Pub Date : 2022-08-01DOI: 10.1109/SmartIoT55134.2022.00020
Matthias Melzer, Jan Dünnweber, Timo Baumann
Recent advances in the development of smart homes have led to the availability of a wide variety of devices providing a high level of convenience via gesture and speech control or fully automated operation. Many smart home appliances also address the aspects of safety and electricity savings by automatically powering themselves off after not being used for a while. However, many devices remain in a typical household that are not themselves “smart”, or are not primarily electric (such as heating systems). We address the savings aspect by identifying processes involving the use of multiple devices in the electrical flow data, as captured by a smart meter in a modern household, rather than focusing on a single appliance. Therefore, we introduce a novel approach to usage pattern analysis based on the idea that a pattern of device usages as a result of a resident's ‘routine’ (such as making breakfast) can be interpreted similarly to a natural language ‘sentence’; Natural Language Processing (NLP) algorithms can then be used for interpreting the residents' behavior. We introduce the notion of bag-oj-devices (BoD), derived from the bag-of-words model used in document classification. In an experiment, we show how we use this model to infer predictions about the inhabitants from device usage, such as the resident leaving for the day or just to fetch the newspaper.
{"title":"Towards Smart Home Data Interpretation Using Analogies to Natural Language Processing","authors":"Matthias Melzer, Jan Dünnweber, Timo Baumann","doi":"10.1109/SmartIoT55134.2022.00020","DOIUrl":"https://doi.org/10.1109/SmartIoT55134.2022.00020","url":null,"abstract":"Recent advances in the development of smart homes have led to the availability of a wide variety of devices providing a high level of convenience via gesture and speech control or fully automated operation. Many smart home appliances also address the aspects of safety and electricity savings by automatically powering themselves off after not being used for a while. However, many devices remain in a typical household that are not themselves “smart”, or are not primarily electric (such as heating systems). We address the savings aspect by identifying processes involving the use of multiple devices in the electrical flow data, as captured by a smart meter in a modern household, rather than focusing on a single appliance. Therefore, we introduce a novel approach to usage pattern analysis based on the idea that a pattern of device usages as a result of a resident's ‘routine’ (such as making breakfast) can be interpreted similarly to a natural language ‘sentence’; Natural Language Processing (NLP) algorithms can then be used for interpreting the residents' behavior. We introduce the notion of bag-oj-devices (BoD), derived from the bag-of-words model used in document classification. In an experiment, we show how we use this model to infer predictions about the inhabitants from device usage, such as the resident leaving for the day or just to fetch the newspaper.","PeriodicalId":422269,"journal":{"name":"2022 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122717931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-01DOI: 10.1109/SmartIoT55134.2022.00031
Mauro Raul Lopez-Noa, Hugo Eladio Chumpitaz-Caycho, Ericka Nelly Espinoza-Gamboa, Manuel Alberto Espinoza-Cruz, Franklin Cordova-Buiza
The study aimed to know how the intelligent transportation system improves the management and control of passenger transportation companies between 2016 and 2021. An adaptation of the Prisma methodology was used, which poses a system for evaluating the systematic review of scientific literature on its relationship with the objective and the research question. The databases used were Scopus, Ebsco, ProQuest and Scielo. A total of 52 scientific articles were found; and after applying the selection criteria,11 original studies were obtained. It is concluded that the intelligent systems were implemented with the aim of improving the management and control of transportation, through the new experience of traveling in these units allowing an important advantage for passengers. In the studies reviewed, the effectiveness of having accurate information regarding the route, stations, trunk lines and, above all, reducing obstacles and collisions due to drivers' lack of attention is exposed. Consequently, in the research reviewed, it has been found that these systems provide the user with real-time information on the various schedules, routes and delays of the units, helping to make decisions.
{"title":"Intelligent system in the management and control of transportation companies: A systematic review","authors":"Mauro Raul Lopez-Noa, Hugo Eladio Chumpitaz-Caycho, Ericka Nelly Espinoza-Gamboa, Manuel Alberto Espinoza-Cruz, Franklin Cordova-Buiza","doi":"10.1109/SmartIoT55134.2022.00031","DOIUrl":"https://doi.org/10.1109/SmartIoT55134.2022.00031","url":null,"abstract":"The study aimed to know how the intelligent transportation system improves the management and control of passenger transportation companies between 2016 and 2021. An adaptation of the Prisma methodology was used, which poses a system for evaluating the systematic review of scientific literature on its relationship with the objective and the research question. The databases used were Scopus, Ebsco, ProQuest and Scielo. A total of 52 scientific articles were found; and after applying the selection criteria,11 original studies were obtained. It is concluded that the intelligent systems were implemented with the aim of improving the management and control of transportation, through the new experience of traveling in these units allowing an important advantage for passengers. In the studies reviewed, the effectiveness of having accurate information regarding the route, stations, trunk lines and, above all, reducing obstacles and collisions due to drivers' lack of attention is exposed. Consequently, in the research reviewed, it has been found that these systems provide the user with real-time information on the various schedules, routes and delays of the units, helping to make decisions.","PeriodicalId":422269,"journal":{"name":"2022 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123284192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-01DOI: 10.1109/SmartIoT55134.2022.00021
Xinzhi Gao, Shoucan Wang, N. Ding
How to design a multi-robot collaborative hunting method according to the local roadmap has become a key issue in the field of Multi-Robot Systems (MRS). This paper firstly establishes a robot potential field model based on the characteristics of the local roadmap, combined with the basic idea of the artificial potential field method. Then a multi-robot collaborative hunting strategy called Mobile Prediction Collaborative Interception (MPCI) is proposed based on the robot potential field model. The Adaptive Artificial Potential Field (AAPF) and the constraints are proposed to improve the MPCI to solve the three main problems of Target Loss, Target Unreachable, and Following Deadlock in the hunting process. On this basis, AAPF-MPCI collaborative hunting algorithm is proposed to improve the efficiency and stability of the system. The final simulation results show that the AAPF-MPCI algorithm is more stable and effectively shortens the time spent for MRS to hunt prey robots in roadmap-restricted scenes.
{"title":"Roadmap-Restricted Multi-Robot Collaborative Hunting Method Based on Improved Artificial Potential Field","authors":"Xinzhi Gao, Shoucan Wang, N. Ding","doi":"10.1109/SmartIoT55134.2022.00021","DOIUrl":"https://doi.org/10.1109/SmartIoT55134.2022.00021","url":null,"abstract":"How to design a multi-robot collaborative hunting method according to the local roadmap has become a key issue in the field of Multi-Robot Systems (MRS). This paper firstly establishes a robot potential field model based on the characteristics of the local roadmap, combined with the basic idea of the artificial potential field method. Then a multi-robot collaborative hunting strategy called Mobile Prediction Collaborative Interception (MPCI) is proposed based on the robot potential field model. The Adaptive Artificial Potential Field (AAPF) and the constraints are proposed to improve the MPCI to solve the three main problems of Target Loss, Target Unreachable, and Following Deadlock in the hunting process. On this basis, AAPF-MPCI collaborative hunting algorithm is proposed to improve the efficiency and stability of the system. The final simulation results show that the AAPF-MPCI algorithm is more stable and effectively shortens the time spent for MRS to hunt prey robots in roadmap-restricted scenes.","PeriodicalId":422269,"journal":{"name":"2022 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123979350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-01DOI: 10.1109/SmartIoT55134.2022.00029
D. Cao, C. Hu, N. Ding
Intelligent and connected vehicles (ICVs) is developed based on Internet of Vehicles (IOV) and intelligent vehicles, has become an effective solution to optimize vehicle traffic and alleviate traffic congestion based on the collaborative strategy of vehicle - road - environment. This paper proposes a lane-changing strategy of vehicles at the exit of roundabout based on the Vehicle Profile(VP) which achieved by the driving characteristics of vehicles in traffic roundabout. Initially, Vehicle Profile(VP) is defined due to the hybrid problem of multi-source heterogeneous data existing in ICVs, then the multi-source heterogeneous data is represented by VP. Moreover, the random forest algorithm is used to dynamically obtain and update the label weight of Vehicle Profile because of the problem of label weight existing in the practical application. In addition, the dynamic weight of the Vehicle Profile is introduced into the design of the vehicle payoff function involved in lane change decision, which solves the problem that the weight of each part of the payoff function is used as a parameter. Finally, the performance of the algorithm is tested and verified by SUMO in roundabout general traffic conditions, congested traffic conditions and sparse traffic conditions. The experimental results show that this algorithm can improve the Efficiency and comfort of vehicle driving in general traffic environment more greatly compared with the situation of traffic congestion and sparse traffic flow. Meanwhile, this algorithm verifies the optimization effect of introducing Vehicle Profile on roundabout traffic strategy.
{"title":"Design of Vehicle Profile for Autonomous Vehicles in Roundabouts used to improve Lane Change Strategy based on Multi-vehicle Collaboration","authors":"D. Cao, C. Hu, N. Ding","doi":"10.1109/SmartIoT55134.2022.00029","DOIUrl":"https://doi.org/10.1109/SmartIoT55134.2022.00029","url":null,"abstract":"Intelligent and connected vehicles (ICVs) is developed based on Internet of Vehicles (IOV) and intelligent vehicles, has become an effective solution to optimize vehicle traffic and alleviate traffic congestion based on the collaborative strategy of vehicle - road - environment. This paper proposes a lane-changing strategy of vehicles at the exit of roundabout based on the Vehicle Profile(VP) which achieved by the driving characteristics of vehicles in traffic roundabout. Initially, Vehicle Profile(VP) is defined due to the hybrid problem of multi-source heterogeneous data existing in ICVs, then the multi-source heterogeneous data is represented by VP. Moreover, the random forest algorithm is used to dynamically obtain and update the label weight of Vehicle Profile because of the problem of label weight existing in the practical application. In addition, the dynamic weight of the Vehicle Profile is introduced into the design of the vehicle payoff function involved in lane change decision, which solves the problem that the weight of each part of the payoff function is used as a parameter. Finally, the performance of the algorithm is tested and verified by SUMO in roundabout general traffic conditions, congested traffic conditions and sparse traffic conditions. The experimental results show that this algorithm can improve the Efficiency and comfort of vehicle driving in general traffic environment more greatly compared with the situation of traffic congestion and sparse traffic flow. Meanwhile, this algorithm verifies the optimization effect of introducing Vehicle Profile on roundabout traffic strategy.","PeriodicalId":422269,"journal":{"name":"2022 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127304305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the development of technology and society, the traditional energy system has become difficult to meet the demand. Applying Deep Reinforcement Learning (DRL) to solve scheduling problems in microgrid cluster edge-cloud collaborative architecture provides a new solution. However, there is no research work has been completed to address the independent training, deployment, and inference of DRL in the microgrid cluster scenario. In this paper, we propose a federated DRL-based request scheduling algorithm for distributed microgrid cluster scenarios with the goal of maximizing the long-term utility of the system. In addition, we prune the DRL model to make it more applicable to resource-constrained edge nodes. The experimental results show that the proposed algorithm has more stable performance and better adaptability to the dynamic system environment compared to the traditional centralized training. In addition, the pruning of the model compresses the size of the model to 50.4% with a 4% loss of accuracy.
{"title":"Lightweight Federated Reinforcement Learning for Independent Request Scheduling in Microgrids","authors":"Zhuoxi Duan, Yufei Qiao, Sheng Chen, Xinying Wang, Guoliang Wu, Xiaofei Wang","doi":"10.1109/SmartIoT55134.2022.00041","DOIUrl":"https://doi.org/10.1109/SmartIoT55134.2022.00041","url":null,"abstract":"With the development of technology and society, the traditional energy system has become difficult to meet the demand. Applying Deep Reinforcement Learning (DRL) to solve scheduling problems in microgrid cluster edge-cloud collaborative architecture provides a new solution. However, there is no research work has been completed to address the independent training, deployment, and inference of DRL in the microgrid cluster scenario. In this paper, we propose a federated DRL-based request scheduling algorithm for distributed microgrid cluster scenarios with the goal of maximizing the long-term utility of the system. In addition, we prune the DRL model to make it more applicable to resource-constrained edge nodes. The experimental results show that the proposed algorithm has more stable performance and better adaptability to the dynamic system environment compared to the traditional centralized training. In addition, the pruning of the model compresses the size of the model to 50.4% with a 4% loss of accuracy.","PeriodicalId":422269,"journal":{"name":"2022 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132007720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-01DOI: 10.1109/SmartIoT55134.2022.00014
Reiner N. Dizon-Paradis, Oliver Ferrigno, Ishamor Reid, S. Bhunia
Light pollution, caused by indiscriminate use of artificial lighting at night, is a growing threat to astronomy, the environment, and other fields. Monitoring light pollution can help inform local communities on its impact on their environment, especially nocturnal plants and animals, such as sea turtles. However, existing systems for light pollution monitoring are expensive, non-scalable, and uni-directional, while others are inaccurate and cannot be deployed at a large scale. In this paper, we propose a modular IoT sensor platform called Pasteables with reconfigurable and easily replaceable components. We tailor this sensor platform to use many of the sensors related to monitoring light pollution. It builds upon our previous work that shares the idea of a generic modular sensing platform [1]. Unlike the previous work, we created new designs for the Components for Uniform Interface (CUI) with sensors, including light sensor, temperature/pressure sensor, and GPS. We fabricated PCB proto-types of this Pasteables platform using FR-4 material and surface mount components. Each CUI connects to the base pad using edge connectors to make the CUIs reconfigurable during installation. With these prototypes, we evaluated its responsiveness and sensitivity at two different locations of varying heights for the light source against the least expensive existing solution.
{"title":"Light Pollution Monitoring Using A Modular IoT Sensor Platform","authors":"Reiner N. Dizon-Paradis, Oliver Ferrigno, Ishamor Reid, S. Bhunia","doi":"10.1109/SmartIoT55134.2022.00014","DOIUrl":"https://doi.org/10.1109/SmartIoT55134.2022.00014","url":null,"abstract":"Light pollution, caused by indiscriminate use of artificial lighting at night, is a growing threat to astronomy, the environment, and other fields. Monitoring light pollution can help inform local communities on its impact on their environment, especially nocturnal plants and animals, such as sea turtles. However, existing systems for light pollution monitoring are expensive, non-scalable, and uni-directional, while others are inaccurate and cannot be deployed at a large scale. In this paper, we propose a modular IoT sensor platform called Pasteables with reconfigurable and easily replaceable components. We tailor this sensor platform to use many of the sensors related to monitoring light pollution. It builds upon our previous work that shares the idea of a generic modular sensing platform [1]. Unlike the previous work, we created new designs for the Components for Uniform Interface (CUI) with sensors, including light sensor, temperature/pressure sensor, and GPS. We fabricated PCB proto-types of this Pasteables platform using FR-4 material and surface mount components. Each CUI connects to the base pad using edge connectors to make the CUIs reconfigurable during installation. With these prototypes, we evaluated its responsiveness and sensitivity at two different locations of varying heights for the light source against the least expensive existing solution.","PeriodicalId":422269,"journal":{"name":"2022 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133380320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-01DOI: 10.1109/SmartIoT55134.2022.00023
Bingjie Han, Xin Chen, D. Guo, Libo Jiao
We propose an intelligent reflecting surface (IRS) enabled millimeter wave (MMW) deviceto-device (D2D) communication in the future B5G/6G scenario to improve throughput. This scheme not only maintains the high transmission rate and low transmitting power of MMW D2D communication, but it also greatly reduces the blocking probability in the presence of assisting IRS. In this paper, we build the system model of IRS-enabled MMW D2D communication and convert it into an IRS activation and selection (IAS) problem which is to find the maximize effective transmission rate through the IRS distribution, then prove that the IAS problem is an NP-hard problem. In addition, we propose an approximation solution named after IAS-A to solve IAS problem efficiently. The experimental results show that the IRS-enabled D2D MMW communication outperforms other cases in terms of throughput and blocking probability, demonstrating the superiority of IAS-A algorithm. The experiment results show that our proposed IAS-A algorithm is 16.59% and 76.17% higher than the shortest distance and random strategies with respect to the total throughput.
{"title":"Intelligent Reflecting Surface Enabled in D2D Millimeter Wave Communication","authors":"Bingjie Han, Xin Chen, D. Guo, Libo Jiao","doi":"10.1109/SmartIoT55134.2022.00023","DOIUrl":"https://doi.org/10.1109/SmartIoT55134.2022.00023","url":null,"abstract":"We propose an intelligent reflecting surface (IRS) enabled millimeter wave (MMW) deviceto-device (D2D) communication in the future B5G/6G scenario to improve throughput. This scheme not only maintains the high transmission rate and low transmitting power of MMW D2D communication, but it also greatly reduces the blocking probability in the presence of assisting IRS. In this paper, we build the system model of IRS-enabled MMW D2D communication and convert it into an IRS activation and selection (IAS) problem which is to find the maximize effective transmission rate through the IRS distribution, then prove that the IAS problem is an NP-hard problem. In addition, we propose an approximation solution named after IAS-A to solve IAS problem efficiently. The experimental results show that the IRS-enabled D2D MMW communication outperforms other cases in terms of throughput and blocking probability, demonstrating the superiority of IAS-A algorithm. The experiment results show that our proposed IAS-A algorithm is 16.59% and 76.17% higher than the shortest distance and random strategies with respect to the total throughput.","PeriodicalId":422269,"journal":{"name":"2022 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134208671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-01DOI: 10.1109/SmartIoT55134.2022.00028
Yan He, Yaqi Cheng, Weihua Liu, Xingguang Li
Many professions rely on disguised voice techniques. In contrast to the conventional linear prediction-based modification technique, we propose a disguised voice algorithm with smoothing filtering to improve the modification effect by smoothing the changed pitch period. This paper is based on linear prediction. The cepstrum method is used to obtain and change the pitch period of the speech residual signal, applying the smoothing process on the obtained pitch period, and the speech synthesis is realized using a linear prediction synthesis filter to achieve the pitch change with the same speech rate. The results show that the synthesized signal tends to be more clear and natural and the modification effect is better than no smoothing.
{"title":"An Algorithm with Smooth Filtering Based on LPC","authors":"Yan He, Yaqi Cheng, Weihua Liu, Xingguang Li","doi":"10.1109/SmartIoT55134.2022.00028","DOIUrl":"https://doi.org/10.1109/SmartIoT55134.2022.00028","url":null,"abstract":"Many professions rely on disguised voice techniques. In contrast to the conventional linear prediction-based modification technique, we propose a disguised voice algorithm with smoothing filtering to improve the modification effect by smoothing the changed pitch period. This paper is based on linear prediction. The cepstrum method is used to obtain and change the pitch period of the speech residual signal, applying the smoothing process on the obtained pitch period, and the speech synthesis is realized using a linear prediction synthesis filter to achieve the pitch change with the same speech rate. The results show that the synthesized signal tends to be more clear and natural and the modification effect is better than no smoothing.","PeriodicalId":422269,"journal":{"name":"2022 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121459510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-01DOI: 10.1109/SmartIoT55134.2022.00039
Zhitian Sun, Xin Chen, Bo Yin, Yijie Wang
Multiple Access Edge Computing (MEC) can provide efficient and low latency computing services for computing tasks generated by mobile devices. How to formulate reasonable and effective resource allocation strategy and pricing strategy to ensure the maximization of overall system utility is a very challenging problem. In order to solve this problem, a dual resource joint auction algorithm (DRJAA) is proposed in this paper. The joint allocation of communication resources and computing resources is modeled as a three-stage parallel auction process considering resource constraints and distance, and a prioritization algorithm is designed to maximize the utility of resource suppliers. Simulation results show that DRJAA algorithm is superior to other existing algorithms in convergence speed, iteration times and transaction success rate, and can effectively reduce user delay.
{"title":"Dual Resource Joint Auction Algorithm For 5G Multiple Access Edge Computing With System Utility Guarantee","authors":"Zhitian Sun, Xin Chen, Bo Yin, Yijie Wang","doi":"10.1109/SmartIoT55134.2022.00039","DOIUrl":"https://doi.org/10.1109/SmartIoT55134.2022.00039","url":null,"abstract":"Multiple Access Edge Computing (MEC) can provide efficient and low latency computing services for computing tasks generated by mobile devices. How to formulate reasonable and effective resource allocation strategy and pricing strategy to ensure the maximization of overall system utility is a very challenging problem. In order to solve this problem, a dual resource joint auction algorithm (DRJAA) is proposed in this paper. The joint allocation of communication resources and computing resources is modeled as a three-stage parallel auction process considering resource constraints and distance, and a prioritization algorithm is designed to maximize the utility of resource suppliers. Simulation results show that DRJAA algorithm is superior to other existing algorithms in convergence speed, iteration times and transaction success rate, and can effectively reduce user delay.","PeriodicalId":422269,"journal":{"name":"2022 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130380506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As quay cranes and RTGs are vital handling equipment at container terminals, their scheduling optimization would significantly affect the terminal's operation efficiency and costs. Most of the existing literature mainly studies a single quay crane, RTG dispatch, or the joint dispatch of handling equipment and horizontal transportation equipment, and rarely combines handling equipment at both ends for research. This paper breaks through the traditional scheduling mode of quay cranes or RTGs and takes the integrated and coordinated scheduling of quay cranes and RTGs as the research object. The objective is to minimize the operating cost, waiting for time penalty cost of container trucks, and re-stow cost, establish a comprehensive scheduling optimization mathematical model. Firstly, according to the features of the optimization model, this paper will use GA (Genetic algorithm) method to calculate withMATLAB2018b designing its program. Additionally, data collecting is based on the survey of actual operations in the terminal. Lastly, all data analysis will be under the computer experiment, compared to the actual operations data to identify the operating cost of the collaborative scheduling model is greatly reduced, the feasibility of the optimization model, and the reliability of its algorithm.
{"title":"Co-Scheduling of Quay Cranes and RTGs in the Container Terminal","authors":"L. Chu, Dong Liang, Yupei Zhou, Xiaowei Xu, Yiming Zhang, Zhiying Ruan, Huanbin Xiao, Shiping Zuo","doi":"10.1109/SmartIoT55134.2022.00027","DOIUrl":"https://doi.org/10.1109/SmartIoT55134.2022.00027","url":null,"abstract":"As quay cranes and RTGs are vital handling equipment at container terminals, their scheduling optimization would significantly affect the terminal's operation efficiency and costs. Most of the existing literature mainly studies a single quay crane, RTG dispatch, or the joint dispatch of handling equipment and horizontal transportation equipment, and rarely combines handling equipment at both ends for research. This paper breaks through the traditional scheduling mode of quay cranes or RTGs and takes the integrated and coordinated scheduling of quay cranes and RTGs as the research object. The objective is to minimize the operating cost, waiting for time penalty cost of container trucks, and re-stow cost, establish a comprehensive scheduling optimization mathematical model. Firstly, according to the features of the optimization model, this paper will use GA (Genetic algorithm) method to calculate withMATLAB2018b designing its program. Additionally, data collecting is based on the survey of actual operations in the terminal. Lastly, all data analysis will be under the computer experiment, compared to the actual operations data to identify the operating cost of the collaborative scheduling model is greatly reduced, the feasibility of the optimization model, and the reliability of its algorithm.","PeriodicalId":422269,"journal":{"name":"2022 IEEE International Conference on Smart Internet of Things (SmartIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131927956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：