Radio frequency identification (RFID) technologies are widely used in many applications. The widespread use of tags in traditional ways of deployment raises a privacy concern: They make their carriers track able. This paper studies the problem of anonymous authentication. Due to resource constraints of low-cost tags, we develop a new technique to generate dynamic tokens for anonymous authentication by following an asymmetric design principle that pushes most complexity to more powerful RFID readers. Instead of implementing complicated cryptographic hash functions, our authentication protocol only requires tags to perform several simple hardware-efficient operations such as bitwise XOR, one-bit left circular shift and bit flip. Moreover, our protocol reduces the communication overhead and online computation overhead to O(1) per authentication for both tags and readers, which compares favorably with the prior art.
{"title":"An Efficient Anonymous Authentication Protocol for RFID Systems Using Dynamic Tokens","authors":"Min Chen, Shigang Chen","doi":"10.1109/ICDCS.2015.94","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.94","url":null,"abstract":"Radio frequency identification (RFID) technologies are widely used in many applications. The widespread use of tags in traditional ways of deployment raises a privacy concern: They make their carriers track able. This paper studies the problem of anonymous authentication. Due to resource constraints of low-cost tags, we develop a new technique to generate dynamic tokens for anonymous authentication by following an asymmetric design principle that pushes most complexity to more powerful RFID readers. Instead of implementing complicated cryptographic hash functions, our authentication protocol only requires tags to perform several simple hardware-efficient operations such as bitwise XOR, one-bit left circular shift and bit flip. Moreover, our protocol reduces the communication overhead and online computation overhead to O(1) per authentication for both tags and readers, which compares favorably with the prior art.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129613367","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 pervasiveness of mobile applications stimulates more eager demand for Quality of Experience (QoE) than Quality of Service (QoS), especially on the aspect of link scheduling in wireless networks. In many applications, end users concern more about transmission quality of an individual task rather than an individual packet. A task may correspond to a piece of video, music, etc. And may include many packets. This paper proposes a new network model aiming at improving users' experience that pushes the scheduling problem to the task layer. We first introduce a QoE requirement that can generalize the QoS requirement in link scheduling, the partial result requirement. Subsequently, a novel scheduling policy is proposed which can capture this requirement for each task, and then performs an application-aware scheduling. We theoretically analyze the performance of the novel scheduling policy, and discuss the impact of the QoE requirements and network settings. Finally, the simulation results indicate that our scheduling policy can significantly improve QoE.
{"title":"An Application-Aware Scheduling Policy for Real-Time Traffic","authors":"Xu Zheng, Zhipeng Cai, Jianzhong Li, Hong Gao","doi":"10.1109/ICDCS.2015.50","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.50","url":null,"abstract":"The pervasiveness of mobile applications stimulates more eager demand for Quality of Experience (QoE) than Quality of Service (QoS), especially on the aspect of link scheduling in wireless networks. In many applications, end users concern more about transmission quality of an individual task rather than an individual packet. A task may correspond to a piece of video, music, etc. And may include many packets. This paper proposes a new network model aiming at improving users' experience that pushes the scheduling problem to the task layer. We first introduce a QoE requirement that can generalize the QoS requirement in link scheduling, the partial result requirement. Subsequently, a novel scheduling policy is proposed which can capture this requirement for each task, and then performs an application-aware scheduling. We theoretically analyze the performance of the novel scheduling policy, and discuss the impact of the QoE requirements and network settings. Finally, the simulation results indicate that our scheduling policy can significantly improve QoE.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129706304","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}
Fusang Zhang, Hai Liu, Y. Leung, Xiaowen Chu, Beihong Jin
Low delivery latency and high delivery ratio are two key goals in the design of routing schemes in Vehicular Ad Hoc Networks (VANETs). The existing routing schemes utilize real-time information (e.g., Geographical position and vehicle density) and historical information (e.g., Contacts of vehicles), which usually suffer from a long delivery latency and a low delivery ratio. Inspired by the unique features of bus systems such as wide coverage, fixed routes and regular service, we propose to use the bus systems as routing backbones of VANETs. In this work, we present a Community-based Bus System (CBS) which consists of two components: a community-based backbone and a routing scheme over the backbone. We collect real traces of 2515 buses in Beijing and build a community-based backbone by applying community detection techniques in the Beijing bus system. A two-level routing scheme is proposed to operate over the backbone. The proposed routing scheme performs sequentially in the inter-community level and the intra-community level, and is able to support message delivery to both mobile vehicles and specific locations/areas. Extensive experiments are conducted on the real trace data of the Beijing bus system and the results show that CBS can significantly lower the delivery latency and improve the delivery ratio. CBS is applicable to any bus-based VANETs.
{"title":"Community-Based Bus System as Routing Backbone for Vehicular Ad Hoc Networks","authors":"Fusang Zhang, Hai Liu, Y. Leung, Xiaowen Chu, Beihong Jin","doi":"10.1109/ICDCS.2015.16","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.16","url":null,"abstract":"Low delivery latency and high delivery ratio are two key goals in the design of routing schemes in Vehicular Ad Hoc Networks (VANETs). The existing routing schemes utilize real-time information (e.g., Geographical position and vehicle density) and historical information (e.g., Contacts of vehicles), which usually suffer from a long delivery latency and a low delivery ratio. Inspired by the unique features of bus systems such as wide coverage, fixed routes and regular service, we propose to use the bus systems as routing backbones of VANETs. In this work, we present a Community-based Bus System (CBS) which consists of two components: a community-based backbone and a routing scheme over the backbone. We collect real traces of 2515 buses in Beijing and build a community-based backbone by applying community detection techniques in the Beijing bus system. A two-level routing scheme is proposed to operate over the backbone. The proposed routing scheme performs sequentially in the inter-community level and the intra-community level, and is able to support message delivery to both mobile vehicles and specific locations/areas. Extensive experiments are conducted on the real trace data of the Beijing bus system and the results show that CBS can significantly lower the delivery latency and improve the delivery ratio. CBS is applicable to any bus-based VANETs.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126313275","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}
Visual sensor networks (VSNs) can track multiple pedestrians and capture high-quality videos of the monitored area. Therefore, VSNs is ideal for providing good broadcast service. In sports broadcasting, a basic requirement for broadcasters is to report the significant events as quickly as possible when they take place. To meet this requirement, we propose the Camera Scheduling for selected area coverage problem (CamS). Considering that Pan-Tilt-Zoom (PTZ) camera sensor has the flexibility of configuring its angle of view in both horizontal and vertical dimensions, we apply PTZ camera sensors to solve CamS. A polynomial time optimal algorithm that schedules PTZ camera sensors elegantly is devised for CamS. We set many realistic application scenarios in simulation and thoroughly study how our algorithm's performance is affected by different environmental parameters, including angle velocity, the number of camera sensors and the number of sub-areas.
{"title":"PTZ Camera Scheduling for Selected Area Coverage in Visual Sensor Networks","authors":"Ling Guo, Yuqing Zhu, Deying Li, Donghyun Kim","doi":"10.1109/ICDCS.2015.46","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.46","url":null,"abstract":"Visual sensor networks (VSNs) can track multiple pedestrians and capture high-quality videos of the monitored area. Therefore, VSNs is ideal for providing good broadcast service. In sports broadcasting, a basic requirement for broadcasters is to report the significant events as quickly as possible when they take place. To meet this requirement, we propose the Camera Scheduling for selected area coverage problem (CamS). Considering that Pan-Tilt-Zoom (PTZ) camera sensor has the flexibility of configuring its angle of view in both horizontal and vertical dimensions, we apply PTZ camera sensors to solve CamS. A polynomial time optimal algorithm that schedules PTZ camera sensors elegantly is devised for CamS. We set many realistic application scenarios in simulation and thoroughly study how our algorithm's performance is affected by different environmental parameters, including angle velocity, the number of camera sensors and the number of sub-areas.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121447976","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}
Microprocessors may need to keep most of their cores off in the era of dark silicon due to thermal constraints. Recent studies have proposed Computational Sprinting, which allows a chip to temporarily exceed its power and thermal limits by turning on all its cores for a short time period, such that its computing performance is boosted for bursty computation demands. However, conducting sprinting in a data center faces new challenges due to power and thermal constraints at the data center level, which are exacerbated by recently proposed power infrastructure under-provisioning and reliance on renewable energy, as well as the increasing server density. In this paper, we propose Data Center Sprinting, a methodology that enables a data center to temporarily boost its computing performance by turning on more cores in the era of dark silicon, in order to handle occasional workload bursts. We demonstrate the feasibility of this approach by analyzing the tripping characteristics of data center circuit breakers and the discharging characteristics of energy storage devices, in order to realize safe sprinting without causing undesired server overheating or shutdown. We evaluate a prototype of Data Center Sprinting on a hardware testbed and in data enter-level simulations. The experimental results show that our solution can improve the average computing performance of a data center by a factor of 1.62 to 2.45 for 5 to 30 minutes.
{"title":"Data Center Sprinting: Enabling Computational Sprinting at the Data Center Level","authors":"Wenli Zheng, Xiaorui Wang","doi":"10.1109/ICDCS.2015.26","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.26","url":null,"abstract":"Microprocessors may need to keep most of their cores off in the era of dark silicon due to thermal constraints. Recent studies have proposed Computational Sprinting, which allows a chip to temporarily exceed its power and thermal limits by turning on all its cores for a short time period, such that its computing performance is boosted for bursty computation demands. However, conducting sprinting in a data center faces new challenges due to power and thermal constraints at the data center level, which are exacerbated by recently proposed power infrastructure under-provisioning and reliance on renewable energy, as well as the increasing server density. In this paper, we propose Data Center Sprinting, a methodology that enables a data center to temporarily boost its computing performance by turning on more cores in the era of dark silicon, in order to handle occasional workload bursts. We demonstrate the feasibility of this approach by analyzing the tripping characteristics of data center circuit breakers and the discharging characteristics of energy storage devices, in order to realize safe sprinting without causing undesired server overheating or shutdown. We evaluate a prototype of Data Center Sprinting on a hardware testbed and in data enter-level simulations. The experimental results show that our solution can improve the average computing performance of a data center by a factor of 1.62 to 2.45 for 5 to 30 minutes.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121732359","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}
Lu Wang, Xiaoke Qi, Jiang Xiao, Kaishun Wu, Jin Zhang, M. Hamdi, Qian Zhang
Partially overlapped channels are barely used for concurrent transmission in WiFi networks, since they lead to collisions where the collided packets cannot be decoded successfully. In this paper, we observe that the actual corrupted symbols by partial-channel interference in OFDM-based WiFi networks are not as severe as we expected. There remains extra coding redundancy that can be exploited from the corrupted symbols, and utilized for packet recovery. Accordingly, we present a novel paradigm termed Piros, in order to Push the lImits of partially concurrent transmission in WiFi networks. Piros strategically leverages the coding redundancy according to the overlap portion in a distributed manner, and extracts useful decoding information from the corrupted symbols to decode the packet with partial-channel interference.
{"title":"Piros: Pushing the Limits of Partially Concurrent Transmission in WiFi Networks","authors":"Lu Wang, Xiaoke Qi, Jiang Xiao, Kaishun Wu, Jin Zhang, M. Hamdi, Qian Zhang","doi":"10.1109/ICDCS.2015.103","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.103","url":null,"abstract":"Partially overlapped channels are barely used for concurrent transmission in WiFi networks, since they lead to collisions where the collided packets cannot be decoded successfully. In this paper, we observe that the actual corrupted symbols by partial-channel interference in OFDM-based WiFi networks are not as severe as we expected. There remains extra coding redundancy that can be exploited from the corrupted symbols, and utilized for packet recovery. Accordingly, we present a novel paradigm termed Piros, in order to Push the lImits of partially concurrent transmission in WiFi networks. Piros strategically leverages the coding redundancy according to the overlap portion in a distributed manner, and extracts useful decoding information from the corrupted symbols to decode the packet with partial-channel interference.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125909242","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}
Distributed file systems such as Google File System and Hadoop Distributed File System have been used to store large volumes of data in Cloud data centers. These systems divide data sets in blocks of fixed size and replicate them over multiple machines to achieve both reliability and efficiency. Recent studies have shown that data blocks tend to have a wide disparity in data popularity. In this context, the naive block replication schemes used by these systems often cause an uneven load distribution across machines, which reduces the overall I/O throughput of the system. While many replication algorithms have been proposed, existing solutions have not carefully studied the placement of data blocks that balances the load across machines, while ensuring node and rack-level reliability requirements are satisfied. In this paper, we study the dynamic data replication problem with the goal of balancing machine load while ensuring machine and rack-level reliability requirements are met. We propose several local search algorithms that provide constant approximation guarantees, yet simple and practical for implementation. We further present Aurora, a dynamic block placement mechanism that implements these algorithms in the Hadoop Distributed File System with minimal overhead. Through experiments using workload traces from Yahoo! and Facebook, we show Aurora reduces machine load imbalance by up to 26.9% compared to existing solutions, while satisfying node and rack-level reliability requirements.
{"title":"Aurora: Adaptive Block Replication in Distributed File Systems","authors":"Qi Zhang, S. Zhang, A. Leon-Garcia, R. Boutaba","doi":"10.1109/ICDCS.2015.52","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.52","url":null,"abstract":"Distributed file systems such as Google File System and Hadoop Distributed File System have been used to store large volumes of data in Cloud data centers. These systems divide data sets in blocks of fixed size and replicate them over multiple machines to achieve both reliability and efficiency. Recent studies have shown that data blocks tend to have a wide disparity in data popularity. In this context, the naive block replication schemes used by these systems often cause an uneven load distribution across machines, which reduces the overall I/O throughput of the system. While many replication algorithms have been proposed, existing solutions have not carefully studied the placement of data blocks that balances the load across machines, while ensuring node and rack-level reliability requirements are satisfied. In this paper, we study the dynamic data replication problem with the goal of balancing machine load while ensuring machine and rack-level reliability requirements are met. We propose several local search algorithms that provide constant approximation guarantees, yet simple and practical for implementation. We further present Aurora, a dynamic block placement mechanism that implements these algorithms in the Hadoop Distributed File System with minimal overhead. Through experiments using workload traces from Yahoo! and Facebook, we show Aurora reduces machine load imbalance by up to 26.9% compared to existing solutions, while satisfying node and rack-level reliability requirements.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120948842","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}
Motivated by many applications such as cognitive radio spectrum scheduling, downlink fading channel scheduling, and unmanned aerial vehicle dynamic routing, we study two restless bandit problems. Given a bandit consisting of multiple restless arms, the state of each arm evolves as a Markov chain. Assume each arm is associated with a positive weight. At each step, we select a subset of arms to play such that the weighted sum of the selected arms cannot exceed a limit. The reward of playing each arm varies according to the arm's state. The exact state of each arm is only revealed when the arm is played. The problem weighted restless bandit aims to maximize the expected average reward over the infinite horizon. We also study an extended problem called multiply-constrained restless bandit where each time there are two simultaneous constraints on the selected arms. First, the weighted sum of the selected arms cannot exceed a limit, Second, the number of the selected arms is at most a constant K. The objective of multiply-constrained restless bandit is to maximize the long term average reward. Both problems are partially observable Markov decision processes and have been proved to be PSPACE-hard even in their special cases. We propose constant approximation algorithms for both problems. Our method involves solving a semi-infinite program, converting back to a low-complexity policy, and accounting for the average reward via a Lyapunov function analysis.
{"title":"Weighted Restless Bandit and Its Applications","authors":"P. Wan, Xiaohua Xu","doi":"10.1109/ICDCS.2015.58","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.58","url":null,"abstract":"Motivated by many applications such as cognitive radio spectrum scheduling, downlink fading channel scheduling, and unmanned aerial vehicle dynamic routing, we study two restless bandit problems. Given a bandit consisting of multiple restless arms, the state of each arm evolves as a Markov chain. Assume each arm is associated with a positive weight. At each step, we select a subset of arms to play such that the weighted sum of the selected arms cannot exceed a limit. The reward of playing each arm varies according to the arm's state. The exact state of each arm is only revealed when the arm is played. The problem weighted restless bandit aims to maximize the expected average reward over the infinite horizon. We also study an extended problem called multiply-constrained restless bandit where each time there are two simultaneous constraints on the selected arms. First, the weighted sum of the selected arms cannot exceed a limit, Second, the number of the selected arms is at most a constant K. The objective of multiply-constrained restless bandit is to maximize the long term average reward. Both problems are partially observable Markov decision processes and have been proved to be PSPACE-hard even in their special cases. We propose constant approximation algorithms for both problems. Our method involves solving a semi-infinite program, converting back to a low-complexity policy, and accounting for the average reward via a Lyapunov function analysis.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122537461","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}
IaaS clouds promise instantaneously available resources to elastic applications. In practice, however, virtual machine (VM) start up times are in the order of several minutes, or at best, several tens of seconds, negatively impacting the elasticity of applications like Web servers that need to scale out to handle dynamically increasing load. VM start up time is strongly influenced by booting the VM's operating system. In this work, we propose using so-called prebaked uVMs to speed up VM start up. Uvms are snapshots of minimal VMs that can be quickly resumed and then configured to application needs by hot-plugging resources. To serve uVMs, we extend our VM boot cache service, Squirrel, allowing to store uVMs for large numbers of VM images on the hosts of a data center. Our experiments show that uVMs can start up in less than one second on a standard file system. Using 1000+ VM images from a production cloud, we show that the respective uVMs can be stored in a compressed and deduplicated file system within 50GB storage per host, while starting up within 2 -- 3 seconds on average.
{"title":"Prebaked µVMs: Scalable, Instant VM Startup for IaaS Clouds","authors":"Kaveh Razavi, Gerrit Van Der Kolk, T. Kielmann","doi":"10.1109/ICDCS.2015.33","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.33","url":null,"abstract":"IaaS clouds promise instantaneously available resources to elastic applications. In practice, however, virtual machine (VM) start up times are in the order of several minutes, or at best, several tens of seconds, negatively impacting the elasticity of applications like Web servers that need to scale out to handle dynamically increasing load. VM start up time is strongly influenced by booting the VM's operating system. In this work, we propose using so-called prebaked uVMs to speed up VM start up. Uvms are snapshots of minimal VMs that can be quickly resumed and then configured to application needs by hot-plugging resources. To serve uVMs, we extend our VM boot cache service, Squirrel, allowing to store uVMs for large numbers of VM images on the hosts of a data center. Our experiments show that uVMs can start up in less than one second on a standard file system. Using 1000+ VM images from a production cloud, we show that the respective uVMs can be stored in a compressed and deduplicated file system within 50GB storage per host, while starting up within 2 -- 3 seconds on average.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126130284","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}
Zhongxing Ming, Mingwei Xu, Ning Wang, Bingjie Gao, Qi Li
User data allowance trading is emerging as a promising field in mobile data networks. Mobile operators are establishing data trading platforms to attract more users. To date, there has been no coherent study on user data allowance trading. In this paper, we develop a truthful framework that allows users to bid for data allowance. We focus on preventing price cheating, guaranteeing fairness and minimizing trading maintenance cost. We model the data trading process as a double auction problem. We develop algorithms to solve the problem. The algorithms use a uniform price based on a competitive equilibrium to defend against price cheating and provide fairness, and use linear programming to minimize trading maintenance cost. We conduct extensive simulations to testify the proposed mechanism. Results show that our mechanism is truthful, fair and can minimize the cost of trading.
{"title":"TAFTA: A Truthful Auction Framework for User Data Allowance Trading in Mobile Networks","authors":"Zhongxing Ming, Mingwei Xu, Ning Wang, Bingjie Gao, Qi Li","doi":"10.1109/ICDCS.2015.118","DOIUrl":"https://doi.org/10.1109/ICDCS.2015.118","url":null,"abstract":"User data allowance trading is emerging as a promising field in mobile data networks. Mobile operators are establishing data trading platforms to attract more users. To date, there has been no coherent study on user data allowance trading. In this paper, we develop a truthful framework that allows users to bid for data allowance. We focus on preventing price cheating, guaranteeing fairness and minimizing trading maintenance cost. We model the data trading process as a double auction problem. We develop algorithms to solve the problem. The algorithms use a uniform price based on a competitive equilibrium to defend against price cheating and provide fairness, and use linear programming to minimize trading maintenance cost. We conduct extensive simulations to testify the proposed mechanism. Results show that our mechanism is truthful, fair and can minimize the cost of trading.","PeriodicalId":129182,"journal":{"name":"2015 IEEE 35th International Conference on Distributed Computing Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133623308","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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