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Energy efficient media streaming in wireless hybrid peer-to-peer systems

Energy efficient media streaming in wireless hybrid peer-to-...

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10th Workshop on Advances in parallel and distributed Computational Models/22nd ieee International parallel and distributed processing symposium

作者： Yeung, Mark Kai Ho Kwok, Yu-Kwong Univ Hong Kong Pokfulam Rd Hong Kong Hong Kong Peoples R China Colorado State Univ Elect & Comp Engn Ft Collins CO 80523 USA

ISBN: (纸本)9781424416936

With the proliferation of sophisticated wireless devices with more than one network interfaces, it is now possible for the devices to form hybrid wireless networks. Specifically, we consider a hybrid wireless networking scenario in which each device has two heterogeneous wireless network interfaces: a server interface (e.g., a CDMA2000 cellular interface) and a peer interface (e.g., a ieee 802.11g WLAN interface). Our insight is that we could exploit the heterogeneity in energy consumption in such a dual-interface networking capability. In view of the higher energy consumption in using the server interface compared with using the client interface, we propose two novel protocols where neighboring clients form either a master-slave or peer-to-peer relationship to reduce their energy consumption. For the master-slave relationship, each master retrieves media packets from the server and sends them to its slaves via the peer interface. On the other hand, each peer-to-peer relationship consists of one coordinator and at least one helpers. Both coordinator and helpers are responsible for retrieving media packets from the server Our analysis shows that the two proposed relationships reduce the energy consumption of participating clients. Furthermore, the relationships are stable where rational clients would not voluntarily leave and unilaterally deviate from the coalition. We evaluate their performance in homogeneous and heterogeneous client distributions. Simulation results indicate that both relationships improve streaming performance without violating the energy consumption constraints of clients.

关键词： wireless media streaming hybrid wireless networks dual-interface ieee 802.11 CDMA2000 game theory heterogeneous networking coalition utility function peer-to-peer sharing Nash equilibrium

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Dynamic On-Line Allocation of Independent Task onto Heterogeneous Computing Systems to Maximize Load Balancing

Dynamic On-Line Allocation of Independent Task onto Heteroge...

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ieee International symposium on Signal processing and Information Technology

作者： Khalifa, Amal S. Fergany, Tahany A. Ammar, Reda A. Tolba, Mohammed F. Ain Shams Univ Fac Comp & Informat Sci Cairo Egypt Univ New Haven Dept Comp Sci West Haven CT USA

ISBN: (纸本)9781424435548

Heterogeneous computing (HC) Systems use different types of machines, networks, and interfaces to coordinate the execution of various task components which have different computational requirements. this variation in tasks requirements as well as machine capabilities has created a very strong need for developing Mapping techniques to decide on which task should be moved to where and when, to optimize some system performance criteria. the existing dynamic heuristics for mapping tasks in HC systems works either on-line (immediate) or in Batch mode. In batch mode, tasks are collected into a set that is examined for mapping at prescheduled times called mapping events. On contrast, on-line mode algorithms map a task onto a machine as soon as it arrives at the mapper. In this paper, we propose an on-line mapping algorithm which is called the Maximum Load Balance, or for short the MLB. It tries to minimize the makespan by maximizing the load balancing of the target system. At each task arrival, the MLB algorithm examines all the machines in the HC suite one by one looking for the one that gives the maximum system balance among all possible mappings. In contrast with the opportunistic load balancing (OLB) heuristic;which assigns a task to the machine that becomes ready next, the MLB takes into consideration both the availability of the machine as well as the execution time of the task on that machine. We have conducted a large number of Simulation experiments to investigate the improvement in performance achieved by the MLB over the OLB heuristic. the comparison was carried out with respect to a set of metrics while considering a variety of system heterogeneity modes.

关键词： distributed Systems Heterogonous Computing Meta-task Dynamic Mapping immediate mode Allocation Load balancing

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A scalable parallel force-directed graph layout algorithm

A scalable parallel force-directed graph layout algorithm

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8th Eurographics symposium on parallel Graphics and Visualization, EGPGV 2008

作者： Tikhonova, Anna Ma, Kwan-Liu Lab University of California at Davis United States

ISBN: (纸本)9783905674040

Understanding the structure, dynamics, and evolution of large graphs is becoming increasingly important in a variety of fields. the demand for visual tools to aid in this process is rising accordingly. Yet, many algorithms that create good representations of small and medium-sized graphs do not scale to larger graph sizes. the exploitation of the massive computational power provided by parallel and distributed computing is a natural progression for handling important problems such as large graph layout. In this paper, we present a scalable parallel graph layout algorithm based on the force-directed model. Our algorithm requires minimal pre-processing and achieves scalability by conducting the layout computation in stages - a portion of the graph at a time, and decreasing the amount of inter-processor communication as the layout computation progresses. We provide the implementation details of our algorithm, evaluate its performance and scalability, and compare the visual quality of the resulting drawings against some of the classic and the fastest algorithms for the layout of general graphs. © 2008 Eurographics Association. All rights reserved.

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Efficient parallel adaptive beamforming algorithm for planar array system

Efficient parallel adaptive beamforming algorithm for planar...

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International symposium on Antennas, Propagation and EM theory (ISAPE)

作者： Fei Huang Wei-xing Sheng Xiao-feng Ma Department of Communication Engineering Nanjing University of Science and Technology of PLA China

For large planar adaptive arrays, the computational load and the terabyte data transmission are two challenging problems in the implementation of adaptive beamforming system. this paper considers the problem of designing an efficient parallel adaptive algorithm using the two dimensional(2D) planar array. this paper extends the efficient parallel adaptive beamforming algorithm based on LCMV to adaptive 2D sensor array processing. the proposed 2D parallel adaptive algorithm can be easily implemented in distributed-parallel-processing system due to its parallel structure. It can save the data transmission as well as computing cost.

关键词： Array signal processing Planar arrays Adaptive arrays Sensor arrays Adaptive algorithm Antenna arrays Data communication Partitioning algorithms Algorithm design and analysis Costs

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Time-critical distributed visualization with fault tolerance

Time-critical distributed visualization with fault tolerance

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8th Eurographics symposium on parallel Graphics and Visualization, EGPGV 2008

作者： Gao, Jinzhu Liu, Huadong Huang, Jian Beck, Micah Wu, Qishi Moore, Terry Kohl, James University of Minnesota Morris United States University of Tennessee United States University of Tennessee United States University of Tennessee United States University of Memphis United States University of Tennessee United States Oak Ridge National Laboratory

ISBN: (纸本)9783905674040

It is often desirable or necessary to perform scientific visualization in geographically remote locations, away from the centralized data storage systems that hold massive amounts of scientific results. the larger such scientific datasets are, the less practical it is to move these datasets to remote locations for collaborators. In such scenarios, efficient remote visualization solutions can be crucial. Yet the use of distributed or heterogeneous computing resources raises several challenges for large-scale data visualization. Algorithms must be robust and incorporate advanced load balancing and scheduling techniques. In this paper, we propose a time-critical remote visualization system that can be deployed over distributed and heterogeneous computing resources. We introduce an "importance" metric to measure the need for processing each data partition based on its degree of contribution to the final visual image. Factors contributing to this metric include specific application requirements, value distributions inside the data partition, and viewing parameters. We incorporate "visibility" in our measurement as well so that empty or invisible blocks will not be processed. Guided by the data blocks’ importance values, our dynamic scheduling scheme determines the rendering priority for each visible block. that is, more important blocks will be rendered first. In time-critical scenarios, our scheduling algorithm also dynamically reduces the level-of-detail for the less important regions so that visualization can be finished in a user-specified time limit with highest possible image quality. this system enables interactive sharing of visualization results. To evaluate the performance of this system, we present a case study using a 250 Gigabyte dataset on 170 distributed processors. © 2008 Eurographics Association. All rights reserved.

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Efficient parallel Adaptive Beamforming Algorithm for Planar Array System

Efficient Parallel Adaptive Beamforming Algorithm for Planar...

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the 8th International symposium on Antennas,Propagation and EM theory（ISAPE2008）

作者： Fei Huang,Wei-xing Sheng,Xiao-feng Ma Department of Communication Engineering,Nanjing University of Science and Technology,210094,China

For large planar adaptive arrays,the computational load and the terabyte data transmission are two challenging problems in the implementation of adaptive beamforming *** paper considers the problem of designing an efficient parallel adaptive algorithm using the two dimensional(2D) planar *** paper extends the efficient parallel adaptive beamforming algorithm based on LCMV to adaptive 2D sensor array *** proposed 2D parallel adaptive algorithm can be easily implemented in distributed-parallel-processing system due to its parallel *** can save the data transmission as well as computing cost.

关键词： Efficient parallel Adaptive Beamforming Algorithm for Planar Array System

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Exploiting object-based parallelism on multi-core multi-processor clusters

Exploiting object-based parallelism on multi-core multi-proc...

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8th International Conference on parallel and distributed Computing, Applications and Technologies

作者： Liu, Xuli Univ Nebraska Kearney Kearney NE 68849 USA

ISBN: (纸本)9780769530499

Programming using message passing or distributed shared memory are the two major parallel programming paradigms on clusters. However these two models have high programming complexity, produce less maintainable parallel code, and are not suitable for multi-core multiprocessor clusters. While object-oriented programming is dominant in serial programming, it has not been well exploited in parallel programming. In this paper we propose an innovative automatic parallelization framework that employs past experience to parallelize serial programs and outputs the parallel code in the form of objects. Supported by a data-driven runtime environment, each parallel task is managed as a thread, exploiting the multiple processing cores on a cluster node. Based on this proposed framework, we have implemented a proof-of-concept parallelizer called PJava to parallelize Java code. the performance benefit of this framework is evaluated through case studies by comparing the execution time of the automatically generated PJava code to that of handcrafted JOPI (a Java dialect of MPI) code.

关键词： parallel programming

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parallel database join operations in heterogeneous grids

Parallel database join operations in heterogeneous grids

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8th International Conference on parallel and distributed Computing, Applications and Technologies

作者： Mach, Werner Schikuta, Erich Univ Vienna Dept Knowledge & Business Engn A-1010 Vienna Austria

ISBN: (纸本)9780769530499

this paper presents an analytical comparison of parallel join algorithms in a generalized multiprocessor framework and a simplified, heterogenous Grid Environment. We develop a concise but comprehensive analytical model for the well-known Hash Join algorithm and compare it to Nested-Loop and Sort-Merge Join algorithms. We concentrate on a limited number of characteristic parameters to keep the analytical model clear and focused. We justify that a meaningful model can be built upon only three characteristic parameter sets, describing node processing performance, the I/O and the disk bandwidth, which are the parameters for the optimization the Grid workflow by a smart brokerage mechanism. Based on these results the paper proves that by a smart enhancement of the algorithms exploiting the specifics of the Grid the known performance results for a homogenous multi-processor architecture are to be revised for a heterogenous Grid environment.

关键词： Hash functions

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Improved genetic algorithms and list scheduling techniques for independent task scheduling in distributed systems

Improved genetic algorithms and list scheduling techniques f...

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8th International Conference on parallel and distributed Computing, Applications and Technologies

作者： Loukopoulos, thanasis Lampsas, Petros Sigalas, Panos Uni Thessaly Dept Comp & Commun Engn Glavani 37 Volos 38221 Greece Technol Educ Inst Lamia Dept Informat & Comp Technol Lamia G-35100 Greece

ISBN: (纸本)9780769530499

Given a set of tasks with certain characteristics, e.g., data size, estimated execution time and a set Of processing nodes with their own parameters, the goal of task scheduling is to allocate tasks at nodes so that the total makespan is minimized. the problem has been studied under various assumptions concerning task and node parameters with the resulting problem statements usually being NP-complete. List scheduling (LS) heuristics such as MaxMin and MinMin together with genetic algorithms (GAs) were applied in the past to find solutions. In this paper we investigate new heuristics for both the LS and the GA paradigm with the specific aim of improving the performance of the standard algorithms when task computations involve large data transfers. Experimental results under various environment assumptions illustrate the merits of the new algorithms.

关键词： Genetic algorithms

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Optimizing multiple queries on scientific datasets with partial replicas 07

Optimizing multiple queries on scientific datasets with part...

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8th ieee/ACM International Conference on Grid Computing

作者： Weng, Li Catalyurek, Umit Kurc, Tahsin Agrawal, Gagan Saltz, Joel Ohio State Univ Dept Comp Sci & Engn Columbus OH 43210 USA Ohio State Univ Dept Biomed Informat Columbus OH 43210 USA

ISBN: (纸本)9781424415595

We propose strategies to efficiently execute a query workload, which consists of multiple related queries submitted against a scientific dataset, on a distributed-memory system in the presence of partial dataset replicas. Partial replication re-organizes and re-distributes one or more subsets of a dataset across the storage system to reduce I/O overheads and increase I/O parallelism. Our work targets a class of queries, called range queries, in which the query predicate specifies lower and upper bounds on the values of all or a subset of attributes of a dataset. Data elements whose attribute values fall into the specified bounds are retrieved from the dataset. If we think of the attributes of a dataset forming multi-dimensional space, where each attribute corresponds to one of the dimensions, a range query defines a bounding box in this multidimensional space. We evaluate our strategies in two scenarios involving range queries. the first scenario represents the case in which queries have overlapping regions of interest, such as those arising from an exploratory analysis of the dataset by multiple users. In the second scenario, queries represent adjacent rectilinear sections that capture an irregular subregion in the multi-dimensional space. this scenario corresponds to a case where the user wants to query and retrieve a spatial feature from the dataset. We propose cost models and an algorithm for optimizing such queries. Our results using queries for subsetting and analysis of medical image datasets show that effective use of partial replicas can result in reduction in query execution times.

关键词： Information retrieval Data engineering Cost function parallel processing Data analysis Hurricanes Computer science Biomedical engineering Biomedical informatics Application software

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