• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권3호
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• pp.1510-1532
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• 2017

In smart grid, privacy implications to individuals and their families are an important issue because of the fine-grained usage data collection. Wireless communications are utilized by many utility companies to obtain information. Network coding is exploited in smart grids, to enhance network performance in terms of throughput, delay, robustness, and energy consumption. However, random linear network coding introduces a new challenge for privacy preserving due to the encoding of data and updating of coefficients in forwarder nodes. We propose a distributed privacy preserving scheme for random linear network coding in smart grid that considers the converged flows character of the smart grid and exploits a homomorphic encryption function to decrease the complexities in the forwarder node. It offers a data confidentiality privacy preserving feature, which can efficiently thwart traffic analysis. The data of the packet is encrypted and the tag of the packet is encrypted by a homomorphic encryption function. The forwarder node random linearly codes the encrypted data and directly processes the cryptotext tags based on the homomorphism feature. Extensive security analysis and performance evaluations demonstrate the validity and efficiency of the proposed scheme.

• 한국통신학회논문지
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• 제22권5호
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• pp.1083-1096
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• 1997

To implement satellite B-ISDN/ATM network, it needs to gurantee reliable transport via satelite in the poor BER environment. So, it requires to use channel coding (FEC:Forward Error Correction) schemes for improvement of BER performance, but these coding effects evoke burst errors and degradation of the QoS. Therefore we have to investigate new algorithm that compensates these weaknesses. We consider convolutional coding and concatenated coding among FEC schemes as FEC for satellite transmission and choose different compensational algorithm by the error characteristics of the using type of FEC. In using concatenated coding, this paper proposes the satellite system structure for interconnection to the terrestrial network and proposes the channel coding algorithm for improvement of transmission performances. We execute performance evaluation of the proposed algorithm by computer simulation. In detail, we propose 4 types of application ATM cell to the block coding(Reed-Solomon) and propose the new 55 byte ATM cell that enforces the error correction capability of cell header by the BCH coding. Then we propose the outer interleaverand the cell unit interleaver that evoke maximum coding effect of BCH code.

• Journal of Communications and Networks
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• 제12권1호
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• pp.86-94
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• 2010

In this paper, we present a decentralized algorithm to find minimum cost quality of service (QoS) flow subgraphs in network coded multicast schemes. The main objective is to find minimum cost subgraphs that also satisfy user-specified QoS constraints, specifically with respect to rate and delay demands. We consider networks with multiple multicast sessions. Although earlier network coding algorithms in this area have demonstrated performance improvements in terms of QoS parameters, the proposed QoS network coding approach provides a framework that guarantees QoS constraints are actually met over the network.

• 한국통신학회논문지
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• 제41권4호
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• pp.433-440
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• 2016

본 논문에서는 사물인터넷 환경에서 통신 기기들이 정보를 직접 공유하고자 할 때 전체 네트워크의 에너지 소모량을 최소화하기 위한 방식을 제안한다. 제안하는 방식은 매 전송 시 동적으로 전송 노드 및 전송 데이터를 선택하는 효과적인 네트워크 부호화 기법을 사용하여 정보 공유에 필요한 총 전송 횟수를 감소시킨다. 실험을 통하여 기존의 고정된 순서로 전송 노드를 설정하는 네트워크 부호화 방식, 랜덤한 순서로 전송 노드를 설정하는 네트워크 부호화 방식, 그리고 랜덤한 순서로 전송 노드를 설정하는 비부호화 방식에 비해 총 전송 횟수 측면에서 보다 뛰어난 성능을 가짐을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권9호
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• pp.2134-2153
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• 2013

A network-coding-based scheme is proposed to improve the energy efficiency of distributed storage systems in WSNs (Wireless Sensor Networks). We mainly focus on two problems: firstly, consideration is given to effective distributed storage technology; secondly, we address how to effectively repair the data in failed storage nodes. For the first problem, we propose a method to obtain a sparse generator matrix to construct network codes, and this sparse generator matrix is proven to be the sparsest. Benefiting from this matrix, the energy consumption required to implement distributed storage is reduced. For the second problem, we designed a network-coding-based iterative repair method, which adequately utilizes the idea of re-encoding at intermediate nodes from network coding theory. Benefiting from the re-encoding, the energy consumption required by data repair is significantly reduced. Moreover, we provide an explicit lower bound of field size required by this scheme, which implies that it can work over a small field and the required computation overhead is very low. The simulation result verifies that the proposed scheme not only reduces the total energy consumption required to implement distributed storage system in WSNs, but also balances energy consumption of the networks.

• Journal of Communications and Networks
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• 제15권4호
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• pp.430-438
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• 2013

This paper addresses the issue of throughput-delay of one-to-many wireless multi-hop flows based on random linear network coding (RLNC). Existing research results have been focusing on the single-hop model which is not suitable for wireless multi-hop networks. In addition, the conditions of related system model are too idealistic. To address these limitations, we herein investigate the performance of a wireless multi-hop network, focusing on the one-to-many flows. Firstly, a system model with multi-hop delay was constructed; secondly, the transmission schemes of system model were gradually improved in terms of practical conditions such as limited queue length and asynchronous forwarding way; thirdly, the mean delay and the mean throughput were quantified in terms of coding window size K and number of destination nodes N for the wireless multi-hop transmission. Our findings show a clear relationship between the multi-hop transmission performance and the network coding parameters. This study results will contribute significantly to the evaluation and the optimization of network coding method.

• Journal of Communications and Networks
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• 제10권4호
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• pp.384-395
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• 2008

Random network coding can be viewed as a single block code applied to all source packets. To manage the concomitant high coding complexity, source packets can be partitioned into generations; block coding is then performed on each set. To reach a better performance-complexity tradeoff, we propose a novel concatenated network code which mixes generations while retaining the desirable properties of generation-based coding. Focusing on the code's erasure performance, we show that the probability of successfully decoding a generation on erasure channels can increase substantially for any erasure rate. Using both analysis (for small networks) and simulations (for larger networks), we show how the code's parameters can be tuned to extract best performance. As a result, the probability of failing to decode a generation is reduced by nearly one order of magnitude.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1298-1310
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• 2019

Network coding (NC) is a promising technology that can improve available bandwidth and packet throughput in wireless sensor networks (WSNs). Sliding window is an improved technology of NC, which is a supplement of TCP/IP technology and can improve data throughput and network lifetime on WSNs. This paper proposes a network coding-based maximum lifetime algorithm for sliding window in WSNs (NC-MLSW) which improves the throughput and network lifetime in WSN. The packets on the source node are sent on the WSNs. The intermediate node encodes the received original packet and forwards the newly encoded packet to the next node. Finally, the destination node decodes the received encoded data packet and recovers the original packet. The performance of the NC-MLSW algorithm is studied using NS2 simulation software and the network packet throughput, network lifetime and data packet loss rate were evaluated. The simulations experiment results show that the NC-MLSW algorithm can obviously improve the network packet throughput and network lifetime.

• Journal of Communications and Networks
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• 제18권3호
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• pp.493-501
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• 2016

In-network storage is an effective technique for avoiding network congestion and reducing power consumption in continuous data collection in wireless sensor networks. In recent years, network coding based storage design has been proposed as a means to achieving ubiquitous access that permits any query to be satisfied by a few random (nearby) storage nodes. To maintain data consistency in continuous data collection applications, the readings of a sensor over time must be sent to the same set of storage nodes. In this paper, we present an efficient approach to updating data at storage nodes to maintain data consistency at the storage nodes without decoding out the old data and re-encoding with new data. We studied a transmission strategy that identifies a set of storage nodes for each source sensor that minimizes the transmission cost and achieves ubiquitous access by transmitting sparsely using the sparse matrix theory. We demonstrate that the problem of minimizing the cost of transmission with coding is NP-hard. We present an approximation algorithm based on regarding every storage node with memory size B as B tiny nodes that can store only one packet. We analyzed the approximation ratio of the proposed approximation solution, and compared the performance of the proposed coding approach with other coding schemes presented in the literature. The simulation results confirm that significant performance improvement can be achieved with the proposed transmission strategy.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.456-459
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• 1999

In this paper, we propose a new neural network based on the DNA coding method. The initial population of the structure information and the weights for the neural network is generated, and then the descendants are chose with the Elitist selection by the genetic algorithm. The evolutionary technique and the suitable fitness measure are used to find a neural network with the fractal number of layers. which represents a good approximation to the given function.