Pub Date : 2015-03-30DOI: 10.1109/MobileCloud.2015.24
Yuuki Wakisaka, H. Ichikawa, Yuusuke Kawakita
Rich participatory sensing applications by smart phones are demonstrating the possibility of useful applications with numerous stationary sensors as well as with smart phones. Electricity consumption of stationary sensors seriously affects their usability and maintenance cost so that many mutually incompatible wireless devices and protocols have been developed for each those different conditions. It is desirable for devices with any different protocol to share the network infrastructure, preserve sensing data, and jointly utilize the data. We proposed an "Appliance-defined ubiquitous network"' (ADUN) that, based on user demands, can distribute sampled RF data streams over the Internet to software-defined radio receivers in cloud data centers. One of the goals of ADUN is to allow users to be able to seek information regarding the radio space of any bandwidth, frequency, place, time, and date. An RF recorder is necessary to distribute past RF data, and should be able to record as broad an RF data stream for as long as needed. In this paper, we detail the basic concepts of RF recorder for ADUN and the results of a study that applies the Btrfs function in Linux to compress and store RF data to distribute or mine an RF signal through time-shifting. The experimental results indicate that the pipeline parallelism of Linux increases the storage writing throughput of high-bitrate RF data streams with some degree of redundancy, though the loss in computation power for RF data compression slows down the storage writing. The RF data compression rate is calculated by the size of the RF data, the chunk size in chunking, and variance in the radio space information according to the number of signals to be received.
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Pub Date : 2015-03-30DOI: 10.1109/MobileCloud.2015.11
A. Ellouze, M. Gagnaire, A. Haddad
In mobile cloud computing, offloading mobile applications to close remote servers appears as a straightforward solution to overcome mobile terminals processor and battery limitations. Remote execution leverages the high computation capacity of the server to enrich user experience and extend battery autonomy through energy savings. However, application offloading is energy efficient only under various conditions. For that purpose, we propose an original algorithm called MAO(Mobile Application's Offloading) triggered by two conditions: The current CPU load and State of Charge (SoC) of the battery.On the basis of various traffic scenarios mixing interactive and delay tolerant mobile applications, we study through numerical simulations the efficiency of the MAO algorithm and assess its performance in terms of rejected jobs and the amount of energy savings achieved. Rejected jobs are those unable to meet user quality of experience (QoE) and/or energy efficiency requirements. Evaluations on simulated workloads show that both traffic loads and user's radio mobile environment have direct impact on the efficiency of the MAO algorithm.
{"title":"A Mobile Application Offloading Algorithm for Mobile Cloud Computing","authors":"A. Ellouze, M. Gagnaire, A. Haddad","doi":"10.1109/MobileCloud.2015.11","DOIUrl":"https://doi.org/10.1109/MobileCloud.2015.11","url":null,"abstract":"In mobile cloud computing, offloading mobile applications to close remote servers appears as a straightforward solution to overcome mobile terminals processor and battery limitations. Remote execution leverages the high computation capacity of the server to enrich user experience and extend battery autonomy through energy savings. However, application offloading is energy efficient only under various conditions. For that purpose, we propose an original algorithm called MAO(Mobile Application's Offloading) triggered by two conditions: The current CPU load and State of Charge (SoC) of the battery.On the basis of various traffic scenarios mixing interactive and delay tolerant mobile applications, we study through numerical simulations the efficiency of the MAO algorithm and assess its performance in terms of rejected jobs and the amount of energy savings achieved. Rejected jobs are those unable to meet user quality of experience (QoE) and/or energy efficiency requirements. Evaluations on simulated workloads show that both traffic loads and user's radio mobile environment have direct impact on the efficiency of the MAO algorithm.","PeriodicalId":373443,"journal":{"name":"2015 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering","volume":"104 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116521112","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 : 2015-03-01DOI: 10.1109/MobileCloud.2015.22
C. Borcea, Xiaoning Ding, N. Gehani, Reza Curtmola, Mohammad A. Khan, Hillol Debnath
Avatar is a system that leverages cloud resources to support fast, scalable, reliable, and energy efficient distributed computing over mobile devices. An avatar is a per-user software entity in the cloud that runs apps on behalf of the user's mobile devices. The avatars are instantiated as virtual machines in the cloud that run the same operating system with the mobile devices. In this way, avatars provide resource isolation and execute unmodified app components, which simplifies technology adoption. Avatar apps execute over distributed and synchronized (mobile device, avatar) pairs to achieve a global goal. The three main challenges that must be overcome by the Avatar system are: creating a high-level programming model and a middleware that enable effective execution of distributed applications on a combination of mobile devices and avatars, re-designing the cloud architecture and protocols to support billions of mobile users and mobile apps with very different characteristics from the current cloud workloads, and explore new approaches that balance privacy guarantees with app efficiency/usability. We have built a basic Avatar prototype on Android devices and Android x86 virtual machines. An application that searches for a lost child by analyzing the photos taken by people at a crowded public event runs on top of this prototype.
{"title":"Avatar: Mobile Distributed Computing in the Cloud","authors":"C. Borcea, Xiaoning Ding, N. Gehani, Reza Curtmola, Mohammad A. Khan, Hillol Debnath","doi":"10.1109/MobileCloud.2015.22","DOIUrl":"https://doi.org/10.1109/MobileCloud.2015.22","url":null,"abstract":"Avatar is a system that leverages cloud resources to support fast, scalable, reliable, and energy efficient distributed computing over mobile devices. An avatar is a per-user software entity in the cloud that runs apps on behalf of the user's mobile devices. The avatars are instantiated as virtual machines in the cloud that run the same operating system with the mobile devices. In this way, avatars provide resource isolation and execute unmodified app components, which simplifies technology adoption. Avatar apps execute over distributed and synchronized (mobile device, avatar) pairs to achieve a global goal. The three main challenges that must be overcome by the Avatar system are: creating a high-level programming model and a middleware that enable effective execution of distributed applications on a combination of mobile devices and avatars, re-designing the cloud architecture and protocols to support billions of mobile users and mobile apps with very different characteristics from the current cloud workloads, and explore new approaches that balance privacy guarantees with app efficiency/usability. We have built a basic Avatar prototype on Android devices and Android x86 virtual machines. An application that searches for a lost child by analyzing the photos taken by people at a crowded public event runs on top of this prototype.","PeriodicalId":373443,"journal":{"name":"2015 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121772187","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 : 2015-03-01DOI: 10.1109/MOBILECLOUD.2015.4
S. Hiroyuki, Dijiang Huang, Axel Küpper
{"title":"Welcome Message from the IEEE MobileCloud 2015 General Chairs","authors":"S. Hiroyuki, Dijiang Huang, Axel Küpper","doi":"10.1109/MOBILECLOUD.2015.4","DOIUrl":"https://doi.org/10.1109/MOBILECLOUD.2015.4","url":null,"abstract":"","PeriodicalId":373443,"journal":{"name":"2015 3rd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122051785","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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