The networking industry is offering new services leveraging recent technological advances in connectivity, storage, and computing such as mobile communications and edge computing. In this regard, extended reality, a term encompassing virtual reality, augmented reality, and mixed reality, can provide unprecedented user experience and pioneering service opportunities such as: live concerts, sports, and other events; interactive gaming and entertainment; immersive education, training, and demos. These services require high-bandwidth, low-latency, and reliable connections, and are supported by next-generation ultra-reliable and low-latency communications in the vision of 6G mobile communication systems. In this work, we devise a novel scheme, called backup from different data centers with multicast and adaptive bandwidth provisioning, to admit reliable, low-latency, and high-bandwidth extended reality live streams in next-generation networks. We consider network services where contents are non-cacheable and investigate how backup services can be offered by different data centers with multicast and adaptive bandwidth provisioning. Our proposed service-provisioning scheme provides protection not only against link failures in the physical network but also against computing and storage failures in data centers. We develop scalable algorithms for the service-provisioning scheme and evaluate their performance on various complex network instances in a dynamic environment. Numerical results show that, compared to conventional service-provisioning schemes such as those seeking backup services from the same data center, our proposed service-provisioning scheme efficiently utilizes network resources, ensures higher reliability, and guarantees low latency; hence, it is highly suitable for extended reality live streams.

With the adoption of edge computing, several data centers are available within the footprint of an optical metro network, and contents are replicated in multiple locations. Such a wide content replication offers a unique opportunity to provide better services to users, especially for content-based services, e.g., video delivery. Thus, a service-provisioning scheme can embrace this opportunity to optimize network resource utilization, improve reliability, and achieve lower latency. In this study, we propose a reliable service-provisioning scheme that selects the optimal subset of data centers hosting the desired content and inversely multiplexes a content request over multiple link-disjoint paths. We formulate an integer linear program and develop heuristics for the problem, and use them to solve various complex and realistic network instances. Numerical data show that, compared to conventional service-provisioning schemes such as multipath routing from a single data center or dedicated-path protection, our proposed scheme efficiently utilizes network resources, improves reliability, and reduces latency; hence, it is suitable for the above-mentioned services.

Cooperation among datacenter providers (DCPs) and network carriers is necessary to support today's ubiquitous cloud services. However, such cooperation can be constrained by limited visibility as confidential information, such as network topology, resource availability, etc., may not be disclosed among these entities due to regulatory policies. We study a DCP-carrier cooperation-based service restoration scheme during a disaster with the aid of a third-party mediator, namely a Provider Neutral Exchange (PNE). We propose a novel resource-driven demand-matching strategy to restore DCP services. When multiple DCPs compete for network resources (due to post-disaster resource crunch), resource balancing by PNE can achieve fair and efficient service restoration. To allow flexibility in demand-resource matching, DCPs generate multiple sets of connection requests and define varying priorities and bandwidth degradations for each request. Carriers evaluate the DCP requests and provide feedback (e.g., whether a request can be satisfied or not) based on their available resources. We present an eight-phase DCP-carrier cooperation framework, with each phase employing individual sub-tasks carried out by DCPs, carriers, and PNE. Results under different disaster scenarios show that our strategy significantly improves DCP service restoration, incurring less restoration time.

Large-scale disasters affecting both network and datacenter (DC) infrastructures can cause severe disruptions in cloud-based services. During post-disaster recovery, repairs are usually carried out in stages in a progressive manner due to limited repair resource availability. The order in which network elements and DCs are repaired can significantly impact users' reachability to important contents/services. We investigate joint progressive network and DC recovery in which network recovery and DC recovery are conducted in a coordinated manner such that users have access to the maximum possible amount of contents/services at each repair stage. We first solve the optimization problem of joint progressive recovery to find the optimal sequence of network element and DC repairs with the objective to maximize cumulative weighted content reachability in the network. We then propose a scalable heuristic for scheduling the sequential repair of network nodes/links and DCs. Our model assumes that, at each repair stage, one network node with adjacent links and one DC can be fully repaired; however, full recovery may not be guaranteed due to limited resource availability. Hence, we also propose a “resource-aware” approach (with two resource-allocation strategies, namely “selective allocation” and “adaptive allocation”), which considers both full and partial recovery of elements based on available resources at each stage. We show that, compared to disjoint progressive recovery approach, in which network recovery and DC recovery plans are independent, our joint progressive recovery approach provides significantly higher per-stage content reachability in the network.

Next-generation optical metro-access networks are expected to support end-to-end virtual network slices for critical 5G services. However, disasters affecting physical infrastructures upon which network slices are mapped can cause significant disruption in these services. Operators can deploy recovery units or trucks to restore services based on slice requirements. In this study, we investigate the problem of slice-aware service restoration in metro-access networks with specialized recovery trucks to restore services after a disaster failure. We model the problem based on classical vehicle-routing problem to find optimal routes for recovery trucks to failure sites to provide temporary backup service until the network components are repaired. Our proposed slice-aware service-restoration approach is formulated as a mixed integer linear program with the objective to minimize penalty of service disruption across different network slices. We compare our slice-aware approach with a slice-unaware approach and show that our proposed approach can achieve significant reduction in service-disruption penalty.

Wireless networks are becoming more heterogeneous; different classes of networks co-exist and users want to connect to any available network, anytime. So, it is important to have a mobility management scheme that can manage handoff for both inter-class and intra-class mobility so that the users can connect to and roam between any network. We propose an end-to- end mobility management scheme, Multi-class SIGMA (mSIGMA), that performs soft handoff for inter-class and intra-class mobility in wireless network. Our analysis shows mSIGMA performs seamless handoff across networks with low delay and packet loss. We have also shown though experimental analysis that mSIGMA is implementable with existing networking technologies and can perform handoff efficiently.