C. Bouras, J. Garofalakis, P. Spirakis, V. Triantafillou
Our work deals with the analysis of the queueing delays of buffered multistage Banyan networks of multiprocessors. We provide tight upper bounds on the mean delays of the second stage and beyond, in the case of infinite buffers. Our results are validated by simulations performed on a network simulator constructed by us. The analytic work for network stages beyond the first, provides a partial answer to open problems posed by previous research.
{"title":"Queueing delays in buffered multistage interconnection networks","authors":"C. Bouras, J. Garofalakis, P. Spirakis, V. Triantafillou","doi":"10.1145/29903.29918","DOIUrl":"https://doi.org/10.1145/29903.29918","url":null,"abstract":"Our work deals with the analysis of the queueing delays of buffered multistage Banyan networks of multiprocessors. We provide tight upper bounds on the mean delays of the second stage and beyond, in the case of infinite buffers. Our results are validated by simulations performed on a network simulator constructed by us. The analytic work for network stages beyond the first, provides a partial answer to open problems posed by previous research.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125165115","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}
Thomas M. M. Meyfroyt, S. Borst, O. Boxma, D. Denteneer
As the use of wireless sensor networks increases, the need for (energy-)efficient and reliable broadcasting algorithms grows. Ideally, a broadcasting algorithm should have the ability to quickly disseminate data, while keeping the number of transmissions low. In this paper we develop a model describing the message count in large-scale wireless sensor networks. We focus our attention on the popular Trickle algorithm, which has been proposed as a suitable communication protocol for code maintenance and propagation in wireless sensor networks. Besides providing a mathematical analysis of the algorithm, we propose a generalized version of Trickle, with an additional parameter defining the length of a listen-only period. This generalization proves to be useful for optimizing the design and usage of the algorithm. For single-cell networks we show how the message count increases with the size of the network and how this depends on the Trickle parameters. Furthermore, we derive distributions of inter-broadcasting times and investigate their asymptotic behavior. Our results prove conjectures made in the literature concerning the effect of a listen-only period. Additionally, we develop an approximation for the expected number of transmissions in multi-cell networks. All results are validated by simulations.
{"title":"Data dissemination performance in large-scale sensor networks","authors":"Thomas M. M. Meyfroyt, S. Borst, O. Boxma, D. Denteneer","doi":"10.1145/2637364.2591981","DOIUrl":"https://doi.org/10.1145/2637364.2591981","url":null,"abstract":"As the use of wireless sensor networks increases, the need for (energy-)efficient and reliable broadcasting algorithms grows. Ideally, a broadcasting algorithm should have the ability to quickly disseminate data, while keeping the number of transmissions low. In this paper we develop a model describing the message count in large-scale wireless sensor networks. We focus our attention on the popular Trickle algorithm, which has been proposed as a suitable communication protocol for code maintenance and propagation in wireless sensor networks. Besides providing a mathematical analysis of the algorithm, we propose a generalized version of Trickle, with an additional parameter defining the length of a listen-only period. This generalization proves to be useful for optimizing the design and usage of the algorithm. For single-cell networks we show how the message count increases with the size of the network and how this depends on the Trickle parameters. Furthermore, we derive distributions of inter-broadcasting times and investigate their asymptotic behavior. Our results prove conjectures made in the literature concerning the effect of a listen-only period. Additionally, we develop an approximation for the expected number of transmissions in multi-cell networks. All results are validated by simulations.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127423843","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}
Qiang Xu, Thomas Andrews, Yong Liao, S. Miskovic, Z. Morley Mao, M. Baldi, A. Nucci
We aim to devise a method that can identify mobile apps related to each individual traffic flow in the wild. Mobile apps are becoming preferred means of Internet access for a growing user population. Such departure from browser based Internet poses a unique challenge to traffic management tools, still largely incapable of handling mobile apps. Consequently, enterprises and service providers become hindered by being unable to deploy effective mobile policies and security solutions. Traditionally, desktop applications and networking protocols were identified by signatures derived from transport-layer ports, ip addresses, or domain names [2, 5]. It is not suitable for mobile apps any more. The main reason is that most mobile apps communicate via generic HTTP/HTTPS traffic, thus being a priori indistinguishable from Internet browsing. State-of-the-art solutions attempted to develop signatures via user studies or app emulations [6, 4, 1]. Neither of the two approaches scales due to a number of key challenges: • Similarity. Besides using similar protocols (HTTP/HTTPS), mobiles apps communicate with largely similar IP-/domainlevel destinations, Content Delivery Networks (CDNs), and cloud services, which makes them difficult to distinguish. • Scalability. With hundreds of thousands of apps, the identification has to devise very efficient matching algorithms at line speeds. Moreover, the references for matching have to be obtained efficiently. One cannot assume running all
{"title":"FLOWR: a self-learning system for classifying mobileapplication traffic","authors":"Qiang Xu, Thomas Andrews, Yong Liao, S. Miskovic, Z. Morley Mao, M. Baldi, A. Nucci","doi":"10.1145/2591971.2592022","DOIUrl":"https://doi.org/10.1145/2591971.2592022","url":null,"abstract":"We aim to devise a method that can identify mobile apps related to each individual traffic flow in the wild. Mobile apps are becoming preferred means of Internet access for a growing user population. Such departure from browser based Internet poses a unique challenge to traffic management tools, still largely incapable of handling mobile apps. Consequently, enterprises and service providers become hindered by being unable to deploy effective mobile policies and security solutions. Traditionally, desktop applications and networking protocols were identified by signatures derived from transport-layer ports, ip addresses, or domain names [2, 5]. It is not suitable for mobile apps any more. The main reason is that most mobile apps communicate via generic HTTP/HTTPS traffic, thus being a priori indistinguishable from Internet browsing. State-of-the-art solutions attempted to develop signatures via user studies or app emulations [6, 4, 1]. Neither of the two approaches scales due to a number of key challenges: • Similarity. Besides using similar protocols (HTTP/HTTPS), mobiles apps communicate with largely similar IP-/domainlevel destinations, Content Delivery Networks (CDNs), and cloud services, which makes them difficult to distinguish. • Scalability. With hundreds of thousands of apps, the identification has to devise very efficient matching algorithms at line speeds. Moreover, the references for matching have to be obtained efficiently. One cannot assume running all","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115755682","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}
Sahil Suneja, C. Isci, Vasanth Bala, E. D. Lara, Todd W. Mummert
The dramatic proliferation of virtual machines (VMs) in datacenters and the highly-dynamic and transient nature of VM provisioning has revolutionized datacenter operations. However, the management of these environments is still carried out using re-purposed versions of traditional agents, originally developed for managing physical systems, or most recently via newer virtualization-aware alternatives that require guest cooperation and accessibility. We show that these existing approaches are a poor match for monitoring and managing (virtual) systems in the cloud due to their dependence on guest cooperation and operational health, and their growing lifecycle management overheads in the cloud. In this work, we first present Near Field Monitoring (NFM), our non-intrusive, out-of-band cloud monitoring and analytics approach that is designed based on cloud operation principles and to address the limitations of existing techniques. NFM decouples system execution from monitoring and analytics functions by pushing monitoring out of the targets systems' scope. By leveraging and extending VM introspection techniques, our framework provides simple, standard interfaces to monitor running systems in the cloud that require no guest cooperation or modification, and have minimal effect on guest execution. By decoupling monitoring and analytics from target system context, NFM provides ``always-on'' monitoring, even when the target system is unresponsive. NFM also works ``out-of-the-box'' for any cloud instance as it eliminates any need for installing and maintaining agents or hooks in the monitored systems. We describe the end-to-end implementation of our framework with two real-system prototypes based on two virtualization platforms. We discuss the new cloud analytics opportunities enabled by our decoupled execution, monitoring and analytics architecture. We present four applications that are built on top of our framework and show their use for across-time and across-system analytics.
{"title":"Non-intrusive, out-of-band and out-of-the-box systems monitoring in the cloud","authors":"Sahil Suneja, C. Isci, Vasanth Bala, E. D. Lara, Todd W. Mummert","doi":"10.1145/2591971.2592009","DOIUrl":"https://doi.org/10.1145/2591971.2592009","url":null,"abstract":"The dramatic proliferation of virtual machines (VMs) in datacenters and the highly-dynamic and transient nature of VM provisioning has revolutionized datacenter operations. However, the management of these environments is still carried out using re-purposed versions of traditional agents, originally developed for managing physical systems, or most recently via newer virtualization-aware alternatives that require guest cooperation and accessibility. We show that these existing approaches are a poor match for monitoring and managing (virtual) systems in the cloud due to their dependence on guest cooperation and operational health, and their growing lifecycle management overheads in the cloud.\u0000 In this work, we first present Near Field Monitoring (NFM), our non-intrusive, out-of-band cloud monitoring and analytics approach that is designed based on cloud operation principles and to address the limitations of existing techniques. NFM decouples system execution from monitoring and analytics functions by pushing monitoring out of the targets systems' scope. By leveraging and extending VM introspection techniques, our framework provides simple, standard interfaces to monitor running systems in the cloud that require no guest cooperation or modification, and have minimal effect on guest execution. By decoupling monitoring and analytics from target system context, NFM provides ``always-on'' monitoring, even when the target system is unresponsive. NFM also works ``out-of-the-box'' for any cloud instance as it eliminates any need for installing and maintaining agents or hooks in the monitored systems. We describe the end-to-end implementation of our framework with two real-system prototypes based on two virtualization platforms. We discuss the new cloud analytics opportunities enabled by our decoupled execution, monitoring and analytics architecture. We present four applications that are built on top of our framework and show their use for across-time and across-system analytics.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126093184","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}
Although millions of users download and use third-party Android applications from the Google Play store, little information is known on an aggregated level about these applications. We have built PlayDrone, the first scalable Google Play store crawler, and used it to index and analyze over 1,100,000 applications in the Google Play store on a daily basis, the largest such index of Android applications. PlayDrone leverages various hacking techniques to circumvent Google's roadblocks for indexing Google Play store content, and makes proprietary application sources available, including source code for over 880,000 free applications. We demonstrate the usefulness of PlayDrone in decompiling and analyzing application content by exploring four previously unaddressed issues: the characterization of Google Play application content at large scale and its evolution over time, library usage in applications and its impact on application portability, duplicative application content in Google Play, and the ineffectiveness of OAuth and related service authentication mechanisms resulting in malicious users being able to easily gain unauthorized access to user data and resources on Amazon Web Services and Facebook.
{"title":"A measurement study of google play","authors":"N. Viennot, Edward Garcia, Jason Nieh","doi":"10.1145/2591971.2592003","DOIUrl":"https://doi.org/10.1145/2591971.2592003","url":null,"abstract":"Although millions of users download and use third-party Android applications from the Google Play store, little information is known on an aggregated level about these applications. We have built PlayDrone, the first scalable Google Play store crawler, and used it to index and analyze over 1,100,000 applications in the Google Play store on a daily basis, the largest such index of Android applications. PlayDrone leverages various hacking techniques to circumvent Google's roadblocks for indexing Google Play store content, and makes proprietary application sources available, including source code for over 880,000 free applications. We demonstrate the usefulness of PlayDrone in decompiling and analyzing application content by exploring four previously unaddressed issues: the characterization of Google Play application content at large scale and its evolution over time, library usage in applications and its impact on application portability, duplicative application content in Google Play, and the ineffectiveness of OAuth and related service authentication mechanisms resulting in malicious users being able to easily gain unauthorized access to user data and resources on Amazon Web Services and Facebook.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115252855","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}
We investigate the IEEE 1901 MAC protocol, the dominant protocol for high data rate power-line communications. 1901 employs a CSMA/CA mechanism similar to - but much more complex than - the backoff mechanism of 802.11. Because of this extra complexity, and although this mechanism is the only widely used MAC layer for power-line networks, there are few analytical results on its performance. We propose a model for the 1901 MAC that comes in the form of a single fixed-point equation for the collision probability. We prove that this equation admits a unique solution, and we evaluate the accuracy of our model by using simulations.
{"title":"Performance analysis of MAC for power-line communications","authors":"C. Vlachou, A. Banchs, J. Herzen, Patrick Thiran","doi":"10.1145/2591971.2592033","DOIUrl":"https://doi.org/10.1145/2591971.2592033","url":null,"abstract":"We investigate the IEEE 1901 MAC protocol, the dominant protocol for high data rate power-line communications. 1901 employs a CSMA/CA mechanism similar to - but much more complex than - the backoff mechanism of 802.11. Because of this extra complexity, and although this mechanism is the only widely used MAC layer for power-line networks, there are few analytical results on its performance. We propose a model for the 1901 MAC that comes in the form of a single fixed-point equation for the collision probability. We prove that this equation admits a unique solution, and we evaluate the accuracy of our model by using simulations.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122408529","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}
Running multiple instances of the MapReduce framework concurrently in a multicluster system or datacenter enables data, failure, and version isolation, which is attractive for many organizations. It may also provide some form of performance isolation, but in order to achieve this in the face of time-varying workloads submitted to the MapReduce instances, a mechanism for dynamic resource (re-)allocations to those instances is required. In this paper, we present such a mechanism called Fawkes that attempts to balance the allocations to MapReduce instances so that they experience similar service levels. Fawkes proposes a new abstraction for deploying MapReduce instances on physical resources, the MR-cluster, which represents a set of resources that can grow and shrink, and that has a core on which MapReduce is installed with the usual data locality assumptions but that relaxes those assumptions for nodes outside the core. Fawkes dynamically grows and shrinks the active MR-clusters based on a family of weighting policies with weights derived from monitoring their operation. We empirically evaluate Fawkes on a multicluster system and show that it can deliver good performance and balanced resource allocations, even when the workloads of the MR-clusters are very uneven and bursty, with workloads composed from both synthetic and real-world benchmarks.
{"title":"Balanced resource allocations across multiple dynamic MapReduce clusters","authors":"Bogdan Ghit, N. Yigitbasi, A. Iosup, D. Epema","doi":"10.1145/2591971.2591998","DOIUrl":"https://doi.org/10.1145/2591971.2591998","url":null,"abstract":"Running multiple instances of the MapReduce framework concurrently in a multicluster system or datacenter enables data, failure, and version isolation, which is attractive for many organizations. It may also provide some form of performance isolation, but in order to achieve this in the face of time-varying workloads submitted to the MapReduce instances, a mechanism for dynamic resource (re-)allocations to those instances is required. In this paper, we present such a mechanism called Fawkes that attempts to balance the allocations to MapReduce instances so that they experience similar service levels. Fawkes proposes a new abstraction for deploying MapReduce instances on physical resources, the MR-cluster, which represents a set of resources that can grow and shrink, and that has a core on which MapReduce is installed with the usual data locality assumptions but that relaxes those assumptions for nodes outside the core. Fawkes dynamically grows and shrinks the active MR-clusters based on a family of weighting policies with weights derived from monitoring their operation.\u0000 We empirically evaluate Fawkes on a multicluster system and show that it can deliver good performance and balanced resource allocations, even when the workloads of the MR-clusters are very uneven and bursty, with workloads composed from both synthetic and real-world benchmarks.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128758591","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}
M. Shafiq, Jeffrey Erman, Lusheng Ji, A. Liu, Jeffrey Pang, Jia Wang
Mobile network operators have a significant interest in the performance of streaming video on their networks because network dynamics directly influence the Quality of Experience (QoE). However, unlike video service providers, network operators are not privy to the client- or server-side logs typically used to measure key video performance metrics, such as user engagement. To address this limitation, this paper presents the first large-scale study characterizing the impact of cellular network performance on mobile video user engagement from the perspective of a network operator. Our study on a month-long anonymized data set from a major cellular network makes two main contributions. First, we quantify the effect that 31 different network factors have on user behavior in mobile video. Our results provide network operators direct guidance on how to improve user engagement --- for example, improving mean signal-to-interference ratio by 1 dB reduces the likelihood of video abandonment by 2%. Second, we model the complex relationships between these factors and video abandonment, enabling operators to monitor mobile video user engagement in real-time. Our model can predict whether a user completely downloads a video with more than 87% accuracy by observing only the initial 10 seconds of video streaming sessions. Moreover, our model achieves significantly better accuracy than prior models that require client- or server-side logs, yet we only use standard radio network statistics and/or TCP/IP headers available to network operators.
{"title":"Understanding the impact of network dynamics on mobile video user engagement","authors":"M. Shafiq, Jeffrey Erman, Lusheng Ji, A. Liu, Jeffrey Pang, Jia Wang","doi":"10.1145/2591971.2591975","DOIUrl":"https://doi.org/10.1145/2591971.2591975","url":null,"abstract":"Mobile network operators have a significant interest in the performance of streaming video on their networks because network dynamics directly influence the Quality of Experience (QoE). However, unlike video service providers, network operators are not privy to the client- or server-side logs typically used to measure key video performance metrics, such as user engagement. To address this limitation, this paper presents the first large-scale study characterizing the impact of cellular network performance on mobile video user engagement from the perspective of a network operator. Our study on a month-long anonymized data set from a major cellular network makes two main contributions. First, we quantify the effect that 31 different network factors have on user behavior in mobile video. Our results provide network operators direct guidance on how to improve user engagement --- for example, improving mean signal-to-interference ratio by 1 dB reduces the likelihood of video abandonment by 2%. Second, we model the complex relationships between these factors and video abandonment, enabling operators to monitor mobile video user engagement in real-time. Our model can predict whether a user completely downloads a video with more than 87% accuracy by observing only the initial 10 seconds of video streaming sessions. Moreover, our model achieves significantly better accuracy than prior models that require client- or server-side logs, yet we only use standard radio network statistics and/or TCP/IP headers available to network operators.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116320896","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}
Adversarial Queueing Theory (AQT) has shown that seemingly innocent traffic injection rates might lead to unbounded queues in packet-switched networks - depending on scheduling strategies as well as topological characteristics. Little attention has been given to quantifying these effects in realistic network configurations. In particular, the existing AQT literature makes two unrealistic assumptions: infinite buffers and perfect synchrony. Because finite buffers inherently limit queue sizes, adversarial effects ultimately lead to packet loss which we address in this work. In addition, we study the effect of imperfect network synchronization under the packet loss metric. Our results, using analysis and simulation, indicate that classical AQT examples appear harmless under realistic assumptions but for a novel class of adversaries considerably higher loss can be observed. We introduce this class by giving examples of two new AQT concepts to construct loss-efficient network adversaries. Our analysis proves the robustness of these new adversaries against randomized de-synchronization effects in terms of variable link delays and nodal processing.
{"title":"On the relevance of adversarial queueing theory in practice","authors":"Daniel S. Berger, M. Karsten, J. Schmitt","doi":"10.1145/2591971.2592006","DOIUrl":"https://doi.org/10.1145/2591971.2592006","url":null,"abstract":"Adversarial Queueing Theory (AQT) has shown that seemingly innocent traffic injection rates might lead to unbounded queues in packet-switched networks - depending on scheduling strategies as well as topological characteristics. Little attention has been given to quantifying these effects in realistic network configurations. In particular, the existing AQT literature makes two unrealistic assumptions: infinite buffers and perfect synchrony. Because finite buffers inherently limit queue sizes, adversarial effects ultimately lead to packet loss which we address in this work. In addition, we study the effect of imperfect network synchronization under the packet loss metric. Our results, using analysis and simulation, indicate that classical AQT examples appear harmless under realistic assumptions but for a novel class of adversaries considerably higher loss can be observed. We introduce this class by giving examples of two new AQT concepts to construct loss-efficient network adversaries. Our analysis proves the robustness of these new adversaries against randomized de-synchronization effects in terms of variable link delays and nodal processing.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132576960","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 work studies electricity markets between power grids and microgrids, an emerging paradigm of electric power generation and supply. It is among the first that addresses the economic challenges arising from such grid integration, and represents the first power auction mechanism design that explicitly handles the Unit Commitment Problem (UCP), a key challenge in power grid optimization previously investigated only for centralized cooperative algorithms. The proposed solution leverages a recent result in theoretical computer science that can decompose an optimal fractional (infeasible) solution to NP-hard problems into a convex combination of integral (feasible) solutions. The end result includes randomized power auctions that are (approximately) truthful and computationally efficient, and achieve small approximation ratios for grid-wide social welfare under UCP constraints and temporal demand correlations. Both power markets with grid-to-microgrid and microgrid-to-grid energy sales are studied, with an auction designed for each, under the same randomized power auction framework. Trace driven simulations are conducted to verify the efficacy of the two proposed inter-grid power auctions.
{"title":"Randomized auction design for electricity markets between grids and microgrids","authors":"Linquan Zhang, Zongpeng Li, Chuan Wu","doi":"10.1145/2591971.2591999","DOIUrl":"https://doi.org/10.1145/2591971.2591999","url":null,"abstract":"This work studies electricity markets between power grids and microgrids, an emerging paradigm of electric power generation and supply. It is among the first that addresses the economic challenges arising from such grid integration, and represents the first power auction mechanism design that explicitly handles the Unit Commitment Problem (UCP), a key challenge in power grid optimization previously investigated only for centralized cooperative algorithms. The proposed solution leverages a recent result in theoretical computer science that can decompose an optimal fractional (infeasible) solution to NP-hard problems into a convex combination of integral (feasible) solutions. The end result includes randomized power auctions that are (approximately) truthful and computationally efficient, and achieve small approximation ratios for grid-wide social welfare under UCP constraints and temporal demand correlations. Both power markets with grid-to-microgrid and microgrid-to-grid energy sales are studied, with an auction designed for each, under the same randomized power auction framework. Trace driven simulations are conducted to verify the efficacy of the two proposed inter-grid power auctions.","PeriodicalId":306456,"journal":{"name":"Measurement and Modeling of Computer Systems","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124182810","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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