Turning Futexes Inside-Out: Efficient and Deterministic User Space Synchronization Primitives for Real-Time Systems with IPCP

In Linux and other operating systems, futexes (fast user space mutexes) are the underlying synchronization primitives to implement POSIX synchronization mechanisms, such as blocking mutexes, condition variables, and semaphores. Futexes allow one to implement mutexes with excellent performance by avoiding system calls in the fast path. However, futexes are fundamentally limited to synchronization mechanisms that are expressible as atomic operations on 32-bit variables. At operating system kernel level, futex implementations require complex mechanisms to look up internal wait queues making them susceptible to determinism issues. In this paper, we present an alternative design for futexes by completely moving the complexity of wait queue management from the operating system kernel into user space, i. e. we turn futexes "inside out". The enabling mechanisms for "inside-out futexes" are an efficient implementation of the immediate priority ceiling protocol (IPCP) to achieve non-preemptive critical sections in user space, spinlocks for mutual exclusion, and interwoven services to suspend or wake up threads. The design allows us to implement common thread synchronization mechanisms in user space and to move determinism concerns out of the kernel while keeping the performance properties of futexes. The presented approach is suitable for multi-processor real-time systems with partitioned fixed-priority (P-FP) scheduling on each processor. We evaluate the approach with an implementation for mutexes and condition variables in a real-time operating system (RTOS). Experimental results on 32-bit ARM platforms show that the approach is feasible, and overheads are driven by low-level synchronization primitives

Hyperion: Building the largest in-memory search tree

Indexes are essential in data management systems to increase the speed of data retrievals. Widespread data structures to provide fast and memory-efficient indexes are prefix tries. Implementations like Judy, ART, or HOT optimize their internal alignments for cache and vector unit efficiency. While these measures usually improve the performance substantially, they can have a negative impact on memory efficiency. In this paper we present Hyperion, a trie-based main-memory key-value store achieving extreme space efficiency. In contrast to other data structures, Hyperion does not depend on CPU vector units, but scans the data structure linearly. Combined with a custom memory allocator, Hyperion accomplishes a remarkable data density while achieving a competitive point query and an exceptional range query performance. Hyperion can significantly reduce the index memory footprint, while being at least two times better concerning the performance to memory ratio compared to the best implemented alternative strategies for randomized string data sets

A Novel Cost Based Model for Energy Consumption in Cloud Computing

Cloud data centers consume enormous amounts of electrical energy. To support green cloud computing, providers also need to minimize cloud infrastructure energy consumption while conducting the QoS. In this study, for cloud environments an energy consumption model is proposed for time-shared policy in virtualization layer. The cost and energy usage of time-shared policy were modeled in the CloudSim simulator based upon the results obtained from the real system and then proposed model was evaluated by different scenarios. In the proposed model, the cache interference costs were considered. These costs were based upon the size of data. The proposed model was implemented in the CloudSim simulator and the related simulation results indicate that the energy consumption may be considerable and that it can vary with different parameters such as the quantum parameter, data size, and the number of VMs on a host. Measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment. Also, measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment

A Novel Cost Based Model for Energy Consumption in Cloud Computing

Cloud data centers consume enormous amounts of electrical energy. To support green cloud computing, providers also need to minimize cloud infrastructure energy consumption while conducting the QoS. In this study, for cloud environments an energy consumption model is proposed for time-shared policy in virtualization layer. The cost and energy usage of time-shared policy were modeled in the CloudSim simulator based upon the results obtained from the real system and then proposed model was evaluated by different scenarios. In the proposed model, the cache interference costs were considered. These costs were based upon the size of data. The proposed model was implemented in the CloudSim simulator and the related simulation results indicate that the energy consumption may be considerable and that it can vary with different parameters such as the quantum parameter, data size, and the number of VMs on a host. Measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment. Also, measured results validate the model and demonstrate that there is a tradeoff between energy consumption and QoS in the cloud environment

Jiko kaifukugata operetingu shisutemu kochiku furemu waku

制度:新 ; 報告番号:甲2786号 ; 学位の種類:博士(工学) ; 授与年月日:2009/2/25 ; 早大学位記番号:新500

Un processus à décision de Markov en temps discret pour minimiser l'énergie sous des contraintes d'échéances

This paper proposes a Discrete Time Markov Decision Process (MDP) approach to compute the optimal on-line speed scaling policy to minimize the energy consumption of a single processor executing a finite or infinite set of jobs with real-time constraints. We provide several qualitative properties of the optimal policy: monotonicity with respect to the jobs parameters, comparison with on-line deterministic algorithms. Numerical experiments in several scenarios show that our proposition performs well when compared with off-line optimal solutions and out-performs on-line solutions oblivious to statistical information on the jobs

Robust services in dynamic systems

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 191-202).Our growing reliance on online services accessible on the Internet demands highly- available systems that work correctly without interruption. This thesis extends previous work on Byzantine-fault-tolerant replication to meet the new requirements of current Internet services: scalability and the ability to reconfigure the service automatically in the presence of a changing system membership. Our solution addresses two important problems that appear in dynamic replicated services: First, we present a membership service that provides servers and clients in the system with a sequence of consistent views of the system membership (i.e., the set of currently available servers). The membership service is designed to be scalable, and to handle membership changes mostly automatically. Furthermore, the membership service is itself reconfigurable, and tolerates arbitrary faults of a subset of the servers that are implementing it at any instant. The second part of our solution is a generic methodology for transforming replicated services that assume a fixed membership into services that support a dynamic system membership. The methodology uses the output from the membership service to decide when to reconfigure.(cont.) We built two example services using this methodology: a dynamic Byzantine quorum system that supports read and write operations, and a dynamic Byzantine state machine replication system that supports any deterministic service. The final contribution of this thesis is an analytic study that points out an obstacle to the deployment of replicated services based on a dynamic membership. The basic problem is that maintaining redundancy levels for the service state as servers join and leave the system is costly in terms of network bandwidth. To evaluate how dynamic the system membership can be, we developed a model for the cost of state maintenance in dynamic replicated services, and we use measured values from real-world traces to determine possible values for the parameters of the model. We conclude that certain deployments (like a volunteer-based system) are incompatible with the goals of large- scale reliable services. We implemented the membership service and the two example services. Our performance results show that the membership service is scalable, and our replicated services perform well, even during reconfigurations.by Rodrigo Seromenho Miragaia Rodrigues.Ph.D