k-mutual exclusion is an important problem for resource-intensive peer-to-peer applications ranging from aggregation to file downloads. In order to be practically useful, k-mutual exclusion algorithms not only need to be safe and live, but they also need to be fair across hosts. We propose a new solution to the k-mutual exclusion problem that provides a notion of time-based fairness. Specifically, our algorithm attempts to minimize the spread of access time for the critical resource. While a client's access time is the time between it requesting and accessing the resource, the spread is defined as a system-wide metric that measures some notion of the variance of access times across a homogeneous host population, e.g., difference between max and mean. We analytically prove the correctness of our algorithm, and evaluate its fairness experimentally using simulations. Our evaluation under two settings - a LAN setting and a WAN based on the King latency data set - shows even with 100 hosts accessing one resource, the spread of access time is within 15 seconds.
{"title":"Fair K Mutual Exclusion Algorithm for Peer to Peer Systems","authors":"V. Korthikanti, Prateek Mittal, Indranil Gupta","doi":"10.1109/ICDCS.2008.76","DOIUrl":"https://doi.org/10.1109/ICDCS.2008.76","url":null,"abstract":"k-mutual exclusion is an important problem for resource-intensive peer-to-peer applications ranging from aggregation to file downloads. In order to be practically useful, k-mutual exclusion algorithms not only need to be safe and live, but they also need to be fair across hosts. We propose a new solution to the k-mutual exclusion problem that provides a notion of time-based fairness. Specifically, our algorithm attempts to minimize the spread of access time for the critical resource. While a client's access time is the time between it requesting and accessing the resource, the spread is defined as a system-wide metric that measures some notion of the variance of access times across a homogeneous host population, e.g., difference between max and mean. We analytically prove the correctness of our algorithm, and evaluate its fairness experimentally using simulations. Our evaluation under two settings - a LAN setting and a WAN based on the King latency data set - shows even with 100 hosts accessing one resource, the spread of access time is within 15 seconds.","PeriodicalId":240205,"journal":{"name":"2008 The 28th International Conference on Distributed Computing Systems","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124746455","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}
Peer-to-peer (P2P) media streaming quickly emerges as an important application over the Internet. A plethora of approaches have been suggested and implemented to support P2P media streaming. In our study, we first classified existing approaches and studied their characteristics by looking at three important quantities: number of upstream peers (parents), number of downstream peers (children) and average number of links per peer. We find that in existing approaches, peers are assigned with a fixed number of parents without regard to their contributions, measured by the amount of outgoing bandwidths. Obviously, this is an undesirable arrangement as it leads to highly inefficient use of the P2P links. This observation motivates us to model the peer selection process as a cooperative game among peers. This results in a novel peer selection protocol such that the number of upstream peers of a peer is related to its outgoing bandwidth. Specifically, peers with larger outgoing bandwidth are given more parents, which makes them less vulnerable to peer dynamics. Simulation results show that the proposed protocol improves delivery ratio with similar number of links per peer, comparing with existing approaches in a wide range of settings.
{"title":"Game Theoretic Peer Selection for Resilient Peer-to-Peer Media Streaming Systems","authors":"M. Yeung, Yu-Kwong Kwok","doi":"10.1109/ICDCS.2008.69","DOIUrl":"https://doi.org/10.1109/ICDCS.2008.69","url":null,"abstract":"Peer-to-peer (P2P) media streaming quickly emerges as an important application over the Internet. A plethora of approaches have been suggested and implemented to support P2P media streaming. In our study, we first classified existing approaches and studied their characteristics by looking at three important quantities: number of upstream peers (parents), number of downstream peers (children) and average number of links per peer. We find that in existing approaches, peers are assigned with a fixed number of parents without regard to their contributions, measured by the amount of outgoing bandwidths. Obviously, this is an undesirable arrangement as it leads to highly inefficient use of the P2P links. This observation motivates us to model the peer selection process as a cooperative game among peers. This results in a novel peer selection protocol such that the number of upstream peers of a peer is related to its outgoing bandwidth. Specifically, peers with larger outgoing bandwidth are given more parents, which makes them less vulnerable to peer dynamics. Simulation results show that the proposed protocol improves delivery ratio with similar number of links per peer, comparing with existing approaches in a wide range of settings.","PeriodicalId":240205,"journal":{"name":"2008 The 28th International Conference on Distributed Computing Systems","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129698899","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}
With the rapid growth of the Internet, online advertisement plays a more and more important role in the advertising market. One of the current and widely used revenue models for online advertising involves charging for each click based on the popularity of keywords and the number of competing advertisers. This pay-per-click model leaves room for individuals or rival companies to generate false clicks (i.e., click fraud), which pose serious problems to the development of healthy online advertising market. To detect click fraud, an important issue is to detect duplicate clicks over decaying window models, such as jumping windows and sliding windows. Decaying window models can be very helpful in defining and determining click fraud. However, although there are available algorithms to detect duplicates, there is still a lack of practical and effective solutions to detect click fraud in pay-per-click streams over decaying window models. In this paper, we address the problem of detecting duplicate clicks in pay-per-click streams over jumping windows and sliding windows, and are the first that propose two innovative algorithms that make only one pass over click streams and require significantly less memory space and operations. GBF algorithm is built on group Bloom filters which can process click streams over jumping windows with small number of sub-windows, while TBF algorithm is based on a new data structure called timing Bloom filter that detects click fraud over sliding windows and jumping windows with large number of sub-windows. Both GBF algorithm and TBF algorithm have zero false negative. Furthermore, both theoretical analysis and experimental results show that our algorithms can achieve low false positive rate when detecting duplicate clicks in pay-per-click streams over jumping windows and sliding windows.
{"title":"Detecting Click Fraud in Pay-Per-Click Streams of Online Advertising Networks","authors":"Linfeng Zhang, Y. Guan","doi":"10.1109/ICDCS.2008.98","DOIUrl":"https://doi.org/10.1109/ICDCS.2008.98","url":null,"abstract":"With the rapid growth of the Internet, online advertisement plays a more and more important role in the advertising market. One of the current and widely used revenue models for online advertising involves charging for each click based on the popularity of keywords and the number of competing advertisers. This pay-per-click model leaves room for individuals or rival companies to generate false clicks (i.e., click fraud), which pose serious problems to the development of healthy online advertising market. To detect click fraud, an important issue is to detect duplicate clicks over decaying window models, such as jumping windows and sliding windows. Decaying window models can be very helpful in defining and determining click fraud. However, although there are available algorithms to detect duplicates, there is still a lack of practical and effective solutions to detect click fraud in pay-per-click streams over decaying window models. In this paper, we address the problem of detecting duplicate clicks in pay-per-click streams over jumping windows and sliding windows, and are the first that propose two innovative algorithms that make only one pass over click streams and require significantly less memory space and operations. GBF algorithm is built on group Bloom filters which can process click streams over jumping windows with small number of sub-windows, while TBF algorithm is based on a new data structure called timing Bloom filter that detects click fraud over sliding windows and jumping windows with large number of sub-windows. Both GBF algorithm and TBF algorithm have zero false negative. Furthermore, both theoretical analysis and experimental results show that our algorithms can achieve low false positive rate when detecting duplicate clicks in pay-per-click streams over jumping windows and sliding windows.","PeriodicalId":240205,"journal":{"name":"2008 The 28th International Conference on Distributed Computing Systems","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130125771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Distributed systems usually have many configurable parameters such as those included in common configuration files. Performance of distributed systems is partially dependent on these system configurations. While operators may choose default settings or manually tune parameters based on their experience and intuition, the resulted settings may not be the optimal one for specific services running on the distributed system. In this paper, we formulate the problem of autotuning configurations as a black-box optimization problem. This problem becomes quite challenging since the joint parameter search space is huge and also no explicit relationship between performance and configurations exists. We propose to use a well known evolutionary algorithm called covariance matrix adaptation (CMA) to automatically tune system parameters. We compare CMA algorithm to another existing techniques called smart hill climbing (SHC) and demonstrate that CMA algorithm outperforms SHC algorithm both on synthetic data and in a real system.
{"title":"Autotuning Configurations in Distributed Systems for Performance Improvements Using Evolutionary Strategies","authors":"A. Saboori, Guofei Jiang, Haifeng Chen","doi":"10.1109/ICDCS.2008.11","DOIUrl":"https://doi.org/10.1109/ICDCS.2008.11","url":null,"abstract":"Distributed systems usually have many configurable parameters such as those included in common configuration files. Performance of distributed systems is partially dependent on these system configurations. While operators may choose default settings or manually tune parameters based on their experience and intuition, the resulted settings may not be the optimal one for specific services running on the distributed system. In this paper, we formulate the problem of autotuning configurations as a black-box optimization problem. This problem becomes quite challenging since the joint parameter search space is huge and also no explicit relationship between performance and configurations exists. We propose to use a well known evolutionary algorithm called covariance matrix adaptation (CMA) to automatically tune system parameters. We compare CMA algorithm to another existing techniques called smart hill climbing (SHC) and demonstrate that CMA algorithm outperforms SHC algorithm both on synthetic data and in a real system.","PeriodicalId":240205,"journal":{"name":"2008 The 28th International Conference on Distributed Computing Systems","volume":"476 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127556826","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}
High volume database-driven e-commerce applications demand a cluster-based infrastructure to offers high availability, scalability and fault tolerance. The current J2EE architecture and containers restrict the transparent deployment of applications over database clusters without engineering data access logic into the applications. Our work extends the J2EE architecture to allow transparent deployment of J2EE applications on a database cluster. The key challenge is to load balance read and write queries between the master and replica database instance and yet provide the application with the most recent data in the cluster while enabling service class based query routing. We validate the applicability and effectiveness of the proposed architecture using IBM WebSphere Trade3 stock trading application.
{"title":"J2EE Architecture for Database Cluster-Based High Volume E-Commerce Web Applications","authors":"Vishal S. Batra, Wen-Syan Li, Sumit Negi","doi":"10.1109/ICDCS.2008.105","DOIUrl":"https://doi.org/10.1109/ICDCS.2008.105","url":null,"abstract":"High volume database-driven e-commerce applications demand a cluster-based infrastructure to offers high availability, scalability and fault tolerance. The current J2EE architecture and containers restrict the transparent deployment of applications over database clusters without engineering data access logic into the applications. Our work extends the J2EE architecture to allow transparent deployment of J2EE applications on a database cluster. The key challenge is to load balance read and write queries between the master and replica database instance and yet provide the application with the most recent data in the cluster while enabling service class based query routing. We validate the applicability and effectiveness of the proposed architecture using IBM WebSphere Trade3 stock trading application.","PeriodicalId":240205,"journal":{"name":"2008 The 28th International Conference on Distributed Computing Systems","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116388710","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}
Sriram Lakshmanan, Cheng-Lin Tsao, Raghupathy Sivakumar, K. Sundaresan
In this paper, we focus on securing communication over wireless data networks from malicious eavesdroppers, using smart antennas. While conventional cryptography based approaches focus on hiding the meaning of the information being communicated from the eavesdropper, we consider a complimentary class of strategies that limit knowledge of the existence of the information from the eavesdropper. We profile the performance achievable using simple beamforming strategies using a newly defined metric called exposure region. We then present three strategies within the context of an approach called virtual arrays of physical arrays to significantly improve the exposure region performance of a wireless LAN environment. Using simulations and analysis, we validate and evaluate the proposed strategies.
{"title":"Securing Wireless Data Networks against Eavesdropping using Smart Antennas","authors":"Sriram Lakshmanan, Cheng-Lin Tsao, Raghupathy Sivakumar, K. Sundaresan","doi":"10.1109/ICDCS.2008.87","DOIUrl":"https://doi.org/10.1109/ICDCS.2008.87","url":null,"abstract":"In this paper, we focus on securing communication over wireless data networks from malicious eavesdroppers, using smart antennas. While conventional cryptography based approaches focus on hiding the meaning of the information being communicated from the eavesdropper, we consider a complimentary class of strategies that limit knowledge of the existence of the information from the eavesdropper. We profile the performance achievable using simple beamforming strategies using a newly defined metric called exposure region. We then present three strategies within the context of an approach called virtual arrays of physical arrays to significantly improve the exposure region performance of a wireless LAN environment. Using simulations and analysis, we validate and evaluate the proposed strategies.","PeriodicalId":240205,"journal":{"name":"2008 The 28th International Conference on Distributed Computing Systems","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126632722","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}
Recently, opportunistic routing (OR) has been widely used to compensate for the low packet delivery ratio of multi-hop wireless networks. Previous works either provide heuristic solutions without optimality analysis, or assume that unlimited retransmission is available for delivering a data packet. In this paper, we apply OR to a utility-based routing where the successful delivery of a data packet generates benefit. The objective is to maximize utility, defined as a function of benefit and cost of transmission. As the link reliability of each relay determines eventual packet delivery and hence utility, OR offers the ability to increase reliability through opportunistic relays. We explore the optimality of utility-based routing through OR without allowing retransmission, and observe that the optimal scheme requires exhaustive searching of all paths from source to destination. We then propose a heuristic solution to select relays and determine priorities among them. Finally, we provide distributed implementations for both schemes. Simulations on NS-2 and our customized simulator are conducted to verify the effectiveness of the heuristic compared with the optimal.
{"title":"Utility-Based Opportunistic Routing in Multi-Hop Wireless Networks","authors":"Jie Wu, Mingming Lu, Feng Li","doi":"10.1109/ICDCS.2008.90","DOIUrl":"https://doi.org/10.1109/ICDCS.2008.90","url":null,"abstract":"Recently, opportunistic routing (OR) has been widely used to compensate for the low packet delivery ratio of multi-hop wireless networks. Previous works either provide heuristic solutions without optimality analysis, or assume that unlimited retransmission is available for delivering a data packet. In this paper, we apply OR to a utility-based routing where the successful delivery of a data packet generates benefit. The objective is to maximize utility, defined as a function of benefit and cost of transmission. As the link reliability of each relay determines eventual packet delivery and hence utility, OR offers the ability to increase reliability through opportunistic relays. We explore the optimality of utility-based routing through OR without allowing retransmission, and observe that the optimal scheme requires exhaustive searching of all paths from source to destination. We then propose a heuristic solution to select relays and determine priorities among them. Finally, we provide distributed implementations for both schemes. Simulations on NS-2 and our customized simulator are conducted to verify the effectiveness of the heuristic compared with the optimal.","PeriodicalId":240205,"journal":{"name":"2008 The 28th International Conference on Distributed Computing Systems","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116036237","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 problem of minimum connected dominating set in geometric k-disk graphs. This research is motivated by the problem of virtual backbone construction in wireless ad hoc and sensor networks, where the coverage area of nodes are disks with different radii. We derive the size relationship of any maximal independent set and the minimum connected dominating set in geometric k-disk graphs, and apply it to analyze the performances of two distributed connected dominating set algorithms we propose in this paper. These algorithms have a bounded performance ratio and low communication overhead, and therefore have the potential to be applied in real ad hoc and sensor networks.
{"title":"Distributed Connected Dominating Set Construction in Geometric k-Disk Graphs","authors":"Kai Xing, Wei Cheng, E. Park, S. Rotenstreich","doi":"10.1109/ICDCS.2008.39","DOIUrl":"https://doi.org/10.1109/ICDCS.2008.39","url":null,"abstract":"In this paper, we study the problem of minimum connected dominating set in geometric k-disk graphs. This research is motivated by the problem of virtual backbone construction in wireless ad hoc and sensor networks, where the coverage area of nodes are disks with different radii. We derive the size relationship of any maximal independent set and the minimum connected dominating set in geometric k-disk graphs, and apply it to analyze the performances of two distributed connected dominating set algorithms we propose in this paper. These algorithms have a bounded performance ratio and low communication overhead, and therefore have the potential to be applied in real ad hoc and sensor networks.","PeriodicalId":240205,"journal":{"name":"2008 The 28th International Conference on Distributed Computing Systems","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133441915","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}
As distributed real-time applications gain in popularity, a key challenge is to allocate resources so that diverse real-time requirements (including non-real-time applications), distributed application components and varying workloads can all be accommodated without violating timeliness constraints. We examine the problem of resource allocation in distributed soft real-time systems, where both network and CPU resources are consumed. The timeliness constraints of applications are expressed through utility functions, which compute "benefit" as a function of end-to-end latency. We present LLA (Lagrangian Latency Assignment), a scalable and efficient distributed algorithm which maximizes aggregate utility by computing an optimal trade-off between end-to-end latency and allocated resources. The algorithm runs continuously and adapts to both workload and resource variations. LLA is guaranteed to converge if the workload and resource requirements stabilize. We evaluate the quality of results and convergence characteristics under various workloads, using both simulation and real-world experimentation.
{"title":"Online Optimization for Latency Assignment in Distributed Real-Time Systems","authors":"C. Lumezanu, S. Bhola, Mark Astley","doi":"10.1109/ICDCS.2008.102","DOIUrl":"https://doi.org/10.1109/ICDCS.2008.102","url":null,"abstract":"As distributed real-time applications gain in popularity, a key challenge is to allocate resources so that diverse real-time requirements (including non-real-time applications), distributed application components and varying workloads can all be accommodated without violating timeliness constraints. We examine the problem of resource allocation in distributed soft real-time systems, where both network and CPU resources are consumed. The timeliness constraints of applications are expressed through utility functions, which compute \"benefit\" as a function of end-to-end latency. We present LLA (Lagrangian Latency Assignment), a scalable and efficient distributed algorithm which maximizes aggregate utility by computing an optimal trade-off between end-to-end latency and allocated resources. The algorithm runs continuously and adapts to both workload and resource variations. LLA is guaranteed to converge if the workload and resource requirements stabilize. We evaluate the quality of results and convergence characteristics under various workloads, using both simulation and real-world experimentation.","PeriodicalId":240205,"journal":{"name":"2008 The 28th International Conference on Distributed Computing Systems","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133794743","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 considers a multi-query optimization issue for distributed similarity query processing, which attempts to exploit the dependencies in the derivation of a query evaluation plan. To the best of our knowledge, this is the first work investigating a multi- query optimization technique for distributed similarity query processing (MDSQ). Four steps are incorporated in our MDSQ algorithm. First when a number of query requests(i.e., m query vectors and m radiuses) are simultaneously submitted by users, then a cost-based dynamic query scheduling(DQS) procedure is invoked to quickly and effectively identify the correlation among the query spheres (requests). After that, an index-based vector set reduction is performed at data node level in parallel. Finally, a refinement process of the candidate vectors is conducted to get the answer set. The proposed method includes a cost-based dynamic query scheduling, a Start-Distance(SD)-based load balancing scheme, and an index-based vector set reduction algorithm. The experimental results validate the efficiency and effectiveness of the algorithm in minimizing the response time and increasing the parallelism of I/O and CPU.
{"title":"Multi-query Optimization for Distributed Similarity Query Processing","authors":"Zhuang Yi, Qing Li, Lei Chen","doi":"10.1109/ICDCS.2008.58","DOIUrl":"https://doi.org/10.1109/ICDCS.2008.58","url":null,"abstract":"This paper considers a multi-query optimization issue for distributed similarity query processing, which attempts to exploit the dependencies in the derivation of a query evaluation plan. To the best of our knowledge, this is the first work investigating a multi- query optimization technique for distributed similarity query processing (MDSQ). Four steps are incorporated in our MDSQ algorithm. First when a number of query requests(i.e., m query vectors and m radiuses) are simultaneously submitted by users, then a cost-based dynamic query scheduling(DQS) procedure is invoked to quickly and effectively identify the correlation among the query spheres (requests). After that, an index-based vector set reduction is performed at data node level in parallel. Finally, a refinement process of the candidate vectors is conducted to get the answer set. The proposed method includes a cost-based dynamic query scheduling, a Start-Distance(SD)-based load balancing scheme, and an index-based vector set reduction algorithm. The experimental results validate the efficiency and effectiveness of the algorithm in minimizing the response time and increasing the parallelism of I/O and CPU.","PeriodicalId":240205,"journal":{"name":"2008 The 28th International Conference on Distributed Computing Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130686597","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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