In this paper, we propose a mitigation system of high-level multiple access interference (MAI) for multimedia optical Code-Division Multiple-Access (CDMA) systems using the optical power selector (OPS). The proposed system can eliminate high-intensity MAI at the receiver for low-priority users. Moreover, the proposed system can reduce by half the required number of code sequences compared to the conventional scheme. As a result, the proposed system can increase the number of weights at the same code-length and, thus, obtain higher code spreading gain. We analyze performances of the proposed system and show that both high-priority users and low-priority users achieve lower bit error rates in comparison to the conventional scheme.

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 propose OOK-CDMA system with optical hard-limiters (OHLs) using schemes of transmitting optical pulses with two-level intensities. The proposed system can be applied to both cases with single OHL and double OHLs. In the proposed system, a frame corresponding to a bit time is divided into two frames, where the low intensity pulses are transmitted in the weighted positions at the former frame, and the high ones are transmitted in the weighted positions at the latter frame. At the receiver side, in each weighted position of low intensity level, the ability of Multiple Access Interferences (MAIs) cancellation by OHL is equal to that of the conventional systems. However, in each weighted position of high intensity level, the OHL with the higher-level threshold value can easily eliminate MAIs with low intensity, while the MAIs are not eliminated in the conventional system. As a result, the ability of interference cancellation by OHL is significantly increased. When using single OHL in the proposed system, the optimum combinations of the values of low-level weights and low-level intensity ratio depend on the received laser power. This means that deploying dynamic control of the values of low-level weights and low-level intensity ratio is an imperative requirement in the proposed system with single OHL. On the other hand, when using double OHLs, the optimum combinations of the values of low-level weights and low-level intensity ratio are always constant. We analyze the performance of the proposed system and show its advantage in terms of bit error probability compared to the conventional system in both cases with single OHL and double OHLs. We also show that the proposed system with double OHLs is more effective and practical than the one with single OHL depending on the received laser power.

We experimentally demonstrate an optical packet and circuit integrated (OPCI) ring network interoperated with a wavelength-switched optical network (WSON) in a network domain. OPCI network and WSON have distinct characteristics from each other: the methods to transfer path control messages and the protocols to set up or delete the optical connections in an optical circuit switch. To interoperate the two types of optical networks, we develop a common path control-plane which can establish or release an end-to-end path by only one autonomous distributed signaling process without stitching. In the common path control-plane, we modify the signaling protocol for OCS so that we can allocate a distinct wavelength to each link on an end-to-end path and also allocate a distinct path route to each of downstream and upstream directions in a bi-directional path. We experimentally show that the common path control-plane can dynamically establish end-to-end paths over the heterogeneous network including the two types of optical networks.

We present our proposed designs of optical access architecture based on WDM technology toward new-generation networks for two types of topologies: Single-star (SS) and passive-double-star (PDS). We adopt the concept of WDM-direct which links multiple wavelengths to each optical network unit (ONU). Our proposed architecture based on WDM-direct can achieve more than 10 Gbps access per ONU. Moreover, our architecture can provide not only conventional bandwidth-shared services but also bandwidth-guaranteed services requiring more than 10 Gbps bandwidth by establishing end-to-end lightpaths directly to each ONU, and thus meet high requirements of QoS in new-generation networks. Firstly, we show our proposed designs of SS-type architecture, and experimentally demonstrate the system. We confirm that the optical line terminal (OLT) successfully switches between packet/lightpath data transmissions for each ONU. In addition, we measure and evaluate optical power loss in upstream/downstream transmissions between the OLT and ONUs. Secondly, we show our proposed designs of PDS-type architecture, and theoretically analyze and evaluate the bit-rate capacity of the system.

Limitations are found in the recent Internet because a lot of functions and protocols are patched to the original suite of layered protocols without considering global optimization. This reveals that end-to-end argument in the original Internet was neither sufficient for the current societal network and nor for a sustainable network of the future. In this position paper, we present design guidelines for a future network, which we call the New Generation Network, which provides the inclusion of diverse human requirements, reliable connection between the real-world and virtual network space, and promotion of social potentiality for human emergence. The guidelines consist of the crystal synthesis, the reality connection, and the sustainable & evolutional guidelines.

Software defined networking (SDN) and OpenFlow, which enables the abstraction of vendor/technology-specific attributes, improve the control and management flexibility of optical transport networks. In this paper, we present an interoperability demonstration of SDN/OpenFlow-based optical path control for multi-domain/multi-technology optical transport networks. We also summarize the abstraction approaches proposed for multi-technology network integration at SDN controllers.

In this paper, we propose a method for automatic virtual resource allocation by using a multi-target classification-based scheme (MTCAS). In our method, an Infrastructure Provider (InP) bundles its CPU, memory, storage, and bandwidth resources as Network Elements (NEs) and categorizes them into several types in accordance to their function, capabilities, location, energy consumption, price, etc. MTCAS is used by the InP to optimally allocate a set of NEs to a Virtual Network Operator (VNO). Such NEs will be subject to some constraints, such as the avoidance of resource over-allocation and the satisfaction of multiple Quality of Service (QoS) metrics. In order to achieve a comparable or higher prediction accuracy by using less training time than the available ensemble-based multi-target classification (MTC) algorithms, we propose a majority-voting based ensemble algorithm (MVEN) for MTCAS. We numerically evaluate the performance of MTCAS by using the MVEN and available MTC algorithms with synthetic training datasets. The results indicate that the MVEN algorithm requires 70% less training time but achieves the same accuracy as the related ensemble based MTC algorithms. The results also demonstrate that increasing the amount of training data increases the efficacy ofMTCAS, thus reducing CPU and memory allocation by about 33% and 51%, respectively.