SCOP which is formed from these TIPs. The algorithm performance is evaluated using MatLab simulation and compares favorably to state-of-the-art algorithms: Centroid, improved version of CPE, Mid-perpendicular and CSCOP localization algorithms. The results show the proposed algorithm outperforms other state-of-the-art algorithms in location accuracy and it has reasonable computational complexity

Energy-efficient and thermal-aware resource management for heterogeneous datacenters

International audienceWe propose in this paper to study the energy-, thermal- and performance-aware resource management in heterogeneous datacenters. Witnessing the continuous development of heterogeneity in datacenters, we are confronted with their different behaviors in terms of performance, power consumption and thermal dissipation: indeed, heterogeneity at server level lies both in the computing infrastructure (computing power, electrical power consumption) and in the heat removal systems (different enclosure, fans, thermal sinks). Also the physical locations of the servers become important with heterogeneity since some servers can (over)heat others. While many studies address independently these parameters (most of the time performance and power or energy), we show in this paper the necessity to tackle all these aspects for an optimal resource management of the computing resources. This leads to improved energy usage in a heterogeneous datacenter including the cooling of the computer rooms. We build our approach on the concept of heat distribution matrix to handle the mutual influence of the servers, in heterogeneous environments, which is novel in this context. We propose a heuristic to solve the server placement problem and we design a generic greedy framework for the online scheduling problem. We derive several single-objective heuristics (for performance, energy, cooling) and a novel fuzzy-based priority mechanism to handle their tradeoffs. Finally, we show results using extensive simulations fed with actual measurements on heterogeneous servers

HaoLap: a Hadoop based OLAP system for big data

International audienceIn recent years, facing information explosion, industry and academia have adopted distributed file system and MapReduce programming model to address new challenges the big data has brought. Based on these technologies, this paper presents HaoLap (Hadoop based oLap), an OLAP (OnLine Analytical Processing) system for big data. Drawing on the experience of Multidimensional OLAP (MOLAP), HaoLap adopts the specified multidimensional model to map the dimensions and the measures; the dimension coding and traverse algorithm to achieve the roll up operation on dimension hierarchy; the partition and linearization algorithm to store dimensions and measures; the chunk selection algorithm to optimize OLAP performance; and MapReduce to execute OLAP. The paper illustrates the key techniques of HaoLap including system architecture, dimension definition, dimension coding and traversing, partition, data storage, OLAP and data loading algorithm. We evaluated HaoLap on a real application and compared it with Hive, HadoopDB, HBaseLattice, and Olap4Cloud. The experiment results show that HaoLap boost the efficiency of data loading, and has a great advantage in the OLAP performance of the data set size and query complexity, and meanwhile HaoLap also completely support dimension operations