For cloud data center, Virtual Machine (VM) consolidation is an effective way to save energy and improve efficiency. However, inappropriate consolidation of VMs, especially aggressive consolidation, can lead to performance problems, and even more serious Service Level Agreement (SLA) violations. Therefore, it is very important to solve the tradeoff between reduction in energy use and reduction of SLA violation level. In this paper, we propose two Host State Detection algorithms and an improved VM placement algorithm based on our proposed Host State Binary Decision Tree Prediction model for SLA-aware and energy-efficient consolidation of VMs in cloud data centers. We propose two formulas of conditions for host state estimate, and our model uses them to build a Binary Decision Tree manually for host state detection. We extend Cloudsim simulator to evaluate our algorithms by using PlanetLab workload and random workload. The experimental results show that our proposed model can significantly reduce SLA violation rates while keeping energy cost efficient, it can reduce the metric of SLAV by at most 98.12% and the metric of Energy by at most 33.96% for real world workload.

Virtual Machine Placement (VMP) plays an important role in ensuring efficient resource provisioning of physical machines (PMs) and energy efficiency in Infrastructure as a Service (IaaS) data centers. Efficient server consolidation assisted by virtual machine (VM) migration can promote the utilization level of the servers and switch the idle PMs to sleep mode to save energy. The trade-off between energy and performance is difficult, because consolidation may cause performance degradation, even service level agreement (SLA) violations. A novel residual available capacity (RAC) resource model is proposed to resolve the VM selection and allocation problem from the cloud service provider (CSP) perspective. Furthermore, a novel heuristic VM selection policy for server consolidation, named Minimized Square Root available Resource (MISR) is proposed. Meanwhile, an efficient VM allocation policy, named Balanced Selection (BS) based on RAC is proposed. The effectiveness validation of the BS-MISR combination is conducted on CloudSim with real workloads from the CoMon project. Evaluation results of experiments show that the proposed combinationBS-MISR can significantly reduce the energy consumption, with an average of 36.35% compared to the Local Regression and Minimum Migration Time (LR-MMT) combination policy. Moreover, the BS-MISR ensures a reasonable level of SLAs compared to the benchmarks.

The Virtual Machine Consolidation (VMC) algorithm is the core strategy of virtualization resource management software. In general, VMC efficiency dictates cloud datacenter efficiency to a great extent. However, all the current Virtual Machine (VM) consolidation strategies, including the Iterative Correlation Match Algorithm (ICMA), are not suitable for the dynamic VM consolidation of the level of physical servers in actual datacenter environments. In this paper, we propose two VM consolidation and placement strategies which are called standard Segmentation Iteration Correlation Combination (standard SICC) and Multi-level Segmentation Iteration Correlation Combination (multi-level SICC). The standard SICC is suitable for the single-size VM consolidation environment and is the cornerstone of multi-level SICC which is suitable for the multi-size VM consolidation environment. Numerical simulation results indicate that the numbers of remaining Consolidated VM (CVM), which are generated by standard SICC, are 20% less than the corresponding parameters of ICMA in the single-level VM environment with the given initial condition. The numbers of remaining CVMs of multi-level SICC are 14% less than the corresponding parameters of ICMA in the multi-level VM environment. Furthermore, the used physical servers of multi-level SICC are also 5% less than the used servers of ICMA under the given initial condition.

Now that the subject of green computing is receiving a lot of attention, the energy consumption of datacenters has emerged as a significant issue. Consolidation of Virtual Machines (VMs) reduces the energy consumption since VM live migration not only optimizes VM placement, but also switches idle nodes to sleep mode. However, VM migration may negatively impact the performance of the system and lead to violations in SLA (Service Level Agreement) requirements between end users and cloud providers. In this study, we propose a VM consolidation mechanism that reduces the energy consumption of datacenters, eliminates unnecessary migrations, and minimizes the SLA violations. Compared to previous studies, the proposed policy shows a reduction of 2% to 3% in energy consumption, 13% to 41% in VM migration frequency, and 15% to 50% in SLA violations.

We propose a novel method for knowledge consolidation based on a knowledge graph as a next step in relation extraction from text. The knowledge consolidation method consists of entity consolidation and relation consolidation. During the entity consolidation process, identical entities are found and merged using both name similarity and relation similarity measures. In the relation consolidation process, incorrect relations are removed using cardinality properties, temporal information and relation weight in given graph structure. In our experiment, we could generate compact and clean knowledge graphs where number of entities and relations are reduced by 6.1% and by 17.4% respectively with increasing relation accuracy from 77.0% to 85.5%.

This paper proposes a session state migration architecture for flexible server consolidation. One of technical challenges is how to split a session state from a connection and bind the session state to another connection in any servers. A conventional server and client application assumes that a session state is statically bound to a connection once the connection has been established. The proposed architecture reduces the migration latency, compared to an existing study by splitting the session state from the connection. This paper classifies common procedures of session state migration for various services. The session state migration architecture enables service providers to conduct server maintenance at their own convenience, and to conserve energy consumption at servers by consolidating them. A simulation to evaluate server consolidation reveals that the session state migration reduces the number of servers for accommdating users, compared to virtual machine migration. This paper also shows implementation of the session state migration architecture. Experimental results reveal that the impact caused by the proposed architecture on real-time applications is small.

The performance of speech translation systems combining automatic speech recognition (ASR) and machine translation (MT) systems is degraded by redundant and irrelevant information caused by speaker disfluency and recognition errors. This paper proposes a new approach to translating speech recognition results through speech consolidation, which removes ASR errors and disfluencies and extracts meaningful phrases. A consolidation approach is spun off from speech summarization by word extraction from ASR 1-best. We extended the consolidation approach for confusion network (CN) and tested the performance using TED speech and confirmed the consolidation results preserved more meaningful phrases in comparison with the original ASR results. We applied the consolidation technique to speech translation. To test the performance of consolidation-based speech translation, Chinese broadcast news (BN) speech in RT04 were recognized, consolidated and then translated. The speech translation results via consolidation cannot be directly compared with gold standards in which all words in speech are translated because consolidation-based translations are partial translations. We would like to propose a new evaluation framework for partial translation by comparing them with the most similar set of words extracted from a word network created by merging gradual summarizations of the gold standard translation. The performance of consolidation-based MT results was evaluated using BLEU. We also propose Information Preservation Accuracy (IPAccy) and Meaning Preservation Accuracy (MPAccy) to evaluate consolidation and consolidation-based MT. We confirmed that consolidation contributed to the performance of speech translation.

We have fabricated ferroelectric Pb(Zr,Ti)O3 (PZT) thin films using low-pressure consolidation process during the sol-gel method. Drastic improvements of electrical properties have been obtained for the PZT thin films fabricated with low-pressure consolidation process. A remanent polarization (Pr) of 37 µC/cm2 and a coercive field (EC) of 64 kV/cm have been achieved. In addition, the leakage current of the PZT films fabricated using low-pressure consolidation is 102 times smaller than that of the films fabricated with the usual process of sol-gel method. It is also found that the low-pressure consolidation process is effective on improvements of electrical properties of PZT films fabricated at lower crystallization temperatures and with sub-100 nm thickness.

In this paper, we propose a new consolidation algorithm called the Selective Backward Resource Management (BRM) cell Feedback (SBF) algorithm. It achieves a fast response and low consolidation noise by selectively forwarding BRM cell from the most congested branch to the source instead of waiting from all branches. Mathematical models are derived to quantitatively characterize the performance, i.e. the response time and ACR of the source, of SBF and previously proposed algorithms. The interoperation of consolidation algorithms in point-to-multipoint available bit rate (ABR) is investigated. We address response time, consolidation noise and the effect of asymmetrical round trip delay (RTD) from branch point to destinations aspects. All combinations of four different consolidation algorithms are interoperated in both local/metropolitan area network (LAN/MAN) and wide area network (WAN) configuration. By a simulation method, we found that the consolidation algorithm used at the uppermost stream branch point, especially in WAN configuration, plays an important role in determining the performance of the network. However, consolidation algorithm used at the lower stream branch point affects the network performance insignificantly. Hence, in order to achieve a good and effective performance of the consolidation algorithms interoperated network, a fast response with low consolidation noise algorithm should be used at the uppermost stream branch point and a simple and easy to implement algorithm should be used at the lower stream branch point.

The major concern at a branch point in asynchronous transfer mode (ATM) networks for point-to-multipoint available bit rate (ABR) services is how to consolidate backward resource management (BRM) cells from each branch for a multicast connection. In this paper, we propose an efficient feedback consolidation algorithm based on an adaptive dynamic threshold (ADT) to eliminate consolidation noise and to reduce consolidation delay. The main idea of the ADT algorithm is that each branch point estimates the ABR traffic condition of the network through virtual queue estimation. Simulation results show that the proposed ADT algorithm can achieve a faster response in congestion status and a higher link utilization compared with the previous works.

In this paper, we first investigate the problems of the existing branch point algorithms for available bit rate (ABR) multicast connections in ATM networks, and then propose various solutions for resolving those problems. By combining these solutions, we also propose a new efficient and scalable branch point algorithm. In the proposed algorithm, each branch point stores the feedback information on a per-branch basis for each virtual connection and only passes BRM cells returning from the farthest destination. Simulation results show that the proposed algorithm can provide a good fairness, a higher efficiency and an excellent scalability, compared with the existing algorithms.

In this study, we propose a branch-point scheme for multicast ABR service in ATM networks. The performance of the proposed scheme is obtained to show that the consolidation noise and delay can be reduced more effectively than those of the existing schemes.