Analyzing Cognitive Radio Network Operation With the Mechanism of Deciding Handoff and Process of Handoff Employing Varied Distribution Models (5G)

Cognitive radio networks (CRNs) deal with sensing, decision making, sharing, and mobility. Among these aspects, spectrum mobility assumes a vital role for spectrum handoff to occur. When the spectrum handoff process is analyzed, there are call drops, spectrum handoff, and interferences with the adjacent channels. For minimizing the handoff of the spectrum's probability as well as the call drops, which involves three processes, which are followed in sequential order, results demonstrate a better QoS. In the following three processes, the first process starts with the Markov model that identifies a channel's states and selects the channel which is apt. The second process, multiple attributes decision making (MADM), methods choose one of the best possible channels among all the channels based on various metrics in the proposed hybrid method. In the third process, the spectrum handoff is analyzed through different distribution models to indicate which model is the desirable one for a handoff process such as the one with stationary users or the other with non-stationary users.

Complex hesitant fuzzy sets and its applications in multiple attributes decision-making problems

Decision-makers (DMs) usually face many obstacles to give the right decision, multiplicity of them highlights a problem to represent a set of potential values to assign a collective membership degree of an object to a set for several DM’s opinions. However, a hesitant fuzzy set (HFS) deals with such problems. The complexity appears in DM’s opinion which can be changed for the same object but with different times/phases. Each of them has a set of potential values in different times/phases of an object. In this paper, the periodicity of hesitant fuzzy information is studied and applied by extending the range of HFS from [0, 1] to the unit disk in the complex plane to provide more ability for illustrating the full meaning of information to overcome the obstacles in decision making in the mathematical model. Moreover, the advantage of CHFS is that the amplitude and phase terms of CHFSs can represent hesitant fuzzy information, some basic operations on CHFS are also presented and we study its properties, in addition, several aggregation operators under CHFS are introduced, also, the relation between CHFS and complex intuitionistic fuzzy sets (CIFS) are presented. Finally, an efficient algorithm with a consistent process and an application in multiple attributes decision-making (MADM) problems are presented to show the effectiveness of the presented approach by using CHFS aggregation operators.

Adopting Distributed Ledger Technology (DLT) For The Sustainable Construction Industry: Evaluating The Barriers Using Ordinal Priority Approach (OPA)

Construction 4.0 has become a buzzword since the penetration of building information modeling (BIM), cyber-physical systems, digital and computing technologies into the construction industry. Among emerging technologies, Distributed Ledger Technology (DLT), or blockchain, is a powerful business enhancer whose potential can disrupt projects, AEC (Architecture, Engineering and Construction) firms, and construction supply chain, and in a broader sense, the whole construction industry. This technology has not reached the plateau of productivity due to several barriers and challenges. Previous studies have started to investigate the barriers to implementing DLT in various sectors and segmentations. However, we still need further surveys in the construction industry. This study evaluates the applicability of identified challenges and barriers based on a sustainability perspective. Precisely, we will answer which challenges need to be addressed for the sustainability of the construction industry. To meet the research objective, the Ordinal Priority Approach (OPA) in multiple attributes decision-making (MADM) was utilized. This novel method determines the importance of the sustainability attributes and barriers simultaneously. The results show that DLT implementation needs i) infrastructure for data management, ii) advanced applications and archetypes, and iii) customers’ demand, interest, and tendency, and iv) taxation and reporting. Solving high-ranked challenges is the key to social sustainability from the aspects of ‘supply chain management and procurement,’ ‘transparency, anti-corruption, and anti-counterfeiting,’ and ‘fair operation and honest competition.’

A Model for Determining the Number of Health Technologies in the Health Systems: An Approach Combining Multiple Attributes Decision Making and Goal Programming

In recent years, health technology policy-making science has gone beyond just a health technology assessment or systematic review or economic evaluation study and the science of operational research in decision making, i.e. multi-attributes and multi-objective decision-making has been included. Hence, currently, health technology policy-making follows a seven-step process. After a technology undergoes these steps and is proven that it is useful for the health system, it must be determined how many of it is needed in the health system. Determining the required number of health technologies is a challenge that remains to be considered. Therefore, this study was designed to overcome this problem. The authors intend to introduce a multi-objective decision-making methodology considering the limited budget, to determine the number of technologies required to complete for the health technology policymaking cycle.

An Optimized Load Balance Solution for Multi-homed Host in Heterogeneous Wireless Networks

The imminent wireless technologies are demanding fusion of several networks with diverse technologies. A convenient user device for such an environment is the multihomed host, which is capable of making use of simultaneous multiple connections of heterogeneous networks and smartly distributing/receiving data among them. The aim of this work is to develop a mechanism for assessing the multihoming concept and to propose a system model for increasing its applicability. The proposed model provided a novel user-centric scheme for multihoming for multi-radio access technologies (multi-RAT). It is considered an evolution of traffic offloading for gaining more capacity, higher data rates, and real-time services. This work assumes data classifications, evaluates and ranks the available connections, and utilizes the application data in an unequal load balance scheme. This is achieved by analyzing the performance of three of the most widely used alternative-choice for multiple attributes decision making (MADM) methods. The analytical hierarchy process (AHP), along with a utility equation, is applied to the system model for unequal load balance solution. The proposed model is targeting an energy efficient mechanism which satisfies application needs. Moreover, it reveals an efficient transmission mechanism for a better quality of service, traffic management, and availability solutions. The simulation results show that the proposed system surpassed its former counterparts.

Tackling Complexity in Green Contractor Selection for Mega Infrastructure Projects: A Hesitant Fuzzy Linguistic MADM Approach with considering Group Attitudinal Character and Attributes’ Interdependency

Continuous environmental concerns regarding construction industry have been driving general constructors of mega infrastructure projects to incorporate green contractors. Although conventional multiple attributes decision-making (MADM) methodologies have provided feasible ways to select contractor, high complexity in scenarios of megaprojects still challenges existing MADM methods in concurrently accommodating three key issues of decision hesitancy, attributes interdependency, and group attitudinal character. To elicit decision-makers’ hesitant fuzzy assessments more objectively and comprehensively, we define an expression tool called interval-valued dual hesitant fuzzy uncertain unbalanced linguistic set (IVDHF_UUBLS) and develop aggregation operators through its operations. To exploit attributes interdependency, we establish a synthesized attributes’ weighting model to fuse an attributes interdependency-based weighting vector and an argument-dependent weighting vector, which are, respectively, derived through Decision-Making and Trial Evaluation Laboratory (DEMATEL) technique and maximizing deviation method. To effectively utilize decision-makers’ group attitudinal characters, we also develop a TOPSIS-based method to rationally transform group ideal attitudes into order-inducing vectors. On the strength of the above methods, an integrated MADM approach is then constructed. Finally, illustrative case study and experiments are conducted to validate our approach.