Pub Date : 2020-01-29DOI: 10.13052/jmm1550-4646.1521
S. Jadhav
The Internet of Things (IoT) is becoming the most relevant next Internet-related revolution in the world of Technology. It permits millions of devices to be connected and communicate with each other. Beside ensuring reliable connectivity their security is also a great challenge. Abounding IoT devices have a minimum of storage and processing capacity and they usually need to be able to operate on limited power consumption. Security paths that depend maximum on encryption are not good for these resource constrained devices, because they are not suited for performing complicated encryption and decryption tasks quickly to be able to transmit data securely in real-time. This paper contains an overview of some of the cryptographic-based schemes related to communication and computational costs for resource constrained devices and considers some approaches towards the development of highly secure and lightweight security mechanisms for IoT devices.
{"title":"Towards Light Weight Cryptography Schemes for Resource Constraint Devices in IoT","authors":"S. Jadhav","doi":"10.13052/jmm1550-4646.1521","DOIUrl":"https://doi.org/10.13052/jmm1550-4646.1521","url":null,"abstract":"The Internet of Things (IoT) is becoming the most relevant next Internet-related revolution in the world of Technology. It permits millions of devices to be connected and communicate with each other. Beside ensuring reliable connectivity their security is also a great challenge. Abounding IoT devices have a minimum of storage and processing capacity and they usually need to be able to operate on limited power consumption. Security paths that depend maximum on encryption are not good for these resource constrained devices, because they are not suited for performing complicated encryption and decryption tasks quickly to be able to transmit data securely in real-time. This paper contains an overview of some of the cryptographic-based schemes related to communication and computational costs for resource constrained devices and considers some approaches towards the development of highly secure and lightweight security mechanisms for IoT devices.","PeriodicalId":38898,"journal":{"name":"Journal of Mobile Multimedia","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45864752","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 : 2019-08-06DOI: 10.13052/1550-4646.15124
Yuexia Zhang, Ziyang Chen
Studying community discovery algorithms for complex networks is necessary to determine the origin of opinions, analyze the mechanisms of public opinion transmission, and control the evolution of public opinion. The problem of the existing clustering algorithm of the central node having a low quality of community detection must also be solved. This study proposes a community detection method based on the two-layer dissimilarity of the central node (TDCN-CD). First, the algorithm selects the central node through the degree and distance of the node. Selecting nodes in the same community as the central node at the same time is avoided. Simultaneously, the algorithm proposes the dissimilarity index of nodes based on two layers, which can deeply explore the heterogeneity of nodes and achieve the effect of accurate community division. The results of using Karate and Dolphins datasets for simulation show that compared to the Girvan–Newman and Fast–Newman classical community partitioning algorithms, the TDCN-CD algorithm can effectively detect the community structure and more accurately divide the community.
{"title":"Community Detection Method Based on Two-layer Dissimilarity of Central Node","authors":"Yuexia Zhang, Ziyang Chen","doi":"10.13052/1550-4646.15124","DOIUrl":"https://doi.org/10.13052/1550-4646.15124","url":null,"abstract":"Studying community discovery algorithms for complex networks is necessary to determine the origin of opinions, analyze the mechanisms of public opinion transmission, and control the evolution of public opinion. The problem of the existing clustering algorithm of the central node having a low quality of community detection must also be solved. This study proposes a community detection method based on the two-layer dissimilarity of the central node (TDCN-CD). First, the algorithm selects the central node through the degree and distance of the node. Selecting nodes in the same community as the central node at the same time is avoided. Simultaneously, the algorithm proposes the dissimilarity index of nodes based on two layers, which can deeply explore the heterogeneity of nodes and achieve the effect of accurate community division. The results of using Karate and Dolphins datasets for simulation show that compared to the Girvan–Newman and Fast–Newman classical community partitioning algorithms, the TDCN-CD algorithm can effectively detect the community structure and more accurately divide the community. \u0000 ","PeriodicalId":38898,"journal":{"name":"Journal of Mobile Multimedia","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47797776","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 : 2019-06-06DOI: 10.13052/1550-4646.15122
Qian Huang, Kyle Kieffer
One of the world’s largest sources of energy dissipation is heating, ventilation, and air conditioning (HVAC), which accounts for 40% of total electricity use in the United States. The main challenge of current HVAC systems is that their operation is determined by a set of predefined setpoints regardless of the actual building occupancy status. This is wasteful, especially when no or fewer people occupy buildings, while these HVAC systems deliver more than enough fresh air. Occupancy-driven HVAC control is a promising strategy to improve the efficiency of HVAC systems. In this paper, we will address the next-generation sensor hardware design and explore new system architectures. We systematically investigate, design, and implement a lowcost, hybrid smart sensor platform for accurate occupancy counting towards energy-efficient buildings. Specifically, the proposed hardware architecture is wisely divided into two modules: main and gate monitoring modules. Five heterogeneous sensors are integrated into this architecture to collect richer building environmental parameters, including temperature, humidity. CO2, acoustic, and infrared signals. These sensor signals can be fused and analyzed for cross-correlation to increase the accuracy of building occupancy counting. The proposed systems have been implemented in breadboards and PCB boards. Experimental measurements have validated system functionality and performance.
{"title":"An Intelligent Internet of Things (IoT) Sensor System for Building Environmental Monitoring","authors":"Qian Huang, Kyle Kieffer","doi":"10.13052/1550-4646.15122","DOIUrl":"https://doi.org/10.13052/1550-4646.15122","url":null,"abstract":"One of the world’s largest sources of energy dissipation is heating, ventilation, and air conditioning (HVAC), which accounts for 40% of total electricity use in the United States. The main challenge of current HVAC systems is that their operation is determined by a set of predefined setpoints regardless of the actual building occupancy status. This is wasteful, especially when no or fewer people occupy buildings, while these HVAC systems deliver more than enough fresh air. Occupancy-driven HVAC control is a promising strategy to improve the efficiency of HVAC systems. In this paper, we will address the next-generation sensor hardware design and explore new system architectures. We systematically investigate, design, and implement a lowcost, hybrid smart sensor platform for accurate occupancy counting towards energy-efficient buildings. Specifically, the proposed hardware architecture is wisely divided into two modules: main and gate monitoring modules. Five heterogeneous sensors are integrated into this architecture to collect richer building environmental parameters, including temperature, humidity. CO2, acoustic, and infrared signals. These sensor signals can be fused and analyzed for cross-correlation to increase the accuracy of building occupancy counting. The proposed systems have been implemented in breadboards and PCB boards. Experimental measurements have validated system functionality and performance. \u0000 ","PeriodicalId":38898,"journal":{"name":"Journal of Mobile Multimedia","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46483022","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}
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