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Access links that connect client networks to public networks have to carry multiple-type and time-varying traffic. Those hybrid traffic flows compete for limited bandwidth, yet at the same time have drastically different performance requirements. As planning the link capacity for peak traffic demand is not economically viable, it is important that bandwidth on the access links is shared between different traffic classes in a way that maximal network utility can be achieved. In this paper, we study the frequency slot allocation problem on IP-over-elastic optical network (EON) access links that carry three types of traffic, namely, packet streams, latency critical circuit connections (e.g., video conferencing), and delay tolerant circuit connections (e.g., bulk data transfers). We define four network operation states; in each of which an access link serves traffic with different levels of fulfillment. We then formulate the allocation problem into a weak-constrained optimization problem and propose a genetic algorithm to solve it in real time. Numerical results show that the relative error of the genetic algorithm is within 3% and the access link keeps maintaining the optimal achievable network operation state. We also show that, by increasing the storage size, the access link can adapt to the increasing traffic load within a certain range without upgrading the expensive access link bandwidth. Our study provides useful insights in managing and operating IP-over-EON access links, and the concept of multiple network operation states can be generalized to networks that serve more than one type of traffic.

Multi-access edge computing (MEC) applications are often implemented in the form of task offloading, which results in an unprecedented demand for data transfers among MEC servers. However, the combination of expensive and limited bandwidth, growing peak demand, and heterogeneous requirements of mixed traffic has posed a great challenge in terms of task offloading. In this study, we present a storage-assisted optical upstream transport scheme (SOUT) to overcome this challenge. Latency-critical (LC) tasks are given preemptive priority over delay-tolerant (DT) tasks. To reduce peak demand, the storage of an MEC server is introduced to temporarily store DT tasks. Resource partitioning is performed with an adjustable boundary based on traffic fluctuation. Analytic models are presented to investigate the interplay between SOUT and the performance of tasks. Our key findings reveal that there exist two trade-offs to be considered in SOUT. To balance the trade-offs, we formulate the spectrum partitioning and storage assignment problem as an optimization model and solve it using a heuristic approach. Studies show that SOUT provides lower blocking probability for both LC and DT tasks at the cost of slight preemption and limited storage usage when compared with two state-of-the-art optical transport schemes. We further show that 60% of network expenditures can be saved by trading cost-efficient storage for expensive link spectrum resources under a certain network scenario. Overall, this study aims to provide useful insights into task offloading over elastic optical links.

Access links that connect cloud data centers or enterprise networks to public networks are important parts of the network infrastructure and make up considerable portions of overall network expenditures. When a customer network is connected to an overlaid elastic optical network, determining the capacity of the access link is difficult. Furthermore, access links carry mixed packet streams and circuit connections, each with different performance requirements. Additionally, traffic loads are time-varying and often exhibit diurnal patterns. In this study, we formulate the access link capacity dimensioning problem as an optimization problem with a nested dynamic constraint satisfaction subproblem. Instead of using hard performance measures, such as packet delays and blocking probabilities, we use the probability of fulfillment with regard to different traffic arrival rates as the performance measure and the performance–cost ratio as our optimization objective. Numerical results suggest that a 7.5% to 19.47% cost savings can be achieved if resources are shared between packet streams and circuit connections. And if resource preemptions are allowed, the delay performance for packet streams can be improved by 12% with more frequent preemptions. Our study provides useful insights into the planning and operation of access links.

We propose a resource allocation strategy on IP-over-EONs access links. It realizes the dynamic self-adaptive spectrum resource adjustment applying to traffic fluctuations and handles the performance requirements under the circuit/packet hybrid architecture.