2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)最新文献_第6页

Distributed Probabilistic Caching strategy in VANETs through Named Data Networking 基于命名数据网络的VANETs分布式概率缓存策略

2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2016-04-10 DOI: 10.1109/INFCOMW.2016.7562093

Gang Deng, Liwei Wang, Fengchao Li, Rere Li

{"title":"Distributed Probabilistic Caching strategy in VANETs through Named Data Networking","authors":"Gang Deng, Liwei Wang, Fengchao Li, Rere Li","doi":"10.1109/INFCOMW.2016.7562093","DOIUrl":"https://doi.org/10.1109/INFCOMW.2016.7562093","url":null,"abstract":"Named Data Networking (NDN) has natural advantages to greatly overcome the challenges such as rapidly changing topology, short-lived and intermittent connectivity in Vehicular Ad hoc Networks (VANETs), owing to its name-based routing and in-network caching characteristics. However, the caching strategy in the Vehicular NDN, AlwaysCache, in which nodes will cache all solicited contents received or overheard, may waste resources and reduce the cache efficiency. This paper presents a Distributed Probabilistic Caching (DPC) strategy in Vehicular Ad hoc Networks (VANETs) through Named Data Networking (NDN). In DPC, the caching decisions are taken by each node separately and independently. The nodes take decisions considering users' demands mined from collected interest entries, the vehicle's importance obtained from the analysis of the Degree Centrality and the Betweenness Centrality in the ego network, and relative movement of the receiver and the sender. Simulation results from ndnSIM network simulator demonstrate that DPC is superior to AlwaysCache and P(0.5) strategy in cache hit ratio, hop count and delay. In addition, DPC improves the caching efficiency and the content diversity in the network.","PeriodicalId":348177,"journal":{"name":"2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116700028","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}

引用次数: 42

Location-based correlation estimation in social network via Collaborative Learning 基于协同学习的社交网络位置相关性估计

2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2016-04-10 DOI: 10.1109/INFCOMW.2016.7562259

Xiaoyu Zhang, Kai Zhang, Xiao-chun Yun, Shupeng Wang, Xiuguo Bao, Qingsheng Yuan

引用次数: 1

T2CBS: Mining taxi trajectories for customized bus systems T2CBS:为定制公交系统挖掘出租车轨迹

2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2016-04-10 DOI: 10.1109/INFCOMW.2016.7562117

Yan Lyu, Chi-Yin Chow, V. Lee, Yanhua Li, Jia Zeng

{"title":"T2CBS: Mining taxi trajectories for customized bus systems","authors":"Yan Lyu, Chi-Yin Chow, V. Lee, Yanhua Li, Jia Zeng","doi":"10.1109/INFCOMW.2016.7562117","DOIUrl":"https://doi.org/10.1109/INFCOMW.2016.7562117","url":null,"abstract":"A customized bus (CB) system is a new emerging public transportation that provides flexible demand-oriented transit services for city commuters. Existing CB systems encounter two challenges of 1) collecting travel demands and discovering travel patterns effectively and efficiently and 2) planning profitable bus lines based on travel patterns. In this paper, we propose a bus line planning framework, called T2CBS, by taking full advantage of taxi trajectory data. In T2CBS, similar travel demands are discovered from passenger trajectories with a clustering algorithm, and CB stops are deployed at pick-up and drop-off points of trajectory clusters with integer linear programming. To plan profitable CB lines, we propose a profit estimation model, by considering the number of taxi passengers who can be attracted to CB buses. A routing algorithm (CBRouting) and a timetabling algorithm (CBTimetabling) are proposed to generate a CB line that can achieve the maximum profit for each trajectory cluster. We conduct experiments on one-month taxi trajectory data in Nanjing, China. Experimental results demonstrate that our T2CBS can generate CB lines with higher profit compared with baseline methods, and the moderate increase in travel time along the CB lines is significantly dominated by the savings in bus fare.","PeriodicalId":348177,"journal":{"name":"2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131553191","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}

引用次数: 26

Towards the evaluation of a big data-as-a-service model: A decision theoretic approach 面向大数据即服务模型的评估:决策理论方法

2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2016-04-10 DOI: 10.1109/INFCOMW.2016.7562202

Georgios Skourletopoulos, C. Mavromoustakis, P. Chatzimisios, G. Mastorakis, E. Pallis, J. M. Batalla

{"title":"Towards the evaluation of a big data-as-a-service model: A decision theoretic approach","authors":"Georgios Skourletopoulos, C. Mavromoustakis, P. Chatzimisios, G. Mastorakis, E. Pallis, J. M. Batalla","doi":"10.1109/INFCOMW.2016.7562202","DOIUrl":"https://doi.org/10.1109/INFCOMW.2016.7562202","url":null,"abstract":"The rise of large data centers has created new business models, where businesses can lease storage and computing capacity and pay only for the storage they actually use, rather than making the large capital investments needed to construct and provision large-scale computer installations. In this context, investments in big-data computing are rapidly gaining ground, having extraordinary near-term and long-term benefits. The mobile cloud can be considered as a marketplace, where the storage and computing capabilities of the mobile cloud-based system architectures can be leased off. However, cloud storage is not less expensive, only that it incurs operating rather than capital expenses. This paper elaborates on a novel cost analysis model, adopting a non-linear and asymmetric approach. The proposed modelling aims to evaluate the adoption of a big data-as-a-service business model against the traditional high-performance data warehouse appliances that exist in the market in order to inform effective and strategic decision making. The lease of cloud storage is investigated, when developing the mathematical formulas, and the research approach is examined with respect to the cost that derives from the unused storage. Possible upgradation of the storage and the risk of entering into new and accumulated costs in the future are also considered in this study. A quantification tool has been also developed as a proof of concept (PoC), implementing the proposed quantitative model and intending to shed light on the adoption of big data-as-a-service business models.","PeriodicalId":348177,"journal":{"name":"2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128162672","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}

引用次数: 18

Optimal master controller assignment for minimizing flow setup latency in SDN 在SDN中最小化流设置延迟的最优主控制器分配

2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2016-04-10 DOI: 10.1109/INFCOMW.2016.7562113

Dongeun Suh, Jaewook Lee, Seokwon Jang, Sangheon Pack

引用次数: 6

Data-driven large scale network-layer Internet simulation 数据驱动的大规模网络层互联网模拟

2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2016-04-10 DOI: 10.1109/INFCOMW.2016.7562257

M. A. Canbaz

{"title":"Data-driven large scale network-layer Internet simulation","authors":"M. A. Canbaz","doi":"10.1109/INFCOMW.2016.7562257","DOIUrl":"https://doi.org/10.1109/INFCOMW.2016.7562257","url":null,"abstract":"Internet is a spontaneously growing complex system whose large scale structure is affected by many interacting units aimed at optimizing local communication efficiency without a central authority. Very large number of nodes; wide-spread geographical distribution; predominant role of wireless access; mobility; strong presence of internet enabled smart devices, and heterogeneity increases the complexity of the internet tremendously. This immense global entity has not been precisely characterized, even though the building blocks of the Internet as well as the protocols and individual components have been subject to intensive studies for more than two decades. In the absence of accurate maps, researchers rely on a general strategy that consists of acquiring local views of the network from several vantage points and merging these views. Such local views are obtained by measuring a certain number of paths to different destinations, through the use of probes or the analysis of routing tables. Size of the output data after running the simulations on these several vantage points can reach up to terabytes in each simulation. The merging of several of these views provides a sample of a map of the internet [1].","PeriodicalId":348177,"journal":{"name":"2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131714323","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}

引用次数: 0

Quantitative workload analysis and prediction using Google cluster traces 使用谷歌集群跟踪进行定量工作负载分析和预测

2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2016-04-10 DOI: 10.1109/INFCOMW.2016.7562213

Bingwei Liu, Yinan Lin, Yu Chen

{"title":"Quantitative workload analysis and prediction using Google cluster traces","authors":"Bingwei Liu, Yinan Lin, Yu Chen","doi":"10.1109/INFCOMW.2016.7562213","DOIUrl":"https://doi.org/10.1109/INFCOMW.2016.7562213","url":null,"abstract":"Resource allocation efficiency and energy consumption are among the top concerns to today's Cloud data center. Finding the optimal point where users' multiple job requests can be accomplished timely with minimum electricity and hardware cost is one of the key factors for system designers and managers to optimize the system configurations. Understanding the characteristics of the distribution of user task is an essential step for this purpose. At large-scale Cloud Computing data centers, a precise workload prediction will significantly help designers and operators to schedule hardware/software resources and power supplies in a more efficient manner, and make appropriate decisions to upgrade the Cloud system when the workload grows. While a lot of study has been conducted for hypervisor-based Cloud, container-based virtualization is becoming popular because of the low overhead and high efficiency in utilizing computing resources. In this paper, we have studied a set of real-world container data center traces from part of Google's cluster. We investigated the distribution of job duration, waiting time and machine utilization and the number of jobs submitted in a fix time period. Based on the quantitative study, an Ensemble Workload Prediction (EnWoP) method and a novel prediction evaluation parameter called Cloud Workload Correction Rate (C-Rate) have been proposed. The experimental results have verified that the EnWoP method achieved high prediction accuracy and the C-Rate evaluates the prediction methods more objective.","PeriodicalId":348177,"journal":{"name":"2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134324205","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}

引用次数: 28

Fast Content Store Lookup Using Locality-Aware Skip List in Content-Centric Networks 在以内容为中心的网络中使用位置感知跳跃表的快速内容存储查找

2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2016-04-10 DOI: 10.1109/INFCOMW.2016.7562069

Tian Pan, Tao Huang, Jiang Liu, Jiao Zhang, Fan Yang, Shufang Li, Yun-jie Liu

{"title":"Fast Content Store Lookup Using Locality-Aware Skip List in Content-Centric Networks","authors":"Tian Pan, Tao Huang, Jiang Liu, Jiao Zhang, Fan Yang, Shufang Li, Yun-jie Liu","doi":"10.1109/INFCOMW.2016.7562069","DOIUrl":"https://doi.org/10.1109/INFCOMW.2016.7562069","url":null,"abstract":"Today's Internet usage evolves rapidly from host-to-host communication to content dissemination. Content-Centric Networking (CCN) is proposed to embrace this trend by providing in-network caching capability via built-in Content Store (CS). However, to satisfy per-packet queries in high-speed networks, CS suffers a noticeable performance penalty and probably becomes the bottleneck of the entire packet forwarding system. The state-of-the-art adopts skip list as CS's underlying data structure. But, due to its O(logn) search complexity, it still has performance issues. In this work, inspired by the extensively existed temporal and spatial locality in content retrieval, we propose locality-aware skip list for performance improvement. In our design, since a packet is likely to share a prefix with previous packets, the search in the skip list could start directly from near the previously reached node of that prefix. This avoids searches repeatedly starting from the head node thus saves considerable search time. Extensive evaluation shows our design can achieve a 3× speedup over the original design on an ×86 machine.","PeriodicalId":348177,"journal":{"name":"2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133018764","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}

引用次数: 11

Dynamic resource orchestration for multi-task application in heterogeneous mobile cloud computing 异构移动云计算中多任务应用的动态资源编排

2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2016-04-10 DOI: 10.1109/INFCOMW.2016.7562076

Q. Qi, J. Liao, Jingyu Wang, Qi Li, Yufei Cao

{"title":"Dynamic resource orchestration for multi-task application in heterogeneous mobile cloud computing","authors":"Q. Qi, J. Liao, Jingyu Wang, Qi Li, Yufei Cao","doi":"10.1109/INFCOMW.2016.7562076","DOIUrl":"https://doi.org/10.1109/INFCOMW.2016.7562076","url":null,"abstract":"The mobile cloud computing (MCC) that takes wireless access network as transmission medium and uses mobile devices as client becomes the newest evolution trends of cloud computing. When offloading the complicated multi-task application to the MCC environment, each task executes individually in terms of its own computation, storage and bandwidth requirement. Due to user's mobility, the provided resources contain different performance metrics that may affect the destination choice. Nevertheless, these heterogeneous MCC resources lack integrated management and can hardly cooperate with each other. Thus, how to choose the appropriate offload destination and orchestrate the resources for multi-task is a challenging problem. This paper decouples resource control of mobile cloud from user plane, where a centralized controller is responsible for resource orchestration, offload and migration. The resource orchestration is formulated as multi-objective optimal problem that contains the metrics of energy consumption, cost and availability. Finally, a particle swarm algorithm is used to obtain the approximate optimal solutions. Simulation results show that the solutions can hit Pareto optimum of resource orchestration in acceptable time.","PeriodicalId":348177,"journal":{"name":"2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)","volume":"9 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133287748","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}

引用次数: 20

Impact of caching on HTTP Adaptive Streaming decisions: Towards an optimal 缓存对HTTP自适应流决策的影响:走向最佳

2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Pub Date : 2016-04-10 DOI: 10.1109/INFCOMW.2016.7562249

V. Poliakov, L. Sassatelli, D. Saucez

引用次数: 2