A disaster-resilient multi-content optical datacenter network architecture

Cloud services based on datacenter networks are becoming very important. Optical networks are well suited to meet the demands set by the high volume of traffic between datacenters, given their high bandwidth and low-latency characteristics. In such networks, path protection against network failures is generally ensured by providing a backup path to the same destination, which is link-disjoint to the primary path. This protection fails to protect against disasters covering an area which disrupts both primary and backup resources. Also, content/service protection is a fundamental problem in datacenter networks, as the failure of a single datacenter should not cause the disappearance of a specific content/service from the network. Content placement, routing and protection of paths and content are closely related to one another, so the interaction among these should be studied together. In this work, we propose an integrated ILP formulation to design an optical datacenter network, which solves all the above-mentioned problems simultaneously. We show that our disaster protection scheme exploiting anycasting provides more protection, but uses less capacity, than dedicated single-link protection. We also show that a reasonable number of datacenters and selective content replicas with intelligent network design can provide survivability to disasters while supporting user demands

Adaptive time- and location-aware routing in telecom mesh networks

In telecom mesh networks, connections can be provisioned considering their availability requirements. A connection's availability can be estimated based on the links' statistical availability (e.g., depending on historical failure occurrences and repair times).The authors remark that the actual failure statistics depend on (i) when and (ii) where a connection is routed (as failure rates throughout the year and in different locations may be different). Moreover, the failure rate is not homogeneous along a link and a detailed time‐ and location‐aware availability calculation is required. Most link failures are caused by dig‐ups, thus there is a direct relationship between construction works, which require excavations, and link failures. So, the probability of a link failure at a certain location depends on (i) the time/day when dig‐up works are performed and (ii) population of the location (assuming that the more crowded the location is, the more constructions occur). By exploiting the time‐ and location‐dependent failure information, the authors investigate a novel adaptive time‐ and location‐aware routing scheme, which provisions connections on highly available paths depending on a connection's duration and availability requirements. The authors' approach shows significant upgrade‐cost savings, while satisfying the service requirements, compared with traditional approaches

Progressive datacenter recovery over optical core networks after a large-scale disaster

Today's cloud system are composed of geographically distributed datacenter interconnected by high-speed optical networks. Disaster failures can severely affect both the communication network as well as datacenters infrastructure and prevent users from accessing cloud services. After large-scale disasters, recovery efforts on both network and datacenters may take days, and, in some cases, weeks or months. Traditionally, the repair of the communication network has been treated as a separate problem from the repair of datacenters. While past research has mostly focused on network recovery, how to efficiently recover a cloud system jointly considering the limited computing and networking resources has been an important and open research problem. In this work, we investigate the problem of progressive datacenter recovery after a large-scale disaster failure, given that a network-recovery plan is made. An efficient recovery plan is explored to determine which datacenters should be recovered at each recovery stage to maximize cumulative content reachability from any source considering limited available network resources. We devise an Integer Linear Program (ILP) formulation to model the associated optimization problem. Our numerical examples using the ILP show that an efficient progressive datacenter-recovery plan can significantly help to increase reachability of contents during the network recovery phase. We succeeded in increasing the number of important contents in the early stages of recovery compared to a random-recovery strategy with a slight increase in resource consumption