2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)最新文献_第2页

Pronto: Efficient Test Packet Generation for Dynamic Network Data Planes 快速:动态网络数据平面的有效测试包生成

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS) Pub Date : 2017-06-05 DOI: 10.1109/ICDCS.2017.55

Yu Zhao, Huazhe Wang, Xiaoze Lin, Tingting Yu, Chen Qian

{"title":"Pronto: Efficient Test Packet Generation for Dynamic Network Data Planes","authors":"Yu Zhao, Huazhe Wang, Xiaoze Lin, Tingting Yu, Chen Qian","doi":"10.1109/ICDCS.2017.55","DOIUrl":"https://doi.org/10.1109/ICDCS.2017.55","url":null,"abstract":"Computer networks are becoming increasingly complex today and thus prone to various network faults. Traditional testing tools (e.g., ping, traceroute) that often involve substantial manual effort to uncover faults are inefficient. This paper focuses on fault detection of the network data plane using test packets. Existing solutions of test packet generation either take very long time (e.g., more than one hour) to complete or generate too many test packets that may hurt regular traffic. In this paper, we present Pronto, an automated test packet generation tool that generates test packets to exercise data plane rules in the entire network in a short time (e.g., several seconds) and can quickly react to rule changes due to network dynamics. In addition, Pronto minimizes the number of test packets by allowing a packet to test multiple rules at different switches. The performance evaluation using two real network data plane rule sets shows that Pronto is faster than a recently developed tool by more than two orders of magnitude. Pronto can update the probes for rule changes using less than 1ms while existing methods have no such update function.","PeriodicalId":127689,"journal":{"name":"2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125981351","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}

引用次数: 16

Opportunistic Energy Sharing Between Power Grid and Electric Vehicles: A Game Theory-Based Pricing Policy 基于博弈论的电网与电动汽车能源共享定价策略

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS) Pub Date : 2017-06-05 DOI: 10.1109/ICDCS.2017.219

Ankur Sarker, Zhuozhao Li, William Kolodzey, Haiying Shen

{"title":"Opportunistic Energy Sharing Between Power Grid and Electric Vehicles: A Game Theory-Based Pricing Policy","authors":"Ankur Sarker, Zhuozhao Li, William Kolodzey, Haiying Shen","doi":"10.1109/ICDCS.2017.219","DOIUrl":"https://doi.org/10.1109/ICDCS.2017.219","url":null,"abstract":"Electric vehicles (EVs) have great potential to reduce dependency on fossil fuels. The recent surge in the development of online EV (OLEV) will help to address the drawbacks associated with current generation EVs, such as the heavy and expensive batteries. OLEVs are integrated with the smart grid of power infrastructure through a wireless power transfer system (WPT) to increase the driving range of the OLEV. However, the integration of OLEVs with the grid creates a tremendous load for the smart grid. The demand of a power grid changes over time and the price of power is not fixed throughout the day. There should be some congestion avoidance and load balancing policy implications to ensure quality of services for OLEVs. In this paper, first, we conduct an analysis to show the existence of unpredictable power load and congestion because of OLEVs. We use the Simulation for Urban MObility tool and hourly traffic counts of a road section of the New York City to analyze the amount of energy OLEVs can receive at different times of the day. Then, we present a game theory based on a distributed power schedule framework to find the optimal schedule between OLEVs and smart grid. In the proposed framework, OLEVs receive the amount of power charging from the smart grid based on a power payment function which is updated using best response strategy. We prove that the updated power requests converge to the optimal power schedule. In this way, the smart grid maximizes the social welfare of OLEVs, which is defined as mixed consideration of total satisfaction and its power charging cost. Finally, we verify the performance of our proposed pricing policy under different scenarios in a simulation study.","PeriodicalId":127689,"journal":{"name":"2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128956203","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}

引用次数: 12

Characterizing Performance and Energy-Efficiency of the RAMCloud Storage System RAMCloud存储系统的性能和能效表征

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS) Pub Date : 2017-06-05 DOI: 10.1109/ICDCS.2017.51

Y. Taleb, Shadi Ibrahim, Gabriel Antoniu, Toni Cortes

{"title":"Characterizing Performance and Energy-Efficiency of the RAMCloud Storage System","authors":"Y. Taleb, Shadi Ibrahim, Gabriel Antoniu, Toni Cortes","doi":"10.1109/ICDCS.2017.51","DOIUrl":"https://doi.org/10.1109/ICDCS.2017.51","url":null,"abstract":"Most large popular web applications, like Facebook and Twitter, have been relying on large amounts of in-memory storage to cache data and offer a low response time. As the main memory capacity of clusters and clouds increases, it becomes possible to keep most of the data in the main memory. This motivates the introduction of in-memory storage systems. While prior work has focused on how to exploit the low-latency of in-memory access at scale, there is very little visibility into the energy-efficiency of in-memory storage systems. Even though it is known that main memory is a fundamental energy bottleneck in computing systems (i.e., DRAM consumes up to 40% of a server's power). In this paper, by the means of experimental evaluation, we have studied the performance and energy-efficiency of RAMCloud - a well-known in-memory storage system. We reveal that although RAMCloud is scalable for read-only applications, it exhibits non-proportional power consumption. We also find that the current replication scheme implemented in RAMCloud limits the performance and results in high energy consumption. Surprisingly, we show that replication can also play a negative role in crash-recovery.","PeriodicalId":127689,"journal":{"name":"2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114718790","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}

引用次数: 4

Learning from Failure Across Multiple Clusters: A Trace-Driven Approach to Understanding, Predicting, and Mitigating Job Terminations 从多个集群的失败中学习:一种跟踪驱动的方法来理解、预测和减轻作业终止

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS) Pub Date : 2017-06-05 DOI: 10.1109/ICDCS.2017.317

Nosayba El-Sayed, Hongyu Zhu, Bianca Schroeder

{"title":"Learning from Failure Across Multiple Clusters: A Trace-Driven Approach to Understanding, Predicting, and Mitigating Job Terminations","authors":"Nosayba El-Sayed, Hongyu Zhu, Bianca Schroeder","doi":"10.1109/ICDCS.2017.317","DOIUrl":"https://doi.org/10.1109/ICDCS.2017.317","url":null,"abstract":"In large-scale computing platforms, jobs are prone to interruptions and premature terminations, limiting their usability and leading to significant waste in cluster resources. In this paper, we tackle this problem in three steps. First, we provide a comprehensive study based on log data from multiple large-scale production systems to identify patterns in the behaviour of unsuccessful jobs across different clusters and investigate possible root causes behind job termination. Our results reveal several interesting properties that distinguish unsuccessful jobs from others, particularly w.r.t. resource consumption patterns and job configuration settings. Secondly, we design a machine learning-based framework for predicting job and task terminations. We show that job failures can be predicted relatively early with high precision and recall, and also identify attributes that have strong predictive power of job failure. Finally, we demonstrate in a concrete use case how our prediction framework can be used to mitigate the effect of unsuccessful execution using an effective task-cloning policy that we propose.","PeriodicalId":127689,"journal":{"name":"2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116890112","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}

引用次数: 52

E-Android: A New Energy Profiling Tool for Smartphones E-Android:智能手机的新能源分析工具

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS) Pub Date : 2017-06-05 DOI: 10.1109/ICDCS.2017.218

Xing Gao, Dachuan Liu, Daiping Liu, Haining Wang, A. Stavrou

{"title":"E-Android: A New Energy Profiling Tool for Smartphones","authors":"Xing Gao, Dachuan Liu, Daiping Liu, Haining Wang, A. Stavrou","doi":"10.1109/ICDCS.2017.218","DOIUrl":"https://doi.org/10.1109/ICDCS.2017.218","url":null,"abstract":"As the limited battery lifetime remains a major factor restricting the applicability of a smartphone, significant research efforts have been devoted to understand the energy consumption in smartphones. Existing energy modeling methods can account energy drain in a fine-grained manner and provide well designed human-battery interfaces for users to characterize energy usage of every app in smartphones. However, in this paper, we demonstrate that there are still pitfalls in current Android energy modeling approaches, leaving collateral energy consumption unaccounted. The existence of collateral energy consumption becomes a serious energy bug. In particular, those energy bugs could be exploited to launch a new class of energy attacks, which deplete battery life and sidestep the supervision of current energy accounting. To unveil collateral energy bugs, we propose E-Android to accurately profile energy consumption of a smartphone in a comprehensive manner. E-Android monitors collateral energy related events and maintains energy consumption maps for relevant apps. We evaluate the effectiveness of E-Android under six different collateral energy attacks and two normal scenarios, and compare the results with those of Android. While Android fails to disclose collateral energy bugs, E-Android can accurately profile energy consumption and reveal the existence of energy bugs with minor overhead.","PeriodicalId":127689,"journal":{"name":"2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117049876","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}

引用次数: 18

City-Hunter: Hunting Smartphones in Urban Areas 城市猎人:在城市地区寻找智能手机

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS) Pub Date : 2017-06-05 DOI: 10.1109/ICDCS.2017.148

Xuefeng Liu, Jiaqi Wen, Shaojie Tang, Jiannong Cao, Jiaxing Shen

引用次数: 2

Decision-Driven Execution: A Distributed Resource Management Paradigm for the Age of IoT 决策驱动的执行:物联网时代的分布式资源管理范式

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS) Pub Date : 2017-06-05 DOI: 10.1109/ICDCS.2017.318

T. Abdelzaher, Md. Tanvir Al Amin, A. Bar-Noy, William Dron, R. Govindan, Reginald L. Hobbs, Shaohan Hu, Jung-Eun Kim, Jongdeog Lee, K. Marcus, Shuochao Yao, Yiran Zhao

引用次数: 11

Specifying a Distributed Snapshot Algorithm as a Meta-Program and Model Checking it at Meta-Level 将分布式快照算法指定为元程序，并在元级别对其进行模型检查

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS) Pub Date : 2017-06-05 DOI: 10.1109/ICDCS.2017.176

Ha Thi Thu Doan, K. Ogata, François Bonnet

引用次数: 5

Optimal Resource Allocation for Multi-user Video Streaming over mmWave Networks 毫米波网络上多用户视频流的优化资源分配

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS) Pub Date : 2017-06-05 DOI: 10.1109/ICDCS.2017.159

Zhifeng He, S. Mao

{"title":"Optimal Resource Allocation for Multi-user Video Streaming over mmWave Networks","authors":"Zhifeng He, S. Mao","doi":"10.1109/ICDCS.2017.159","DOIUrl":"https://doi.org/10.1109/ICDCS.2017.159","url":null,"abstract":"We investigate the resource allocation problem, including time slot allocation, channel allocation, and power adaptation, in a millimeter Wave (mmWave) network with multiple transmission links, multiple channels, and a PicoNet Coordinator (PNC). Each link has a video session to transmit from the transmitter to the receiver. The objective is to minimize the number of time slots to finish the video sessions of all links by jointly optimizing channel allocation and time slot allocation for links, while considering the possible interference between different links on the same channel. The optimal solution for the formulated problem is computationally prohibitive to obtain due to the exponential complexity. We developed a column generation based method to reformulate the original problem into a main problem along with a series of sub-problems, with greatly reduced complexity. We prove that the optimal solution for the reformulated problem converges to the optimal solution of the original problem, and we derived a lower bound for the performance of the reformulated problem at each iteration, which will finally converge to the global optimal solution. The proposed scheme is validated with simulations with its superior performance over existing work is observed.","PeriodicalId":127689,"journal":{"name":"2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133474095","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}

引用次数: 1

MELODY: A Long-Term Dynamic Quality-Aware Incentive Mechanism for Crowdsourcing 旋律:众包的长期动态质量意识激励机制

2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS) Pub Date : 2017-06-05 DOI: 10.1109/ICDCS.2017.28

Hongwei Wang, Song Guo, Jiannong Cao, M. Guo

{"title":"MELODY: A Long-Term Dynamic Quality-Aware Incentive Mechanism for Crowdsourcing","authors":"Hongwei Wang, Song Guo, Jiannong Cao, M. Guo","doi":"10.1109/ICDCS.2017.28","DOIUrl":"https://doi.org/10.1109/ICDCS.2017.28","url":null,"abstract":"Crowdsourcing allows requesters to allocate tasks to a group of workers on the Internet to make use of their collective intelligence. Quality control is a key design objective in incentive mechanisms for crowdsourcing as requesters aim at obtaining answers of high quality under a given budget. However, when measuring workers' long-term quality, existing mechanisms either fail to utilize workers' historical information, or treat workers' quality as stable and ignore its temporal characteristics, hence performing poorly in a long run. In this paper we propose MELODY, a long-term dynamic quality-aware incentive mechanism for crowdsourcing. MELODY models interaction between requesters and workers as reverse auctions that run continuously. In each run of MELODY, we design a truthful, individual rational, budget feasible and quality-aware algorithm for task allocation with polynomial-time computation complexity and O(1) performance ratio. Moreover, taking into consideration the long-term characteristics of workers' quality, we propose a novel framework in MELODY for quality inference and parameters learning based on Linear Dynamical Systems at the end of each run, which takes full advantage of workers' historical information and predicts their quality accurately. Through extensive simulations, we demonstrate that MELODY outperforms existing work in terms of both quality estimation (reducing estimation error by 17.6% ~ 24.2%) and social performance (increasing requester's utility by 18.2% ~ 46.6%) in long-term scenarios.","PeriodicalId":127689,"journal":{"name":"2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)","volume":"12 45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114755992","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}

引用次数: 66