%0 Journal Article %J SIGCOMM Comput. Commun. Rev. %D 2012 %T Refactoring Network Infrastructure to Improve Manageability: A Case Study of Home Networking %A Marshini Chetty %A Feamster, Nick %K home networking %K management %K Monitoring %K software defined networking %X Managing a home network is challenging because the underlying infrastructure is so complex. Existing interfaces either hide or expose the network's underlying complexity, but in both cases, the information that is shown does not necessarily allow a user to complete desired tasks. Recent advances in software defined networking, however, permit a redesign of the underlying network and protocols, potentially allowing designers to move complexity further from the user and, in some cases, eliminating it entirely. In this paper, we explore whether the choices of what to make visible to the user in the design of today's home network infrastructure, performance, and policies make sense. We also examine whether new capabilities for refactoring the network infrastructure - changing the underlying system without compromising existing functionality - should cause us to revisit some of these choices. Our work represents a case study of how co-designing an interface and its underlying infrastructure could ultimately improve interfaces for that infrastructure. %B SIGCOMM Comput. Commun. Rev. %V 42 %P 54 - 61 %8 2012/06// %@ 0146-4833 %G eng %U http://doi.acm.org/10.1145/2317307.2317318 %N 3 %0 Conference Paper %B 2011 IEEE 36th Conference on Local Computer Networks (LCN) %D 2011 %T Design methods for Wireless Sensor Network Building Energy Monitoring Systems %A Cho, Inkeun %A Chung-Ching Shen %A Potbhare, S. %A Bhattacharyya, Shuvra S. %A Goldsman,N. %K Analytical models %K application-level interfacing behavior %K building energy monitoring system %K Buildings %K dataflow technique %K embedded sensor node %K energy analysis method %K Energy consumption %K energy management systems %K Energy resolution %K IEEE 802.15.4 MAC functionality %K Monitoring %K OPTIMIZATION %K wireless sensor network %K Wireless sensor networks %K WSNBEMS %K Zigbee %X In this paper, we present a new energy analysis method for evaluating energy consumption of embedded sensor nodes at the application level and the network level. Then we apply the proposed energy analysis method to develop new energy management schemes in order to maximize lifetime for Wireless Sensor Network Building Energy Monitoring Systems (WSNBEMS). At the application level, we develop a new design approach that uses dataflow techniques to model the application-level interfacing behavior between the processor and sensors on an embedded sensor node. At the network level, we analyze the energy consumption of the IEEE 802.15.4 MAC functionality. Based on our techniques for modeling and energy analysis, we have implemented an optimized WSNBEMS for a real building, and validated our energy analysis techniques through measurements on this implementation. The performance of our implementation is also evaluated in terms of monitoring accuracy and energy consumption savings. We have demonstrated that by applying the proposed scheme, system lifetime can be improved significantly without affecting monitoring accuracy. %B 2011 IEEE 36th Conference on Local Computer Networks (LCN) %P 974 - 981 %8 2011 %G eng %0 Conference Paper %B 2010 Proceedings IEEE INFOCOM %D 2010 %T On Computing Compression Trees for Data Collection in Wireless Sensor Networks %A Li,Jian %A Deshpande, Amol %A Khuller, Samir %K Approximation algorithms %K Base stations %K Communications Society %K Computer networks %K Computer science %K computing compression trees %K Costs %K data collection %K Data communication %K data compression %K designing algorithms %K Educational institutions %K Entropy %K graph concept %K Monitoring %K Protocols %K trees (mathematics) %K weakly connected dominating sets %K Wireless sensor networks %X We address the problem of efficiently gathering correlated data from a wireless sensor network, with the aim of designing algorithms with provable optimality guarantees, and understanding how close we can get to the known theoretical lower bounds. Our proposed approach is based on finding an optimal or a near-optimal compression tree for a given sensor network: a compression tree is a directed tree over the sensor network nodes such that the value of a node is compressed using the value of its parent. We focus on broadcast communication model in this paper, but our results are more generally applicable to a unicast communication model as well. We draw connections between the data collection problem and a previously studied graph concept called weakly connected dominating sets, and we use this to develop novel approximation algorithms for the problem. We present comparative results on several synthetic and real-world datasets showing that our algorithms construct near-optimal compression trees that yield a significant reduction in the data collection cost. %B 2010 Proceedings IEEE INFOCOM %I IEEE %P 1 - 9 %8 2010/03/14/19 %@ 978-1-4244-5836-3 %G eng %R 10.1109/INFCOM.2010.5462035 %0 Conference Paper %B IEEE 25th International Conference on Data Engineering, 2009. ICDE '09 %D 2009 %T Web Monitoring 2.0: Crossing Streams to Satisfy Complex Data Needs %A Roitman,H. %A Gal,A. %A Raschid, Louiqa %K Bandwidth %K complex client information need %K Data Delivery %K Data engineering %K database management systems %K Educational institutions %K Internet %K Mashups %K mashups generation %K Monitoring %K multiple information source %K offline algorithmic solution %K Portals %K PROBES %K Profiles %K Query processing %K scalability %K scheduling %K volatile information stream %K Web 2.0 %K Web Monitoring %X Web monitoring 2.0 supports the complex information needs of clients who probe multiple information sources and generate mashups by integrating across these volatile streams. A proxy that aims at satisfying multiple customized client profiles will face a scalability challenge in trying to maximize the number of clients served while at the same time fully satisfying complex client needs. In this paper, we introduce an abstraction of complex execution intervals, a combination of time intervals and information streams, to capture complex client needs. Given some budgetary constraints (e.g., bandwidth), we present offline algorithmic solutions for the problem of maximizing completeness of capturing complex profiles. %B IEEE 25th International Conference on Data Engineering, 2009. ICDE '09 %I IEEE %P 1215 - 1218 %8 2009/04/29/March %@ 978-1-4244-3422-0 %G eng %R 10.1109/ICDE.2009.204 %0 Conference Paper %B IEEE 24th International Conference on Data Engineering, 2008. ICDE 2008 %D 2008 %T Online Filtering, Smoothing and Probabilistic Modeling of Streaming data %A Kanagal,B. %A Deshpande, Amol %K Data analysis %K data streaming %K declarative query %K dynamic probabilistic model %K Filtering %K Global Positioning System %K hidden Markov models %K Monitoring %K Monte Carlo methods %K Noise generators %K Noise measurement %K online filtering %K particle filter %K particle filtering (numerical methods) %K probabilistic database view %K probability %K Real time systems %K real-time application %K relational database system %K Relational databases %K sequential Monte Carlo algorithm %K Smoothing methods %K SQL %X In this paper, we address the problem of extending a relational database system to facilitate efficient real-time application of dynamic probabilistic models to streaming data. We use the recently proposed abstraction of model-based views for this purpose, by allowing users to declaratively specify the model to be applied, and by presenting the output of the models to the user as a probabilistic database view. We support declarative querying over such views using an extended version of SQL that allows for querying probabilistic data. Underneath we use particle filters, a class of sequential Monte Carlo algorithms, to represent the present and historical states of the model as sets of weighted samples (particles) that are kept up-to-date as new data arrives. We develop novel techniques to convert the queries on the model-based view directly into queries over particle tables, enabling highly efficient query processing. Finally, we present experimental evaluation of our prototype implementation over several synthetic and real datasets, that demonstrates the feasibility of online modeling of streaming data using our system and establishes the advantages of tight integration between dynamic probabilistic models and databases. %B IEEE 24th International Conference on Data Engineering, 2008. ICDE 2008 %I IEEE %P 1160 - 1169 %8 2008/04/07/12 %@ 978-1-4244-1836-7 %G eng %R 10.1109/ICDE.2008.4497525 %0 Conference Paper %B IEEE INFOCOM 2002. Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings %D 2002 %T Clustering and server selection using passive monitoring %A Andrews,M. %A Shepherd,B. %A Srinivasan, Aravind %A Winkler,P. %A Zane,F. %K client assignment %K client-server systems %K clustering %K content servers %K Delay %K distributed system %K Educational institutions %K Internet %K IP addresses %K Monitoring %K network conditions %K Network servers %K Network topology %K optimal content server %K passive monitoring %K server selection %K Space technology %K TCPIP %K Transport protocols %K Web pages %K Web server %K Webmapper %X We consider the problem of client assignment in a distributed system of content servers. We present a system called Webmapper for clustering IP addresses and assigning each cluster to an optimal content server. The system is passive in that the only information it uses comes from monitoring the TCP connections between the clients and the servers. It is also flexible in that it makes no a priori assumptions about network topology and server placement and it can react quickly to changing network conditions. We present experimental results to evaluate the performance of Webmapper. %B IEEE INFOCOM 2002. Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies. Proceedings %I IEEE %V 3 %P 1717- 1725 vol.3 - 1717- 1725 vol.3 %8 2002/// %@ 0-7803-7476-2 %G eng %R 10.1109/INFCOM.2002.1019425 %0 Journal Article %J IEEE Transactions on Parallel and Distributed Systems %D 1998 %T Critical path profiling of message passing and shared-memory programs %A Hollingsworth, Jeffrey K %K Computer Society %K Concurrent computing %K critical path computation %K critical path profile %K critical path zeroing %K distributed processing %K distributed shared memory systems %K Instruments %K Message passing %K Monitoring %K online algorithm %K online critical path profiling %K Parallel algorithms %K program bottlenecks %K Runtime %K runtime nontrace-based algorithm %K runtime overhead %K shared-memory programs %K system monitoring %K Time measurement %K Yarn %X We introduce a runtime, nontrace-based algorithm to compute the critical path profile of the execution of message passing and shared-memory parallel programs. Our algorithm permits starting or stopping the critical path computation during program execution and reporting intermediate values. We also present an online algorithm to compute a variant of critical path, called critical path zeroing, that measures the reduction in application execution time that improving a selected procedure will have. Finally, we present a brief case study to quantify the runtime overhead of our algorithm and to show that online critical path profiling can be used to find program bottlenecks %B IEEE Transactions on Parallel and Distributed Systems %V 9 %P 1029 - 1040 %8 1998/10// %@ 1045-9219 %G eng %N 10 %R 10.1109/71.730530 %0 Journal Article %J IEEE Transactions on Software Engineering %D 1998 %T Modeling and evaluating design alternatives for an on-line instrumentation system: a case study %A Waheed, A. %A Rover, D. T %A Hollingsworth, Jeffrey K %K alternative system configurations %K Application software %K batch-and-forward %K collect-and-forward %K Computer aided software engineering %K design alternatives %K design decisions %K Feedback %K IBM SP-2 platform %K Instruments %K massively parallel processing %K model-based evaluation approach %K Monitoring %K multiprocessing programs %K on-line instrumentation system %K Paradyn parallel performance measurement tool %K PARALLEL PROCESSING %K Real time systems %K scalability characteristics %K software metrics %K software tools %K Space technology %K symmetric multiprocessors %K system architectures %K system monitoring %K System testing %K task scheduling policies %K tool developers %K tree forwarding configuration %K Workstations %X This paper demonstrates the use of a model-based evaluation approach for instrumentation systems (ISs). The overall objective of this study is to provide early feedback to tool developers regarding IS overhead and performance; such feedback helps developers make appropriate design decisions about alternative system configurations and task scheduling policies. We consider three types of system architectures: network of workstations (NOW), symmetric multiprocessors (SMP), and massively parallel processing (MPP) systems. We develop a Resource OCCupancy (ROCC) model for an on-line IS for an existing tool and parameterize it for an IBM SP-2 platform. This model is simulated to answer several “what if” questions regarding two policies to schedule instrumentation data forwarding: collect-and-forward (CF) and batch-and-forward (BF). In addition, this study investigates two alternatives for forwarding the instrumentation data: direct and binary tree forwarding for an MPP system. Simulation results indicate that the BF policy can significantly reduce the overhead and that the tree forwarding configuration exhibits desirable scalability characteristics for MPP systems. Initial measurement-based testing results indicate more than 60 percent reduction in the direct IS overhead when the BF policy was added to Paradyn parallel performance measurement tool %B IEEE Transactions on Software Engineering %V 24 %P 451 - 470 %8 1998/06// %@ 0098-5589 %G eng %N 6 %R 10.1109/32.689402 %0 Conference Paper %B Proceedings of the 1996 ACM/IEEE Conference on Supercomputing, 1996 %D 1996 %T Modeling, Evaluation, and Testing of Paradyn Instrumentation System %A Waheed, A. %A Rover, D. T %A Hollingsworth, Jeffrey K %K Distributed control %K Feedback %K High performance computing %K Instruments %K Monitoring %K Real time systems %K Software measurement %K Software systems %K Software testing %K System testing %X This paper presents a case study of modeling, evaluating, and testing the data collection services (called an instrumentation system) of the Paradyn parallel performance measurement tool using well-known performance evaluation and experiment design techniques. The overall objective of the study is to use modeling- and simulation-based evaluation to provide feedback to the tool developers to help them choose system configurations and task scheduling policies that can significantly reduce the data collection overheads. We develop and parameterize a resource occupancy model for the Paradyn instrumentation system (IS) for an IBM SP-2 platform. This model is parameterized with a measurement-based workload characterization and subsequently used to answer several "what if" questions regarding configuration options and two policies to schedule instrumentation system tasks: collect-and-forward (CF) and batch-and-forward (BF) policies. Simulation results indicate that the BF policy can significantly reduce the overheads. Based on this feedback, the BF policy was implemented in the Paradyn IS as an option to manage the data collection. Measurement-based testing results obtained from this enhanced version of the Paradyn IS are reported in this paper and indicate more than 60% reduction in the direct IS overheads when the BF policy is used. %B Proceedings of the 1996 ACM/IEEE Conference on Supercomputing, 1996 %I IEEE %P 18 - 18 %8 1996/// %@ 0-89791-854-1 %G eng %R 10.1109/SUPERC.1996.183524