Maotong Xu, Sultan Alamro, Tian Lan, S. Subramaniam
In this paper, we bring various speculative scheduling strategies together under a unifying optimization framework, which defines a new metric, Probability of Completion before Deadlines (PoCD), to measure the probability that MapReduce jobs meet their desired deadlines. We propose an optimization problem to jointly optimize PoCD and execution cost in different strategies. Three strategies are prototyped on Hadoop MapReduce and evaluated against two baseline strategies using experiments. A 78% net utility increase with up to 94% PoCD and 12% cost improvement is achieved.
{"title":"Optimizing Speculative Execution of Deadline-Sensitive Jobs in Cloud","authors":"Maotong Xu, Sultan Alamro, Tian Lan, S. Subramaniam","doi":"10.1145/3078505.3078541","DOIUrl":"https://doi.org/10.1145/3078505.3078541","url":null,"abstract":"In this paper, we bring various speculative scheduling strategies together under a unifying optimization framework, which defines a new metric, Probability of Completion before Deadlines (PoCD), to measure the probability that MapReduce jobs meet their desired deadlines. We propose an optimization problem to jointly optimize PoCD and execution cost in different strategies. Three strategies are prototyped on Hadoop MapReduce and evaluated against two baseline strategies using experiments. A 78% net utility increase with up to 94% PoCD and 12% cost improvement is achieved.","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"56 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":"123225524","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}
Brandon Wang, Xiaoye Li, L. P. D. Aguiar, D. Menasché, Zubair Shafiq
Industrial Control Systems (ICS) are widely deployed in mission critical infrastructures such as manufacturing, energy, and transportation. The mission critical nature of ICS devices poses important security challenges for ICS vendors and asset owners. In particular, the patching of ICS devices is usually deferred to scheduled production outages so as to prevent potential operational disruption of critical systems. In this paper, we present the results from our longitudinal measurement and characterization study of ICS patching behavior. Our analysis of more than 100 thousand Internet-exposed ICS devices reveals that fewer than 30% upgrade to newer patched versions within 60 days of a vulnerability disclosure. Based on our measurement and analysis, we further propose a model to forecast the patching behavior of ICS devices.
{"title":"Characterizing and Modeling Patching Practices of Industrial Control Systems","authors":"Brandon Wang, Xiaoye Li, L. P. D. Aguiar, D. Menasché, Zubair Shafiq","doi":"10.1145/3078505.3078524","DOIUrl":"https://doi.org/10.1145/3078505.3078524","url":null,"abstract":"Industrial Control Systems (ICS) are widely deployed in mission critical infrastructures such as manufacturing, energy, and transportation. The mission critical nature of ICS devices poses important security challenges for ICS vendors and asset owners. In particular, the patching of ICS devices is usually deferred to scheduled production outages so as to prevent potential operational disruption of critical systems. In this paper, we present the results from our longitudinal measurement and characterization study of ICS patching behavior. Our analysis of more than 100 thousand Internet-exposed ICS devices reveals that fewer than 30% upgrade to newer patched versions within 60 days of a vulnerability disclosure. Based on our measurement and analysis, we further propose a model to forecast the patching behavior of ICS devices.","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"104 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":"133181873","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}
In this paper, we study the accuracy of mean-field approximation. We show that, under general conditions, the expectation of any performance functional converges at rate O(1/N) to its mean-field approximation. Our result applies for finite and infinite-dimensional mean-field models. We provide numerical experiments that demonstrate that this rate of convergence is tight.
{"title":"Expected Values Estimated via Mean-Field Approximation are 1/N-Accurate: Extended Abstract","authors":"Nicolas Gast","doi":"10.1145/3078505.3078523","DOIUrl":"https://doi.org/10.1145/3078505.3078523","url":null,"abstract":"In this paper, we study the accuracy of mean-field approximation. We show that, under general conditions, the expectation of any performance functional converges at rate O(1/N) to its mean-field approximation. Our result applies for finite and infinite-dimensional mean-field models. We provide numerical experiments that demonstrate that this rate of convergence is tight.","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"40 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":"134473249","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 modern world is becoming increasingly dependent on computing and communication technology to function, but unfortunately its application and impact on areas such as critical infrastructure and industrial control system (ICS) networks remains to be thoroughly studied. Significant research has been conducted to address the myriad security concerns in these areas, but they are virtually all based on artificial testbeds or simulations designed on assumptions about their behavior either from knowledge of traditional IT networking or from basic principles of ICS operation. In this work, we provide the most detailed characterization of an example ICS to date in order to determine if these common assumptions hold true. A live power distribution substation is observed over the course of two and a half years to measure its behavior and evolution over time. Then, a horizontal study is conducted that compared this behavior with three other substations from the same company. Although most predictions were found to be correct, some unexpected behavior was observed that highlights the fundamental differences between ICS and IT networks including round trip times dominated by processing speed as opposed to network delay, several well known TCP features being largely irrelevant, and surprisingly large jitter from devices running real-time operating systems. The impact of these observations is discussed in terms of generality to other embedded networks, network security applications, and the suitability of the TCP protocol for this environment.
{"title":"A Case Study in Power Substation Network Dynamics","authors":"David Formby, A. Elwalid, R. Beyah","doi":"10.1145/3078505.3078525","DOIUrl":"https://doi.org/10.1145/3078505.3078525","url":null,"abstract":"The modern world is becoming increasingly dependent on computing and communication technology to function, but unfortunately its application and impact on areas such as critical infrastructure and industrial control system (ICS) networks remains to be thoroughly studied. Significant research has been conducted to address the myriad security concerns in these areas, but they are virtually all based on artificial testbeds or simulations designed on assumptions about their behavior either from knowledge of traditional IT networking or from basic principles of ICS operation. In this work, we provide the most detailed characterization of an example ICS to date in order to determine if these common assumptions hold true. A live power distribution substation is observed over the course of two and a half years to measure its behavior and evolution over time. Then, a horizontal study is conducted that compared this behavior with three other substations from the same company. Although most predictions were found to be correct, some unexpected behavior was observed that highlights the fundamental differences between ICS and IT networks including round trip times dominated by processing speed as opposed to network delay, several well known TCP features being largely irrelevant, and surprisingly large jitter from devices running real-time operating systems. The impact of these observations is discussed in terms of generality to other embedded networks, network security applications, and the suitability of the TCP protocol for this environment.","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"257 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":"131836243","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":"Session details: SIGMETRICS Rising Star Award: Sewoong Oh","authors":"B. Hajek","doi":"10.1145/3248544","DOIUrl":"https://doi.org/10.1145/3248544","url":null,"abstract":"","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"14 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":"128040714","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}
Yi Cao, Javad Nejati, Muhammad Wajahat, A. Balasubramanian, Anshul Gandhi
Mobile Web page performance is critical to content providers, service providers, and users, as Web browsers are one of the most popular apps on phones. Slow Web pages are known to adversely affect profits and lead to user abandonment. While improving mobile web performance has drawn increasing attention, most optimizations tend to overlook an important factor, energy. Given the importance of battery life for mobile users, we argue that web page optimizations should be evaluated for their impact on energy consumption. However, examining the energy effects of a web optimization is challenging, even if one has access to power monitors, for several reasons. First, the page load process is relatively short-lived, ranging from several milliseconds to a few seconds. Fine-grained resource monitoring on such short timescales to model energy consumption is known to incur substantial overhead. Second, Web pages are complex. A Web enhancement can have widely varying effects on different page load activities. Thus, studying the energy impact of a Web enhancement on page loads requires understanding its effects on each page load activity. Existing approaches to analyzing mobile energy typically focus on profiling and modeling the resource consumption of the device during execution. Such approaches consider long-running services and apps such as games, audio, and video streaming, for which low-overhead, coarse-grained resource monitoring suffices. For page loads, however, coarse-grained resource monitoring is not sufficient to analyze the energy consumption of individual, short-lived, page load activities. We present RECON (REsource- and COmpoNent-based modeling), a modeling approach that addresses the above challenges to estimate the energy consumption of any Web page load. The key intuition behind RECON is to go beyond resource-level information and exploit application-level semantics to capture the individual Web page load activities. Instead of modeling the energy consumption at the full page load level, which is too coarse grained, RECON models at a much finer component level granularity. Components are individual page load activities such as loading objects, parsing the page, or evaluating JavaScript. To do this, RECON combines coarse-grained resource utilization and component-level Web page load information available from existing tools. During the initial training stage, RECON uses a power monitor to measure the energy consumption during a set of page load processes and juxtaposes this power consumption with coarse-grained resource and component information. RECON uses both simple linear regression and more complex neural networks to build a model of the power consumption as a function of the resources used and the individual page load components, thus providing benefits over individual models. Using the model, RECON can estimate the energy consumption of any Web page loaded as-is or upon applying any enhancement, without the monitor. We experimentally
{"title":"Deconstructing the Energy Consumption of the Mobile Page Load","authors":"Yi Cao, Javad Nejati, Muhammad Wajahat, A. Balasubramanian, Anshul Gandhi","doi":"10.1145/3143314.3078587","DOIUrl":"https://doi.org/10.1145/3143314.3078587","url":null,"abstract":"Mobile Web page performance is critical to content providers, service providers, and users, as Web browsers are one of the most popular apps on phones. Slow Web pages are known to adversely affect profits and lead to user abandonment. While improving mobile web performance has drawn increasing attention, most optimizations tend to overlook an important factor, energy. Given the importance of battery life for mobile users, we argue that web page optimizations should be evaluated for their impact on energy consumption. However, examining the energy effects of a web optimization is challenging, even if one has access to power monitors, for several reasons. First, the page load process is relatively short-lived, ranging from several milliseconds to a few seconds. Fine-grained resource monitoring on such short timescales to model energy consumption is known to incur substantial overhead. Second, Web pages are complex. A Web enhancement can have widely varying effects on different page load activities. Thus, studying the energy impact of a Web enhancement on page loads requires understanding its effects on each page load activity. Existing approaches to analyzing mobile energy typically focus on profiling and modeling the resource consumption of the device during execution. Such approaches consider long-running services and apps such as games, audio, and video streaming, for which low-overhead, coarse-grained resource monitoring suffices. For page loads, however, coarse-grained resource monitoring is not sufficient to analyze the energy consumption of individual, short-lived, page load activities. We present RECON (REsource- and COmpoNent-based modeling), a modeling approach that addresses the above challenges to estimate the energy consumption of any Web page load. The key intuition behind RECON is to go beyond resource-level information and exploit application-level semantics to capture the individual Web page load activities. Instead of modeling the energy consumption at the full page load level, which is too coarse grained, RECON models at a much finer component level granularity. Components are individual page load activities such as loading objects, parsing the page, or evaluating JavaScript. To do this, RECON combines coarse-grained resource utilization and component-level Web page load information available from existing tools. During the initial training stage, RECON uses a power monitor to measure the energy consumption during a set of page load processes and juxtaposes this power consumption with coarse-grained resource and component information. RECON uses both simple linear regression and more complex neural networks to build a model of the power consumption as a function of the resources used and the individual page load components, thus providing benefits over individual models. Using the model, RECON can estimate the energy consumption of any Web page loaded as-is or upon applying any enhancement, without the monitor. We experimentally ","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"21 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":"128394828","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":"Session details: Session 1: Load Balancing among Switch and Caches","authors":"Yi Lu","doi":"10.1145/3248535","DOIUrl":"https://doi.org/10.1145/3248535","url":null,"abstract":"","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"13 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":"123735245","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}
One of the major issues with the integration of renewable energy sources into the power grid is the increased uncertainty and variability that they bring. If this uncertainty is not sufficiently addressed, it will limit the further penetration of renewables into the grid and even result in blackouts. Compared to energy storage, Demand Response (DR) has advantages to provide reserves to the load serving entities (LSEs) in a cost-effective and environmentally friendly way. DR programs work by changing customers' loads when the power grid experiences a contingency such as a mismatch between supply and demand. Uncertainties from both the customer-side and LSE-side make designing algorithms for DR a major challenge. This paper makes the following main contributions: (i) We propose DR control policies based on the optimal structures of the offline solution. (ii) A distributed algorithm is developed for implementing the control policies without efficiency loss. (iii) We further offer an enhanced policy design by allowing flexibilities into the commitment level. (iv) We perform real world trace based numerical simulations which demonstrate that the proposed algorithms can achieve near optimal social cost. Details can be found in our extended version.
{"title":"Incentivizing Reliable Demand Response with Customers' Uncertainties and Capacity Planning","authors":"Joshua Comden, Zhenhua Liu, Yue Zhao","doi":"10.1145/3078505.3078546","DOIUrl":"https://doi.org/10.1145/3078505.3078546","url":null,"abstract":"One of the major issues with the integration of renewable energy sources into the power grid is the increased uncertainty and variability that they bring. If this uncertainty is not sufficiently addressed, it will limit the further penetration of renewables into the grid and even result in blackouts. Compared to energy storage, Demand Response (DR) has advantages to provide reserves to the load serving entities (LSEs) in a cost-effective and environmentally friendly way. DR programs work by changing customers' loads when the power grid experiences a contingency such as a mismatch between supply and demand. Uncertainties from both the customer-side and LSE-side make designing algorithms for DR a major challenge. This paper makes the following main contributions: (i) We propose DR control policies based on the optimal structures of the offline solution. (ii) A distributed algorithm is developed for implementing the control policies without efficiency loss. (iii) We further offer an enhanced policy design by allowing flexibilities into the commitment level. (iv) We perform real world trace based numerical simulations which demonstrate that the proposed algorithms can achieve near optimal social cost. Details can be found in our extended version.","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131868493","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}
This paper presents a novel cache design based on Multi-Level Cell Spin-Transfer Torque RAM (MLC STT-RAM).Our design exploits the asymmetric nature of the MLC STT-RAM to build cache lines featuring heterogeneous performances, that is, half of the cache lines are read-friendly,while the other half are write-friendly--this asymmetry in read/write latencies are then used by a migration policy in order to overcome the high latency of the baseline MLC cache. Furthermore, in order to enhance the device lifetime, we propose to dynamically deactivate ways of a set in underutilized sets to convert MLC to Single-Level Cell (SLC)mode.Our experiments show that our design gives an average improvement of 12% in system performance and 26% in last-level cache(L3) access energy for various workloads.
{"title":"A Study on Performance and Power Efficiency of Dense Non-Volatile Caches in Multi-Core Systems","authors":"A. Jadidi, M. Arjomand, M. Kandemir, C. Das","doi":"10.1145/3078505.3078547","DOIUrl":"https://doi.org/10.1145/3078505.3078547","url":null,"abstract":"This paper presents a novel cache design based on Multi-Level Cell Spin-Transfer Torque RAM (MLC STT-RAM).Our design exploits the asymmetric nature of the MLC STT-RAM to build cache lines featuring heterogeneous performances, that is, half of the cache lines are read-friendly,while the other half are write-friendly--this asymmetry in read/write latencies are then used by a migration policy in order to overcome the high latency of the baseline MLC cache. Furthermore, in order to enhance the device lifetime, we propose to dynamically deactivate ways of a set in underutilized sets to convert MLC to Single-Level Cell (SLC)mode.Our experiments show that our design gives an average improvement of 12% in system performance and 26% in last-level cache(L3) access energy for various workloads.","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122664797","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}
It has been shown that it is impossible to achieve both stringent end-to-end deadline and reliability guarantees in a large network without having complete information of all future packet arrivals. In order to maintain desirable performance in the presence of uncertainty of future packet arrivals, common practice is to add redundancy by increasing link capacities. This paper studies the amount of capacity needed to provide stringent performance guarantees and propose a low-complexity online algorithm. Without adding redundancy, we further propose a low-complexity order-optimal online policy for the network.
{"title":"On the Capacity Requirement for Arbitrary End-to-End Deadline and Reliability Guarantees in Multi-hop Networks","authors":"Han Deng, I.-Hong Hou","doi":"10.1145/3078505.3078540","DOIUrl":"https://doi.org/10.1145/3078505.3078540","url":null,"abstract":"It has been shown that it is impossible to achieve both stringent end-to-end deadline and reliability guarantees in a large network without having complete information of all future packet arrivals. In order to maintain desirable performance in the presence of uncertainty of future packet arrivals, common practice is to add redundancy by increasing link capacities. This paper studies the amount of capacity needed to provide stringent performance guarantees and propose a low-complexity online algorithm. Without adding redundancy, we further propose a low-complexity order-optimal online policy for the network.","PeriodicalId":133673,"journal":{"name":"Proceedings of the 2017 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems","volume":"309 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124394854","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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