You Lu, Biao Zhou, L. Tung, M. Gerla, Ashwin Ramesh, Lohith Nagaraja
Mobile cloud computing (MCC) has recently been drawing increased attention in academia as well as industry. Content retrieval is a critical service, for many mobile cloud applications and in turns relies on other resources and tools, e.g., internal storage, content searching and sharing, etc. Previous studies have shown that conventional ICN interest query schemes and content searching architectures, if not properly designed, can cause significant performance degradation and energy consumption, especially for large scale MANETs. In this paper, we specifically address the scalability and energy efficiency of the content retrieval scheme in mobile cloud computing. We propose a direction-selective forwarding scheme for the content query method that decreases traffic overhead and energy cost caused by duplicate copies of the query packets. We also advocate the parallel search method of multiple caches to increase the hit rate. Simulation experiments show that the proposed scheme yields significant improvements in efficiency and scalability for the content retrieval in large scale MANETs.
{"title":"Energy-efficient content retrieval in mobile cloud","authors":"You Lu, Biao Zhou, L. Tung, M. Gerla, Ashwin Ramesh, Lohith Nagaraja","doi":"10.1145/2491266.2491271","DOIUrl":"https://doi.org/10.1145/2491266.2491271","url":null,"abstract":"Mobile cloud computing (MCC) has recently been drawing increased attention in academia as well as industry. Content retrieval is a critical service, for many mobile cloud applications and in turns relies on other resources and tools, e.g., internal storage, content searching and sharing, etc. Previous studies have shown that conventional ICN interest query schemes and content searching architectures, if not properly designed, can cause significant performance degradation and energy consumption, especially for large scale MANETs.\u0000 In this paper, we specifically address the scalability and energy efficiency of the content retrieval scheme in mobile cloud computing. We propose a direction-selective forwarding scheme for the content query method that decreases traffic overhead and energy cost caused by duplicate copies of the query packets. We also advocate the parallel search method of multiple caches to increase the hit rate. Simulation experiments show that the proposed scheme yields significant improvements in efficiency and scalability for the content retrieval in large scale MANETs.","PeriodicalId":237435,"journal":{"name":"MCC '13","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125779987","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 we embrace new technologies and services like smartphones and cloud services, we also need to understand various "security pitfalls". In this talk, I will go over the background on Android smartphones, some of the security issues and also, how malware writers can take advantages of the platform to launch new and stealthy mobile attacks.
{"title":"A peek into smartphones, cloud services and their security","authors":"John C.S. Lui","doi":"10.1145/2491266.2491278","DOIUrl":"https://doi.org/10.1145/2491266.2491278","url":null,"abstract":"As we embrace new technologies and services like smartphones and cloud services, we also need to understand various \"security pitfalls\". In this talk, I will go over the background on Android smartphones, some of the security issues and also, how malware writers can take advantages of the platform to launch new and stealthy mobile attacks.","PeriodicalId":237435,"journal":{"name":"MCC '13","volume":"29 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134398182","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}
The increase in the size of mobile cloud as well as the volume of information necessitates efficient search mechanisms for finding the searched information or the target node. In this paper, we focus on search mechanisms to retrieve information from within a mobile cloud in which nodes have intermittent connectivity and hence operate on a store-carry-forward manner. We design an opportunistic search scheme in which the searching node spreads a limited number of replicas of the query to the nodes it meets and these nodes, so called seekers, perform the search on behalf of the searching node. We assume that nodes are grouped into communities based on their interest profiles, and seekers use this community information to forward the data and the query to the right community - the community that is more likely to store the searched content. Since people store and search for similar information in the scope of their interest, the nodes in the same community as the searching node have higher probability to store the searched content. We model this seeker-assisted search scheme as a continuous time Markov process and analyze its performance under various inter-community/intra-community meeting rate, number of replicas, and network population. Our analysis shows that seeker-assisted search achieves a good balance between the search response time and search cost compared to the two extremes of epidemic search and direct delivery search.
{"title":"Seeker-assisted information search in mobile clouds","authors":"S. Bayhan, Esa Hyytiä, J. Kangasharju, J. Ott","doi":"10.1145/2491266.2491269","DOIUrl":"https://doi.org/10.1145/2491266.2491269","url":null,"abstract":"The increase in the size of mobile cloud as well as the volume of information necessitates efficient search mechanisms for finding the searched information or the target node. In this paper, we focus on search mechanisms to retrieve information from within a mobile cloud in which nodes have intermittent connectivity and hence operate on a store-carry-forward manner. We design an opportunistic search scheme in which the searching node spreads a limited number of replicas of the query to the nodes it meets and these nodes, so called seekers, perform the search on behalf of the searching node. We assume that nodes are grouped into communities based on their interest profiles, and seekers use this community information to forward the data and the query to the right community - the community that is more likely to store the searched content. Since people store and search for similar information in the scope of their interest, the nodes in the same community as the searching node have higher probability to store the searched content. We model this seeker-assisted search scheme as a continuous time Markov process and analyze its performance under various inter-community/intra-community meeting rate, number of replicas, and network population. Our analysis shows that seeker-assisted search achieves a good balance between the search response time and search cost compared to the two extremes of epidemic search and direct delivery search.","PeriodicalId":237435,"journal":{"name":"MCC '13","volume":"168 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123185824","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}
Mobile Web page loads are notoriously slow due to limited computing power and slow network access. Our preliminary experiments show that computation is a significant fraction of page load time on mobile devices. Also, energy arguments suggest that it will stay this way. To compensate the limited computing power, our position is that offloading portions of the page load process to the cloud can significantly improve mobile page load time. We propose a measurement-based framework that allows to offload portions of mobile page load process to the cloud. Unlike browsers that offload fixed parts of page loads such as Opera Mini, our framework will allow to offload any portion of the page load process. We will experiment with a large variety of real-world situations (e.g., varying computing power on mobile devices) by offloading varying portions of page loads using our framework. Informed by the experimental results, we will develop a mobile browser that considers the diverse situations as well as energy and data usage.
{"title":"Accelerating the mobile web with selective offloading","authors":"Xiao Sophia Wang, Haichen Shen, D. Wetherall","doi":"10.1145/2491266.2491275","DOIUrl":"https://doi.org/10.1145/2491266.2491275","url":null,"abstract":"Mobile Web page loads are notoriously slow due to limited computing power and slow network access. Our preliminary experiments show that computation is a significant fraction of page load time on mobile devices. Also, energy arguments suggest that it will stay this way. To compensate the limited computing power, our position is that offloading portions of the page load process to the cloud can significantly improve mobile page load time. We propose a measurement-based framework that allows to offload portions of mobile page load process to the cloud. Unlike browsers that offload fixed parts of page loads such as Opera Mini, our framework will allow to offload any portion of the page load process. We will experiment with a large variety of real-world situations (e.g., varying computing power on mobile devices) by offloading varying portions of page loads using our framework. Informed by the experimental results, we will develop a mobile browser that considers the diverse situations as well as energy and data usage.","PeriodicalId":237435,"journal":{"name":"MCC '13","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116379487","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}
Abderrahmen Mtibaa, A. Fahim, Khaled A. Harras, M. Ammar
Despite the increased capabilities of mobile devices, mobile application resource requirements can often transcend what can be accomplished on a single device. This has been addressed through several proposals for efficient computation offloading from mobile devices to remote cloud resources or closely located computing resources known as cloudlets. In this paper we consider an environment in which computational offloading is performed among a set of mobile devices. We call this environment a Mobile Device Cloud (MDC). We are interested in MDCs where nodes are {em highly collaborative}. We develop computational offloading schemes that {em maximize the lifetime} of the ensemble of mobile devices where we consider the network to be alive as long as no device has depleted its battery. As a secondary contribution in this work, we develop and use an experimentation platform that allows us to evaluate a range of computational models and profiles derived from a realistic testbed. We use this platform as a first step in an evaluation exercise that demonstrates the effectiveness of our computation offloading algorithms in extending the lifetime of an MDC.
{"title":"Towards resource sharing in mobile device clouds: power balancing across mobile devices","authors":"Abderrahmen Mtibaa, A. Fahim, Khaled A. Harras, M. Ammar","doi":"10.1145/2491266.2491276","DOIUrl":"https://doi.org/10.1145/2491266.2491276","url":null,"abstract":"Despite the increased capabilities of mobile devices, mobile application resource requirements can often transcend what can be accomplished on a single device. This has been addressed through several proposals for efficient computation offloading from mobile devices to remote cloud resources or closely located computing resources known as cloudlets. In this paper we consider an environment in which computational offloading is performed among a set of mobile devices. We call this environment a Mobile Device Cloud (MDC). We are interested in MDCs where nodes are {em highly collaborative}. We develop computational offloading schemes that {em maximize the lifetime} of the ensemble of mobile devices where we consider the network to be alive as long as no device has depleted its battery. As a secondary contribution in this work, we develop and use an experimentation platform that allows us to evaluate a range of computational models and profiles derived from a realistic testbed. We use this platform as a first step in an evaluation exercise that demonstrates the effectiveness of our computation offloading algorithms in extending the lifetime of an MDC.","PeriodicalId":237435,"journal":{"name":"MCC '13","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132656683","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}
Mobile Cloud Computing (MCC) enables smartphones to offload compute-intensive codes and data to clouds or cloudlets for energy conservation. Thus, MCC liberates smartphones from battery shortage and embraces more versatile mobile applications. Most pioneering MCC research work requires a consistent network performance for offloading. However, such consistency is challenged by frequent mobile user movements and unstable network quality, thereby resulting in a suboptimal offloading decision. To embrace network inconsistency, we propose ENDA, a three-tier architecture that leverages user track prediction, realtime network performance and server loads to optimize offloading decisions. On cloud tier, we first design a greedy searching algorithm to predict user track using historical user traces stored in database servers. We then design a cloud-enabled Wi-Fi access point (AP) selection scheme to find the most energy efficient AP for smartphone offloading. We evaluate the performance of ENDA through simulations under a real-world scenario. The results demonstrate that ENDA can generate offloading decisions with optimized energy efficiency, desirable response time, and potential adaptability to a variety of scenarios. ENDA outperforms existing offloading techniques that do not consider user mobility and server workload balance management.
{"title":"ENDA: embracing network inconsistency for dynamic application offloading in mobile cloud computing","authors":"Jiwei Li, Kai Bu, Xuan Liu, Bin Xiao","doi":"10.1145/2491266.2491274","DOIUrl":"https://doi.org/10.1145/2491266.2491274","url":null,"abstract":"Mobile Cloud Computing (MCC) enables smartphones to offload compute-intensive codes and data to clouds or cloudlets for energy conservation. Thus, MCC liberates smartphones from battery shortage and embraces more versatile mobile applications. Most pioneering MCC research work requires a consistent network performance for offloading. However, such consistency is challenged by frequent mobile user movements and unstable network quality, thereby resulting in a suboptimal offloading decision. To embrace network inconsistency, we propose ENDA, a three-tier architecture that leverages user track prediction, realtime network performance and server loads to optimize offloading decisions. On cloud tier, we first design a greedy searching algorithm to predict user track using historical user traces stored in database servers. We then design a cloud-enabled Wi-Fi access point (AP) selection scheme to find the most energy efficient AP for smartphone offloading. We evaluate the performance of ENDA through simulations under a real-world scenario. The results demonstrate that ENDA can generate offloading decisions with optimized energy efficiency, desirable response time, and potential adaptability to a variety of scenarios. ENDA outperforms existing offloading techniques that do not consider user mobility and server workload balance management.","PeriodicalId":237435,"journal":{"name":"MCC '13","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128693912","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}
Kirak Hong, D. Lillethun, U. Ramachandran, Beate Ottenwälder, B. Koldehofe
The ubiquitous deployment of mobile and sensor devices is creating a new environment, namely the Internet of Things(IoT), that enables a wide range of future Internet applications. In this work, we present Mobile Fog, a high level programming model for the future Internet applications that are geospatially distributed, large-scale, and latency-sensitive. We analyze use cases for the programming model with camera network and connected vehicle applications to show the efficacy of Mobile Fog. We also evaluate application performance through simulation.
{"title":"Mobile fog: a programming model for large-scale applications on the internet of things","authors":"Kirak Hong, D. Lillethun, U. Ramachandran, Beate Ottenwälder, B. Koldehofe","doi":"10.1145/2491266.2491270","DOIUrl":"https://doi.org/10.1145/2491266.2491270","url":null,"abstract":"The ubiquitous deployment of mobile and sensor devices is creating a new environment, namely the Internet of Things(IoT), that enables a wide range of future Internet applications. In this work, we present Mobile Fog, a high level programming model for the future Internet applications that are geospatially distributed, large-scale, and latency-sensitive. We analyze use cases for the programming model with camera network and connected vehicle applications to show the efficacy of Mobile Fog. We also evaluate application performance through simulation.","PeriodicalId":237435,"journal":{"name":"MCC '13","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132273935","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}
R. Kravets, H. Alkaff, A. Campbell, Karrie Karahalios, K. Nahrstedt
Proliferation of mobile smartphones has opened up possibilities of using crowd-sourcing to gather data from and so monitor large crowds. However, depending on the size of the crowd, current solutions either put unpredictable stress on the infrastructure and energy-constrained smartphones or do not capture the crowd behavior accurately. In response, we present CrowdWatch, a scalable, distributed and energy-efficient crowd-sourcing framework. CrowdWatch achieves its goal through off-loading some of the processing to the devices and establishing a hierarchy of participants by exploiting devices with multiple radios (i.e. WiFi (high-power) and BlueTooth (low-power)). CrowdWatch can outperform traditional crowd-sourcing frameworks by reducing the stress on the infrastructures to 10% of that of a traditional crowd-sourcing solution, while only requiring each phone to use their Wi-Fi radios 15% of the time in a dense environment.
{"title":"CrowdWatch: enabling in-network crowd-sourcing","authors":"R. Kravets, H. Alkaff, A. Campbell, Karrie Karahalios, K. Nahrstedt","doi":"10.1145/2491266.2491277","DOIUrl":"https://doi.org/10.1145/2491266.2491277","url":null,"abstract":"Proliferation of mobile smartphones has opened up possibilities of using crowd-sourcing to gather data from and so monitor large crowds. However, depending on the size of the crowd, current solutions either put unpredictable stress on the infrastructure and energy-constrained smartphones or do not capture the crowd behavior accurately. In response, we present CrowdWatch, a scalable, distributed and energy-efficient crowd-sourcing framework. CrowdWatch achieves its goal through off-loading some of the processing to the devices and establishing a hierarchy of participants by exploiting devices with multiple radios (i.e. WiFi (high-power) and BlueTooth (low-power)). CrowdWatch can outperform traditional crowd-sourcing frameworks by reducing the stress on the infrastructures to 10% of that of a traditional crowd-sourcing solution, while only requiring each phone to use their Wi-Fi radios 15% of the time in a dense environment.","PeriodicalId":237435,"journal":{"name":"MCC '13","volume":"276 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115295917","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}
The development of wireless technologies, such as 3G and Wi-Fi, and the rapid growth of mobile devices equipped with sensors have enabled the practical use of Mobile Participatory Sensing (MPS). By gathering and utilizing sensor data using mobile devices, the deployment cost of services can be reduced. In the context of MPS, it is important to establish a method of storing and locating sensor data collected by millions of mobile devices. In this paper, the development of a sensor data repository system for a large-scale MPS platform is proposed. By storing sensor information in the mobile device's storage, the storage cost can be distributed. The proposed method of tracking the acquisition locations of sensor data can reduce management costs. In addition, a cache mechanism that can minimize duplicate transmissions of sensor data from mobile devices due to overlapping queries is introduced. Based on a two-day simulation, the proposed method can reduce the management cost of the acquisition locations by 80%. Furthermore, the cache method can reduce the transmission of duplicated sensor data on mobile devices.
{"title":"MPSDataStore: a sensor data repository system for mobile participatory sensing","authors":"J. Niwa, Kazuya Okada, T. Okuda, S. Yamaguchi","doi":"10.1145/2491266.2513576","DOIUrl":"https://doi.org/10.1145/2491266.2513576","url":null,"abstract":"The development of wireless technologies, such as 3G and Wi-Fi, and the rapid growth of mobile devices equipped with sensors have enabled the practical use of Mobile Participatory Sensing (MPS). By gathering and utilizing sensor data using mobile devices, the deployment cost of services can be reduced. In the context of MPS, it is important to establish a method of storing and locating sensor data collected by millions of mobile devices. In this paper, the development of a sensor data repository system for a large-scale MPS platform is proposed. By storing sensor information in the mobile device's storage, the storage cost can be distributed. The proposed method of tracking the acquisition locations of sensor data can reduce management costs. In addition, a cache mechanism that can minimize duplicate transmissions of sensor data from mobile devices due to overlapping queries is introduced. Based on a two-day simulation, the proposed method can reduce the management cost of the acquisition locations by 80%. Furthermore, the cache method can reduce the transmission of duplicated sensor data on mobile devices.","PeriodicalId":237435,"journal":{"name":"MCC '13","volume":"2010 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127355372","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}
The increasing spread of location-based services (LBSs) has led to a renewed research interest in the security of services. To ensure the credibility and availability of LBSs, there is a pressing requirement for addressing access control, authentication and privacy issues of LBSs in a synergistic way. In this paper, we propose an innovative location-based fine-grained access control mechanism for LBSs, enabling effective fine-grained access control, location-based authentication and privacy protection. Our proposed approach is based on the construction of a spatio-temporal predicate-based encryption by means of efficient secure integer comparison. Our experimental results not only validate the effectiveness of our scheme, but also demonstrate that the proposed integer comparison scheme performs better than previous bitwise comparison scheme.
{"title":"Enabling secure location-based services in mobile cloud computing","authors":"Yan Zhu, Di Ma, Dijiang Huang, Changjun Hu","doi":"10.1145/2491266.2491272","DOIUrl":"https://doi.org/10.1145/2491266.2491272","url":null,"abstract":"The increasing spread of location-based services (LBSs) has led to a renewed research interest in the security of services. To ensure the credibility and availability of LBSs, there is a pressing requirement for addressing access control, authentication and privacy issues of LBSs in a synergistic way. In this paper, we propose an innovative location-based fine-grained access control mechanism for LBSs, enabling effective fine-grained access control, location-based authentication and privacy protection. Our proposed approach is based on the construction of a spatio-temporal predicate-based encryption by means of efficient secure integer comparison. Our experimental results not only validate the effectiveness of our scheme, but also demonstrate that the proposed integer comparison scheme performs better than previous bitwise comparison scheme.","PeriodicalId":237435,"journal":{"name":"MCC '13","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114920541","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：