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PurposeThe purpose of this paper is to provide an overview of the existing interoperability models in digital libraries and to introduce related projects in each model.Design/methodology/approachThe study starts from searching various databases with a combination of important keywords in the field, such as interoperability, digital library, meta‐searching and cross‐searching. The study follows up with describing related digital library projects in the field of technical interoperability. The projects are described under three main categories, Federated, Harvesting and Gathering.FindingsThe study shows that most of the studied projects are located in the USA and also most of the digital library projects use OAI protocol and the harvesting model in order to be technically interoperable. Also, the results of the study showed that the projects mostly paid attention to metadata interoperability and only a few mentioned full‐text interoperability issues.Originality/valueThe paper makes an original contribution of exploring an area (interoperability models in digital libraries), that is at the forefront of discussion in libraries worldwide.

Number of cloud data centers which consists of hundreds of hosts has increased tremendously around the world due to increase in demands for cloud services. It is expected energy consumption of data centers will reach 139.8 billion Kwh by 2020. Many algorithms are proposed to reduce energy consumption as well as service level agreement violationby minimizing the number of active hosts.Current proposed algorithms do not consider data center architecture, the physical position of hosts, and energy consumption of numerous switches that are in data centers. In this paper, a novel hierarchical cloud resource management is proposed that not only minimizes the number of hosts but also aggregates virtual machines on a limited subset of data center racks and modules to minimize energy consumption. Experimental results with Cloudsim show that our proposed algorithm reduces energy consumption up to 26% and service level agreement violation up to 96%. KEYWORDS data center architecture, dynamic consolidation, power efficiency, resource management, virtualization 1 | INTRODUCTIONIn recent years, cloud computing has attracted attention from both the academic and industrial communities. Cloud computing services are pay-as-you-go and are easily accessible via internet around the world. 1,2 The infrastructure for cloud services are cloud data centers that are composed of hundreds of computational hosts (servers), tens of high speed switches, and other network devices, all of which consume a significant amount of energy. Number of cloud data centers has increased tremendously around the world due to increase in demands for cloud services.Data center energy consumption in the world was 61 billion kWh in 2006 and 100 billion kWh in 2011, and it is expected to reach 139.8 billion kWh by 2020. [3][4][5] Hence, data center energy consumption is of great concern because it increases carbon dioxide (CO 2 ) emission, which has a catastrophic environmental impact. 6 Servers, storage, switches, and other network devices are the main sources of energy consumption in data centers. These devices consume energy near maximum power levels even when they are idle or not fully utilized.Cloud services are provided through virtualization, 7-9 ie, assigning a virtual machine (VM) for each cloud service. 10 Virtualization technology allows allocation and execution of multiple VMs on a host that leads to an increase in host utilization that brings about energy efficiency in a cloud data center. Virtualization technology also provides live migration VMs from 1 host to another in case a host is overutilized or underutilized. There will be a waste of energy if servers are underutilized, because servers use around 30% of their peak power consumption while they are in idle mode 70% of time. 11To tackle energy consumption of underutilized hosts, a common solution is VM consolidation. 9,12 If a host is underutilized or has no work to do, VM consolidation if possible, tries to live migrate its VMs to another host and switch it to sleep mode or turns it off to con...

This study represents an attempt to compare indexing consistency between the catalogers of the National Library of Iran (NLI) on one side and 12 major academic and special libraries located in Tehran on the other. The research findings indicate that in 75% of the libraries the subject inconsistency values are 60% to 85%. In terms of subject classes, the consistency values are 10% to 35.2%, the mean of which is 22.5%. Moreover, the findings show that whenever the number of assigned terms increases, the probability of consistency decreases. This confirms Markey's findings in 1984.

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.