Runtong Zhang

Some Generalized Pythagorean Fuzzy Bonferroni Mean Aggregation Operators with Their Application to Multiattribute Group Decision-Making

The Pythagorean fuzzy set as an extension of the intuitionistic fuzzy set characterized by membership and nonmembership degrees has been introduced recently. Accordingly, the square sum of the membership and nonmembership degrees is a maximum of one. The Pythagorean fuzzy set has been previously applied to multiattribute group decision-making. This study develops a few aggregation operators for fusing the Pythagorean fuzzy information, and a novel approach to decision-making is introduced based on the proposed operators. First, we extend the generalized Bonferroni mean to the Pythagorean fuzzy environment and introduce the generalized Pythagorean fuzzy Bonferroni mean and the generalized Pythagorean fuzzy Bonferroni geometric mean. Second, a new generalization of the Bonferroni mean, namely, the dual generalized Bonferroni mean, is proposed by considering the shortcomings of the generalized Bonferroni mean. Furthermore, we investigate the dual generalized Bonferroni mean in the Pythagorean fuzzy sets and introduce the dual generalized Pythagorean fuzzy Bonferroni mean and dual generalized Pythagorean fuzzy Bonferroni geometric mean. Third, a novel approach to multiattribute group decision-making based on proposed operators is proposed. Lastly, a numerical instance is provided to illustrate the validity of the new approach.

Design theory, modelling and the application for the Internet of Things service

ABSTRACT The Internet of Things (IoT) makes it possible for us to sense the physical world and locate objects in it using the enabling technologies associated with IoT. Compared with traditional information systems, IoT enabling technologies can help acquire real-time data necessary for managing enterprise business process. An IoT system should have an ability beyond integrating enabling technologies and traditional information systems that are only used to access environmental data. This paper begins with a literature review of IoT-related issues and a discussion of the difference between traditional information service and IoT service. Three principles for IoT service design from the perceptive of service classification, coordination and compatibility are proposed. The paper also proposes a utility model for resource allocation in order to improve IoT service performance, and an application involving a cold chain visibility platform is given to illustrate our research.

An inter-PAN mobility support scheme for IP-based wireless sensor networks and its applications

Mobility support for Wireless Sensor Networks (WSN) can significantly extend the use of WSN in many fields, such as industrial control, healthcare and smart home. And high-efficiency mobility support schemes are essential for WSN because this is a typical energy constrained network. This paper proposes a LoW cost inter-PAN Mobility Support Scheme (LoWMS) for IPv6 based WSN, which follows the network based idea. The scheme aims at reducing signaling cost when sensor nodes move between two Personal Area Networks. In order to realize it, the handoff related control messages are designed to transmit in link layer, and resolution for ping-pong handoff is also given. Simulation results show the novel scheme efficiently reduces the amount of handoff messages, which is benefit for energy saving of WSN. At the end of the paper, we illustrate two possible application scenarios which could be beneficial from LoWMS, one is healthcare system, and another is logistics and storage.

An Improved Identity Authentication Scheme for Internet of Things in Heterogeneous Networking Environments

Considering the differences between the Internet and the Internet of Things in security problems, we propose an identity authentication scheme based on elliptic curve algorithm for public and private key pair in order to meet the security requirements of the Internet of Things in heterogeneous networking environments. After being simulated with OPNET, the plan proves to be both safe and effective.

A Novel Approach to Multi-Attribute Group Decision-Making with q-Rung Picture Linguistic Information

The proposed q-rung orthopair fuzzy set (q-ROFS) and picture fuzzy set (PIFS) are two powerful tools for depicting fuzziness and uncertainty. This paper proposes a new tool, called q-rung picture linguistic set (q-RPLS) to deal with vagueness and impreciseness in multi-attribute group decision-making (MAGDM). The proposed q-RPLS takes full advantages of q-ROFS and PIFS and reflects decision-makers’ quantitative and qualitative assessments. To effectively aggregate q-rung picture linguistic information, we extend the classic Heronian mean (HM) to q-RPLSs and propose a family of q-rung picture linguistic Heronian mean operators, such as the q-rung picture linguistic Heronian mean (q-RPLHM) operator, the q-rung picture linguistic weighted Heronian mean (q-RPLWHM) operator, the q-rung picture linguistic geometric Heronian mean (q-RPLGHM) operator, and the q-rung picture linguistic weighted geometric Heronian mean (q-RPLWGHM) operator. The prominent advantage of the proposed operators is that the interrelationship between q-rung picture linguistic numbers (q-RPLNs) can be considered. Further, we put forward a novel approach to MAGDM based on the proposed operators. We also provide a numerical example to demonstrate the validity and superiorities of the proposed method.

Some Hesitant Fuzzy Linguistic Muirhead Means with Their Application to Multiattribute Group Decision-Making

The proposed hesitant fuzzy linguistic set (HFLS) is a powerful tool for expressing fuzziness and uncertainty in multiattribute group decision-making (MAGDM). This paper aims to propose novel aggregation operators to fuse hesitant fuzzy linguistic information. First, we briefly recall the notion of HFLS and propose new operations for hesitant fuzzy linguistic elements (HFLEs). Second, considering the Muirhead mean (MM) is a useful aggregation technology that can consider the interrelationship among all aggregated arguments, we extend it to hesitant fuzzy linguistic environment and propose new hesitant fuzzy linguistic aggregation operators, such as the hesitant fuzzy linguistic Muirhead mean (HFLMM) operator, the hesitant fuzzy linguistic dual Muirhead mean (HFLDMM) operator, the hesitant fuzzy linguistic weighted Muirhead mean (HFLMM) operator, and the hesitant fuzzy linguistic weighted dual Muirhead mean (HFLWDMM) operator. These operators can reflect the correlations among all HFLEs. Several desirable properties and special cases of the proposed operators are also studied. Furthermore, we propose a novel approach to MAGDM in a hesitant fuzzy linguistic context based on the proposed operators. Finally, we conduct a numerical experiment to demonstrate the validity of our method. Additionally, we compare our method with others to illustrate its merits and superiorities.

ECIS, an Energy Conservation and Interconnection Scheme between WSN and Internet Based on the 6LoWPAN

Wireless sensor network (WSN), which has broad application prospects, consists small nodes with sensing, computation and communications capabilities. Short for IPv6 over low power WPAN, 6LoWPAN is a kind of technology which makes IPv6 stack run on the Low PAN devices. In order to establish seamless connection of two heterogeneous networks, WSN and IPv6 network, this paper proposes an improved Energy Conservation and Interconnection Scheme (ECIS) based the analysis of current schemes. Detailed design of each functional component in the new scheme is proposed, and an expansion of SSCS module in NS2 802.15.4 simulator is examined. Comprehensive experiments on the simulation platform show that this newly proposed scheme is advantageous over existed similar attempts.

Some Partitioned Maclaurin Symmetric Mean Based on q-Rung Orthopair Fuzzy Information for Dealing with Multi-Attribute Group Decision Making

In respect to the multi-attribute group decision making (MAGDM) problems in which the evaluated value of each attribute is in the form of q-rung orthopair fuzzy numbers (q-ROFNs), a new approach of MAGDM is developed. Firstly, a new aggregation operator, called the partitioned Maclaurin symmetric mean (PMSM) operator, is proposed to deal with the situations where the attributes are partitioned into different parts and there are interrelationships among multiple attributes in same part whereas the attributes in different parts are not related. Some desirable properties of PMSM are investigated. Then, in order to aggregate the q-rung orthopair fuzzy information, the PMSM is extended to q-rung orthopair fuzzy sets (q-ROFSs) and two q-rung orthopair fuzzy partitioned Maclaurin symmetric mean (q-ROFPMSM) operators are developed. To eliminate the negative influence of unreasonable evaluation values of attributes on aggregated result, we further propose two q-rung orthopair fuzzy power partitioned Maclaurin symmetric mean (q-ROFPPMSM) operators, which combine the PMSM with the power average (PA) operator within q-ROFSs. Finally, a numerical instance is provided to illustrate the proposed approach and a comparative analysis is conducted to demonstrate the advantage of the proposed approach.

Some new Pythagorean fuzzy Choquet-Frank aggregation operators for multi-attribute decision making

Pythagorean fuzzy set (PFS) whose main feature is that the square sum of the membership degree and the non‐membership degree is equal to or less than one, is a powerful tool to express fuzziness and uncertainty. The aim of this paper is to investigate aggregation operators of Pythagorean fuzzy numbers (PFNs) based on Frank t‐conorm and t‐norm. We first extend the Frank t‐conorm and t‐norm to Pythagorean fuzzy environments and develop several new operational laws of PFNs, based on which we propose two new Pythagorean fuzzy aggregation operators, such as Pythagorean fuzzy Choquet–Frank averaging operator (PFCFA) and Pythagorean fuzzy Choquet–Frank geometric operator (PFCFG). Moreover, some desirable properties and special cases of the operators are also investigated and discussed. Then, a novel approach to multi‐attribute decision making (MADM) in Pythagorean fuzzy context is proposed based on these operators. Finally, a practical example is provided to illustrate the validity of the proposed method. The result shows effectiveness and flexible of the new method. A comparative analysis is also presented.

Socially aware mobile application integrations in heterogeneous environments

Mobile web integration technologies and wireless sensor networks provide much more opportunities for human beings to interact with heterogeneous network environment including the communication network, the internet and sensor network. This paper investigates the integrated use of socially aware computing and data mining techniques through a mobile web application. It emphasises the study of regularity of human social activities through mobile applications in order to provide mobile users with intelligent assistance and support in the real world. The research investigates the effectiveness of single-layer and multi-layer evolutionary models of socially aware computing in order for these mobile web applications to be better integrated with the human social activities. Experimental analysis of our self-developed mobile platform as proposed from this research showed the superiority of socially aware computing when applied in the mobile field.