• ETRI Journal
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• v.42 no.3
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• pp.388-398
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• 2020

We herein propose a heuristic redundancy selection algorithm that combines resubmission, replication, and checkpointing redundancies to reduce the resiliency overhead in fault-tolerant workflow scheduling. The appropriate combination of these redundancies for workflow tasks is obtained in two consecutive phases. First, to compute the replication vector (number of task replicas), we apportion the set of provisioned resources among concurrently executing tasks according to their needs. Subsequently, we obtain the optimal checkpointing interval for each task as a function of the number of replicas and characteristics of tasks and computational environment. We formulate the problem of obtaining the optimal checkpointing interval for replicated tasks in situations where checkpoint files can be exchanged among computational resources. The results of our simulation experiments, on both randomly generated workflow graphs and real-world applications, demonstrated that both the proposed replication vector computation algorithm and the proposed checkpointing scheme reduced the resiliency overhead.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.2
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• pp.195-208
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• 2009

In this paper, we introduce a grid-based key pre-distribution scheme in wireless sensor networks, which aims to improve the connectivity and resiliency while maintaining a reasonable overhead. We consider simplification of the key establishment logic and enhancement of the connectivity via plat polynomial assignment on a three-dimensional grid for node allocation and keying material assignment. We demonstrate that our scheme results in improvements via a detailed discussion on the connectivity, resource usage, security features and resiliency. A comparison with other relevant works from the literature along with a demonstrated implementation on typical sensor nodes shows the feasibility of the introduced scheme and its applicability for large networks.

• IEMEK Journal of Embedded Systems and Applications
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• v.16 no.1
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• pp.9-15
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• 2021

Recently, it is increasingly necessary to run high-end neural network applications with huge computation overhead on top of resource-constrained embedded systems, such as wearable devices. While the huge computational overhead can be alleviated by distributed neural networks running on multiple separate devices, existing distributed neural network techniques suffer from a large traffic between the devices; thus are very vulnerable to communication failures. These drawbacks make the distributed neural network techniques inapplicable to wearable devices, which are connected with each other through unstable and low data rate communication medium like human body communication. Therefore, in this paper, we propose a distributed neural network partitioning technique that is resilient to communication failures. Furthermore, we show that the proposed technique also improves the inference accuracy even in case of no communication failure, thanks to the improved network partitioning. We verify through comparative experiments with a real-life neural network application that the proposed technique outperforms the existing state-of-the-art distributed neural network technique in terms of accuracy and resiliency to communication failures.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.56-68
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• 2002

The Universal Variable Length Coding(UVLC) scheme in H.26L has nice features such as error resiliency and two-way decodability. However, it has lower coding efficiency than the conventional Huffman coding. To improve the coding efficiency of UVLC, we Propose to use a dynamic codeword mapping that changes association between symbols and codewords in order to utilize the statistical characteristics of symbols as much as possible but without losing any features of the UVLC. Both encoder and decoder use the same re-association table, and hence the encoder need not send additional overhead for the re-mapping relationship to the decoder. Simulation results show that without significant change of the current H.26L coding scheme, the proposed method additionally attains up to about 8% and about 5% bit reductions respectively in intra and inter frames over the current H.26L encoding method.

• The KIPS Transactions:PartA
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• v.13A no.2 s.99
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• pp.147-156
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• 2006

Recently, streaming service accounts for large part of internet traffic and it is becoming the most popular service. Because of P2P's scalability, P2P-based streaming system is proposed. There are frequent leave and join of a node. To overcome the group dynamics, Multiple Multicast Trees Methods were suggested. However, since they did not consider discrepancy in peers' capacity, it may cause the trees to be long and unstable. So we suggest Resilient Capacity-Aware Multicast Tree construction scheme (R-CAT) that promotes superior peer to upper position in the tree and construct more stable and short multicast trees. By simulation we can show that R-CAT cost more overhead packets for tree joining process, but it reduce the end-to-end delay of the resulting tree and the number of packets lost during the node joining and leaving processes much more than SplitStream.