Energy-efficient vertical handover parameters, classification and solutions over wireless heterogeneous networks: a comprehensive survey

In the last few decades, the popularity of wireless networks has been growing dramatically for both home and business networking. Nowadays, smart mobile devices equipped with various wireless networking interfaces are used to access the Internet, communicate, socialize and handle short or long-term businesses. As these devices rely on their limited batteries, energy-efficiency has become one of the major issues in both academia and industry. Due to terminal mobility, the variety of radio access technologies and the necessity of connecting to the Internet anytime and anywhere, energy-efficient handover process within the wireless heterogeneous networks has sparked remarkable attention in recent years. In this context, this paper first addresses the impact of specific information (local, network-assisted, QoS-related, user preferences, etc.) received remotely or locally on the energy efficiency as well as the impact of vertical handover phases, and methods. It presents energy-centric state-of-the-art vertical handover approaches and their impact on energy efficiency. The paper also discusses the recommendations on possible energy gains at different stages of the vertical handover process

Network selection in a virtual network operator environment

Service offerings of virtual network operators should focus on the needs of distinct groups of users in order to face challenges posed in the saturated telecommunications mass market. Since a virtual operator may hire capacity from a number of host networks with varied characteristics, the selection of an optimal host network according to network attributes, user preferences and QoS requirements results to the provision of services with desirable characteristics adding value for the user. Network selection in such an environment has not been studied as all previous works have focused exclusively on handover decisions in heterogeneous wireless networks. This article describes a network selection method in a virtual operator environment that uses a modified version of TOPSIS to rank alternative networks. The proposed modification enables the inclusion of QoS requirements in the ranking results. The uncertainty of user preferences is handled through the use of linguistic assessments and triangular fuzzy numbers. Simulations conducted show that the proposed approach is effective in deciding the optimum network according to all decision factors. © 2012 IFIP International Federation for Information Processing

A utility-based fuzzy TOPSIS method for energy efficient network selection in heterogeneous wireless networks

Mobile terminals in 4G heterogeneous wireless networks continuously undergo horizontal and vertical handovers. In order for a mobile terminal to be connected to a network in the best possible way in terms of QoS performance and energy consumption, access network selection as the main decision within the handover process is obviously crucial. This paper presents a novel method that takes into account user preferences, network conditions, QoS and energy consumption requirements in order to select the optimal network which achieves the best balance between performance and energy consumption. The proposed network selection method incorporates the use of parameterized utility functions in order to model diverse QoS elasticities of different applications, and adopts different energy consumption metrics for real-time and non-real-time applications. User preferences are easily configured for different application and situation contexts through the use of linguistic assessments and their representation as triangular fuzzy numbers. The aggregation of multiple criteria for the calculation of the overall rating of the networks is performed through the use of the Fuzzy Set Representation TOPSIS method that resolves the issue of inconsistency related to conflicting decision criteria and is modified through the use of the employed utility functions for the elimination of the ranking abnormality problem. Finally, simulations are conducted in order to demonstrate how the proposed method would work and confirm its suitability and effectiveness. © 2011 Elsevier B.V

A utility-based fuzzy TOPSIS method for energy efficient network selection in heterogeneous wireless networks

Mobile terminals in 4G heterogeneous wireless networks continuously undergo horizontal and vertical handovers. In order for a mobile terminal to be connected to a network in the best possible way in terms of QoS performance and energy consumption, access network selection as the main decision within the handover process is obviously crucial. This paper presents a novel method that takes into account user preferences, network conditions, QoS and energy consumption requirements in order to select the optimal network which achieves the best balance between performance and energy consumption. The proposed network selection method incorporates the use of parameterized utility functions in order to model diverse QoS elasticities of different applications, and adopts different energy consumption metrics for real-time and non-real-time applications. User preferences are easily configured for different application and situation contexts through the use of linguistic assessments and their representation as triangular fuzzy numbers. The aggregation of multiple criteria for the calculation of the overall rating of the networks is performed through the use of the Fuzzy Set Representation TOPSIS method that resolves the issue of inconsistency related to conflicting decision criteria and is modified through the use of the employed utility functions for the elimination of the ranking abnormality problem. Finally, simulations are conducted in order to demonstrate how the proposed method would work and confirm its suitability and effectiveness. © 2011 Elsevier B.V. All rights reserved

Customer evaluation for order acceptance using a novel class of fuzzy methods based on TOPSIS

Customer evaluation plays an important role as a part of the order acceptance process of suppliers in optimally allocating resources and prioritizing orders accordingly. In this paper, a new class of fuzzy methods for evaluating customers is applied. Firstly, our approach tackles the issue of uncertainty that is inherent in the problem of customer evaluation that involves qualitative criteria by employing the method proposed by Yong [Yong, D. (2006). Plant location selection based on fuzzy TOPSIS. International Journal of Advanced Manufacturing Technology, 28(7-8), 839-844] in order to efficiently transform linguistic assessments of the weights of criteria and of the ratings of customers into crisp numbers. Secondly, the TOPSIS method is modified in order to integrate the behavioral pattern of the decision maker into its "principle of compromise". In this context, a new model for the aggregating function of TOPSIS that is based on a fuzzy set representation of the closeness to the ideal and the negative ideal solution is applied. In particular, we use the class of intersection connectives proposed by Yager [Yager, R. R. (1980). On a general class of fuzzy connectives. Fuzzy Sets and Systems, 4(3), 235-242] that enables a formal definition of the relation between the closeness to the ideal solution and the closeness to the negative ideal solution. Thus, a class of methods is formulated whose different instances correspond to different behavioral patterns of the decision makers, e.g. with preference to customers that make as much profit as possible but also avoid as much risk as possible or to customers that are performing well in at least one of the profit and risk criteria. A numerical example, illustrating the application of this class of methods to customer evaluation is given. © 2008 Elsevier Ltd. All rights reserved

In-depth analysis and simulation study of an innovative fuzzy approach for ranking alternatives in multiple attribute decision making problems based on TOPSIS

In this paper, an innovative fuzzy approach for ranking alternatives in multiple attribute decision making problems based on TOPSIS is presented in-depth and studied through simulation comparison with the original method. The TOPSIS method provides the principle of compromise that the chosen alternative should have the shortest distance from the ideal solution and, simultaneously, the farthest distance from the negative ideal solution. However, the TOPSIS method does not always produce results in harmony with this principle due to an oversimplified definition of its aggregation function which does not grasp the contradictory nature of the principle's formulation. Our approach addresses this issue through the introduction of a fuzzy set representation of the closeness to the ideal and to the negative ideal solution for the definition of the aggregation function which is modeled as the membership function of the intersection of two fuzzy sets. This model enables a parameterization of the method according to the risk attitude of the decision maker. Thus, a class of methods is formulated whose different instances correspond to different risk attitudes of the decision makers. In order to define some clear advises for decision makers facilitating a proper parameterization of the method, a comparative analysis of the proposed class of methods with the original TOPSIS method is performed according to well defined simulation techniques. The results of the simulation experiment show on the one hand that there is no direct correspondence between the proposed class of methods and TOPSIS, and on the other hand that it is adequate to distinguish three instances that correspond respectively to risk-averse, risk-neutral and risk-seeking decision makers. Finally, a numerical example pertaining to the problem of service provider selection is presented to illustrate the application of the proposed class of methods and its functioning. © 2010 Elsevier B.V. All rights reserved

"Liquid" electronic marketplaces

"Neutral" electronic marketplaces fail because their structure and mode of operation does not allow for the effective accommodation of multiple business models that could serve the interests of a critical mass of adopters. We propose a fresh approach for the creation of economically viable "neutral" electronic marketplaces showing that this can be accomplished through the ability to transcend taxonomical classifications with a generic agent-mediated ontology and, simultaneously, through the provision of flexible and active decision support. Taxonomies may stifle innovation by imposing artificial boundaries through categorization schemes and levels of abstraction. The proposed architecture addresses this issue underlying a "liquid" e-hub that may mutate from one taxonomical classification to another

Network Selection in a Virtual Network Operator Environment

Part 11: Engineering Applications of AI and Artificial Neural NetworksInternational audienceService offerings of virtual network operators should focus on the needs of distinct groups of users in order to face challenges posed in the saturated telecommunications mass market. Since a virtual operator may hire capacity from a number of host networks with varied characteristics, the selection of an optimal host network according to network attributes, user preferences and QoS requirements results to the provision of services with desirable characteristics adding value for the user. Network selection in such an environment has not been studied as all previous works have focused exclusively on handover decisions in heterogeneous wireless networks. This article describes a network selection method in a virtual operator environment that uses a modified version of TOPSIS to rank alternative networks. The proposed modification enables the inclusion of QoS requirements in the ranking results. The uncertainty of user preferences is handled through the use of linguistic assessments and triangular fuzzy numbers. Simulations conducted show that the proposed approach is effective in deciding the optimum network according to all decision factors