scholarly journals Multiobjective Optimization Method of Coevolution to Intelligent Agricultural Dynamic Services under the Internet of Things Environment

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Haihong Liang

The agricultural Internet of Things system, with its large-scale, highly heterogeneous, and dynamic characteristics, brings certain difficulties to the provision of agricultural Internet of Things services. Considering the multiple requests of the agricultural Internet of Things at any random moment, which have the characteristics of multiple sources, multiple types, and uneven tasks, this paper establishes an optimization model for the minimum service cost and proposes a collaborative evolution to intelligent agricultural dynamic services under the Internet of Things environment multiobjective optimization method. First, according to the probability that the allele on the fragment to be vaccinated has appeared in the memory bank, use the detection strategy to judge whether the solution is illegal; secondly, compare the optimal individual with other values appearing on the gene locus, judge whether the optimal gene or fall into the local optimal, and inoculate with probability through simulated annealing; finally, the total service cost and service time were evaluated under the two service provision strategies and compared with the other three intelligent algorithms; the results confirmed the feasibility and effectiveness of the proposed algorithm. At the same time, the simulation results show that the proposed collaborative multiobjective optimization algorithm can achieve better performance.

2018 ◽  
Vol 7 (3.12) ◽  
pp. 545
Author(s):  
Risabh Mishra ◽  
M Safa ◽  
Aditya Anand

Recent advances in wireless communication technologies and automobile industry have triggered a significant research interest in the field of Internet of Vehicles over the past few years.The advanced period of the Internet of Things is guiding the development of conventional Vehicular Networks to the Internet of Vehicles.In the days of Internet connectivity there is need to be in safe and problem-free environment.The Internet of Vehicles (IoV) is normally a mixing of three networks: an inter-vehicleNetwork, an intra-vehicle network, and a vehicle to vehicle network.Based on  idea of three networks combining into one, we define  Internet of Vehicles as a large-scale distributed system to wireless communication and information exchange between vehicle2X (X: vehicle, road, human and internet).It is a combined   network for supporting intelligent traffic management, intelligent dynamic information service, and intelligent vehicle control, representation of an application of the Internet of Things (IoT) technology for intelligent transportation system (ITS).  


Sensors ◽  
2018 ◽  
Vol 18 (6) ◽  
pp. 1920 ◽  
Author(s):  
Juanli Li ◽  
Jiacheng Xie ◽  
Zhaojian Yang ◽  
Junjie Li

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Jun Huang ◽  
Liqian Xu ◽  
Cong-cong Xing ◽  
Qiang Duan

The design of wireless sensor networks (WSNs) in the Internet of Things (IoT) faces many new challenges that must be addressed through an optimization of multiple design objectives. Therefore, multiobjective optimization is an important research topic in this field. In this paper, we develop a new efficient multiobjective optimization algorithm based on the chaotic ant swarm (CAS). Unlike the ant colony optimization (ACO) algorithm, CAS takes advantage of both the chaotic behavior of a single ant and the self-organization behavior of the ant colony. We first describe the CAS and its nonlinear dynamic model and then extend it to a multiobjective optimizer. Specifically, we first adopt the concepts of “nondominated sorting” and “crowding distance” to allow the algorithm to obtain the true or near optimum. Next, we redefine the rule of “neighbor” selection for each individual (ant) to enable the algorithm to converge and to distribute the solutions evenly. Also, we collect the current best individuals within each generation and employ the “archive-based” approach to expedite the convergence of the algorithm. The numerical experiments show that the proposed algorithm outperforms two leading algorithms on most well-known test instances in terms of Generational Distance, Error Ratio, and Spacing.


2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Federica Paganelli ◽  
David Parlanti

Current trends towards the Future Internet are envisaging the conception of novel services endowed with context-aware and autonomic capabilities to improve end users’ quality of life. The Internet of Things paradigm is expected to contribute towards this ambitious vision by proposing models and mechanisms enabling the creation of networks of “smart things” on a large scale. It is widely recognized that efficient mechanisms for discovering available resources and capabilities are required to realize such vision. The contribution of this work consists in a novel discovery service for the Internet of Things. The proposed solution adopts a peer-to-peer approach for guaranteeing scalability, robustness, and easy maintenance of the overall system. While most existing peer-to-peer discovery services proposed for the IoT support solely exact match queries on a single attribute (i.e., the object identifier), our solution can handle multiattribute and range queries. We defined a layered approach by distinguishing three main aspects: multiattribute indexing, range query support, peer-to-peer routing. We chose to adopt an over-DHT indexing scheme to guarantee ease of design and implementation principles. We report on the implementation of a Proof of Concept in a dangerous goods monitoring scenario, and, finally, we discuss test results for structural properties and query performance evaluation.


2018 ◽  
Vol 33 (6) ◽  
pp. 749-767 ◽  
Author(s):  
Seppo Leminen ◽  
Mervi Rajahonka ◽  
Mika Westerlund ◽  
Robert Wendelin

Purpose This study aims to understand their emergence and types of business models in the Internet of Things (IoT) ecosystems. Design/methodology/approach The paper builds upon a systematic literature review of IoT ecosystems and business models to construct a conceptual framework on IoT business models, and uses qualitative research methods to analyze seven industry cases. Findings The study identifies four types of IoT business models: value chain efficiency, industry collaboration, horizontal market and platform. Moreover, it discusses three evolutionary paths of new business model emergence: opening up the ecosystem for industry collaboration, replicating the solution in multiple services and return to closed ecosystem as technology matures. Research limitations/implications Identifying business models in rapidly evolving fields such as the IoT based on a small number of case studies may result in biased findings compared to large-scale surveys and globally distributed samples. However, it provides more thorough interpretations. Practical implications The study provides a framework for analyzing the types and emergence of IoT business models, and forwards the concept of “value design” as an ecosystem business model. Originality/value This paper identifies four archetypical IoT business models based on a novel framework that is independent of any specific industry, and argues that IoT business models follow an evolutionary path from closed to open, and reversely to closed ecosystems, and the value created in the networks of organizations and things will be shareable value rather than exchange value.


IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 57192-57203 ◽  
Author(s):  
Yanhua He ◽  
Sunxuan Zhang ◽  
Liangrui Tang ◽  
Yun Ren

2020 ◽  
Vol 106 ◽  
pp. 102240
Author(s):  
Saci Medileh ◽  
Abdelkader Laouid ◽  
El Moatez Billah Nagoudi ◽  
Reinhardt Euler ◽  
Ahcène Bounceur ◽  
...  

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