Wearable devices have become popular and innovative and are converging with technologies such as big data, Cloud and Internet of Things (IoT). Traditional physiological sensors in fitness tracking and mHealth provide health data periodically or are captured manually when required. In future, physicians as well as IoT devices will benefit from this data to provide their services. These situations can cause rapid battery consumption, consume significant bandwidth, and raise privacy issues. There have been many attempts to extend battery life and improve communication methodologies; however, they have not been able to solve the resource constraints arising from physical hardware limits, such as the size of sensors. As an alternative, this paper presents a novel approach and solution to controlling body sensors to reduce both unnecessary data transmission and battery consumption. This can be done by implementing an inference system on sensors using sensed data to transfer it efficiently to other networks without burdening the workload from IoT onto sensor devices. In this paper, we experimented with reducing the bandwidth requirements for heart-rate sensors. Our results show savings in resource usage of between 66% and 99%. Such savings have the potential of making always-on mHealth devices a practical reality.
{"title":"Inference System of Body Sensors for Health and Internet of Things Networks","authors":"James Jin Kang, T. Luan, Henry Larkin","doi":"10.1145/3007120.3007145","DOIUrl":"https://doi.org/10.1145/3007120.3007145","url":null,"abstract":"Wearable devices have become popular and innovative and are converging with technologies such as big data, Cloud and Internet of Things (IoT). Traditional physiological sensors in fitness tracking and mHealth provide health data periodically or are captured manually when required. In future, physicians as well as IoT devices will benefit from this data to provide their services. These situations can cause rapid battery consumption, consume significant bandwidth, and raise privacy issues. There have been many attempts to extend battery life and improve communication methodologies; however, they have not been able to solve the resource constraints arising from physical hardware limits, such as the size of sensors. As an alternative, this paper presents a novel approach and solution to controlling body sensors to reduce both unnecessary data transmission and battery consumption. This can be done by implementing an inference system on sensors using sensed data to transfer it efficiently to other networks without burdening the workload from IoT onto sensor devices. In this paper, we experimented with reducing the bandwidth requirements for heart-rate sensors. Our results show savings in resource usage of between 66% and 99%. Such savings have the potential of making always-on mHealth devices a practical reality.","PeriodicalId":394387,"journal":{"name":"Proceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126722198","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}
In this work, we propose an energy efficient scheme for application ordering and execution on modern smartphone processors. We propose to improve the branch prediction piece present inside pipelined processors, by suitable clustering and scheduling of applications that exhibit similar control flow. We expect that these applications can benefit by sharing predictor table data structures, that can do away with table initializations and predictions every time an application context switch is encountered. Preliminary experiments show promising results, and we believe this proposal will open up several interesting avenues of research.
{"title":"Improving Energy Efficiency of Mobile Execution Exploiting Similarity of Application Control Flow","authors":"Moumita Das, A. Banerjee","doi":"10.1145/3007120.3011075","DOIUrl":"https://doi.org/10.1145/3007120.3011075","url":null,"abstract":"In this work, we propose an energy efficient scheme for application ordering and execution on modern smartphone processors. We propose to improve the branch prediction piece present inside pipelined processors, by suitable clustering and scheduling of applications that exhibit similar control flow. We expect that these applications can benefit by sharing predictor table data structures, that can do away with table initializations and predictions every time an application context switch is encountered. Preliminary experiments show promising results, and we believe this proposal will open up several interesting avenues of research.","PeriodicalId":394387,"journal":{"name":"Proceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126621226","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}
In this paper, we propose a digital cash system named Blockchain-LI. This is an activity-based micro-pricing system implemented on cryptocurrency technologies. Activity-based micro-pricing is a pervasive technology to influence people's behavior through economic incentives. Implementing activity-based micro-pricing based on cryptocurrency technologies enables us to solve potential technical issues of traditional implementation. The Blockchain-LI architecture adopts a hierarchical currency network containing two types of currencies. The public coin is widely prevalent and has high integrity. The private coins are low integrity digital currencies that connect to the public coin. This approach enables us to solve cryptocurrency problems including scalability and block size. However, to use Blockchain-LI as a social infrastructure system, unresolved problems remain. This paper proposes sustainability, conversion protocols, and security issues as topics for future study.
{"title":"Blockchain-LI: A Study on Implementing Activity-Based Micro-Pricing using Cryptocurrency Technologies","authors":"Yuki Yamada, T. Nakajima, Mizuki Sakamoto","doi":"10.1145/3007120.3007151","DOIUrl":"https://doi.org/10.1145/3007120.3007151","url":null,"abstract":"In this paper, we propose a digital cash system named Blockchain-LI. This is an activity-based micro-pricing system implemented on cryptocurrency technologies. Activity-based micro-pricing is a pervasive technology to influence people's behavior through economic incentives. Implementing activity-based micro-pricing based on cryptocurrency technologies enables us to solve potential technical issues of traditional implementation. The Blockchain-LI architecture adopts a hierarchical currency network containing two types of currencies. The public coin is widely prevalent and has high integrity. The private coins are low integrity digital currencies that connect to the public coin. This approach enables us to solve cryptocurrency problems including scalability and block size. However, to use Blockchain-LI as a social infrastructure system, unresolved problems remain. This paper proposes sustainability, conversion protocols, and security issues as topics for future study.","PeriodicalId":394387,"journal":{"name":"Proceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116810592","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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