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We propose a novel distributed denial of service (DDoS) attack suppression system that significantly reduces discarding of normal traffic (i.e., the traffic from Internet of Things (IoT) devices that are not infected with a malware) with a small number of equipment by controlling the priority of frames in a network accommodating IoT devices. Experimental results showed that our proposed system prevented the discarding of the normal traffic in a few seconds when attack traffic was generated by a traffic generator. Moreover, we constructed Mirai-based DDoS attack traffic and experimentally demonstrated that the discarding of the normal traffic was prevented in 30 milliseconds in our proposed system. We also confirmed that the attack traffic detected by a DDoS protector that was installed in front of an IoT server was autonomously blocked at the switches that the traffic came through from the IoT devices (i.e., the entrances to a backbone network) by integrating various vendors’ products.

There is an increasing demand for motion control of Internet of Things devices such as drones and industrial machines from large computational resources on the network side. Since the delay between communication devices adversely affects the control performance, utilization of low-latency platforms such as edge computing is promising. However, no other study focuses on architecture and control methods in optical access network for motion control. We aim at realizing the access edge that performs real-time motion control on an edge server located in a central office. This paper proposes an access edge configuration and a control method that offers time-varying delay compensation based on delay information. We evaluate control performance of our method when delay is increased and packet loss occurs under a high network load environment. We demonstrate that when the downstream traffic changes from 9 to 10 Gbps, the proposed method offers motor control settling times of 2.7 s and 8.0 s, respectively, while the conventional method cannot control the motor in either case.

An aggregating switch (SW) network offers cost-effective accommodation to Internet-of-Things (IoT) traffic by aggregating the traffic. In such a network, it is crucial to eliminate the discarded traffic caused by the simultaneous transmission of massive IoT devices, namely microburst. Traffic shaping is a technique of storing traffic in one SW to mitigate microbursts. Conventional traffic shaping is limited because only one SW performs shaping with a limited queue length. Thus, we propose cooperated traffic shaping using multiple SWs to accommodate more traffic. We formulated equations to derive the minimum queue length with shaping rates which gradually decrease in geometric progression. To acquire the queue length using general SWs without short-cycle monitoring, we propose a scheme for estimating the instantaneous input rate and data size of microburst traffic required for our equations. If the calculated queue length cannot be prepared in the current path, we propose reallocating the path to another one with more SWs. We experimentally demonstrated the proposed coordinated traffic shaping technique by implementing it in commercial SWs with 125 emulated IoT devices. The results showed that the difference between the experimental and numerical results was below 4.2%, and the queue length can be reduced by 40% when there are three SWs. In addition, a path with two SWs was successfully reallocated to one with three SWs.

To accommodate various applications in optical access systems, the Software-Defined Network (SDN) with edge computing is the key allowing telecom operators to achieve flexible and cost-effective deployment. To control the various network functions needed to meet the variety of requests, softwarization of all access system functions, including transmission functions, and open Application Programming Interfaces (APIs) have been studied. As well as function changes, we aim at maximizing the merits of SDN by adaptively configuring network function parameters to meet individual application requirements. This paper proposes a novel access system architecture with configuration optimizer that adaptively generates parameter configuration values from application requirements, and adaptive configuration values for image transmission to enhance computation efficiency. Our proposal includes Forward Error Correction (FEC) with error correction control in decoding to suit image quality requirements. Our proposal is implemented on a general-purpose server and we demonstrate its performance using the softwarized 10G-EPON Physical Coding Sublayer (PCS) functionality on an optical system. The demonstration results show that the proposed algorithm adjusts the error correction capability of FEC, and that the received image quality approaches the required value. Evaluations of FEC computation load show that the processing time of FEC is reduced compared to the standard functions of 10G-EPON depending on the optical received power and the required image quality by adjusting the error correction capability.

The application of network function virtualization (NFV) and software-defined networks (SDNs) to optical access systems continues to attract a lot of attention. Their use on general-purpose hardware allows for cost-effective implementation and quick response to functional requirements. This paper demonstrates the softwarization of the complete downstream physical (PHY)-layer functions of the optical line terminal (OLT), including a scrambler, which uses a serial processing algorithm that cannot be parallelized by a general-purpose graphics processing unit (GPU). We propose CPU-GPU cooperative implementation architecture that softwarizes the complete 10G-EPON OLT downstream PHY. We achieve 10.3125-Gbps real-time performance through experiments for the first time.