Abstract
In the literature of distributed database system (DDBS), several methods sought to meet the satisfactory reduction on transmission cost (TC) and were seen substantially effective. Data Fragmentation, site clustering, and data distribution have been considered the major leading TC-mitigating influencers. Sites clustering, on one hand, aims at grouping sites appropriately according to certain similarity metrics. On the other hand, data distribution seeks to allocate the fragmented data into clusters/sites properly. The combination of these methods, however, has been shown fruitful concerning TC reduction along with network overheads. In this work, hence, a heuristic clustering-based approach for vertical fragmentation and data allocation is meticulously designed. The focus is directed on proposing an influential solution for improving relational DDBS throughputs across an aggregated similarity-based fragmentation procedure, an effective site clustering and a greedy algorithm-driven data allocation model. Moreover, the data replication is also considered so TC is further minimized. Through the delineated-below evaluation, the findings of experimental implementation have been observed to be promising.
Highlights
Over the past forty years, numerous approaches have been evolved in distributed database system (DDBS) literature to functionally manage the ever-growing data
We are going to: present experimental setup for ASGOP and its competitive peers, draw the datasets used in experiments conduction, give a demonstrative example to show the way in which ASGOP works, and analyze ASGOP performance along with its peers
This work comes with the main task embedded at presenting a wellarticulated solution for DDBS design
Summary
Over the past forty years, numerous approaches have been evolved in DDBS literature to functionally manage the ever-growing data. The continuous interest is still emphasized towards finding the well-designed approaches to keep the sustainability of DDBS performance. The most critical contributor in performance is that how much amount of data is being transmitted over the network when distributed queries are under processing. This dominant contributor has widely known as Transmission Costs (TC) for which most of the previous DDBS works had come to find a solution of influential impact. It has been noted that almost the majority of earlier works have never been recorded to come up with a clear definition for this contributor by which performance is set to be graded (Amer et al, 2018a, b)
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