22546900
An Efficient Motion Vector Composition Scheme for Arbitrary Frame Down-Sampling Video Transcoder
A new motion vector composition scheme, which we call spatial dominant vector selection (SDVS), for arbitrary down-sampling of precoded video using cascaded pixel domain transcoder is presented. The SDVS uses the existing relationship between pixels of a frame and its reference frame(s) via motion vectors and selects a dominant motion vector from a set of candidate vectors to minimize prediction errors. Compared with the existing methods, experimental results show performance gain, in terms of both quality and bit rate, with reduced computation. We also propose a refinement method that adaptively adjusts the search range to further improve the performance at marginal cost
5790802
Object-oriented symbol management in syntax-directed compiler systems
Each symbol in a source program has a series of attributes that govern the operations performed on it. In this paper, we explore object-oriented techniques for representing the attributes of symbols and translating the operations performed on them. This approach is shown superior in memory and run-time speed to the procedural style traditionally used for writing compilers. We demonstrate object-oriented symbol management in a compiler for an arithmetic subset of C. We have used C++ --- a single-dispatching language --- to implement the same, but we emphasize the need for multiple dispatching to develop programs in a heavily-object-oriented style.
537233
Evolutionary Multimodal Optimization Revisited
We revisit a class of multimodal function optimizations using evolutionary algorithms reformulated into a multiobjective framework where previous implementations have needed niching/sharing to ensure diversity. In this paper, we use a steady-state multiobjective algorithm which preserves diversity without niching to produce diverse sampling of the Pareto-front with significantly lower computational effort.
24684227
Adaptive Control of Anytime Algorithm Parameters
6342150
Frame based fair multiprocessor scheduler: a fast fair algorithm for real-time embedded systems
This paper presents frame based fair multiprocessor scheduler (FBFMS) which provides accurate real-time proportional fair scheduling for a set of dynamic tasks on a symmetric multiprocessor environment with O(1) scheduling overhead. FBFMS meets these seemingly contradictory goals by applying the benefits of virtual time round-robin scheduling mechanism along with a frame based scheduling approach. Simulation results show that the algorithm provides 2.5 to 26 times speedup (over O(lg n) complexity schedulers) with distortion in fairness less than 1% in most cases, and less than 15% in the worst case.
39741624
An Efficient Technique for Dynamic Slicing of Concurrent Java Programs
Program slice has many applications such as program debugging, testing, maintenance and complexity measurement. We propose a new dynamic program slicing technique for concurrent Java programs that is more efficient than the related algorithms. We introduce the notion of Concurrent Program Dependence Graph (CPDG). Our algorithm uses CPDG as the intermediate representation and is based on marking and unmarking the edges in the CPDG as and when the dependencies arise and cease during run-time. Our approach eliminates the use of trace files and is more efficient than the existing algorithms.
47199334
Computation Hierarchy for In-Network Processing
In this paper we explore the network level architecture of distributed sensor systems that perform in-network processing. We propose a system with heterogeneous nodes that organizes into a hierarchical structure dictated by the computational capabilities. The presence of high-performance nodes amongst a sea of resource-constrained nodes exposes new tradeoffs for the efficient implementation of network-wide applications. Our experiments show that even for a low relative density of resource-constrained nodes to high-performance nodes there are certain gains in performance for a heterogeneous and hierarchical network over a homogeneous one. The introduction of hierarchy enables partitioning of the application into sub-tasks that can be mapped onto the heterogeneous nodes in the network in multiple ways. We analyze the tradeoffs between the execution time of the application, accuracy of the output produced and the overall energy consumption of the network for the different mapping of the sub-tasks onto the heterogeneous nodes. We evaluate the performance and energy consumption of a typical sensor network application of target tracking via beamforming and line of bearing (LOB) calculations on the different nodes. Our experiments also include the study of the overall performance and energy consumption of the LOB calculation using two different types of resource constrained sensor nodes (MICA and MICA2 nodes) and show how these metrics are affected by changes in the node architecture and operation. Our results indicate that when using MICA motes as resource-constrained nodes, 85% of the time on average the hierarchical network outperforms a homogeneous network for approximately the same energy budget. When using MICA2 motes as resource-constrained nodes, 54% of the time the hierarchical network performs better than a homogeneous network with approximately the same energy budget.
262403
Collaboration and multimedia authoring on mobile devices
This paper introduces adaptation-aware editing and progressive update propagation, two novel mechanisms that enable authoring multimedia content and collaborative work on mobile devices. Adaptation-aware editing enables editing content that was adapted to reduce download time to the mobile device. Progressive update propagation reduces the time for propagating content generated at the mobile device by transmitting either a fraction of the modifications or transcoded versions thereof.With application-aware editing and progressive update propagation, an object present at a mobile device is characterized not only by a particular version, as in conventional replication, but also by a particular fidelity. We demonstrate that replication models can be extended to account for fidelity independently of the mechanisms used for concurrency control and consistency maintenance. As a result, the two techniques described in this paper can easily be added to any replication protocol, whether optimistic or pessimistic.We report on our experience implementing adaptation-aware editing and progressive update propagation. Experiments with two multimedia applications, an email reader and a presentation software package, show that both mechanisms can be added with modest programming effort and achieve substantial reductions in upload and download latencies.
7841699
Dynamic data fusion for future sensor networks
DFuse is an architectural framework for dynamic application-specified data fusion in sensor networks. It bridges an important abstraction gap for developing advanced fusion applications that takes into account the dynamic nature of applications and sensor networks. Elements of the DFuse architecture include a fusion API, a distributed role assignment algorithm that dynamically adapts the placement of the application task graph on the network, and an abstraction migration facility that aids such dynamic role assignment. Experimental evaluations show that the API has low overhead, and simulation results show that the role assignment algorithm significantly increases the network lifetime over static placement.
13974246
Decentralized failure diagnosis of discrete event systems
By decentralized diagnosis we mean diagnosis using multiple diagnosers, each possessing its own set of sensors, without involving any communication among diagnosers or to any coordinators. The notion of decentralized diagnosis is formalized by introducing the notion of codiagnosability that requires that a failure be detected by one of the diagnosers within a bounded delay. Algorithms of complexity polynomial in the size of the system and the nonfault specification are provided for: 1) testing codiagnosability, 2) computing the bound in delay of diagnosis, 3) offline synthesis of individual diagnosers, and 4) online diagnosis using them. The notion of codiagnosability and the above algorithms are initially presented in a setting of a specification language (violation of which represents a fault) and are later specialized to the case where faults are modeled as the occurrences of certain events. The notion of strong codiagnosability is also introduced to capture the ability of being certain about both the failure as well as the nonfailure conditions in a system within a bounded delay.
15931484
Optimal slope bin classification in gradient adjusted predictor for lossless compression of medical images
Gradient adjusted predictor (GAP) uses seven fixed range of slope quantization bins and different predictors associated with each bin, for prediction of pixels of all kinds of images. Criteria for range of slope in the bins and associated predictors are not reported in the literature. This paper presents a technique for slope quantization bins which are optimum for a given set of images. It also presents a technique for finding a statistically optimal predictor for a given range of slope bin. Simulation results, for medical images, using optimal slope bins and associated predictors show a significant better compression performance as compared to the other methods such as GAP and edge-directed prediction (EDP) method. The proposed method and GAP has same order of computational complexity while EDP is computationally much expensive.