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This paper will demonstrate a novel method for consolidating data in an engineered hypercube network for the purpose of optimizing query processing. Query processing typically calls for merging data collected from a small subset of server nodes in a network. This poses the problem of managing efficiently the exchange of data between processing nodes to complete some relational data operation. The method developed here is designed to minimize data transfer, measured as the product of data quantity and network distance, by delegating the processing to a node that is relatively central to the subset. A hypercube not only supports simple computation of network distance between nodes, but also allows for identifying a node to serve as the center for any data consolidation operations.We will show how the consolidation process can be performed by selecting a subgraph of a complex network to simplify the selection of a central node and thus facilitate the computations required. We will also show a prototype implementation of a hypercube using Software-Defined Networking to support query optimization in a distributed heterogeneous database system, making use of network distance information and data quantity. 

We previously proposed a method to locate high packetdelay variance links for OpenFlow networks by probing multicast measurement packets along a designed route and by collecting flow-stats of the probe packets from selected OpenFlow switches (OFSs). It is worth AQ1 noting that the packet-delay variance of a link is estimated based on arrival time intervals of probe packets without measuring delay times over the link. However, the previously used route scheme based on the shortest path tree may generate a probing route with many branches in a large network, resulting in many accesses to OFSs to locate all high delay variance links. In this paper, therefore, we apply an Eulerian cycle-based scheme which we previously developed, to control the number of branches in a multicast probing route. Our proposal can reduce the load on the control-plane (i.e., the number of accesses to OFSs) while maintaining an acceptable measurement accuracy with a light load on the data-plane. Additionally, the impacts of packet losses and correlated delays over links on those different types of loads are investigated. By comparing our proposal with the shortest path tree-based and the unicursal route schemes through numerical simulations, we evaluate the advantage of our proposal. 

The major construction and initial-phase operation of a second-generation gravitational-wave detector, KAGRA, has been completed. The entire 3 km detector is installed underground in a mine in order to be isolated from background seismic vibrations on the surface. This allows us to achieve a good sensitivity at lowfrequencies and high stability of the detector. Bare-bones equipment for the interferometer operation has been installed and the first test runwas accomplished in March and April of 2016 with a rather simple configuration. The initial configuration of KAGRA is called iKAGRA. In this paper, we summarize the construction of KAGRA, including a study of the advantages and challenges of building an underground detector, and the operation of the iKAGRA interferometer together with the geophysics interferometer that has been constructed in the same tunnel.