the proceedings contain 35 papers. the topics discussed include: side effect mitigation algorithm for cache maintenance in opportunistic networks;simple floor plan construction via cloudsourcing;using open edX forum f...
ISBN:
(纸本)9781467375894
the proceedings contain 35 papers. the topics discussed include: side effect mitigation algorithm for cache maintenance in opportunistic networks;simple floor plan construction via cloudsourcing;using open edX forum for supporting collaborative learning;towards an automatic prediction of image processingalgorithms performances on embedded heterogeneous architectures;multi-core approach towards efficient biometric cryptosystems;sparse matrix sparse vector multiplication - a novel approach;thread-level value speculation for image-processing applications;a special sorting method for neighbor search procedure in smoothed particle hydrodynamics on GPUs;the design and implementation of embedded online laboratory;and spatial join query processing in cloud: analyzing design choices and performance comparisons.
Meminductor generated on the basis of the conception of a memristor has many promising characteristics, such as analog processing capacity, storing energy and operating as non-volatile memories with essentially loss l...
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ISBN:
(纸本)9781479974894
Meminductor generated on the basis of the conception of a memristor has many promising characteristics, such as analog processing capacity, storing energy and operating as non-volatile memories with essentially loss less data reading and storing, etc.([1]) However, there are few studies about meminductor's applications due to the unavailability of solid-state meminductor and composite behaviors of multiple meminductor series-parallel circuits are not fully understood. In this paper, we investigate the composite characteristics of multiple meminductor circuits via the relationships among charge, the time integral of flux and meminductance of each meminductor and composite device. Furthermore, a general computing method of composite meminductance for multiple meminductor circuits is proposed. the results of this study can be used to construct composite meminductor circuits with complex characteristics and have promising applications in the non-volatile memory circuits.
Dynamic programming techniques are well-established and employed by various practical algorithms which are used as similarity measures, for instance the edit-distance algorithm or the dynamic time warping algorithm. T...
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ISBN:
(纸本)9783319250878;9783319250861
Dynamic programming techniques are well-established and employed by various practical algorithms which are used as similarity measures, for instance the edit-distance algorithm or the dynamic time warping algorithm. these algorithms usually operate in iteration-based fashion where new values are computed from values of the previous iteration, thus they cannot be processed by simple data-parallel approaches. In this paper, we propose a way how to utilize computational power of massively parallel GPUs to compute dynamic programming algorithms effectively and efficiently. We address boththe problem of computing one distance on large inputs concurrently and the problem of computing large number of distances simultaneously (e.g., when a similarity query is being resolved).
In this article, a quantum version of the parallel self organizing neural network (QPSONN) architecture for extraction of pure color objects from a noisy perspective is proposed. the QPSONN architecture operates in a ...
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ISBN:
(纸本)9781479917976
In this article, a quantum version of the parallel self organizing neural network (QPSONN) architecture for extraction of pure color objects from a noisy perspective is proposed. the QPSONN architecture operates in a phased manner to process input noisy pure color images. After the segregation of the pure color inputs into pure color components in the initial phase, these components are subsequently forwarded for processing to three component quantum multilayer self organizing neural network (QMLSONN) architectures composed of three processing layers viz., input, hidden and output layers characterized by qubits based neurons. the interconnection weights are represented by single qubit rotation gates. Quantum measurements at the component output layers destroy the quantum states of the processed information facilitating adjustment of network interconnection weights by a quantum backpropagation algorithm using linear indices of fuzziness. Finally, a fusion of the stable component outputs are brought about in a sink layer to produce extracted outputs. Results of application of the QPSONN are demonstrated on a synthetic and a real life spanner image with various degrees of Gaussian noise. A comparison withthe classical PSONN architecture reveals the extraction and time efficiency of the proposed QPSONN architecture.
Hierarchical identity-based cryptography is an efficient technology to address the security issues in cloud storage. However, the inherent key escrow problem primarily hinders the widespread adoption of this cryptosys...
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ISBN:
(纸本)9783319271613;9783319271606
Hierarchical identity-based cryptography is an efficient technology to address the security issues in cloud storage. However, the inherent key escrow problem primarily hinders the widespread adoption of this cryptosystem in practice. To address the key escrow problem, this paper proposes an escrow-free hierarchical identity-based signature model, in which a user signs messages with a user-selected secret and PKG signing factor apart from the private key. For proving the full security, we formulate three security games with respect to our signature model. We instantiate the escrow-free model into a specific scheme based on the SHER-IBS scheme and prove that our scheme is secure against adaptive chosen ID and message attacks.
Cloud storage has become one of the integral parts of online life. However, the cloud storage brings in new kinds of data security issues as well. Authentication framework for both users and services provides an effic...
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ISBN:
(纸本)9783319271613;9783319271606
Cloud storage has become one of the integral parts of online life. However, the cloud storage brings in new kinds of data security issues as well. Authentication framework for both users and services provides an efficient solution to the security and privacy problems of the cloud storage. In this paper we propose a Hierarchical Identity-Based Signature (HIBS) scheme using composite order bilinear groups. We present the methodology of dual system signature to prove that our scheme is secure against existential forgery on adaptively chosen message and identity attack under standard model. Our HIBS scheme shares the same system parameters withthe hierarchical identity-based encryption (LW-HIBE) scheme by Lewko and Waters, and it is as efficient as the LW-HIBE. Combining our signature scheme withthe LW-HIBE scheme yields a complete solution of an identity-based public key system, which can be utilized to build an authentication framework for cloud storage.
To realize conveniently deployed video surveillance applications, this paper designs a cloud service system employing ubiquitously available IoT nodes. Considering limited capacity of each IoT node, this paper first d...
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ISBN:
(纸本)9783319271613;9783319271606
To realize conveniently deployed video surveillance applications, this paper designs a cloud service system employing ubiquitously available IoT nodes. Considering limited capacity of each IoT node, this paper first describes the system architecture and operation procedure for application requests, and introduces the design of scheduler's function and typical video processingalgorithms. Further, for decreasing transmission conflicts among video/image processor nodes, this paper proposes a scheduling methods based on Genetic Algorithm to rationally utilize the cooperative IoT nodes. Simulation results show that, compared with common methods such as random scheduling and opportunity-balanced scheduling, this method yields much smaller processing delay and transmission delay, together with higher packet delivery ratio.
Smart grid is one of the most important area for big data applications, while the cloud-based platform is believed to be the deserved paradigm to conduct smart grid big data processing. Hence, elastic resource reconfi...
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ISBN:
(纸本)9783319271613;9783319271606
Smart grid is one of the most important area for big data applications, while the cloud-based platform is believed to be the deserved paradigm to conduct smart grid big data processing. Hence, elastic resource reconfiguration is a critical issue for smart grid big data application, since the widespread of data sources make the workload changing frequently. In this paper, we focus on the problem of context-aware QoS assurance for electric power application via elastic cloud resource reconfiguration, especially using the VM migration method. We present a framework of dynamical resource reconfiguration that characterize the major components needed for the QoS assurance during elastic resource reconfiguration. We take VM migration as the special concern, and discuss the major issues during VM migration procedure, and propose a VM migration mechanism for QoS assurance for application.
In parallel magnetic resonance imaging (pMRI), to find a joint solution for the image and coil sensitivity functions is a nonlinear and nonconvex problem in the existing literature. It is shown in this paper that, if ...
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the proceedings contain 48 papers. the topics discussed include: phase aware warp scheduling: mitigating effects of phase behavior in GPGPU applications;NVMMU: a non-volatile memory management unit for heterogeneous G...
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the proceedings contain 48 papers. the topics discussed include: phase aware warp scheduling: mitigating effects of phase behavior in GPGPU applications;NVMMU: a non-volatile memory management unit for heterogeneous GPU-SSD architectures;exploiting inter-warp heterogeneity to improve GPGPU performance;scalable SIMD-efficient graph processing on GPUs;parallel methods for verifying the consistency of weakly-ordered architectures;stadium hashing: scalable and flexible Hashing on GPUs;TSXProf: profiling hardware transactions;ALEA: fine-grain energy profiling with basic block sampling;towards general-purpose neural network computing;practical near-data processing for in-memory analytics frameworks;scalable task scheduling and synchronization using hierarchical effects;PENCIL: a platform-neutral compute intermediate language for accelerator programming;communication avoiding algorithms: analysis and code generation for parallel systems;and exploiting program semantics to place data in hybrid memory.
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