The preferred channel for listening to music is shifting towards the Internet and especially to mobile networks. Here, the overall traffic is predicted to grow by 45% annually till 2021. However, the resulting increase in network traffic challenges mobile operators. As a result, methods are researched to decrease costly transit traffic and the traffic load inside operator networks using in-network and client-side caching. Additionally to traditional reactive caching, recent works show that proactive caching increases cache efficiency. Thus, in this work, a mobile network using proactive caching is assumed. As music represents the most popular content category on YouTube, this work focuses on studying the potential of proactively caching content of this particular category using a YouTube trace containing over 4 million music video user sessions. The contribution of this work is threefold: First, music content-specific user behavior is derived and audio features of the content are analyzed. Second, using these audio features, genre and mood classifiers are compared in order to guide the design of new proactive caching policies. Third, a novel trace-based evaluation methodology for music-specific proactive in-network caching is proposed and used to evaluate novel proactive caching policies to serve either an aggregate of users or individual clients.
{"title":"Proactive Caching of Music Videos based on Audio Features, Mood, and Genre","authors":"Christian Koch, Ganna Krupii, D. Hausheer","doi":"10.1145/3083187.3083197","DOIUrl":"https://doi.org/10.1145/3083187.3083197","url":null,"abstract":"The preferred channel for listening to music is shifting towards the Internet and especially to mobile networks. Here, the overall traffic is predicted to grow by 45% annually till 2021. However, the resulting increase in network traffic challenges mobile operators. As a result, methods are researched to decrease costly transit traffic and the traffic load inside operator networks using in-network and client-side caching. Additionally to traditional reactive caching, recent works show that proactive caching increases cache efficiency. Thus, in this work, a mobile network using proactive caching is assumed. As music represents the most popular content category on YouTube, this work focuses on studying the potential of proactively caching content of this particular category using a YouTube trace containing over 4 million music video user sessions. The contribution of this work is threefold: First, music content-specific user behavior is derived and audio features of the content are analyzed. Second, using these audio features, genre and mood classifiers are compared in order to guide the design of new proactive caching policies. Third, a novel trace-based evaluation methodology for music-specific proactive in-network caching is proposed and used to evaluate novel proactive caching policies to serve either an aggregate of users or individual clients.","PeriodicalId":123321,"journal":{"name":"Proceedings of the 8th ACM on Multimedia Systems Conference","volume":"23 3-4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114019406","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}
Mohammad Hosseini, Yu Jiang, Ali Yekkehkhany, R. E. Berlin, L. Sha
Use of telecommunication technologies for remote, continuous monitoring of patients can enhance effectiveness of emergency ambulance care during transport from rural areas to a regional center hospital. However, the communication along the various routes in rural areas may have wide bandwidth ranges from 2G to 4G; some regions may have only lower satellite bandwidth available. Bandwidth fluctuation together with real-time communication of various clinical multimedia pose a major challenge during rural patient ambulance transport.; AB@The availability of a pre-transport route-dependent communication bandwidth database is an important resource in remote monitoring and clinical multimedia transmission in rural ambulance transport. Here, we present a geo-communication dataset from extensive profiling of 4 major US mobile carriers in Illinois, from the rural location of Hoopeston to the central referral hospital center at Urbana. In collaboration with Carle Foundation Hospital, we developed a profiler, and collected various geographical and communication traces for realistic emergency rural ambulance transport scenarios. Our dataset is to support our ongoing work of proposing "physiology-aware DASH", which is particularly useful for adaptive remote monitoring of critically ill patients in emergency rural ambulance transport. It provides insights on ensuring higher Quality of Service (QoS) for most critical clinical multimedia in response to changes in patients' physiological states and bandwidth conditions. Our dataset is available online1 for research community.
{"title":"A Mobile Geo-Communication Dataset for Physiology-Aware DASH in Rural Ambulance Transport","authors":"Mohammad Hosseini, Yu Jiang, Ali Yekkehkhany, R. E. Berlin, L. Sha","doi":"10.1145/3083187.3083211","DOIUrl":"https://doi.org/10.1145/3083187.3083211","url":null,"abstract":"Use of telecommunication technologies for remote, continuous monitoring of patients can enhance effectiveness of emergency ambulance care during transport from rural areas to a regional center hospital. However, the communication along the various routes in rural areas may have wide bandwidth ranges from 2G to 4G; some regions may have only lower satellite bandwidth available. Bandwidth fluctuation together with real-time communication of various clinical multimedia pose a major challenge during rural patient ambulance transport.; AB@The availability of a pre-transport route-dependent communication bandwidth database is an important resource in remote monitoring and clinical multimedia transmission in rural ambulance transport. Here, we present a geo-communication dataset from extensive profiling of 4 major US mobile carriers in Illinois, from the rural location of Hoopeston to the central referral hospital center at Urbana. In collaboration with Carle Foundation Hospital, we developed a profiler, and collected various geographical and communication traces for realistic emergency rural ambulance transport scenarios. Our dataset is to support our ongoing work of proposing \"physiology-aware DASH\", which is particularly useful for adaptive remote monitoring of critically ill patients in emergency rural ambulance transport. It provides insights on ensuring higher Quality of Service (QoS) for most critical clinical multimedia in response to changes in patients' physiological states and bandwidth conditions. Our dataset is available online1 for research community.","PeriodicalId":123321,"journal":{"name":"Proceedings of the 8th ACM on Multimedia Systems Conference","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116837185","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}
{"title":"Proceedings of the 8th ACM on Multimedia Systems Conference","authors":"","doi":"10.1145/3083187","DOIUrl":"https://doi.org/10.1145/3083187","url":null,"abstract":"","PeriodicalId":123321,"journal":{"name":"Proceedings of the 8th ACM on Multimedia Systems Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130990467","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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