Katsuya Suto

An Energy-Efficient and Delay-Aware Wireless Computing System for Industrial Wireless Sensor Networks

Industrial wireless sensor networks have attracted much attention as a cornerstone to making the smart factories real. Utilizing industrial wireless sensor networks as a base for smart factories makes it possible to optimize the production line without human resources, since it provides industrial Internet of Things service, where various types of data are collected from sensors and mined to control the machines based on the analysis result. On the other hand, a fog computing node, which executes such real-time feedback control, should be capable of real-time data collection, management, and processing. To achieve these requirements, in this paper, we introduce wireless computing system (WCS) as a fog computing node. Since there are a lot of servers and each server has 60 GHz antennas to connect to other servers and sensors, WCS has high collecting and processing capabilities. However, in order to fulfill a demand for real-time feedback control, WCS needs to satisfy an acceptable delay for data collection. In addition, lower power consumption is required in order to reduce the cost for the factory operation. Therefore, we propose an energy-efficient and delay-aware WCS. Since there is a tradeoff relationship between the power consumption and the delay for data collection, our proposed system controls the sleep schedule and the number of links to minimize the power consumption while satisfying an acceptable delay constraint. Furthermore, the effectiveness of our proposed system is evaluated through extensive computer simulations.

A cloud radio access network with power over fiber toward 5G networks: QoE-guaranteed design and operation

While the concept of Cloud Radio Access Networks (C-RANs) presents a promising solution to provide required quality of service (QoS) for the future network environment, i.e., more than 10 Gbps capacity, less than 1 ms latency, and connectivity for numerous devices, it is still susceptible to quality of experience (QoE) problems. Until now, only a few researchers considered the design and operation of C-RANs based on QoE. In this article we describe our envisioned C-RAN based on passive optical networks (PONs) exploiting power over fiber (PoF), which can be installed with low installation cost and is capable of providing communication services without external power supply for remote radio head (RRH), and describe QoE requirement on the envisioned network. For all users in the envisioned network to satisfy their QoE, effective network design and operation approaches are then presented. Our proposed design and operation approaches demonstrate how to construct the envisioned network, i.e. the numbers of RRHs and optical line terminals (OLTs), and sleep scheduling of RRHs for an energy-efficient optical power transmission.

Designing P2P Networks Tolerant to Attacks and Faults Based on Bimodal Degree Distribution

Recently, in contrast with the centralized net- works (e.g., traditional client/server systems), the distributed networks such as Peer-to-Peer (P2P) networks and grid networks have attracted much attention due to their scal- ability. While the distributed networks have the advantage of allowing the node(s) to join or leave the network easily, the issue of lack of resiliency to both attacks and faults still remains. In this paper, we classify the existing distributed networks based on their degree distributions. Then, we demonstrate that they are not resilient to attacks and/or faults. For example, unstructured P2P networks, which have a power-law degree distribution, are vulnerable to attacks such as DOS. To address and resolve this issue, we propose a method to construct a network following bimodal degree distribution, which is robust to deal with both attacks and faults. Performance evaluation is conducted through computer simulations, which show that the proposed method can achieve higher resilience compared with other existing networking approaches.

THUP: A P2P Network Robust to Churn and DoS Attack Based on Bimodal Degree Distribution

Hierarchical unstructured peer-to-peer (P2P) networks for file sharing systems such as Gnutella and Kazaa have made a tremendous achievement in the last decade. However, while these P2P networks can be tolerant to churn, i.e., the dynamics of peer participation and departure (or fault), there still remains the issue of vulnerability to Denial of Service (DoS) attacks, i.e., when the highest degree peers are removed. In order to overcome this shortcoming, we focus on a bimodal degree distribution, which is tolerant to both churn and DoS attacks. However, the network topology affects the network stability that was not taken into considered in the previous works. Therefore, we analyze the optimal network topology for DoS attack tolerance, and accordingly develop the peer joining procedure to construct and maintain the proposed network topology. Our proposed scheme is dubbed THUP (churn/DoS Tolerant, Hierarchical, Unstructured, P2P network). Performance evaluation conducted through computer simulations shows that THUP substantially improves the stability and communication efficiency compared with other existing P2P networking structures.

QoE-Guaranteed and Power-Efficient Network Operation for Cloud Radio Access Network With Power Over Fiber

A concept of cloud radio access networks (C-RANs) is becoming a popular solution to support the required communication quality for new emerging service in the future network environment, i.e., more than 10 Gbps capacity, less than 1 ms latency, and connectivity for numerous devices. In this paper, we envision a C-RAN based on passive optical network (PON) exploiting power over fiber (PoF), which achieves low installation and operation costs since it is capable of providing communication services without external power supply for large amount of remote radio heads (RRHs). This network, however, needs to reduce the optical transmission power of PoF due to the fiber fuse issue. Additionally, the diversification of services, devices, and personality indicates the need to improve user satisfaction, i.e., quality of experience (QoE), based on the users perspective, which is different from previous approaches that aim to guarantee quality of services (QoS). Therefore, we propose a QoE-guaranteed and power-efficient network operation strategy. Our proposed operation is able to reduce the transmission power while satisfying the QoE constraint by controlling both the schedule of RRHs sleep and optical transmission power of PoF. Furthermore, the effectiveness of our proposed operation scheme is evaluated through extensive computer simulations.

An Overlay-Based Data Mining Architecture Tolerant to Physical Network Disruptions

Management scheme for highly scalable big data mining has not been well studied in spite of the fact that big data mining provides many valuable and important information for us. An overlay-based parallel data mining architecture, which executes fully distributed data management and processing by employing the overlay network, can achieve high scalability. However, the overlay-based parallel mining architecture is not capable of providing data mining services in case of the physical network disruption that is caused by router/communication line breakdowns because numerous nodes are removed from the overlay network. To cope with this issue, this paper proposes an overlay network construction scheme based on node location in physical network, and a distributed task allocation scheme using overlay network technology. The numerical analysis indicates that the proposed schemes considerably outperform the conventional schemes in terms of service availability against physical network disruption.

Toward integrating overlay and physical networks for robust parallel processing architecture

Recently, much research attention is being paid toward the wide-area parallel processing architectures whereby all the network devices in the entire network execute the processing function in order to shorten the completion time of big data mining tasks. Despite some advancement, such architectures still suffer from physical network failures, which lead to critical service unavailability. As a remedy to this problem, an overlay-based parallel processing architecture, where nodes manage each other by employing the overlay network, can achieve higher service availability against small-scale failures. However, the overlay-based parallel processing architecture is not capable of providing data mining services in case large-scale network failures disrupt the overlay network. To deal with this issue, our article introduces a design methodology of an overlay-based parallel processing architecture based on integration of overlay and physical networks. Additionally, we introduce basic principles based on the design methodology. Through numerical calculation, we evaluate the effectiveness of an integration approach on the performance of parallel data processing in terms of higher service availability against physical network failures while minimizing traffic load.

A Failure-Tolerant and Spectrum-Efficient Wireless Data Center Network Design for Improving Performance of Big Data Mining

Wireless Data Center Network (Wi-DCN) is considered one of the most promising future data center architectures due to its low installation and management cost and high flexibility of network design. However, the existing Wi-DCN is, still, not capable of providing an efficient big data mining service such as MapReduce because its topology (i.e., Cayley graph with same degree) cannot achieve enough connectivity on the breakdown of servers and spectrum efficiency, which are important factors to improve the performance of big data mining. Therefore, in order to modify the existing Wi-DCN for big data mining, this paper proposes a spherical rack architecture based on a bimodal degree distribution that improves both failure tolerance and spectrum efficiency. Extensive computer simulations demonstrate the effectiveness of our proposed rack architecture in terms of data transmission time required for MapReduce under a failure-prone environment.

Context-aware task allocation for fast parallel big data processing in optical-wireless networks

MapReduce architecture has been considered as one of the most promising candidates for efficient and reliable big data mining. While current MapReduce is basically designed for data center and enterprise networks, in which a number of servers are interconnected with optical fiber cables, prospective MapReduce would be applied in optical-wireless environment such as optical-wireless data center network, fiber-wireless (FiWi) access network, and so forth. To modify MapReduce for opticalwireless hybrid network, we need to answer the fundamental research problem, “How does MapReduce architecture use optical and wireless resources for task allocation?” To answer this question, this paper reveals some challenging issues and proposes a context-aware task allocation scheme that is designed by considering characteristics of both optical and wireless communications. Our proposed task allocation scheme can minimize the completion time of big data processing. Numerical results are presented to demonstrate the effectiveness of our proposed method compared with existing task allocation schemes.

Towards a Low-Delay Edge Cloud Computing through a Combined Communication and Computation Approach

There are many applications which cannot be executed by mobile devices due to their limitations in memory, processing, battery, among others. One solution to this would be offloading heavy tasks to cloud servers in the edge of the network, in a service model called Edge Cloud Computing. The main Quality of Service requirement of this model is a low Service Delay, which can be achieved by lowering Transmission Delay and Processing Delay. Works in literature focus on either one of those two types of delay. This paper, however, argues that an approach which combines transmission and processing technologies to lower Service Delay would be more efficient. This idea is defended by an analysis of the service model and existing stochastic modeling of the Edge Cloud Computing system. We conclude that a dual focus approach would be the only way of truly minimizing the Service Delay, therefore being the desired method to improve Quality of Service. We conclude by laying the foundation for a future model that follows such concept.