Authors:
Pablo Adasme
1
;
Rafael Andrade
2
;
Janny Leung
3
and
Abdel Lisser
4
Affiliations:
1
Universidad de Santiago de Chile, Chile
;
2
Universidade Federal do Ceará, Brazil
;
3
Chinese University of Hong Kong, Hong Kong
;
4
Université Paris-Sud XI, France
Keyword(s):
Healthcare Wireless Body Area Networks, Network Design Topology Approach, Mixed Integer Linear Programming, Variable Neighborhood Search.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Mathematical Modeling
;
Methodologies and Technologies
;
Operational Research
;
Optimization
;
Symbolic Systems
Abstract:
In this paper, we propose a minmax robust formulation for routing in healthcare wireless body area networks (WBAN). The proposed model minimizes the highest power consumption of each bio-sensor node placed in the body of a patient subject to flow rate and network topology constraints. We consider three topologies in the problem: a spanning tree, a star, and a ring topology as well. In particular, we use an equivalent polynomial formulation of the spanning tree polytope (Yannakakis, 1991) to avoid having an exponential number of cycle elimination constraints in the model. For the ring topology approach, we use constraints from the well known mixed integer linear programming (MILP) formulation of the traveling salesman problem (Pataki, 2003). Thus, we compute optimal solutions and lower bounds directly using the MILP and linear programming (LP) relaxations. Finally, we propose a Kruskal-based (Cormen et al., 2001) variable neighborhood
search metaheuristic to improve the solutions obta
ined with the star topology approach. Our preliminary numerical results indicate that the tree approach is more convenient as it allows saving significantly more power while the ring approach is the most expensive one. They also indicate that the difference between the optimal objective function values for the tree and star formulations is not very large and that VNS can improve significantly the solutions obtained with the star configuration, although, at a higher computational cost.
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