Open AccessEfficient data replica placement for sensor clouds
Author(s) -
Tao Yaling,
Zhang Yongbing,
Ji Yusheng
Publication year - 2016
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2015.0466
Subject(s) - replica , computer science , integer programming , cache , node (physics) , linear programming , lagrangian relaxation , relaxation (psychology) , greedy algorithm , linear programming relaxation , mathematical optimization , heuristic , scheme (mathematics) , upper and lower bounds , algorithm , mathematics , parallel computing , art , social psychology , psychology , mathematical analysis , structural engineering , engineering , visual arts
The authors address the problem of determining a replica placement scheme for sensor data in a cache network constructed by a number of cache nodes in edge networks of the Internet, with the purpose of minimising the total costs for data placement and access. They formulate the placement problem as a mixed integer programming (MIP) problem and then propose several heuristic approaches to solve the problem. They first relax the MIP problem to a linear programming (LP) problem and then round the fractional solution values of the LP problem to integers. Next, they employ a Lagrangian relaxation approach to find a solution for each data item without considering node capacity and then rearrange the placement at each node to satisfy the capacity constraint. For comparison, they also propose a greedy approach that determines a replica placement at a node by using the node local information. They show that the former two approaches lead to good performance that is only <8% worst than the theoretical lower bound.