An efficient resource sharing technique for multi-tenant databases

Multi-tenancy is one of the key components of cloud computing environment. Multi-tenant database system in SaaS (Software as a Service) has gained a lot of attention in academics, research and business arena. These database systems provide scalability and economic benefits for both cloud service providers and customers(organizations/companies referred as tenants) by sharing same resources and infrastructure in isolation of shared databases, network and computing resources with Service level agreement (SLA) compliances. In a multitenant scenario, active tenants compete for resources in order to access the database. If one tenant blocks up the resources, the performance of all the other tenants may be restricted and a fair sharing of the resources may be compromised. The performance of tenants must not be affected by resource-intensive activities and volatile workloads of other tenants. Moreover, the prime goal of providers is to accomplish low cost of operation, satisfying specific schemas/SLAs of each tenant. Consequently, there is a need to design and develop effective and dynamic resource sharing algorithms which can handle above mentioned issues. This work presents a model embracing a query classification and worker sorting technique to efficiently share I/O, CPU and Memory thus enhancing dynamic resource sharing and improvising the utilization of idle instances proficiently. The model is referred as Multi-Tenant Dynamic Resource Scheduling Model (MTDRSM) .The MTDRSM support workload execution of different benchmark such as TPC-C(Transaction Processing Performance Council), YCSB(The Yahoo! Cloud Serving Benchmark)etc. and on different database such as MySQL, Oracle, H2 database etc. Experiments are conducted for different benchmarks with and without SLA compliances to evaluate the performance of MTDRSM in terms of latency and throughput achieved. The experiments show significant performance improvement over existing Mute Bench model in terms of latency and throughput

Fault aware task scheduling in cloud using min-min and DBSCAN

Cloud computing leverages computing resources by managing these resources globally in a more efficient manner as compared to individual resource services. It requires us to deliver the resources in a heterogeneous environment and also in a highly dynamic nature. Hence, there is always a risk of resource allocation failure that can maximize the delay in task execution. Such adverse impact in the cloud environment also raises questions on quality of service (QoS). Resource management for cloud application and service have bigger challenges and many researchers have proposed several solutions but there is room for improvement. Clustering the resources clustering and mapping them according to task can also be an option to deal with such task failure or mismanaged resource allocation. Density-based spatial clustering of applications with noise (DBSCAN) is a stochastic approach-based algorithm which has the capability to cluster the resources in a cloud environment. The proposed algorithm considers high execution enabled powerful data centers with least fault probability during resource allocation which reduces the probability of fault and increases the tolerance. The simulation is cone using CloudsSim 5.0 tool kit. The results show 25% average improve in execution time, 6.5% improvement in number of task completed and 3.48% improvement in count of task failed as compared to ACO, PSO, BB-BC (Bib = g bang Big Crunch) and WHO(Whale optimization algorithm)

Development of geobiophysical models for cartographic representation of wetlands in Yellow Creek Basin, West Virginia

In the Appalachian Mountains of Canaan Valley, the warmer temperatures and fading native species are conducive for invading foreign species. Localized relic communities of red spruce, sphagnum and polytrichum are sensitive to climatic change and potential indicators of global warming. Therefore, the development of a baseline assessment and further research are necessary to observe and model changes. Influencing factors in wetland ecology include slope, aspect, biologically rich and diverse vegetation associations, micro-topography, hydrology, underlying soils, and geology. Three uniquely independent study sites have been established along a single transect of the Yellow Creek stream terraces, in Tucker County, West Virginia. Vegetation physiognomic association, micro-topography, hydrology, and soils data were collected using a variety of technologies. A plane table polar coordinate paper, with K&E® alidade, and Sonin® sonic ranging device for vegetation physiognomic association mappings was originally employed. This was replaced by Magellan® ProMarkX-CP-GPS providing more efficient vegetation association delineation and registration to UTM mapping coordinates. A detailed micro-topographic survey was performed using Nikon® Theodolite Total Station to accurately determine the micro-topography. Collected field data were imported into ER Mapper®5.5 software, the geobiophysical modeling system, via an iterative registration process. Digitized 1995 color infrared one-meter resolution aerial imagery supplied by the United States Forest Service formed the base map for all registration. A combination of image processing techniques including principal component analysis and cluster analysis was applied to extract features for pattern recognition. The processed spectral, spatial, and multi-temporal components were geobiophysically modeled to characterize vegetation physiognomic associations and other identified features. The three-dimensional cartographic representations illustrate the subtle relationships between sphagnum, eriophorum and polytrichum physiognomic associations and surface hydrology

Internet... the final frontier: an ethnographic account: exploring the cultural space of the Net from the inside

The research project The Internet as a space for interaction, which completed its mission in Autumn 1998, studied the constitutive features of network culture and network organisation. Special emphasis was given to the dynamic interplay of technical and social conventions regarding both the Net’s organisation as well as its change. The ethnographic perspective chosen studied the Internet from the inside. Research concentrated upon three fields of study: the hegemonial operating technology of net nodes (UNIX) the network’s basic transmission technology (the Internet Protocol IP) and a popular communication service (Usenet). The project’s final report includes the results of the three branches explored. Drawing upon the development in the three fields it is shown that changes that come about on the Net are neither anarchic nor arbitrary. Instead, the decentrally organised Internet is based upon technically and organisationally distributed forms of coordination within which individual preferences collectively attain the power of developing into definitive standards. --

Optical remote sensing of aboveground forest biomass and carbon stocks in resource-constrained African environments.

Ph. D. University of KwaZulu-Natal, Pietermaritzburg 2015.No abstract available