48,221 research outputs found

    Clathrin Adaptor Complex-interacting Protein Irc6 Functions through the Conserved C-Terminal Domain.

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    Clathrin coats drive transport vesicle formation from the plasma membrane and in pathways between the trans-Golgi network (TGN) and endosomes. Clathrin adaptors play central roles orchestrating assembly of clathrin coats. The yeast clathrin adaptor-interacting protein Irc6 is an orthologue of human p34, which is mutated in the inherited skin disorder punctate palmoplantar keratoderma type I. Irc6 and p34 bind to clathrin adaptor complexes AP-1 and AP-2 and are members of a conserved family characterized by a two-domain architecture. Irc6 is required for AP-1-dependent transport between the TGN and endosomes in yeast. Here we present evidence that the C-terminal two amino acids of Irc6 are required for AP-1 binding and transport function. Additionally, like the C-terminal domain, the N-terminal domain when overexpressed partially restores AP-1-mediated transport in cells lacking full-length Irc6. These findings support a functional role for Irc6 binding to AP-1. Negative genetic interactions with irc6∆ are enriched for genes related to membrane traffic and nuclear processes, consistent with diverse cellular roles for Irc6

    Sparse Signal Processing Concepts for Efficient 5G System Design

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    As it becomes increasingly apparent that 4G will not be able to meet the emerging demands of future mobile communication systems, the question what could make up a 5G system, what are the crucial challenges and what are the key drivers is part of intensive, ongoing discussions. Partly due to the advent of compressive sensing, methods that can optimally exploit sparsity in signals have received tremendous attention in recent years. In this paper we will describe a variety of scenarios in which signal sparsity arises naturally in 5G wireless systems. Signal sparsity and the associated rich collection of tools and algorithms will thus be a viable source for innovation in 5G wireless system design. We will discribe applications of this sparse signal processing paradigm in MIMO random access, cloud radio access networks, compressive channel-source network coding, and embedded security. We will also emphasize important open problem that may arise in 5G system design, for which sparsity will potentially play a key role in their solution.Comment: 18 pages, 5 figures, accepted for publication in IEEE Acces

    Reliable Prediction of Channel Assignment Performance in Wireless Mesh Networks

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    The advancements in wireless mesh networks (WMN), and the surge in multi-radio multi-channel (MRMC) WMN deployments have spawned a multitude of network performance issues. These issues are intricately linked to the adverse impact of endemic interference. Thus, interference mitigation is a primary design objective in WMNs. Interference alleviation is often effected through efficient channel allocation (CA) schemes which fully utilize the potential of MRMC environment and also restrain the detrimental impact of interference. However, numerous CA schemes have been proposed in research literature and there is a lack of CA performance prediction techniques which could assist in choosing a suitable CA for a given WMN. In this work, we propose a reliable interference estimation and CA performance prediction approach. We demonstrate its efficacy by substantiating the CA performance predictions for a given WMN with experimental data obtained through rigorous simulations on an ns-3 802.11g environment.Comment: Accepted in ICACCI-201

    Predicting Performance of Channel Assignments in Wireless Mesh Networks through Statistical Interference Estimation

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    Wireless Mesh Network (WMN) deployments are poised to reduce the reliance on wired infrastructure especially with the advent of the multi-radio multi-channel (MRMC) WMN architecture. But the benefits that MRMC WMNs offer viz., augmented network capacity, uninterrupted connectivity and reduced latency, are depreciated by the detrimental effect of prevalent interference. Interference mitigation is thus a prime objective in WMN deployments. It is often accomplished through prudent channel allocation (CA) schemes which minimize the adverse impact of interference and enhance the network performance. However, a multitude of CA schemes have been proposed in research literature and absence of a CA performance prediction metric, which could aid in the selection of an efficient CA scheme for a given WMN, is often felt. In this work, we offer a fresh characterization of the interference endemic in wireless networks. We then propose a reliable CA performance prediction metric, which employs a statistical interference estimation approach. We carry out a rigorous quantitative assessment of the proposed metric by validating its CA performance predictions with experimental results, recorded from extensive simulations run on an ns-3 802.11g environment

    The "MIND" Scalable PIM Architecture

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    MIND (Memory, Intelligence, and Network Device) is an advanced parallel computer architecture for high performance computing and scalable embedded processing. It is a Processor-in-Memory (PIM) architecture integrating both DRAM bit cells and CMOS logic devices on the same silicon die. MIND is multicore with multiple memory/processor nodes on each chip and supports global shared memory across systems of MIND components. MIND is distinguished from other PIM architectures in that it incorporates mechanisms for efficient support of a global parallel execution model based on the semantics of message-driven multithreaded split-transaction processing. MIND is designed to operate either in conjunction with other conventional microprocessors or in standalone arrays of like devices. It also incorporates mechanisms for fault tolerance, real time execution, and active power management. This paper describes the major elements and operational methods of the MIND architecture

    Eliminating Network Protocol Vulnerabilities Through Abstraction and Systems Language Design

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    Incorrect implementations of network protocol message specifications affect the stability, security, and cost of network system development. Most implementation defects fall into one of three categories of well defined message constraints. However, the general process of constructing network protocol stacks and systems does not capture these categorical con- straints. We introduce a systems programming language with new abstractions that capture these constraints. Safe and efficient implementations of standard message handling operations are synthesized by our compiler, and whole-program analysis is used to ensure constraints are never violated. We present language examples using the OpenFlow protocol
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