Continuous skyline queries in distributed environment
by Ibrahim Gomaa; Hoda M.O. Mokhtar
International Journal of Data Science (IJDS), Vol. 4, No. 1, 2019

Abstract: With the expanding number of communications from different mobile applications that acquire location information, the demand for continuous skyline queries has increased. In addition, the extremely fast increase in the data volume and mobile applications that deal with such volume of data such as check-ins recommendation, information services and applications of road networks; have both driven the need to adapt new processing environments to deal with huge amounts of data. In this paper, we present a number of efficient algorithms for processing continuous skyline queries on large datasets using MapReduce framework. The main idea of our proposed algorithms is to compute the skyline query only once at the starting position; then update on the result at the movement of the query point rather than computing the skyline at every time from scratch. In addition, experimental results are conducted which demonstrate the accuracy, performance and efficiency of the proposed algorithms.

Online publication date: Mon, 11-Mar-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Data Science (IJDS):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email