Pub Date : 2014-12-01DOI: 10.1109/PCCC.2014.7017056
Qian Yu, WeiTao Weng, Kai Zhang, Kai Lei, Kuai Xu
Sina Weibo has become an increasingly critical social media in China for sharing latest news, marketing new products, and discussing controversial issues. The rising importance of Sina Weibo on the society makes it very important to understand “what”, “when”, “who” on hot topics that are being continuously tweeted and searched by millions of active users. In this paper, we develop a systematic approach to characterize temporal distribution of hot topics searched by Sina Weibo users over a four-month time-span and to uncover correlated hot topics that are not only tweeted by the same users, but also appear in the similar set of tweet messages. We analyze real-time Sina Weibo tweet data streams and study volume correlations and temporal gaps between user searches and tweeting activities on hot topics. In addition, we examine the correlations between hot topic searches on social media and on search engines to understand hot topics and user behaviors across different platforms. Given the challenges of analyzing massive amount of tweet data, we explore Hadoop MapReduce framework to effectively process millions of tweets from the collected data-sets, and quantify the performance benefits of MapReduce on analyzing tweet streams. To the best of our knowledge, this paper is the first effort to characterize temporal search patterns of hot topics on Sina Weibo and to study their correlations with tweeting data streams as well as search engine statistics.
{"title":"Hot topic analysis and content mining in social media","authors":"Qian Yu, WeiTao Weng, Kai Zhang, Kai Lei, Kuai Xu","doi":"10.1109/PCCC.2014.7017056","DOIUrl":"https://doi.org/10.1109/PCCC.2014.7017056","url":null,"abstract":"Sina Weibo has become an increasingly critical social media in China for sharing latest news, marketing new products, and discussing controversial issues. The rising importance of Sina Weibo on the society makes it very important to understand “what”, “when”, “who” on hot topics that are being continuously tweeted and searched by millions of active users. In this paper, we develop a systematic approach to characterize temporal distribution of hot topics searched by Sina Weibo users over a four-month time-span and to uncover correlated hot topics that are not only tweeted by the same users, but also appear in the similar set of tweet messages. We analyze real-time Sina Weibo tweet data streams and study volume correlations and temporal gaps between user searches and tweeting activities on hot topics. In addition, we examine the correlations between hot topic searches on social media and on search engines to understand hot topics and user behaviors across different platforms. Given the challenges of analyzing massive amount of tweet data, we explore Hadoop MapReduce framework to effectively process millions of tweets from the collected data-sets, and quantify the performance benefits of MapReduce on analyzing tweet streams. To the best of our knowledge, this paper is the first effort to characterize temporal search patterns of hot topics on Sina Weibo and to study their correlations with tweeting data streams as well as search engine statistics.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"34 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133008489","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}
Pub Date : 2014-12-01DOI: 10.1109/PCCC.2014.7017031
W. Zhou, Yun Gao, Jizhong Han, Zhiyong Xu
In this paper, we propose Marbor, a novel graph data processing framework to analyze the large-scale data in social network services. It develops an efficient graph organization model to minimize the costs of graph data accesses and reduce the memory consumption. In addition, we present a novel control message method in Marbor to improve the synchronization iterations performance. During the graph data processing, in each iteration, it analyzes the relationships among tasks and forwards the tasks to the next iteration with control messages, so no synchronization operations are used. We compare Marbor with other graph processing methods on several large-scale real world SNS datasets with two widely used applications, and the results show that Marbor outperforms the current mechanisms.
{"title":"Marbor: A novel large-scale graph data storage and processing framework","authors":"W. Zhou, Yun Gao, Jizhong Han, Zhiyong Xu","doi":"10.1109/PCCC.2014.7017031","DOIUrl":"https://doi.org/10.1109/PCCC.2014.7017031","url":null,"abstract":"In this paper, we propose Marbor, a novel graph data processing framework to analyze the large-scale data in social network services. It develops an efficient graph organization model to minimize the costs of graph data accesses and reduce the memory consumption. In addition, we present a novel control message method in Marbor to improve the synchronization iterations performance. During the graph data processing, in each iteration, it analyzes the relationships among tasks and forwards the tasks to the next iteration with control messages, so no synchronization operations are used. We compare Marbor with other graph processing methods on several large-scale real world SNS datasets with two widely used applications, and the results show that Marbor outperforms the current mechanisms.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131281879","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}
Pub Date : 2014-12-01DOI: 10.1109/PCCC.2014.7017113
Yimao Wang, Yanmin Zhu, Ruobing Jiang, Juan Li
Wireless sensor networks (WSNs) are gaining popularity in practical monitoring and surveillance applications. Because of the limited energy of sensor nodes, many WSNs work in a low duty cycle mode to effectively extend their network lifetime. However, low duty cycling also decreases transmission efficiency and makes data gathering more challenging. By exploiting the redundancy of in real sensing data, we propose a novel and distributed approach for data gathering in wireless sensor networks, employing the compressed sensing theory. Instead of selecting a fixed sink, all data can be retrieved from an arbitrary node within the network. Moreover, we use sequential observations to dynamically fit the sparsity of various data sets. With extensive simulations, we show that our approach is efficient with tunable accuracy in different node duty cycles.
{"title":"Distributed compressive data gathering in low duty cycled wireless sensor networks","authors":"Yimao Wang, Yanmin Zhu, Ruobing Jiang, Juan Li","doi":"10.1109/PCCC.2014.7017113","DOIUrl":"https://doi.org/10.1109/PCCC.2014.7017113","url":null,"abstract":"Wireless sensor networks (WSNs) are gaining popularity in practical monitoring and surveillance applications. Because of the limited energy of sensor nodes, many WSNs work in a low duty cycle mode to effectively extend their network lifetime. However, low duty cycling also decreases transmission efficiency and makes data gathering more challenging. By exploiting the redundancy of in real sensing data, we propose a novel and distributed approach for data gathering in wireless sensor networks, employing the compressed sensing theory. Instead of selecting a fixed sink, all data can be retrieved from an arbitrary node within the network. Moreover, we use sequential observations to dynamically fit the sparsity of various data sets. With extensive simulations, we show that our approach is efficient with tunable accuracy in different node duty cycles.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131552059","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}
Pub Date : 2014-12-01DOI: 10.1109/PCCC.2014.7017047
Tiantian Ren, Xinli Huang
With the increasing scale of cloud datacenters, the volumes of traffic flows inside a single datacenter become larger. An effective virtual machine (VM) replacement among physical machines (PMs) can improve resource utilization rate and reduce overall network cost in cloud datacenters. In this paper, we propose a Modified Max-Min Ant Colony Optimization (M3ACO) algorithm which can be used to solve the VMs replacement problem. Furthermore, we apply the M3ACO algorithm into a new framework based on Software Defined Network (SDN), which provides an integrated solution for resource optimization problem in cloud datacenters.
{"title":"A modified max-min ant colony optimization algorithm for virtual machines replacement in cloud datacenter§","authors":"Tiantian Ren, Xinli Huang","doi":"10.1109/PCCC.2014.7017047","DOIUrl":"https://doi.org/10.1109/PCCC.2014.7017047","url":null,"abstract":"With the increasing scale of cloud datacenters, the volumes of traffic flows inside a single datacenter become larger. An effective virtual machine (VM) replacement among physical machines (PMs) can improve resource utilization rate and reduce overall network cost in cloud datacenters. In this paper, we propose a Modified Max-Min Ant Colony Optimization (M3ACO) algorithm which can be used to solve the VMs replacement problem. Furthermore, we apply the M3ACO algorithm into a new framework based on Software Defined Network (SDN), which provides an integrated solution for resource optimization problem in cloud datacenters.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123048148","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}
Pub Date : 2014-12-01DOI: 10.1109/PCCC.2014.7017033
Mario J. Illera, S. Sepulveda
A key parameter in the analysis of electronic devices behavior is their current-voltage curve, also known as characteristic curve. This information allows the designer to select the type of components required for a given application in order to obtain an optimal system performance. This paper presents a low-cost and low-power consumption embedded system able to accurately generate the characteristic curve of electronic devices. Microcontroller PIC18F4550 effectively handles different serial communication protocols to exchange data between a Java application running on a computer and different peripheral devices. The firmware within the microcontroller receives data from the Java interface and executes an algorithm to send a series of analog voltages to the element being characterized and it also measures the resultant current for each voltage; then, the pair of data points is sent back to the Java application to build the plot. The resultant data can be exported to a spreadsheet to be further analyzed. We characterized different electronic devices to evaluate the performance of the prototype. Successful repeatability tests and validation of theoretical models with experimental data indicated that the embedded system developed is accurate and reliable.
{"title":"Embedded system based on microcontroller for generating I-V curves of electronic devices","authors":"Mario J. Illera, S. Sepulveda","doi":"10.1109/PCCC.2014.7017033","DOIUrl":"https://doi.org/10.1109/PCCC.2014.7017033","url":null,"abstract":"A key parameter in the analysis of electronic devices behavior is their current-voltage curve, also known as characteristic curve. This information allows the designer to select the type of components required for a given application in order to obtain an optimal system performance. This paper presents a low-cost and low-power consumption embedded system able to accurately generate the characteristic curve of electronic devices. Microcontroller PIC18F4550 effectively handles different serial communication protocols to exchange data between a Java application running on a computer and different peripheral devices. The firmware within the microcontroller receives data from the Java interface and executes an algorithm to send a series of analog voltages to the element being characterized and it also measures the resultant current for each voltage; then, the pair of data points is sent back to the Java application to build the plot. The resultant data can be exported to a spreadsheet to be further analyzed. We characterized different electronic devices to evaluate the performance of the prototype. Successful repeatability tests and validation of theoretical models with experimental data indicated that the embedded system developed is accurate and reliable.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116493640","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}
Pub Date : 2014-12-01DOI: 10.1109/PCCC.2014.7017023
Timothy Matti, Yuntao Zhu, Kuai Xu
Detecting financial fraud is a daunting challenge for banks and credit card companies due to massive amount of transaction data and wide diversity of user behaviors [1]. In recent years social media has demonstrated the capability of crowdsourcing in a broad range of applications, e.g., disseminating breaking news, launching marketing campaigns, and tracking the flu [2], [3], [4]. Inspired by these novel applications, this paper explores the benefits of social media crowdsourcing, in particularly the tweets, re-tweets and comments from Twitter online social network for effectively detecting financial fraud events.
{"title":"Financial fraud detection using social media crowdsourcing","authors":"Timothy Matti, Yuntao Zhu, Kuai Xu","doi":"10.1109/PCCC.2014.7017023","DOIUrl":"https://doi.org/10.1109/PCCC.2014.7017023","url":null,"abstract":"Detecting financial fraud is a daunting challenge for banks and credit card companies due to massive amount of transaction data and wide diversity of user behaviors [1]. In recent years social media has demonstrated the capability of crowdsourcing in a broad range of applications, e.g., disseminating breaking news, launching marketing campaigns, and tracking the flu [2], [3], [4]. Inspired by these novel applications, this paper explores the benefits of social media crowdsourcing, in particularly the tweets, re-tweets and comments from Twitter online social network for effectively detecting financial fraud events.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114816746","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}
Pub Date : 2014-12-01DOI: 10.1109/PCCC.2014.7017092
B. Barrefors, Ying Lu, Shivashis Saha, J. Deogun
Next-generation multiprocessor real-time systems consume less energy at the cost of increased power density. This increase in power density results in high heat density and may affect the reliability and performance of real-time systems. Thus, incorporating maximum temperature constraints in scheduling of real-time task sets is an important challenge. This paper investigates a novel algorithm for thermal-constrained energy-aware partitioning of periodic real-time tasks in heterogeneous multiprocessor systems. When designing our new algorithm, we have applied insights gained from a famous knapsack problem solution. Both simulation and experimental results show that our new branch-and-bound based partitioning algorithm can significantly reduce the total energy consumption of multiprocessor real-time systems.
{"title":"A novel thermal-constrained energy-aware partitioning algorithm for heterogeneous multiprocessor real-time systems","authors":"B. Barrefors, Ying Lu, Shivashis Saha, J. Deogun","doi":"10.1109/PCCC.2014.7017092","DOIUrl":"https://doi.org/10.1109/PCCC.2014.7017092","url":null,"abstract":"Next-generation multiprocessor real-time systems consume less energy at the cost of increased power density. This increase in power density results in high heat density and may affect the reliability and performance of real-time systems. Thus, incorporating maximum temperature constraints in scheduling of real-time task sets is an important challenge. This paper investigates a novel algorithm for thermal-constrained energy-aware partitioning of periodic real-time tasks in heterogeneous multiprocessor systems. When designing our new algorithm, we have applied insights gained from a famous knapsack problem solution. Both simulation and experimental results show that our new branch-and-bound based partitioning algorithm can significantly reduce the total energy consumption of multiprocessor real-time systems.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117173430","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}
Pub Date : 2014-12-01DOI: 10.1109/PCCC.2014.7017082
Z. Zhao, Xuanxuan Wu, Xin Zhang, Jing Zhao, Xiangyang Li
Wireless coexistence is crucial with the explosive development of wireless technologies in recent years. The coexistence issues of IEEE 802.11 b/g and IEEE 802.15.4 have been well studied, however few work focused on 802.11n new features including MIMO, channel bonding and frame aggregation. In this paper, we conducted extensive experiments to understand how 802.11n impact on 802.15.4 and vice versa in a systematic way. We consider primary features of 802.11n both in symmetric and asymmetric scenarios. The goal of our work is to gain more insights into the coexistence issues of 802.11n and 802.15.4 and thus to help protocol design and co-located network deployments.
{"title":"ZigBee vs WiFi: Understanding issues and measuring performances of their coexistence","authors":"Z. Zhao, Xuanxuan Wu, Xin Zhang, Jing Zhao, Xiangyang Li","doi":"10.1109/PCCC.2014.7017082","DOIUrl":"https://doi.org/10.1109/PCCC.2014.7017082","url":null,"abstract":"Wireless coexistence is crucial with the explosive development of wireless technologies in recent years. The coexistence issues of IEEE 802.11 b/g and IEEE 802.15.4 have been well studied, however few work focused on 802.11n new features including MIMO, channel bonding and frame aggregation. In this paper, we conducted extensive experiments to understand how 802.11n impact on 802.15.4 and vice versa in a systematic way. We consider primary features of 802.11n both in symmetric and asymmetric scenarios. The goal of our work is to gain more insights into the coexistence issues of 802.11n and 802.15.4 and thus to help protocol design and co-located network deployments.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115545121","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}
Pub Date : 2014-12-01DOI: 10.1109/PCCC.2014.7017034
Hayala Nepomuceno Curto, A. Ziviani, J. Caetano, Carlos Henrique S. Malab, J. Almeida, H. T. Marques-Neto
The high popularity of human communication based on mobile phone services exhibits different behaviors in different places and time. Large-scale events, such as the FIFA World Cup, create an auspicious atmosphere for the attendees to use such services to share their experiences with relatives and friends. This work characterizes the workload dynamics of a major mobile phone network on different days when major soccer matches took place in Rio de Janeiro, Brazil. We analyze the usage behavior of three profiles of attendees of two major matches of the FIFA 2014 World Cup, including the final between Germany and Argentina on July 13, 2014. We compare these profiles with similar results computed on a dataset of calls and SMS collected on the day of the final match of 2013 Brazilian Cup, which happened at the same stadium of the World Cup final. We note that users of each analyzed profile, i.e. (i) attendees who made cellphone calls and sent SMS messages, (ii) attendees who only made calls, and (iii) attendees who only sent SMS, have different behaviors in different periods of the event.
{"title":"Characterizing the workload dynamics of a mobile phone network during the FIFA 2014 World Cup","authors":"Hayala Nepomuceno Curto, A. Ziviani, J. Caetano, Carlos Henrique S. Malab, J. Almeida, H. T. Marques-Neto","doi":"10.1109/PCCC.2014.7017034","DOIUrl":"https://doi.org/10.1109/PCCC.2014.7017034","url":null,"abstract":"The high popularity of human communication based on mobile phone services exhibits different behaviors in different places and time. Large-scale events, such as the FIFA World Cup, create an auspicious atmosphere for the attendees to use such services to share their experiences with relatives and friends. This work characterizes the workload dynamics of a major mobile phone network on different days when major soccer matches took place in Rio de Janeiro, Brazil. We analyze the usage behavior of three profiles of attendees of two major matches of the FIFA 2014 World Cup, including the final between Germany and Argentina on July 13, 2014. We compare these profiles with similar results computed on a dataset of calls and SMS collected on the day of the final match of 2013 Brazilian Cup, which happened at the same stadium of the World Cup final. We note that users of each analyzed profile, i.e. (i) attendees who made cellphone calls and sent SMS messages, (ii) attendees who only made calls, and (iii) attendees who only sent SMS, have different behaviors in different periods of the event.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124069210","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}
Servers and network contribute about 60% to the total cost of data center in cloud computing. How to efficiently place virtual machines so that the cost can be saved as much as possible, while guaranteeing the quality of service plays a critical role in enhancing the competitiveness of service cloud provider. Considering the heterogeneous servers and the random property of multiple resources requirements of virtual machines, the problem is formulated as a multi-objective nonlinear programming in this paper. Virtual machine cluster with higher traffic is made staying together. This reduces the communication delay while saving the inter-server bandwidth consumption, especially the relatively scarce higher level bandwidth, by exploiting the topology information of data center. At the same time, statistic multiplex and newly defined “similarity” techniques are leveraged to consolidate virtual machines. The violation of resource capacity is kept at any designated minimal probability. Thus the quality of service will not be deteriorated while saving servers and network cost. An offline and an online algorithms are proposed to address this problem. Experiments compared with several baseline algorithms show the validity of the new algorithms: more cost is cut down at less computation effort.
{"title":"SLA aware cost efficient virtual machines placement in cloud computing","authors":"Jiangtao Zhang, Zhixiang He, Hejiao Huang, Xuan Wang, Chonglin Gu, Lingmin Zhang","doi":"10.1109/PCCC.2014.7017101","DOIUrl":"https://doi.org/10.1109/PCCC.2014.7017101","url":null,"abstract":"Servers and network contribute about 60% to the total cost of data center in cloud computing. How to efficiently place virtual machines so that the cost can be saved as much as possible, while guaranteeing the quality of service plays a critical role in enhancing the competitiveness of service cloud provider. Considering the heterogeneous servers and the random property of multiple resources requirements of virtual machines, the problem is formulated as a multi-objective nonlinear programming in this paper. Virtual machine cluster with higher traffic is made staying together. This reduces the communication delay while saving the inter-server bandwidth consumption, especially the relatively scarce higher level bandwidth, by exploiting the topology information of data center. At the same time, statistic multiplex and newly defined “similarity” techniques are leveraged to consolidate virtual machines. The violation of resource capacity is kept at any designated minimal probability. Thus the quality of service will not be deteriorated while saving servers and network cost. An offline and an online algorithms are proposed to address this problem. Experiments compared with several baseline algorithms show the validity of the new algorithms: more cost is cut down at less computation effort.","PeriodicalId":105442,"journal":{"name":"2014 IEEE 33rd International Performance Computing and Communications Conference (IPCCC)","volume":"248 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132817702","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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