The power consumption of optical network units (ONUs) is a major issue in optical access networks. The downstream buffer is one of the largest power consumers among the functional blocks of an ONU. A cyclic sleep scheme for reducing power has been reported, which periodically powers off not only the downstream buffer but also other components, such as optical transceivers, when the idle period is long. However, when the idle period is short, it cannot power off those components even if the input data rate is low. Therefore, as continuous traffic, such as video, increases, the power-reduction effect decreases. To resolve this issue, we propose another sleep scheme in which the downstream buffer can be partially powered off by cooperative operation with an optical line terminal. Simulation and experimental results indicate that the proposed scheme reduces ONU power consumption without causing frame loss even while the ONU continuously receives traffic and the idle period is short.

Emerging byte-addressable non-volatile memory devices attract much attention. A non-volatile main memory (NVMM) built on them enables larger memory size and lower power consumption than a traditional DRAM main memory. To fully utilize an NVMM, both software and hardware must be cooperatively optimized. Simultaneously, even focusing on a memory module, its micro architecture is still being developed though real non-volatile memory modules, such as Intel Optane DC persistent memory (DCPMM), have been on the market. Looking at existing NVMM evaluation environments, software simulators can evaluate various micro architectures with their long simulation time. Emulators can evaluate the whole system fast with less flexibility in their configuration than simulators. Thus, an NVMM emulator that can realize flexible and fast system evaluation still has an important role to explore the optimal system. In this paper, we introduce an NVMM emulator for embedded systems and explore a direction of optimization techniques for NVMMs by using it. It is implemented on an SoC-FPGA board employing three NVMM behaviour models: coarse-grain, fine-grain and DCPMM-based. The coarse and fine models enable NVMM performance evaluations based on extensions of traditional DRAM behaviour. The DCPMM-based model emulates the behaviour of a real DCPMM. Whole evaluation environment is also provided including Linux kernel modifications and several runtime functions. We first validate the developed emulator with an existing NVMM emulator, a cycle-accurate NVMM simulator and a real DCPMM. Then, the program behavior differences among three models are evaluated with SPEC CPU programs. As a result, the fine-grain model reveals the program execution time is affected by the frequency of NVMM memory requests rather than the cache hit ratio. Comparing with the fine-grain model and the coarse-grain model under the condition of the former's longer total write latency than the latter's, the former shows lower execution time for four of fourteen programs than the latter because of the bank-level parallelism and the row-buffer access locality exploited by the former model.

In order to erase data including confidential information stored in storage devices, an unrelated and random sequence is usually overwritten, which prevents the data from being restored. The problem of minimizing the cost for information erasure when the amount of information leakage of the confidential information should be less than or equal to a constant asymptotically has been introduced by T. Matsuta and T. Uyematsu. Whereas the minimum cost for overwriting has been given for general sources, a single-letter characterization for stationary memoryless sources is not easily derived. In this paper, we give single-letter characterizations for stationary memoryless sources under two types of restrictions: one requires the output distribution of the encoder to be independent and identically distributed (i.i.d.) and the other requires it to be memoryless but not necessarily i.i.d. asymptotically. The characterizations indicate the relation among the amount of information leakage, the minimum cost for information erasure and the rate of the size of uniformly distributed sequences. The obtained results show that the minimum costs are different between these restrictions.

In a network topology design problem, it is important to analyze the reliability and construction cost of complex network systems. This paper addresses a topological optimization problem of minimizing the total cost of a network system with separate subsystems under a reliability constraint. To solve this problem, we develop three algorithms. The first algorithm finds an exact solution. The second one finds an exact solution, specialized for a system with identical subsystems. The third one is a heuristic algorithm, which finds an approximate solution when a network system has several identical subsystems. We also conduct numerical experiments and demonstrate the efficacy and efficiency of the developed algorithms.

Because solar energy is intermittent and a ship's power-system load fluctuates and changes abruptly, in this work, the solar radiation parameters were adjusted according to the latitude and longitude of the ship and the change of the sea environment. An objective function was constructed that accounted for the cost and service life simultaneously to optimize the configuration of the marine diesel engine hybrid energy system. Finally, the improved artificial bee colony algorithm was used to optimize and obtain the optimal system configuration. The feasibility of the method was verified by ship navigation tests. This method exhibited better configuration performance optimization than the traditional methods.

In this letter, a two-stage QR decomposition scheme based on Givens rotation with novel modified real-value decomposition (RVD) is presented. With the modified RVD applied to the result from complex Givens rotation at first stage, the number of non-zero terms needed to be eliminated by real Givens rotation at second stage decreases greatly and the computational complexity is thereby reduced significantly compared to the decomposition scheme with the conventional RVD. Besides, the proposed scheme is suitable for the hardware design of QR decomposition. Evaluation shows that the proposed QR decomposition scheme is superior to the related works in terms of computational complexity.

A modified whale optimization algorithm (MWOA) with dynamic leader selection mechanism and novel population updating procedure is introduced for pattern synthesis of linear antenna array. The current best solution is dynamic changed for each whale agent to overcome premature with local optima in iteration. A hybrid crossover operator is embedded in original algorithm to improve the convergence accuracy of solution. Moreover, the flow of population updating is optimized to balance the exploitation and exploration ability. The modified algorithm is tested on a 28 elements uniform linear antenna array to reduce its side lobe lever and null depth lever. The simulation results show that MWOA algorithm can improve the performance of WOA obviously compared with other algorithms.

A global content delivery plays an important role in the current Internet. Information-Centric Networking (ICN) is a future internet architecture which attempts to redesign the Internet with a focus on the content delivery. However, it has the potential performance degradation in the global content delivery. In this paper, we propose an ICN performance enhancing proxy (ICN-PEP) to mitigate this performance degradation. The key idea is to prefetch Data packets and to serve them to the consumer with the shorter round trip time. By utilizing ICN features, it can be developed as an offline and state-less proxy which has an advantage of scalability. We evaluate the performance of ICN-PEP in both simulation and experiment on global testbed and show that ICN-PEP improves the performance of global content delivery.

Coherent transceivers are now regarded as promising candidates for upgrading the current 400Gigabit Ethernet (400GbE) transceivers to 800G. However, due to the complicated structure of a dual-polarization IQ modulator (DP-IQM) with its bulky polarization-beam splitter/comber (PBS/PBC), the increase in the transmitter size and cost is inevitable. In this paper, we propose a compact PBS/PBC-free transmitter structure with a straight-line configuration. By using the concept of polarization differential modulation, the proposed transmitter is capable of generating a DP phase-shift-keyed (DP-PSK) signal, which makes it directly applicable to the current coherent systems. A detailed analysis of the system performance reveals that the imperfect equalization and the bandwidth limitation at the receiver are the dominant penalty factors. Although such a penalty is usually unacceptable in long-haul applications, the proposed transmitter can be attractive due to its significant simplicity and compactness for short-reach applications, where the cost and the footprint are the primary concerns.

The Software-defined network (SDN) uses a centralized SDN controller to store flow entries in the flow table of each SDN switch; the entries in the switch control packet flows. When a multicast service is provided in an SDN, the SDN controller stores a multicast entry dedicated for a multicast group in each SDN switch. Due to the limited capacity of each flow table, the number of flow entries required to set up a multicast tree must be suppressed. A conventional multicast routing scheme suppresses the number of multicast entries in one multicast tree by replacing some of them with unicast entries. However, since the conventional scheme individually determines a multicast tree for each request, unicast entries dedicated to the same receiver are distributed to various SDN switches if there are multiple multicast service requests. Therefore, further reduction in the number of flow entries is still possible. In this paper, we propose a multicast routing model for multiple multicast requests that minimizes the number of flow entries. This model determines multiple multicast trees simultaneously so that a unicast entry dedicated to the same receiver and stored in the same SDN switch is shared by multicast trees. We formulate the proposed model as an integer linear programming (ILP) problem. In addition, we develop a heuristic algorithm which can be used when the ILP problem cannot be solved in practical time. Numerical results show that the proposed model reduces the required number of flow entries compared to two benchmark models; the maximum reduction ratio is 49.3% when the number of multicast requests is 40.

As the nodes of AWSN (Aerial Wireless Sensor Networks) fly around, the network topology changes frequently with high energy consumption and high cluster head mortality, and some sensor nodes may fly away from the original cluster and interrupt network communication. To ensure the normal communication of the network, this paper proposes an improved LEACH-M protocol for aerial wireless sensor networks. The protocol is improved based on the traditional LEACH-M protocol and MCR protocol. A Cluster head selection method based on maximum energy and an efficient solution for outlier nodes is proposed to ensure that cluster heads can be replaced prior to their death and ensure outlier nodes re-home quickly and efficiently. The experiments show that, compared with the LEACH-M protocol and MCR protocol, the improved LEACH-M protocol performance is significantly optimized, increasing network data transmission efficiency, improving energy utilization, and extending network lifetime.

This paper proposes a parallel peak cancellation (PC) process for the computational complexity-efficient algorithm called PC with a channel-null constraint (PCCNC) in the adaptive peak-to-average power ratio (PAPR) reduction method using the null space in a multiple-input multiple-output (MIMO) channel for MIMO-orthogonal frequency division multiplexing (OFDM) signals. By simultaneously adding multiple PC signals to the time-domain transmission signal vector, the required number of iterations of the iterative algorithm is effectively reduced along with the PAPR. We implement a constraint in which the PC signal is transmitted only to the null space in the MIMO channel by beamforming (BF). By doing so the data streams do not experience interference from the PC signal on the receiver side. Since the fast Fourier transform (FFT) and inverse FFT (IFFT) operations at each iteration are not required unlike the previous algorithm and thanks to the newly introduced parallel processing approach, the enhanced PCCNC algorithm reduces the required total computational complexity and number of iterations compared to the previous algorithms while achieving the same throughput-vs.-PAPR performance.

Application-aware Traffic Engineering (TE) plays a crucial role in ensuring quality of services (QoS) for recently emerging applications such as AR, VR, cloud gaming, and connected vehicles. While a deterministic application-aware TE is required for these mission-critical applications, a negotiation procedure between applications and network operators needs to undergo major simplification to fulfill the scalability of the application based on emerging microservices and container-based architecture. In this paper, we propose a NetworkAPI framework which allows an application to indicate a desired TE behavior inside IP packets by leveraging Segment Routing over IPv6 (SRv6). In the NetworkAPI framework, the TE behavior provided by the network operator is expressed as an SRv6 Segment Identifier (SID) in the form of a 128-bit IPv6 address. Because the IPv6 address of an SRv6 SID is distributed using IP anycast, the application can utilize the unchanged SRv6 SID regardless of the application's location, as if the application controls an API on the transport network. We implement a prototype of the NetworkAPI framework on a Linux kernel. On the prototype implementation, a basic packet forwarding performance is evaluated to demonstrate the feasibility of our framework.

Multimedia data and information management is an important task according to the development of media processing technology. Multimedia is a useful resource that people understand complex situations such as the elderly care domain. Appropriate annotation is beneficial in several tasks of information management, such as storing, retrieval, and summarization of data, from a semantic perspective. However, the metadata annotation for multimedia data remains problematic because metadata is obtained as a result of interpretation depending on domain-specific knowledge, and it needs well-controlled and comprehensive vocabulary for annotation. In this study, we proposed a collaborative methodology for developing ontologies and annotation with domain experts. The method includes (1) classification of knowledge types for collaborative construction of annotation data, (2) division of tasks among a team composed of domain experts, ontology engineers, and annotators, and (3) incremental approach to ontology development. We applied the proposed method to 11 videos on elderly care domain for the confirmation of its feasibility. We focused on annotation of actions occurring in these videos, thereby the annotated data is used as a support in evaluating staff skills. The application results show the content in the ontology during annotation increases monotonically. The number of “action concepts” is saturated and reused among the case studies. This demonstrates that the ontology is reusable and could represent various case studies by using a small number of “action concepts”. This study concludes by presenting lessons learnt from the case studies.

In this letter we analyze the economic worth of GPU on analytical processing of GPU-accelerated database management systems (DBMSes). To this end, we conducted rigorous experiments with TPC-H across three popular GPU DBMSes. Consequently, we show that co-processing with CPU and GPU in the GPU DBMSes was cost-effective despite exposed concerns.

The Topics over Time (TOT) model allows users to be aware of changes in certain topics over time. The proposed method inputs the divided dataset of security blog posts based on a fixed period using an overlap period to the TOT. The results suggest the extraction of topics that include malware and attack campaign names that are appropriate for the multi-labeling of cyber threat intelligence reports.

In this paper, the effective Long Range (LoRa) based wireless sensor network is designed and implemented to provide the remote data sensing functions for the planned smart agricultural recycling rapid processing factory. The proposed wireless sensor network transmits the sensing data from various sensors, which measure the values of moisture, viscosity, pH, and electrical conductivity of agricultural organic wastes for the production and circulation of organic fertilizers. In the proposed wireless sensor network design, the LoRa transceiver module is used to provide data transmission functions at the sensor node, and the embedded platform by Raspberry Pi module is applied to support the gateway function. To design the cloud data server, the MySQL methodology is applied for the database management system with Apache software. The proposed wireless sensor network for data communication between the sensor node and the gateway supports a simple one-way data transmission scheme and three half-duplex two-way data communication schemes. By experiments, for the one-way data transmission scheme under the condition of sending one packet data every five seconds, the packet data loss rate approaches 0% when 1000 packet data is transmitted. For the proposed two-way data communication schemes, under the condition of sending one packet data every thirty seconds, the average packet data loss rates without and with the data-received confirmation at the gateway side can be 3.7% and 0%, respectively.

With the widespread diffusion of Internet of Things (IoT), the number of applications using wireless sensor devices are increasing, and Quality of Service (QoS) required for these applications is diversifying. Thus, it becomes difficult to satisfy a variety of QoS with a single wireless system, and many kinds of wireless systems are working in the same domains; time, frequency, and place. This paper considers coexistence environments of ZigBee and Wi-Fi networks, which use the same frequency band channels, in the same place. In such coexistence environments,ZigBee devices suffer radio interference from Wi-Fi networks, which results in severe ZigBee packet losses because the transmission power of Wi-Fi is much higher than that of ZigBee. Many existing methods to avoid interference from Wi-Fi networks focus on only one of time, frequency, or space domain. However, such avoidance in one domain is insufficient particularly in near future IoT environments where more ZigBee devices and Wi-Fi stations transfer more amount of data. Therefore, in this paper, we propose joint channel allocation and routing in both frequency and space domains. Finally, we show the effectiveness of the proposed method by computer simulation.

Network function virtualization (NFV) enables network operators to flexibly provide diverse virtualized functions for services such as Internet of things (IoT) and mobile applications. To meet multiple quality of service (QoS) requirements against time-varying network environments, infrastructure providers must dynamically adjust the amount of computational resources, such as CPU, assigned to virtual network functions (VNFs). To provide agile resource control and adaptiveness, predicting the virtual server load via machine learning technologies is an effective approach to the proactive control of network systems. In this paper, we propose an adjustment mechanism for regressors based on forgetting and dynamic ensemble executed in a shorter time than that of our previous work. The framework includes a reducing training data method based on sparse model regression. By making a short list of training data derived from the sparse regression model, the relearning time can be reduced to about 57% without degrading provisioning accuracy.

In this paper, we used the data set of domain names Global Top 1M provided by Alexa to analyze the effectiveness of Fallback in ECN. For the same test server, we first negotiate a connection with Not-ECN-Capable, and then negotiate a connection with ECN-Capable, if the sender does not receive the response to ECN-Capable negotiation from the receiver by the end of retransmission timeout, it will enter the Fallback state, and switch to negotiating a connection with Not-ECN-Capable. By extracting the header fields of the TCP/IP packets, we confirmed that in most regions, connectivity will be slightly improved after Fallback is enabled and Fallback has a positive effect on the total time of the whole access process. Meanwhile, we provided the updated information about the characteristics related to ECN with Fallback in different regions by considering the geographical region distribution of all targeted servers.