Abstract Cross‐silo federated learning (FL) has been proposed and applied in many domains such as financial risk prediction, pharmaceutical discovery, electronic health records mining. In this paradigm, multiple clients can collaboratively train machine learning models with higher accuracy while protecting their privacy under the coordination of a central server. To interconnect these geo‐distributed clients and the central server, the architecture of FL is proposed over software‐defined wide area network (SD‐WAN). The total time to achieve the required accuracy for FL depends on both the time of each iteration and the number of iterations. Because the bandwidth for each path from client to central server is constrained, different client selection schemes and different path routing mechanisms may lead to different times of iteration. The authors propose FedMT algorithm to minimize the total time through well‐designed client selection and routing, which greatly reduces the upload time of each iteration while slightly affecting the number of iterations. Extensive experiments are conducted and demonstrated the time to achieve the same accuracy for FedMT is less than half of that for FedAvg and FedProx.

Federated learning has been a promising distributed machine learning approach in many fields like e-economic, autodriving and medical imaging for its privacy-aware manner. However, researchers have discovered that the performance of traditional federated learning approaches such as Federated Averaging (FEDAVG) declines extremely under Non-Independent and Identical (Non-IID) situations. We observed that part of the reason is the improper way of traditional federated learning’s server-side aggregation method.The contributions of clients in federated learning can be distinguished by their trained models’ validated accuracies. Based on that observation, we proposed a new federated learning algorithm, Accuracy Based Averaging (ABAVG), which improves the server-side aggregation method of traditional federated learning so that it can accelerate the convergence speed of federated learning in Non-IID situations. We extensively evaluate our proposed algorithm with FEDAVG as a baseline and we experiment on various Non-IID conditions to demonstrate the robust of our proposed algorithm. Experimental results show that the convergence speed averagely increased by 47% in Mnist dataset, 59% in Fashion-Mnist dataset and 33% in CIFAR-10 dataset in different data distributions by ABAVG.

In optical satellite network, the possible optical inter-satellite links (OISLs) candidate for each satellite are usually more than laser communication terminals (LCTs) equipped. This poses the link assignment problem (LAP) of how to assign LCTs of each satellite to establish OISLs with the others. In order to make full use of huge bandwidth provided by LCT, the problem of assigning all satellite LCTs to establish OISLs is modeled as a perfect matching problem in the perfect match model, where a perfect matching is searched over a mixed complete bipartite graph. The regular, random greedy and perfect match model based link assignment schemes are considered. Simulation results show that the average node-to-node distance and LCT utilization of perfect match model based link assignment scheme are better than the regular and random greedy link assignment schemes.

In the High Speed Internet (HSI) service of the Fiber-To-The-Home (FTTH) networks, there are increasingly various applications, such as browsing, video streaming, large downloads and online games. They are competing for the fixed bandwidth on a best-effort basis, and finally resulting in the network congestion and poor quality of experience (QoE). Users want to improve the quality of certain applications. However, today's network service controller (e.g. Broadband Remote Access Server, BRAS) lacks mechanisms to meet the users' desire to enhance the QoE of specific applications. Moreover, BRAS still lacks mechanisms to allocate the bandwidth resources properly for users' different applications according to their “sweet points”. “Sweet points” is a specific bandwidth value. The QoE gets worse quickly when the bandwidth is smaller than the “sweet point”, and keeps the same approximately when the bandwidth is larger than the “sweet point”. In this paper, we proposed a novel BRAS architecture using Software-Defined Networking (SDN) technology, which can improve the user's QoE by adjusting the bandwidth of a specific application to its “sweet point” according to their requirements. To demonstrate the feasibility of our proposed novel BRAS, we built a prototype using SDN to help the user to adjust the bandwidth for the specific application and improve the users' QoE. The experimental results show that users could enhance the QoE of specific applications according to users' preference.

The Ethernet passive optical network (EPON) has recently emerged as the mainstream of broadband access networks. The registration process of EPON, which is defined by the IEEE 802.3av standard, is a multi-point control protocol within the media access control layer. As with other contention-based channel access methods, such as ALOHA and CSMA, stability and delay are critical issues concerning the performances of implementing the protocol on systems with finite channel capacity. In this paper, the registration process of an EPON subscriber, called optical network units (ONUs), is modeled as a discrete-time Markov chain, from which we derive the fundamental throughput equation of EPON that characterizes the registration processes. The solutions of this characteristic equation depend on the maximum waiting time. The aim of our stability analysis is to pinpoint the region of the maximum waiting time that can guarantee a stable registration throughput and a bounded registration delay. For a maximum waiting time selected from the stable region, we obtain the expression of registration delay experienced by an ONU attempting to register. All analytic results presented in this paper were verified by simulations.

In Ethernet Passive Optical Networks (EPONs) with offline Dynamic Bandwidth Allocation (DBA) framework, the Optical Line Terminal (OLT) will first collect bandwidth requests from all Optical Network Units (ONUs), and then make bandwidth allocation and scheduling decisions for the shared upstream channel. Due to varying Round-Trip Time (RTT) and grant window sizes, the transmission order of ONUs will greatly affect the mean packet delay. In this paper, we address this grant scheduling problem aiming at minimizing the mean packet delay. We prove several theorems which could determine the ONU to transmit first which will minimize the mean packet delay. And then, by iteratively using these theorems, we propose an Integrated Grant Scheduling (IGS) algorithm to determine the optimal transmission order to minimize the mean packet delay. We then conduct simulations to evaluate the performance of our algorithm, and find that the performance of our algorithm is better compared with other algorithms under various conditions.

Bulk data transfers, which require reliable and efficient transfer of terabits or even petabits of data for data-intensive applications, have been extensively studied. In these applications, usually, a specified amount of data needs to be transferred within strict deadline. Previous researches mainly focus on routing deadline-constrained bulk data transfers to improve the utilization of network resources for guarantying deadline requirements, without considering network failures. This paper proposes novel routing algorithm for deadline-constrained bulk data transfers based on Transfer Failure Probability using continuous-time Markov model. The goal of the novel algorithm is to guarantee the deadline requirement by decreasing the failure probability of data transfer request under network failure settings. Simulation evaluates the performance and demonstrates the effectiveness of our algorithm in terms of deadline violation ratio and service blocking ratio under network failures.

Multi-channel delivery is one competitive solution to reduce channel change time in IPTV. We presented the performance analysis on finite duration multi-channel delivery method in our previous work, when channel changes are sequential and adjacent. In this paper, we develop mathematical models to evaluate the performance of this method when channel change happens randomly. This in fact generalizes the previous model. We find that, in typical setup, a delivery duration of 20 seconds is enough to reduce the channel change time by 47.5%, yet the peak bandwidth increase on carrier's uplink is 66.7%. This indicates that the finite duration multi-channel delivery method can improve viewers' experience effectively when channel changes are random.

The integrated computing system optical network has been viewed as a promising platform to support real-time distributed computing applications. For such a system involving so many heterogeneous computing and network resources, faults seem to be inevitable. Therefore, a fault-tolerant scheme is necessary to improve the availability of the integrated system. However, existing joint task scheduling schemes for real-time distributed computing applications generally do not consider the application availability issues when making scheduling decisions. In this paper, we develop an availability-aware joint task scheduling (AAJTS) scheme, by both taking into account availability improvement and timing requirements. The proposed scheme iteratively enhances the application availability under deadline constraint to protect data communication tasks from network link failures. Extensive simulations demonstrate the effectiveness and the feasibility of the proposed scheme.

In this paper, we study the efficiency of inter-domain state advertising in multi-domain networks, in which the intra-domain topology is substituted with a full-mesh topology of abstract links interconnecting the border nodes of the domain. The advertising trigger rate of individual abstract link is taken as the metric of efficiency. We present an analytical model that reveals the contributions of different physical links to the advertising trigger rate of individual abstract links. According to the model, we propose a state based advertising mechanism, called partial link based advertising (PLA) which can discern and advertise the state variation of individual abstract link by monitoring only a portion of physical links. We formulate the problem of how to optimally selecting physical links to monitor, and provide a heuristic algorithm for link selection. Results show that the PLA performs more efficiently than existing mechanisms in terms of advertising trigger rate and blocking probability.

The optical network based distributed computing system has been thought as a promising technology to support large-scale data-intensive distributed applications. For such a system with so many heterogeneous resources and middlewares involved, faults seem to be inevitable. However, for those applications that need to be finished before the given deadline, a fault in the system will lead to the failure of the application. Therefore, fault-tolerant policy is necessary to improve the performance of the system when faults could happen. In this paper, we address to the fault-tolerant problem for the optical network based distributed computing system. We first propose an overlay approach which applies the existing fault-tolerant policies for distributed computing and optical network. Then we present a joint fault-tolerant policy which takes into account the fault tolerance for computing resource and network resource in the same time. We compare the performances of different polices by simulation. The simulation results show that the joint fault-tolerant policy achieves much better performances compared to overlay approaches.

In this paper, we investigated designing multicast-capable optical cross-connects (MC-OXCs) on a basis of the 4- stage multicast network. Firstly, we derive the sufficient wide- sense nonblocking (WSNB) and rearrangeable nonblocking (RNB) conditions for the 4-stage multicast network with only two (the second and output) stages being multicast-capable. Both WSNB and RNB 4-stage multicast networks need 0(N3/2) crosspoints. Then MC-OXCs empoying the WSNB and RNB 4-stage multicast network are proposed and proven to be power efficient in reducing the total power loss caused by light splitting.

Data-intensive Grid applications require huge data transferring between multiple geographically separated computing nodes where computing tasks are executed. For a future WDM network to efficiently support this type of emerging applications, traditional approaches to establishing lightpaths between given source destination pairs are not sufficient because a computing task may be executed on any one of several computing nodes having the necessary resources. Therefore, lightpath establishment has to be considered jointly with task scheduling to achieve best performance. We study the optimization problems of jointly scheduling both computing resources and network resources. We first present the formulation of two optimization problems with the objectives being the minimization of the completion time of a job and minimization of the resource usage/cost to satisfy a job with a deadline respectively. When the objective is to minimize the completion time, we devise an optimal algorithm for a special type of applications. Furthermore, we propose efficient heuristics to deal with general applications with either optimization objective and demonstrate their good performances via simulation.

It is widely believed that IP over optical networks will be a major component of the next generation Internet However, it is not efficient to map a single multicast IP flow into one light-tree, since the bandwidth of an IP flow required is usually much less than that of a light-tree. In this paper, we study the problem of multicast flow aggregation (MFA) in the IP over optical two-layered networks under the overlay model, which can be defined as follows: given a set of head ends (i.e. optical multicasting sources), each of which can provide a set of contents (i.e. multicast IP flows) with different required transmission bandwidth, and a set of requested content at the access routers (i.e. optical multicasting destinations), find a set of light-trees as well as the optimal aggregation of multicast IP flows in each light-tree. We model MFA by a tri-partite graph with multiple criteria and show that the problem is NP-complete. Optimal solutions are designed by exploiting MFA to formulate an integer linear programming (ILP), with two parameters: the multicast receiving index alpha and the redundant transmitting index beta. We also propose a heuristic algorithm. Finally, we compare the performance of MFA for different combination of alpha and beta via experiments and show our heuristic algorithm is effective for large-scale network in numerical results

To support large-scale IP-TV signal delivering, a new multicast-IP over light-tree network model was proposed in W. Sun et al. In this paper, we study the problem of topology-independent IP group aggregation in the multicast capable optical network. We first use a tri-partite graph to describe the problem, and then formulate the problem by a mixed integer linear programming (MILP) model. Finally, we propose a pre-estimation for the number of light-trees to reduce the searching space, which significantly saves solving time of MILP

This paper focuses on dynamic integrated routing in multifiber Internet protocol/wavelength-division multiplexing (IP/WDM) networks, which can be implemented through either one-step routing (OSR) or two-step routing (TSR) approach. Based on an extended layered-graph, two resource assignment strategies, termed channel-level balance (CLB) and link-level balance (LLB), are proposed to balance the traffic in the network at different levels. To further improve the performance, a parameter K is introduced to make a dynamic tradeoff between the logical-layer links and the optical-layer links. Simulation studies are carried out for various topologies. The results show that LLB is better than CLB in most cases, and LLB combined with OSR has the optimal performance. Also, we find that the routing approach and the resource assignment strategy individually play different roles with different values of r/sub l/ that is introduced to indicate the resource richness of the network. As a multifiber network is functionally equivalent to a single-fiber network with limited wavelength conversion, we investigate the effects of wavelength conversion by studying the multifiber IP/WDM networks. The analysis shows that, when the granularity of each connection request is much smaller than the wavelength granularity, wavelength conversion may increase the request blocking probability in the network.