Many large-scale utility computing infrastructures comprise heterogeneous hardware and software resources. This raises the need for scalable resource selection services, which identify resources that match application requirements, and can potentially be assigned to these applications. We present a fully decentralized resource selection algorithm by which resources autonomously select themselves when their attributes match a query. An application specifies what it expects from a resource by means of a conjunction of (attribute, value-range) pairs, which are matched against the attribute values of resources. We show that our solution scales in the number of resources as well as in the number of attributes, while being relatively insensitive to churn and other membership changes such as node failures.
{"title":"Autonomous Resource Selection for Decentralized Utility Computing","authors":"Paolo Costa, Jeff Napper, G. Pierre, M. Steen","doi":"10.1109/ICDCS.2009.70","DOIUrl":"https://doi.org/10.1109/ICDCS.2009.70","url":null,"abstract":"Many large-scale utility computing infrastructures comprise heterogeneous hardware and software resources. This raises the need for scalable resource selection services, which identify resources that match application requirements, and can potentially be assigned to these applications. We present a fully decentralized resource selection algorithm by which resources autonomously select themselves when their attributes match a query. An application specifies what it expects from a resource by means of a conjunction of (attribute, value-range) pairs, which are matched against the attribute values of resources. We show that our solution scales in the number of resources as well as in the number of attributes, while being relatively insensitive to churn and other membership changes such as node failures.","PeriodicalId":387968,"journal":{"name":"2009 29th IEEE International Conference on Distributed Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126946375","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}
A. Arefin, Md Yusuf Sarwar Uddin, Indranil Gupta, K. Nahrstedt
Users and administrators of large distributed systems are frequently in need of monitoring and management of its various components, data items and resources. Though there exist several distributed query and aggregation systems, the clustered structure of tele-immersive interactive frameworks and their time-sensitive nature and application requirements represent a new class of systems which poses different challenges on this distributed search. Multi-attribute composite range queries are one of the key features in this class. Queries are given in high level descriptions and then transformed into multi-attribute composite range queries. Designing such a query engine with minimum traffic overhead, low service latency, and with static and dynamic nature of large datasets, is a challenging task. In this paper, we propose a general multi-attribute based range query framework, Q-Tree, that provides efficient support for this class of systems. In order to serve efficient queries, Q-Tree builds a single topology-aware tree overlay by connecting the participating nodes in a bottom-up approach, and assigns range intervals on each node in a hierarchical manner. We show the relative strength of Q-Tree by analytically comparing it against P-Tree, P-Ring, Skip-Graph and Chord. With fine-grained load balancing and overlay maintenance, our simulations with PlanetLab traces show that our approach can answer complex queries within a fraction of a second.
{"title":"Q-Tree: A Multi-Attribute Based Range Query Solution for Tele-immersive Framework","authors":"A. Arefin, Md Yusuf Sarwar Uddin, Indranil Gupta, K. Nahrstedt","doi":"10.1109/ICDCS.2009.41","DOIUrl":"https://doi.org/10.1109/ICDCS.2009.41","url":null,"abstract":"Users and administrators of large distributed systems are frequently in need of monitoring and management of its various components, data items and resources. Though there exist several distributed query and aggregation systems, the clustered structure of tele-immersive interactive frameworks and their time-sensitive nature and application requirements represent a new class of systems which poses different challenges on this distributed search. Multi-attribute composite range queries are one of the key features in this class. Queries are given in high level descriptions and then transformed into multi-attribute composite range queries. Designing such a query engine with minimum traffic overhead, low service latency, and with static and dynamic nature of large datasets, is a challenging task. In this paper, we propose a general multi-attribute based range query framework, Q-Tree, that provides efficient support for this class of systems. In order to serve efficient queries, Q-Tree builds a single topology-aware tree overlay by connecting the participating nodes in a bottom-up approach, and assigns range intervals on each node in a hierarchical manner. We show the relative strength of Q-Tree by analytically comparing it against P-Tree, P-Ring, Skip-Graph and Chord. With fine-grained load balancing and overlay maintenance, our simulations with PlanetLab traces show that our approach can answer complex queries within a fraction of a second.","PeriodicalId":387968,"journal":{"name":"2009 29th IEEE International Conference on Distributed Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122381364","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}
Event stream processing (ESP) applications target the real-time processing of huge amounts of data. Events traverse a graph of stream processing operators where the information of interest is extracted. As these applications gain popularity, the requirements for scalability, availability, and dependability increase. In terms of dependability and availability, many applications require a precise recovery, i.e., a guarantee that the outputs during and after a recovery would be the same as if the failure that triggered recovery had never occurred. Existing solutions for precise recovery induce prohibitive latency costs, either by requiring continuous checkpoint or logging (in a passive replication approach) or perfect synchronization between replicas executing the same operations (in an active replication approach). We introduce a novel technique to guarantee precise recovery for ESP applications while minimizing the latency costs as compared to traditional approaches. The technique minimizes latencies via speculative execution in a distributed system. In terms of scalability, the key component of our approach is a modified software transactional memory that provides not only the speculation capabilities but also optimistic parallelization for costly operations.
{"title":"Minimizing Latency in Fault-Tolerant Distributed Stream Processing Systems","authors":"Andrey Brito, C. Fetzer, P. Felber","doi":"10.1109/ICDCS.2009.35","DOIUrl":"https://doi.org/10.1109/ICDCS.2009.35","url":null,"abstract":"Event stream processing (ESP) applications target the real-time processing of huge amounts of data. Events traverse a graph of stream processing operators where the information of interest is extracted. As these applications gain popularity, the requirements for scalability, availability, and dependability increase. In terms of dependability and availability, many applications require a precise recovery, i.e., a guarantee that the outputs during and after a recovery would be the same as if the failure that triggered recovery had never occurred. Existing solutions for precise recovery induce prohibitive latency costs, either by requiring continuous checkpoint or logging (in a passive replication approach) or perfect synchronization between replicas executing the same operations (in an active replication approach). We introduce a novel technique to guarantee precise recovery for ESP applications while minimizing the latency costs as compared to traditional approaches. The technique minimizes latencies via speculative execution in a distributed system. In terms of scalability, the key component of our approach is a modified software transactional memory that provides not only the speculation capabilities but also optimistic parallelization for costly operations.","PeriodicalId":387968,"journal":{"name":"2009 29th IEEE International Conference on Distributed Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121522724","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 distributed object systems, including RMI and CORBA, enable object-oriented programs to be easily dis- tributed across a network, achieving acceptable performance usually requires client-specific optimization of server inter- faces, making such systems difficult to maintain and evolve. Automatic optimization techniques, including Batched Fu- tures and Communication Restructuring, do not work as well as hand optimization. This paper presents Batched Remote Method Invocation (BRMI), a language-level technique for clients to specify explicit batches of operations on remote objects. We have implemented BRMI for Java as an extension of RMI, with support for batches with array cursors, custom exception handling, conditionals and loops. BRMI allows common design patterns, including Data Transfer Objects and Remote Object Facade, to be constructed on the fly by clients. The performance benefits of batching operations are well known; our evaluation focuses on the usability of explicit batches, but we also confirm that BRMI outperforms RMI and scales significantly better when clients make multi- ple remote calls. The applicability of BRMI is demonstrated by rewriting third-party RMI client applications to use BRMI.
{"title":"Explicit Batching for Distributed Objects","authors":"E. Tilevich, W. Cook, Yang Jiao","doi":"10.1109/ICDCS.2009.39","DOIUrl":"https://doi.org/10.1109/ICDCS.2009.39","url":null,"abstract":"Although distributed object systems, including RMI and CORBA, enable object-oriented programs to be easily dis- tributed across a network, achieving acceptable performance usually requires client-specific optimization of server inter- faces, making such systems difficult to maintain and evolve. Automatic optimization techniques, including Batched Fu- tures and Communication Restructuring, do not work as well as hand optimization. This paper presents Batched Remote Method Invocation (BRMI), a language-level technique for clients to specify explicit batches of operations on remote objects. We have implemented BRMI for Java as an extension of RMI, with support for batches with array cursors, custom exception handling, conditionals and loops. BRMI allows common design patterns, including Data Transfer Objects and Remote Object Facade, to be constructed on the fly by clients. The performance benefits of batching operations are well known; our evaluation focuses on the usability of explicit batches, but we also confirm that BRMI outperforms RMI and scales significantly better when clients make multi- ple remote calls. The applicability of BRMI is demonstrated by rewriting third-party RMI client applications to use BRMI.","PeriodicalId":387968,"journal":{"name":"2009 29th IEEE International Conference on Distributed Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116775385","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}
Busy networks today cannot afford to log all traffic traversing them, and consequently many network-monitoring applications make due with coarse traffic summaries. In this talk we will describe an approach we have developed to improve the fidelity of these traffic summaries, by coordinating the monitoring performed by the network's routers so as to achieve network-wide monitoring goals while respecting each router's processing constraints. We will also describe our use of traffic summaries to detect a variety of stealthy network abuses—e.g., file-sharing traffic masquerading on other application ports, "hit-list" scans and malware propagation, data exfiltration by spyware, and botnet command-and-control traffic—and even to identify the origin of epidemic malware spreads.
{"title":"Better Architectures and New Security Applications for Network Monitoring","authors":"M. Reiter","doi":"10.1109/ICDCS.2009.85","DOIUrl":"https://doi.org/10.1109/ICDCS.2009.85","url":null,"abstract":"Busy networks today cannot afford to log all traffic traversing them, and consequently many network-monitoring applications make due with coarse traffic summaries. In this talk we will describe an approach we have developed to improve the fidelity of these traffic summaries, by coordinating the monitoring performed by the network's routers so as to achieve network-wide monitoring goals while respecting each router's processing constraints. We will also describe our use of traffic summaries to detect a variety of stealthy network abuses—e.g., file-sharing traffic masquerading on other application ports, \"hit-list\" scans and malware propagation, data exfiltration by spyware, and botnet command-and-control traffic—and even to identify the origin of epidemic malware spreads.","PeriodicalId":387968,"journal":{"name":"2009 29th IEEE International Conference on Distributed Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131871261","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}
Content sharing through vehicle-to-vehicle communication can help people find their interested content on the road. In VANETs, due to limited contact duration and unreliable wireless connection, a vehicle can get the useful data only when it meets another vehicle and the encountered vehicle has the exactly matched data. However, the probability of such case is very low. To improve the performance of content sharing in intermittently connected VANETs, we propose a novel P2P content sharing scheme called Roadcast. Roadcast ensures popular data is more likely to be shared with other vehicles so that the overall query delay and the query hit ratio can be improved. Roadcast consists of two components called popularity aware content retrieval and popularity aware data replacement. The popularity aware content retrieval scheme makes use of Information Retrieval (IR) techniques to find the most relevant and popular data towards user's query. The popularity aware data replacement algorithm ensures that the density of different data is proportional to their popularity in the system steady state, which firmly obeys the optimal "square-root" replication rule. Results based on real city map and real traffic model show that Roadcast outperforms other content sharing schemes in VANETs.
{"title":"Roadcast: A Popularity Aware Content Sharing Scheme in VANETs","authors":"Yang Zhang, J. Zhao, G. Cao","doi":"10.1145/1740437.1740439","DOIUrl":"https://doi.org/10.1145/1740437.1740439","url":null,"abstract":"Content sharing through vehicle-to-vehicle communication can help people find their interested content on the road. In VANETs, due to limited contact duration and unreliable wireless connection, a vehicle can get the useful data only when it meets another vehicle and the encountered vehicle has the exactly matched data. However, the probability of such case is very low. To improve the performance of content sharing in intermittently connected VANETs, we propose a novel P2P content sharing scheme called Roadcast. Roadcast ensures popular data is more likely to be shared with other vehicles so that the overall query delay and the query hit ratio can be improved. Roadcast consists of two components called popularity aware content retrieval and popularity aware data replacement. The popularity aware content retrieval scheme makes use of Information Retrieval (IR) techniques to find the most relevant and popular data towards user's query. The popularity aware data replacement algorithm ensures that the density of different data is proportional to their popularity in the system steady state, which firmly obeys the optimal \"square-root\" replication rule. Results based on real city map and real traffic model show that Roadcast outperforms other content sharing schemes in VANETs.","PeriodicalId":387968,"journal":{"name":"2009 29th IEEE International Conference on Distributed Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121991786","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}
Mobile disk arrays, disk arrays located in mobile data centers, are crucial for mobile applications such as disaster recovery. Due to their unusual application domains, mobile disk arrays face several new challenges including harsh operating environments, very limited power supply, and extremely small number of spare disks. Consequently, data reconstruction schemes for mobile disk arrays must be performance-driven, reliability-aware, and energy-efficient. In this paper, we develop a flash assisted data reconstruction strategy called CORE (collaboration-oriented reconstruction) on top of a hybrid disk array architecture, where hard disks and flash disks collaborate to shorten data reconstruction time, alleviate performance degradation during disk recovery. Experimental results demonstrate that CORE noticeably improves the performance and energy-efficiency over existing schemes.
{"title":"Collaboration-Oriented Data Recovery for Mobile Disk Arrays","authors":"T. Xie, Abhinav Sharma","doi":"10.1109/ICDCS.2009.13","DOIUrl":"https://doi.org/10.1109/ICDCS.2009.13","url":null,"abstract":"Mobile disk arrays, disk arrays located in mobile data centers, are crucial for mobile applications such as disaster recovery. Due to their unusual application domains, mobile disk arrays face several new challenges including harsh operating environments, very limited power supply, and extremely small number of spare disks. Consequently, data reconstruction schemes for mobile disk arrays must be performance-driven, reliability-aware, and energy-efficient. In this paper, we develop a flash assisted data reconstruction strategy called CORE (collaboration-oriented reconstruction) on top of a hybrid disk array architecture, where hard disks and flash disks collaborate to shorten data reconstruction time, alleviate performance degradation during disk recovery. Experimental results demonstrate that CORE noticeably improves the performance and energy-efficiency over existing schemes.","PeriodicalId":387968,"journal":{"name":"2009 29th IEEE International Conference on Distributed Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126838947","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}
V. Ciriani, S. Vimercati, S. Foresti, S. Jajodia, S. Paraboschi, P. Samarati
The balance between privacy and utility is a classical problem with an increasing impact on the design of modern information systems. On the one side it is crucial to ensure that sensitive information is properly protected; on the other side, the impact of protection on the workload must be limited as query efficiency and system performance remain a primary requirement. We address this privacy/efficiency balance proposing an approach that, starting from a flexible definition of confidentiality constraints on a relational schema, applies encryption on information in a parsimonious way and mostly relies on fragmentation to protect sensitive associations among attributes. Fragmentation is guided by workload considerations so to minimize the cost of executing queries over fragments. We discuss the minimization problem when fragmenting data and provide a heuristic approach to its solution.
{"title":"Fragmentation Design for Efficient Query Execution over Sensitive Distributed Databases","authors":"V. Ciriani, S. Vimercati, S. Foresti, S. Jajodia, S. Paraboschi, P. Samarati","doi":"10.1109/ICDCS.2009.52","DOIUrl":"https://doi.org/10.1109/ICDCS.2009.52","url":null,"abstract":"The balance between privacy and utility is a classical problem with an increasing impact on the design of modern information systems. On the one side it is crucial to ensure that sensitive information is properly protected; on the other side, the impact of protection on the workload must be limited as query efficiency and system performance remain a primary requirement. We address this privacy/efficiency balance proposing an approach that, starting from a flexible definition of confidentiality constraints on a relational schema, applies encryption on information in a parsimonious way and mostly relies on fragmentation to protect sensitive associations among attributes. Fragmentation is guided by workload considerations so to minimize the cost of executing queries over fragments. We discuss the minimization problem when fragmenting data and provide a heuristic approach to its solution.","PeriodicalId":387968,"journal":{"name":"2009 29th IEEE International Conference on Distributed Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116225058","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}
Modern data centers usually have computing resources sized to handle expected peak demand, but average demand is generally much lower than peak. This means that the systems in the data center usually operate at very low utilization rates. Past techniques have exploited this fact to achieve significant power savings, but they generally focus on centrally managed, throughput-oriented systems that process a single fine-grained request stream. We propose a more general solution — a technique to save power by dynamically migrating virtual machines and packing them onto fewer physical machines when possible. We call our scheme Power-Aware Domain Distribution (PADD). In this paper, we report on simulation results for PADD and demonstrate that the power and performance changes from using PADD are primarily dependent on how much buffering or reserve capacity it maintains. Our adaptive buffering scheme achieves energy savings within 7% of the idealized system that has no performance penalty. Our results also show that we can achieve an energy savings up to 70% with fewer than 1% of the requests violating their service level agreements.
{"title":"PADD: Power Aware Domain Distribution","authors":"M. Lim, F. Rawson, T. Bletsch, V. Freeh","doi":"10.1109/ICDCS.2009.47","DOIUrl":"https://doi.org/10.1109/ICDCS.2009.47","url":null,"abstract":"Modern data centers usually have computing resources sized to handle expected peak demand, but average demand is generally much lower than peak. This means that the systems in the data center usually operate at very low utilization rates. Past techniques have exploited this fact to achieve significant power savings, but they generally focus on centrally managed, throughput-oriented systems that process a single fine-grained request stream. We propose a more general solution — a technique to save power by dynamically migrating virtual machines and packing them onto fewer physical machines when possible. We call our scheme Power-Aware Domain Distribution (PADD). In this paper, we report on simulation results for PADD and demonstrate that the power and performance changes from using PADD are primarily dependent on how much buffering or reserve capacity it maintains. Our adaptive buffering scheme achieves energy savings within 7% of the idealized system that has no performance penalty. Our results also show that we can achieve an energy savings up to 70% with fewer than 1% of the requests violating their service level agreements.","PeriodicalId":387968,"journal":{"name":"2009 29th IEEE International Conference on Distributed Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114995350","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}
W. J. Jeon, Kyungtae Kang, R. Campbell, K. Nahrstedt
The recent development of high-speed data transmission over wireless networks enables multimedia broadcasting service to mobile users. Multimedia broadcasting service involves interactions among different system and network components, so it is crucial for the service provider to verify the correctness of system/service model and design, and their behaviors before a new type of service is deployed. However, due to limitations of using network simulations or scaled experimental testbeds, there has been none of research on such verification and simulation framework in 3G broadcasting networks. Therefore, we propose a simulation and analysis framework for multimedia broadcasting service over wireless networks. With concrete modeling of wireless physical channel, network, and data processing on a client device, it enables the prediction of various interesting system parameters and perceived quality of multimedia streams to users. Different models of system and network components can be plugged easily in our simulation framework for further extensions. Using this framework, we analyze the processing performance for decoding scalable videos on mobile devices in CDMA2000 wireless networks.
{"title":"Simulation Framework and Performance Analysis of Multimedia Broadcasting Service over Wireless Networks","authors":"W. J. Jeon, Kyungtae Kang, R. Campbell, K. Nahrstedt","doi":"10.1109/ICDCS.2009.49","DOIUrl":"https://doi.org/10.1109/ICDCS.2009.49","url":null,"abstract":"The recent development of high-speed data transmission over wireless networks enables multimedia broadcasting service to mobile users. Multimedia broadcasting service involves interactions among different system and network components, so it is crucial for the service provider to verify the correctness of system/service model and design, and their behaviors before a new type of service is deployed. However, due to limitations of using network simulations or scaled experimental testbeds, there has been none of research on such verification and simulation framework in 3G broadcasting networks. Therefore, we propose a simulation and analysis framework for multimedia broadcasting service over wireless networks. With concrete modeling of wireless physical channel, network, and data processing on a client device, it enables the prediction of various interesting system parameters and perceived quality of multimedia streams to users. Different models of system and network components can be plugged easily in our simulation framework for further extensions. Using this framework, we analyze the processing performance for decoding scalable videos on mobile devices in CDMA2000 wireless networks.","PeriodicalId":387968,"journal":{"name":"2009 29th IEEE International Conference on Distributed Computing Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128444685","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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