PRUNING REDUNDANT SERVICES FOR FAST SERVICE SELECTION

2013 ◽  
Vol 10 (06) ◽  
pp. 1350036
Author(s):  
S. G. WANG ◽  
Z. P. LIU ◽  
Q. B. SUN ◽  
H. ZOU ◽  
F. C. YANG
Keyword(s):  
Quality Of Service ◽  
Integer Programming ◽  
Mixed Integer Programming ◽  
Service Selection ◽  
Search Space ◽  
Mixed Integer ◽  
Time Cost ◽  
Test Bed ◽  
Optimal Service

Selecting the optimal service from a mass of functionally equivalent services with low time cost is significant. Previous research addressed this issue excessively relying on several kinds of optimization algorithms. In this work, we propose an approach that prunes redundant services and reduces search space of service selection on the basis of Skyline computing and context inference. We firstly adopt Skyline computing to prune redundant services. Then, we present the notion of context service based on context inference to further reduce the size of service selection problem. Finally, mixed integer programming is employed to find the optimal service from context services according to users' Quality of Service (QoS) requirements. Experimental results on a test bed indicate that our approach can find the optimal service with low time cost.

scholarly journals Solving the Quality of Service Multicast Tree Problem

2021 ◽  
Vol 33 (2) ◽  
pp. 163-172
Author(s):  
Claudio Enrique Risso-Montaldo ◽  
Franco Rafael Robledo-Amoza ◽  
Sergio Enrique Nesmachnow-Cánovas
Keyword(s):  
Quality Of Service ◽  
Integer Programming ◽  
Mixed Integer Programming ◽  
Multicast Tree ◽  
Mixed Integer ◽  
Programming Formulation ◽  
Integer Programming Formulation ◽  
Realistic Problem ◽  
Problem Instances

This article presents a flow-based mixed integer programming formulation for the Quality of Service Multicast Tree problem. This is a relevant problem related to nowadays telecommunication networksto distribute multimedia over cloud-based Internet systems. To the best of our knowledge, no previous mixed integer programming formulation was proposed for Quality of Service Multicast Tree Problem. Experimental evaluation is performed over a set of realistic problem instances from SteinLib, to prove that standard exact solvers can find solutions to real-world size instances. Exact method is applied for benchmarking the proposed formulations, finding optimal solutions and low feasible-to-optimal gaps in reasonable execution times.

Application of Mixed-Integer Programming and Dispatching Rules on Parallel Machine Scheduling with Inserted Idle Time

2013 ◽  
Vol 437 ◽  
pp. 748-751
Author(s):  
Chi Yang Tsai ◽  
Yi Chen Wang
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Parallel Machines ◽  
Optimal Solution ◽  
Parallel Machine Scheduling ◽  
Idle Time ◽  
Dispatching Rules ◽  
Mixed Integer ◽  
Scheduling Problems

This research considers the problem of scheduling jobs on unrelated parallel machines with inserted idle times to minimize the earliness and tardiness. The aims at investigating how particular objective value can be improved by allowing machine idle time and how quality solutions can be more effectively obtained. Two mixed-integer programming formulations combining with three dispatching rules are developed to solve such scheduling problems. They can easy provide the optimal solution to problem involving about nine jobs and four machines. From the results of experiments, it is found that: (1) the inserted idle times decreases objective values more effectively; (2) three dispatching rules are very competitive in terms of efficiency and quality of solutions.

scholarly journals Dynamic Service Selection Based on Adaptive Global QoS Constraints Decomposition

Symmetry ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 403 ◽  
Author(s):  
Yuan Yuan ◽  
Weishi Zhang ◽  
Xiuguo Zhang ◽  
Huawei Zhai
Keyword(s):  
Optimal Solution ◽  
Service Selection ◽  
Computation Time ◽  
Time Cost ◽  
Service Class ◽  
Local Constraints ◽  
Optimal Service ◽  
Maximum Utility ◽  
Selection Approach

As there are more and more available Web services with the same or similar functionalities but different Quality of Service (QoS), the challenge of QoS-aware service composition is to efficiently select appropriate component services to achieve maximum utility and meet the global QoS constraints with low time cost. In this paper, we propose a dynamic service selection approach based on adaptive global QoS constraints decomposition. Fuzzy logic technology and Cultural Genetic Algorithm are used to adaptively decompose global QoS constraints into near-optimal local constraints. According to the near-optimal local constraints, the optimal service is selected for each service class during the running time efficiently. Experimental results show that the proposed approach not only achieves the near-optimal solution, but also significantly reduces the computation time, and has good adaptability and scalability.

Non-blocking Supervisory Design Using Mixed Integer Programming

2009 ◽  
Vol 35 (2) ◽  
pp. 180-185
Author(s):  
Mi ZHAO ◽  
Zhi-Wu LI ◽  
Na WEI
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Mixed Integer
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