• Journal of Communications and Networks
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• v.10 no.2
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• pp.204-212
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• 2008

We study the routing problem in all-wireless networks based on cooperative transmissions. We model the minimum-energy cooperative path (MECP) problem and prove that this problem is NP-complete. We hence design an approximation algorithm called cooperative shortest path (CSP) algorithm that uses Dijkstra's algorithm as the basic building block and utilizes cooperative transmissions in the relaxation procedure. Compared with traditional non-cooperative shortest path algorithms, the CSP algorithm can achieve a higher energy saving and better balanced energy consumption among network nodes, especially when the network is in large scale. The nice features lead to a unique, scalable routing scheme that changes the high network density from the curse of congestion to the blessing of cooperative transmissions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2362-2378
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• 2017

To mitigate the performance degradation caused by performance anomaly, a number of channel assignment algorithms have been proposed for multi-rate wireless mesh networks. However, network conditions have not been fully considered for routing process in these algorithms. In this paper, a joint scheme called Multi-rate Dijkstra's Shortest path - Rate Separated (MDSRS) is proposed, combining routing metrics and channel assignment algorithm. In MDSRS, the routing metric are determined through the synthesized deliberations of link costs and rate matches; then the rate separated channel assignment is operated based on the determined routing metric. In this way, the competitions between high and low rate links are avoided, and performance anomaly problem is settled, and the network capacity is efficiently improved. Theoretical analysis and NS-3 simulation results indicate that, the proposed MDSRS can significantly improve the network throughput, and decrease the average end-to-end delay as well as packet loss probability. Performance improvements could be achieved even in the heavy load network conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4865-4886
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• 2017

The user experience of practical indoor power line communication (PLC) applications is greatly affected by the system quality-of-service (QoS) criteria. With a general broadcast-and-multi-access (BMA) relay scheme, in this work we investigate the joint source and relay power optimization of the amplify-and-forward (AF) relay systems used under indoor broad-band PLC environments. To achieve both time diversity and spatial diversity from the relay-involved PLC channel, which is time-varying in nature, the source node has been configured to transmit an identical message twice in the first and second signalling phase, respectively. The QoS constrained power allocation problem is not convex, which makes the global optimal solution is computationally intractable. To solve this problem, an alternating optimization (AO) method has been adopted and decomposes this problem into three convex/quasi-convex sub-problems. Simulation results show the fast convergence and short delay of the proposed algorithm under realistic relay-involved PLC channels. Compared with the two-hop and broadcast-and-forward (BF) relay systems, the proposed general relay system meets the same QoS requirement with less network power assumption.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.6
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• pp.1492-1511
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• 2013

A novel, chaotic map that is based on concatenated torus automorphisms is proposed in this paper. As we know, cat map, which is based on torus automorphism, is highly chaotic and is often used to encrypt information. But cat map is periodic, which decreases the security of the cryptosystem. In this paper, we propose a novel chaotic map that concatenates several torus automorphisms. The concatenated mechanism provides stronger chaos and larger key space for the cryptosystem. It is proven that the period of the concatenated torus automorphisms is the total sum of each one's period. By this means, the period of the novel automorphism is increased extremely. Based on the novel, concatenated torus automorphisms, two application schemes in image encryption are proposed, i.e., 2D and 3D concatenated chaotic maps. In these schemes, both the scrambling matrices and the iteration numbers act as secret keys. Security analysis shows that the proposed, concatenated, chaotic maps have strong chaos and they are very sensitive to the secret keys. By means of concatenating several torus automorphisms, the key space of the proposed cryptosystem can be expanded to $2^{135}$. The diffusion function in the proposed scheme changes the gray values of the transferred pixels, which makes the periodicity of the concatenated torus automorphisms disappeared. Therefore, the proposed cryptosystem has high security and they can resist the brute-force attacks and the differential attacks efficiently. The diffusing speed of the proposed scheme is higher, and the computational complexity is lower, compared with the existing methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4345-4363
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• 2021

Deep Learning as a Service (DLaaS), utilizing the cloud-based deep neural network models to provide customer prediction services, has been widely deployed on mobile cloud computing (MCC). Such services raise privacy concerns since customers need to send private data to untrusted service providers. In this paper, we devote ourselves to building an efficient protocol to classify users' images using the convolutional neural network (CNN) model trained and held by the server, while keeping both parties' data secure. Most previous solutions commonly employ homomorphic encryption schemes based on Ring Learning with Errors (RLWE) hardness or two-party secure computation protocols to achieve it. However, they have limitations on large communication overheads and costs in MCC. To address this issue, we present LeHE4SCNN, a scalable privacy-preserving and communication-efficient framework for CNN-based DLaaS. Firstly, we design a novel low-expansion rate homomorphic encryption scheme with packing and unpacking methods (LeHE). It supports fast homomorphic operations such as vector-matrix multiplication and addition. Then we propose a secure prediction framework for CNN. It employs the LeHE scheme to compute linear layers while exploiting the data shuffling technique to perform non-linear operations. Finally, we implement and evaluate LeHE4SCNN with various CNN models on a real-world dataset. Experimental results demonstrate the effectiveness and superiority of the LeHE4SCNN framework in terms of response time, usage cost, and communication overhead compared to the state-of-the-art methods in the mobile cloud computing environment.

• Nuclear Engineering and Technology
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• v.56 no.3
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• pp.1116-1123
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• 2024

-In recent years, unmanned underwater vehicles (UUV) have been vigorously developed, and with the continuous deepening of marine exploration, traditional energy can no longer meet the energy supply. Nuclear energy can achieve a huge and sustainable energy supply. The heat pipe reactor has no flow system and related auxiliary systems, and the supporting mechanical moving parts are greatly reduced, the noise is relatively small, and the system is simpler and more reliable. It is more favorable for the control of unmanned systems. The use of heat pipe reactors in unmanned underwater vehicles can meet the needs for highly compact, long-life, unmanned, highly reliable, ultra-quiet power supplies. In this paper, a heat pipe reactor scheme named UPR-S that can be applied to unmanned underwater vehicles is designed. The reactor core can provide 1 MW of thermal power, and it can operate at full power for 5 years. UPR-S has negative reactive feedback, it has inherent safety. The temperature and stress of the reactor are within the limits of the material, and the core safety can still be guaranteed when the two heat pipes are failed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.91-107
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• 2014

Device-to-device (D2D) communication is an excellent technology to improve the system capacity by sharing the spectrum resources of cellular networks. Multicast service is considered as an effective transmission mode for the future mobile social contact services. Therefore, multicast based on D2D technology can exactly improve the spectrum resource efficiency. How to apply D2D technology to support multicast service is a new issue. In this paper, a resource allocation scheme based on cognitive radio (CR) for D2D underlay multicast communication (CR-DUM) is proposed to improve system performance. In the cognitive cellular system, the D2D users as secondary users employing multicast service form a group and reuse the cellular resources to accomplish a multicast transmission. The proposed scheme includes two steps. First, a channel allocation rule aiming to reduce the interference from cellular networks to receivers in D2D multicast group is proposed. Next, to maximize the total system throughput under the condition of interference and noise impairment, we formulate an optimal transmission power allocation jointly for the cellular and D2D multicast communications. Based on the channel allocation, optimal power solution is in a closed form and achieved by searching from a finite set and the interference between cellular and D2D multicast communication is coordinated. The simulation results show that the proposed method can not only ensure the quality of services (QoS), but also improve the system throughput.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3497-3515
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• 2018

Differential privacy has broadly applied to statistical analysis, and its mainly objective is to ensure the tradeoff between the utility of noise data and the privacy preserving of individual's sensitive information. However, an individual could not achieve expected data utility under differential privacy mechanisms, since the adding noise is random. To this end, we proposed an adaptive Gaussian mechanism based on expected data utility under conditional filtering noise. Firstly, this paper made conditional filtering for Gaussian mechanism noise. Secondly, we defined the expected data utility according to the absolute value of relative error. Finally, we presented an adaptive Gaussian mechanism by combining expected data utility with conditional filtering noise. Through comparative analysis, the adaptive Gaussian mechanism satisfies differential privacy and achieves expected data utility for giving any privacy budget. Furthermore, our scheme is easy extend to engineering implementation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.5-23
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• 2011

One inevitable problem in Ad Hoc networks is the limited battery capacity, which explains why portable devices might shut down suddenly when the power of hardware is depleted. Hence, how to decrease the power consumption is an important issue in ad hoc networks. With the development of wireless technology, mobile devices can transmit voices, surf the Internet, download entertaining stuffs, and even support some P2P applications, like sharing real-time streaming. In order to keep the quality stable, the transmission must be continuous and it is thus necessary to select some managers to coordinate all nodes in a P2P community. In addition to assigning jobs to the staffs (children) when needed, these managers (ancestors) are able to reappoint jobs in advance when employees retire. This paper proposed a mechanism called Cluster-based Power Management (CPM) to stabilize the transmissions and increase Time to Live (TTL) of mobile hosts. In our new proposed method, we establish the clusters according to every node's joining order and capability, and adjust their sleep time dynamically through three different mathematical models. Our simulation results reveal that this proposed scheme not only reduces the power consumption efficiently, but also increases the total TTLs evidently.

• Journal of the Society of Naval Architects of Korea
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• v.37 no.4
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• pp.1-10
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• 2000

A panel method based on the raised panel approach is developed for the nonlinear ship wave problem of practical hull forms. For the validation of the present numerical scheme. the developed method is first applied to Series 60 hull for which the extensive experimental data are available. As practical applications. the developed method is applied to KRISO 3600 TEU container ship and KRISO 300K VLCC. With the primary emphasis on the nonlinear effects of the global wave pattern generated by the two commercial ships. the calculated wave patterns are compared and verified with the experiments of KRISO. It is found that the calculated results of the present method are quite satisfactory compared with the linear methods like Dawson's approach and Neumann-Kelvin solution.