In recent years, edge computing has attracted significant attention because it can effectively support many delay-sensitive applications. Despite such a salient feature, edge computing also faces many challenges, espe...
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In recent years, edge computing has attracted significant attention because it can effectively support many delay-sensitive applications. Despite such a salient feature, edge computing also faces many challenges, especially for efficiency and security, because edge devices are usually heterogeneous and may be untrustworthy. To address these challenges, we propose a unified framework to provide efficiency and confidentiality by coded distributed computing. Within the proposed framework, we use matrix multiplication, a fundamental building block of many distributed machine learning algorithms, as the representative computation task. To minimize resource consumption while achieving information-theoretic security, we investigate two highly-coupled problems, (1) task allocation that assigns data blocks in a computing task to edge devices and (2) linear code design that generates data blocks by encoding the original data with random information. Specifically, we first theoretically analyze the necessary conditions for the optimal solution. Based on the theoretical analysis, we develop an efficient task allocation algorithm to obtain a set of selected edge devices and the number of coded vectors allocated to them. Using the task allocation results, we then design secure coded computing schemes, for two cases, (1) with redundant computation and (2) without redundant computation, all of which satisfy the availability and security conditions. Moreover, we also theoretically analyze the optimization of the proposed scheme. Finally, we conduct extensive simulation experiments to demonstrate the effectiveness of the proposed schemes.
A new triangulation-based optical profilometry-linearly coded profilometry (LCP)-is presented. In this method, a linear coding technique is introduced. It uses a periodic sawtoothlike structure light to code the surfa...
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A new triangulation-based optical profilometry-linearly coded profilometry (LCP)-is presented. In this method, a linear coding technique is introduced. It uses a periodic sawtoothlike structure light to code the surface being measured and the phase-shifting technique to decode the profile. A coding light that has isosceles triangle teeth is proposed. To realize the decoding, at least three samples are needed. When more than three samples are used, higher accuracy can be obtained. A decoding method of LCP with an even number of samples is provided. This method has been realized in my laboratory and the experimental results verify the reliability of LCP. Because the coding method used in LCP is simpler than that used in phase-measuring profilometry, LCP has a faster measuring speed. (C) 1997 Optical Society of America.
This correspondence is concerned with new connections between source coding and two kinds of families of hash functions known as the families of universal hash functions and N-strongly universal hash functions, where ...
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This correspondence is concerned with new connections between source coding and two kinds of families of hash functions known as the families of universal hash functions and N-strongly universal hash functions, where N >= 2 is an integer. First, it is pointed out that such families contain classes of well-known source codes such as bin codes and linear codes. Next, performance of a source coding scheme using either of the two kinds of families is evaluated. An upper bound on the expectation of the decoding error probability is obtained for each family. The expectation of the decoding error probability is analyzed in detail for the cases of discrete memoryless sources and sources without the memoryless assumption under a certain class of decoders.
We propose a novel adaptive locality-constrained regularized robust coding (ALRRC) for image recognition by considering both the effects of the test sample's features and the local relationships between the test s...
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We propose a novel adaptive locality-constrained regularized robust coding (ALRRC) for image recognition by considering both the effects of the test sample's features and the local relationships between the test sample and the training samples in the linear coding procedure. By adaptively calculating out a feature weight matrix of a test sample, ALRRC measures the effects of the test sample's features in the linear coding procedure. Furthermore, ALRRC can obtain the weighted test sample by multiplying the test sample by the feature weight matrix, which has reduced the roles of the aberrant features as far as possible. Similarly, ALRRC can get the weighted training samples by multiplying the training samples by the feature weight matrix. Moreover, using the similarities between the weighted test sample and weighted training samples, ALRRC adaptively calculates out a locality-constrained matrix that can truly characterize the local relationships between the test sample and the training samples. Finally, by incorporating the feature weight matrix and locality-constrained matrix into the linear coding framework, ALRRC is inclined to select the true local training samples to represent the test sample. In addition, we also propose an iterative algorithm to solve the optimization problem of ALRRC. Experimental results on several image databases show that ALRRC is more effective and robust than state-of-the-art linear coding-based methods.
We show the sufficient conditions for coding by nodes such that every sink can decode all information multicasted by the single source when there exists time-varying delay of information transmission at links in the n...
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We show the sufficient conditions for coding by nodes such that every sink can decode all information multicasted by the single source when there exists time-varying delay of information transmission at links in the network coding.
Network coding shows,that data rate can be increased if information is allowed, to be encoded in the network nodes. The recent work of Li, Yeung and Cai [1], and Koetter and Medard [2], shows that linear network codin...
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ISBN:
(纸本)0780386477
Network coding shows,that data rate can be increased if information is allowed, to be encoded in the network nodes. The recent work of Li, Yeung and Cai [1], and Koetter and Medard [2], shows that linear network coding is sufficient for single source multicast network. The restrictiveness of usage of linear code is still an unknown in the general multisource multicast network. In this paper, we characterize the achievable information rate region for single source node multi-source multicast networks with two sinks. We further show that linear coding is sufficient for achieving the maximum network capacity.
Gossip is a scalable and easy-to-deploy broadcast method for distributed systems. In gossip a broadcast message is disseminated through repeated information exchanges between randomly chosen nodes. Gossip can also ach...
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ISBN:
(纸本)9780769545905
Gossip is a scalable and easy-to-deploy broadcast method for distributed systems. In gossip a broadcast message is disseminated through repeated information exchanges between randomly chosen nodes. Gossip can also achieve high reliability using a large amount of redundant messages;but this also incurs high load on the network. This paper proposes a new gossip algorithm which incorporates network coding techniques to mitigate the high load. With random linear coding, each message propagated in the new algorithm is randomly generated from the broadcast message. Unlike in ordinary gossip, this feature prevents nodes from receiving an identical message more than once, allowing to achieve the same reliability at a lower message cost.
With momentum gained from programmable data plane (PDP), in-band network telemetry (INT) has been widely considered as a promising technique for realtime network monitoring. In this work, we leverage network coding (N...
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ISBN:
(数字)9781538683477
ISBN:
(纸本)9781538683477
With momentum gained from programmable data plane (PDP), in-band network telemetry (INT) has been widely considered as a promising technique for realtime network monitoring. In this work, we leverage network coding (NC) to design CodedINT, for improving the visibility of INT in lossy networks. Specifically, we propose to encode the telemetry data in multiple packets with NC and distribute the encoded data over a group of packets. Then, among the group of packets, if we can receive enough ones that satisfy the decoding condition of NC, the whole original telemetry data can be recovered. We first explain the design of CodedINT to elaborate on its operation principle, packet format, and system implementation. Then, we implement and experimentally evaluate CodedINT in a real network testbed. Our experiments demonstrate that in a lossy network with packet loss rate at 80%, CodedINT ensures that 89:48% of the telemetry data carried by INT packets can be recovered successfully.
Relay networks aid in increasing the rate of communication from source to destination. However, the capacity of even a three-terminal relay channel is an open problem. In this paper, we propose a new lower bound for t...
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Relay networks aid in increasing the rate of communication from source to destination. However, the capacity of even a three-terminal relay channel is an open problem. In this paper, we propose a new lower bound for the capacity of the three-terminal relay channel with destination-to-source feedback in the presence of noise with memory. Our lower bound improves on the existing bounds in the literature. We then extend our lower bound to general relay network configurations using an arbitrary number of filter-and-forward relay nodes. Such network configurations are common in many multihop communication systems where the intermediate nodes can only perform minimal processing due to limited computational power. Simulation results show that significant improvements in the achievable rate can be obtained through our approach. We next derive a coding strategy (optimized using post processed signal-to-noise ratio as a criterion) for the three-terminal relay channel with noisy channel output feedback for two transmissions. This coding scheme can be used in conjunction with open-loop codes for applications like automatic repeat request (ARQ) or hybrid-ARQ.
A new optical profilometry-linearly coded profilometry (LCP)-is presented. It uses a sawtoothlike linear light structure to code the surface to be measured and a phase-shifting technique to decode the profile. Two kin...
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A new optical profilometry-linearly coded profilometry (LCP)-is presented. It uses a sawtoothlike linear light structure to code the surface to be measured and a phase-shifting technique to decode the profile. Two kinds of coding-light structure, one with right-angle triangle teeth and the other with isosceles triangle teeth, are proposed. For coding with light with right-angle triangle teeth, a general decoding method is given. In addition, an optimum sampling manner and the measurement error are discussed with respect to a special case. For coding with light with isosceles triangle teeth, a decoding method with three samples is given. In our laboratory, an experimental system was established, and experiments that verified the reliability of the proposed methods were performed. Experimental results typical of those obtained are given. We find that LCP is similar to the widely used phase-measuring profilometry but has a faster measuring speed. (C) 1997 Optical Society of America.
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