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Decoupling control and data planes in a software-defined network (SDN) has its advantages along with its challenges. Especially, resilient communication between elements in the data plane (switches) and in the control plane (controllers) is key to SDN’s success as disruption of this communication after a failure can severely affect data-plane functions. After a failure, simultaneous recovery of all switch-controller communication paths (control paths) may not be possible, and multiple recovery stages may be required. Since restoration of disrupted data paths depends on the recovery of disrupted control paths feeding control information to switches, the performance of control-path recovery seriously affects data-path recovery performance. The assignment of controller to switches and the routing of controller-switch control paths are what determines the control-plane recovery performance, and hence should be performed in conjunction with a recovery plan after failures. This study proposes an algorithm for recovery-aware switch-controller assignment and routing (RASCAR), which enables fast data-path recovery after a set of failures (e.g., single point of failures and disasters). We formulate the problem as an integer linear program and propose an efficient heuristic algorithm to solve large problem instances. Our illustrative numerical studies show that RASCAR significantly reduces the data-path restoration times after any failure with a minor increase in resource consumption of control paths.

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.

The rapid increase in network traffic with new bandwidth-hungry applications such as cloud computing and telemedicine makes disaster survivability a crucial concern as the data (and revenue) loss caused by large-scale correlated cascading failures can be very high. To alleviate their impact, new measures should be taken since the nature of the network changes dramatically as available resources decrease during disasters. We develop a metric, called degraded-service tolerance, which can reduce protection cost and network disruption, and support maximal carried traffic in case of disasters. Degraded-service-tolerant connections can be admitted and recovered with reduced bandwidth under resource crunch. Our scheme re-assigns resources among connections by leveraging their degraded-service tolerance. A case study shows how our proposal can be applied to boost network performance during the resource crunch following a disaster.

The exam statistics are crucial for instructors to better assess the exam metrics, e.g., exam duration. However, one statistic, time spent on each question by each student, is not available or difficult to obtain by human observation. In this work, we propose a smart exam system that obtains such statistics and sends data to a web application for further processing by using an internet-of-things based technology. The information obtained by the proposed system can even be used to diagnose students with learning difficulties or disabilities, e.g., dyslexia. We provided an experimental setup and conducted experiments with volunteers. The experiments conducted during the study show that the proposed system effectively collect information and process data for the use of instructor.

Effective post-disaster cloud-network recovery can significantly improve users' access to important cloud services. We propose a joint progressive recovery strategy for optical network and datacenters to maximize content reachability to users at each repair stage.

Failures caused by disasters (e.g., weapons of mass destruction (WMD) attacks, earthquakes, hurricanes, etc.) can create huge amount of loss and disruptions in optical backbone networks. Due to major network disruptions in recent disasters, network operators need solutions to prevent connections from disasters, and recover them after disasters. 1) Prevention requires proactive approaches where the damage from a possible disaster should be estimated. Specifically, we propose disaster-risk-aware provisioning, which minimizes loss to a network operator in case of a disaster. 2) Recovery methods should consider that, after the initial failure, more connections might be disconnected by correlated cascading failures. Thus, we investigate a reprovisioning scheme to recover disrupted connections. Numerical examples conducted for different disaster types (WMD attack, earthquake, and tornado) show that our schemes significantly reduce the risk and loss in case of a disaster.

Cloud services delivered by high-capacity optical datacenter networks are subject to disasters which may cause large-area failures, leading to huge data loss. Survivable service provisioning is crucial to minimize the effects of network/datacenter failures and maintain critical services in case of a disaster. We propose a novel disaster-aware service-provisioning scheme that multiplexes service over multiple paths destined to multiple servers/datacenters with manycasting. Our scheme maintains some bandwidth (i.e., degraded service) after a disaster failure vs. no service at all. We formulate this problem into a mathematical model which turns out to be an Integer Linear Program (ILP), and we provide heuristic optimization approaches as ILP is intractable for large problem instances. Numerical examples show that exploiting manycasting by intelligently selecting destinations in a risk-aware manner for service provisioning offers high level of survivability against link and node failures that may be caused by disasters and post-disaster failures at no extra cost compared to the other survivable schemes.

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.

Earthquakes cause huge data loss when a major ground motion strikes backbone telecom infrastructure. However, necessary actions can be taken if an earthquake early warning system is integrated to optical WDM networks, which is the typical architecture of backbone telecom networks. While earthquake early warning systems are used to provide warnings to railway transportation, nuclear power plants, or semiconductor factories, they have been not used to provide warnings to telecom networks. However, many connections can be reprovisioned to avoid data loss in case of a disaster if a warning is provided seconds before a major earthquake. In this study, we explore three different strategies for such situation; 1) Extreme approach that reprovisions all connections in danger with full or degraded bandwidth, 2) relax approach that reprovisions only critical connections, and 3) careful approach that reprovisions some or all connections based on the alarm level. We compare these strategies for a case study, an earthquake on San Andreas Fault Line. We conduct numerical examples over a 24-node US-wide topology where the connections have heterogeneous bandwidth and availability requirements. The numerical examples show that careful approach provides a better solution than extreme and relax approaches, especially for heavy network loads in terms of expected penalty in case of an earthquake.

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.

With the increasing social and economic reliance on the Internet and the significant monetary and non-monetary societal cost associated with service interruption, network survivability is an important element in telecommunication network design. A major cause of Internet service interruption is breakage of fiber-optic cables due to man-made or natural disasters such as earthquakes. In addition to the societal cost, there is also cost of repairing damaged cables paid by the cable owner. A disaster-resilient submarine cable deployment can achieve significant cost saving when disaster strikes. In this study, we investigate a disaster-aware submarine fiber-optic cable deployment optimization problem to minimize such expected costs in case of a disaster. While selecting paths for the cables, our approach aims to minimize the expected cost for both cable owner and the affected society, considering that submarine fiber-optic cables may break because of natural disasters, subject to limitation of available deployment budget and other constraints. In our approach, localized disaster-unrelated potential disconnection (e.g., due to shark bites) are avoided by providing a backup cable along with primary cable. We consider a mesh topology network with multiple nodes located at different sea/ocean shores, submarine fiber-optic cables of irregular shape, and a topography of undersea environment. We present an Integer Linear Program to address the problem, together with illustrative numerical examples. Finally, we validate our approach by applying it to a case study of an existing cable system in the Mediterranean Sea, and the results show that we can significantly reduce overall expected cost at a slight increase in deployment cost. The results demonstrate a potential saving of billions of US dollars for the society in case of a future disaster. In order to achieve such large savings, cable companies may require to lay somewhat longer cables to avoid potential disaster areas, which may increase deployment cost that is relatively smaller compared to potential savings in case of a disaster. Understanding such trade-offs is important for stakeholders, including government agencies, cable industry, and insurance companies, which may have different objectives, but can work together for the overall benefit of the society.

Survivability against disasters-both natural and deliberate attacks, and spanning large geographical areas-is becoming a major challenge in communication networks. Cloud services delivered by datacenter networks yield new opportunities to provide protection against disasters. Cloud services require a network substrate with high capacity, low latency, high availability, and low cost, which can be delivered by optical networks. In such networks, path protection against network failures is generally ensured by providing a backup path to the same destination (i.e., a datacenter), which is link-disjoint to the primary path. This protection fails to protect against disasters covering an area which disrupts both primary and backup paths. Also, protection against destination (datacenter) node failure is not ensured by a generic protection scheme. Moreover, content/service protection is a fundamental problem in a datacenter network, as the failure of a datacenter should not cause the disappearance of a specific content/service from the network. So content placement, routing, and protection of paths and content should be addressed together. In this work, we propose an integrated Integer Linear Program (ILP) to design an optical datacenter network, which solves 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 failure protection. We show that a reasonable number of datacenters and selective content replicas with intelligent network design can provide survivability to disasters while supporting user demands. We also propose ILP relaxations and heuristics to solve the problem for large networks.

Excess capacity (EC) is the unused capacity in a network. We propose EC management techniques to improve network performance. Our techniques exploit the EC in two ways. First, a connection preprovisioning algorithm is used to reduce the connection setup time. Second, whenever possible, we use protection schemes that have higher availability and shorter protection switching time. Specifically, depending on the amount of EC available in the network, our proposed EC management techniques dynamically migrate connections between high-availability, high-backup-capacity protection schemes and low-availability, low-backup-capacity protection schemes. Thus, multiple protection schemes can coexist in the network. The four EC management techniques studied in this paper differ in two respects: when the connections are migrated from one protection scheme to another, and which connections are migrated. Specifically, Lazy techniques migrate connections only when necessary, whereas Proactive techniques migrate connections to free up capacity in advance. Partial Backup Reprovisioning (PBR) techniques try to migrate a minimal set of connections, whereas Global Backup Reprovisioning (GBR) techniques migrate all connections. We develop integer linear program (ILP) formulations and heuristic algorithms for the EC management techniques. We then present numerical examples to illustrate how the EC management techniques improve network performance by exploiting the EC in wavelength-division-multiplexing (WDM) mesh networks.

Network virtualization has become an important feature for cloud-based services. Virtual networks can be set up over high-capacity optical networks. They consist of virtual links and nodes, which are mapped over physical resources. Operational virtual networks get gradually upgraded to avoid capacity exhaustion and create resources to handle traffic growth. These upgrades require leasing of new virtual resources (e.g., additional bandwidth for virtual links) and might be costly to network operators. The additional capital expenditure (CapEx) to upgrade the network can be reduced or eliminated by relocating spare virtual resources which were already-leased in the network, but are unused (e.g., due to optimistic forecasts or excessive overprovisioning). Relocating, here, is basically release some of the unused bandwidth from a virtual link and lease the same amount of bandwidth for another virtual link that will be upgraded. We investigate a cost-effective scheme to relocate spare virtual capacity in a virtual network over an optical WDM backbone network to (i) reduce or eliminate upgrade costs, (ii) avoid capacity exhaustion (by migrating resources from underutilized links to overutilized links), and (iii) improve network robustness (by migrating resources from links supported by unreliable lightpaths to links supported by reliable lightpaths). We propose an efficient relocation scheme to avoid capacity exhaustion and improve network robustness while minimizing or even eliminating requirement of new bandwidth. We build our problem into a mathematical formulation which turns out to be an Integer Linear Program (ILP). Our results show that network operator can significantly reduce CapEx while upgrading/improving a virtual network by using our relocation scheme.

Network survivability is an important element in telecommunication network design nowadays because of the social and economic reliance on the Internet and the significant cost associated with service interruption. Moreover, the fact that submarine fiber-optic cables are susceptible to man-made or natural disasters, such as earthquakes, is well recognized. A disaster-resilient submarine cable deployment can save cost incurred by network operators such as the capacity loss cost, the cruising cost and the repair cost of the damaged cables, in order to restore network service when a cable break is prompted by a disaster occurrence. In this work, we investigate disaster-aware submarine cable deployment problem. While selecting a path for the cables, our approach aims to minimize the total expected loss cost, considering that submarine fiber-optic cables may break because of natural disasters, subject to deployment budget, path uniqueness, regular protection, elliptic shape, and linearization constraints. In our approach, we assume disaster-unrelated failures are handled by providing a backup cable along with primary cable. We consider a scenario with two nodes located on two different lands separated by a water body (sea/ocean). We then consider an elliptic cable shape to formulate the problem, which can be extended to other cable shapes, subject to avoiding deploying cable in disaster zones. We provide an Integer Linear Programming formulation for the problem. Finally, we present illustrative numerical examples that show the potential benefit of our approach as well as conclusion and future work.

Connections provisioned in a backbone network are usually protected. A "good" protection scheme can decrease the downtime experienced by a connection, which can reduce (or eliminate) penalties for the violation of the Service Level Agreement (SLA) between the network operator and its customer. Although "good" protection schemes can guarantee high availability to connections, they usually require high capacity (e.g., bandwidth). However, backbone networks usually have some excess capacity (EC) to accommodate traffic fluctuations and growth, and when there is enough EC, the high capacity requirement of protection schemes can be tolerated. However, under traffic growth, the network operator has to add more bandwidth to avoid capacity exhaustion, which increases upgrade costs. In this study, we show that, in case of connections supporting differentiated services, where connections' tolerable downtimes are diverse, efficient exploitation of EC can decrease both SLA violations and upgrade costs. We develop a novel EC management (ECM) approach that provides high-availability high-capacity protection schemes when EC is available, and reprovisions backup resources with multiple protection schemes so that SLAs are still respected, but network upgrade costs are kept under control. We formulate this problem as an integer linear program (ILP) and develop an efficient heuristic as the ILP is intractable for large problems. We present several alternatives of our ECM approach to show its compatibility with different protection-scheme combinations. Numerical examples are presented to illustrate how the proposed ECM technique finds a tradeoff between upgrade costs and penalties paid for SLA violations while reducing the total cost significantly.

Recent targeted attacks and natural disasters have made disaster-resilient cloud network design an important issue. Network operators are investigating proactive and reactive measures to prevent huge data loss and service disruptions in case of a disaster. We present novel techniques for disaster-aware datacenter placement and content management in cloud networks that can mitigate such loss by avoiding placement in given disaster-vulnerable locations. We first solve a static disaster-aware datacenter and content placement problem by adopting an integer linear program with the objective to minimize risk, defined as expected loss of content. It is a measure of how much, in terms of cost or penalty, a network operator may lose probabilistically due to possible disasters in a cloud network. We also show how a service provider's budget constraint can affect disaster-aware placement design. Since disaster scenarios, content popularity, and/or importance are always changing in time, content placement should rapidly adapt to these changes. We propose a disaster-aware dynamic content-management algorithm that can adjust the existing placement based on dynamic settings. Besides reducing the overall risk and making the network disaster-aware, reducing network resource usage and satisfying quality-of-service requirements can also be achieved in this approach. We also provide a cost analysis of employing a dynamic disaster-aware placement design in the network based on real-world cloud pricing.

Backbone networks usually have some excess capacity (EC) to accommodate traffic fluctuations and to avoid early capacity exhaustion. Network operators can exploit EC in optical wavelength division multiplexed (WDM) backbone networks to support survivable traffic grooming, where connection requests are of subwavelength granularity and each provisioned request has to be protected from single-link failures. We investigate novel EC management techniques that can improve network performance, in terms of Service-Level Agreement (SLA) violations and bandwidth blockings, with no requirement of deploying additional capacity. We investigate exploiting and managing EC by the following techniques. i) Preprovisioning: When traffic is light, network resources are reserved by a preprovisioning scheme, i. e., a connection can be provisioned on reserved protected links to increase availability. We show that preprovisioning also decreases connection setup time, an important metric for delay-sensitive services. ii) Backup reprovisioning: Since high-availability protection schemes usually consume more resources, connections in our solution can be switched to a protection scheme that provides lower availability (but higher resource efficiency) by reprovisioning backup resources when traffic increases. iii) Hold-lightpath: We propose a new "hold-lightpath" scheme to exploit EC. This scheme prevents the termination of pre-established (but unused) resources to increase availability and decrease connection setup time. We compare our techniques with traditional protection schemes for typical daily fluctuating traffic on typical backbone network topologies and find that significant improvements can be achieved in terms of decreasing SLA violations, bandwidth blocking, and connection setup time.

Cloud-computing services are provided to consumers through a network of servers and network equipment. Cloud-network (CN) providers virtualize resources [e.g., virtual machine (VM) and virtual network (VN)] for efficient and secure resource allocation. Disasters are one of the worst threats for CNs as they can causemassive disruptions andCN disconnection. A disaster may also induce post-disaster correlated, cascading failures which can disconnect more CNs. Survivable virtual-network embedding (SVNE) approaches have been studied to protect VNs against single physicallink/- node and dual physical-link failures in communication infrastructure, but massive disruptions due to a disaster and their consequences can make SVNE approaches insufficient to guarantee cloud-computing survivability. In this work, we study the problem of survivable CN mapping from disaster. We consider risk assessment, VM backup location, and post-disaster survivability to reduce the risk of failure and probability of CN disconnection and the penalty paid by operators due to loss of capacity.We formulate the proposed approach as an integer linear program and study two scenarios: a natural disaster, e.g., earthquake and a human-made disaster, e.g., weapons-of-mass-destruction attack. Our illustrative examples show that our approach reduces the risk of CN disconnection and penalty up to 90% compared with a baseline CNmapping approach and increases the CN survivability up to 100% in both scenarios. © 2014 Springer Science+Business Media New York.

Disasters can cause severe service disruptions due to large-scale correlated cascading failures in telecom networks. Major network disruptions due to disasters — both natural (e.g., Hurricane Sandy, 2011 Japan Tsunami) and human-made (e.g., 9/11 terrorist attack) — deprive the affected population of essential network services for weeks and severely hamper rescue operations. Many techniques exist to provide fast network protection, but they are optimized for limited faults without addressing the extent of disaster failures. Thus, there is a pressing need for novel robust survivability methods to mitigate the effects of disasters on telecom networks. While researchers in climatology, geology, and environmental science have been studying how to predict disasters and assess disaster risks for certain regions, networking research can exploit this information to develop novel methods to prepare networks to handle disasters with the knowledge of risky regions and to better prepare them for a predicted disaster. The events during the aftermath of a disaster should also be considered. For instance, methods to re-arrange network resources and services on a partially damaged network, which is the property of a self-organizing network, should be developed, and new algorithms to manage the post-disaster traffic deluge and to relieve the rescue operations after a disaster, with the knowledge of the post-disaster failures, should be investigated. Since cloud services today are an integral part of our society and massive amounts of content/services have been created and shared over the cloud, loss/disruption of critical content/ services caused by disasters can significantly affect the security and economic well being of our society. As the network is becoming increasingly an end-to-content (vs. end-toend) connection provider, we have to ensure reachability of content from any point of a network, which we call content connectivity (in contrast to network connectivity) after disaster failures. This article presents the nature of possible disruptions in telecom networks caused by disaster events, and sheds light on how to prepare the network and cloud services against disasters, and adapt them for disaster disruptions and cascading failures.

Content placement in cloud networks should be resilient to data loss due to disaster-driven failures. We propose a disaster-aware dynamic content placement scheme to reduce the expected content loss while satisfying resource constraints and QoS.

With the frequent occurrences of natural disasters damaging large portions of communication networks and the rising risk of intentional attacks, network vulnerability to multiple cascading, correlated, and collocated failures has become a major concern. Optical backbone networks provide highly-scalable connectivity across large distances. These networks exploit optical technology to carry huge aggregated data and can support ''higher-layer'' networks, such as SONET, Ethernet, IP, MPLS, ATM, etc. Given the high complexity and scale of backbone networks, multiple correlated failures can have a devastating impact on topological connectivity, which in turn can cause widespread ''end-to-end'' connection-level disruptions. These outages may affect many applications/services supported by the optical layer, irrespective of the importance of the service and/or sensitivity of the carried data. Hence, it is crucial to understand the vulnerability of optical backbone networks to disasters and design appropriate countermeasures. In this paper, we present a general classification of the existing research works on disaster survivability in optical networks and a survey on relevant works based on that classification. We also classify disasters based on their characteristics and impact on communication networks and discuss different ways to combat them. We conclude the paper with open issues and challenges.

Operational networks get gradually upgraded to avoid capacity exhaustion and create resources to handle traffic growth. These upgrades require installation of new physical resources (e.g., line cards) and might be costly to network operators. The additional capital expenditure (CapEx) to upgrade the network can be reduced or eliminated by relocating excess resources which were deployed into the network, but are unused (e.g., due to optimistic forecasts or excessive overprovisioning). We investigate a cost-effective scheme to relocate excess capacity in an optical WDM backbone network to (i) reduce or eliminate upgrade costs, (ii) avoid capacity exhaustion (by migrating resources from underutilized links to overutilized links), and (iii) improve network robustness (by migrating resources from unreliable links to reliable links). We propose a novel generic relocation scheme that network operators can use based on their objectives to determine how to relocate excess resources. We also provide a solution which maximizes various benefits (e.g., network robustness and capacity exhaustion avoidance) of network operators by using game theory for our relocation scheme. Our results show that network operator can save a lot of CapEx while upgrading/improving the network by using our relocation scheme.

Recent advances in (optical) network survivability is discussed such as disaster survivability, data protection for cloud services, the notion of degraded service/partial protection, exploiting multipath provisioning and excess capacity for improved robustness.

Regional failures caused by disasters precipitate huge amount of loss and jeopardize many connections. A risk model for disasters, considering differentiated services, is introduced and a disaster-aware provisioning scheme is proposed to reduce the risk.