The proposed system of Hierarchical Virtual K-Means architecture has developed the hierarchical virtual k-means algorithm to create a net output of homogenous data spread across several machines and data centers
So, what is a cluster in cloud computing? Simply put, it is a group of nodes hosted on virtual machines and connected within a virtual private cloud. Using the cloud allows for much of the overhead involved in setting up a cluster to be entirely bypassed. Virtual machines can be provision...
Cloud computing as an emerging technology, has revolutionized the information technology industry by elastic on-demand provisioning and De-provisioning of computing resources. Due to the huge amount of electrical energy consumption by large-scale Datacenters, it is essential to investigate various ...
centroids=randCent(dataSet,k)clusterChanged=TruewhileclusterChanged:clusterChanged=Falseforiinrange(m):#foreach data point assign it to the closest centroid minDist=inf;minIndex=-1forjinrange(k):distJI=distEclud(centroids[j,:],dataSet[i,:])ifdistJI<minDist:minDist=distJI;minIndex=jifclust...
Cloud computing has recently emerged as a new paradigm to provide computing services through large-size data centers where customers may run their applications in a virtualized environment. The advantages of cloud in terms of flexibility and economy encourage many enterprises to migrate from local data...
process is generally known asclustering. In a similar vein, the set of synchronized, load-balanced servers are collectively called acluster. Resin supports robust clustering including persistent sessions, distributed sessions and dynamically adding/removing servers from a cluster (elastic/cloud computing)...
In the recent decade, there has been a considerable amount of changes and developments in time-series clustering area that are caused by emerging concepts such as big data and cloud computing which increased size of datasets exponentially. For example, one hour of ECG (electrocardiogram) data occu...
Figure 1 shows the development process of cloud computing. As a result, it would be of significant real-world implications to explore big data clustering mining in combination with the cloud environment. The swarm intelligence optimization algorithm is a technology that has emerged in recent years....
In this paper, we provide a simple, fast and powerful method using dynamic clustering and cloud computing to detect genome-wide multi-locus epistatic interactions. We have constructed systematic experiments to compare powers performance against some recently proposed algorithms, including TEAM, SNPRuler,...
One feature of cloud storage systems is data fragmentation (or sharding) so that data can be distributed over multiple servers and subqueries can be run in parallel on the fragments. On the other hand, flexible query answering can enable a database system to find related information for a user...