M. Farhan Habib

Network adaptability from disaster disruptions and cascading failures

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-to-end) 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.

Disaster-aware datacenter placement and dynamic content management in cloud networks

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 providers 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.

Network adaptability to disaster disruptions by exploiting degraded-service tolerance

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.

Disaster-aware data-center and content placement in cloud networks

Recent occurrences of disasters and targeted attacks have made disaster-resilient data-center network design an important issue. Network operators are investigating proactive and reactive measures to avoid huge data loss and service disruptions in case of a disaster. Disaster-aware data-center and content placement can mitigate the effects of such failures by avoiding placement in disaster-vulnerable locations. Compared to disaster-unaware approach, this approach can significantly reduce the risk, i.e., expected loss of content due to a disaster, in a cloud network.

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.

Disaster-aware service provisioning by exploiting multipath routing with manycasting in telecom networks

Disasters may cause large-area failures in high-capacity telecom networks, 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., reduced service) after a disaster failure vs. no service at all. Numerical examples show that our approach 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.

Traveling repairman problem for optical network recovery to restore virtual networks after a disaster [invited]

Virtual networks mapped over a physical network can suffer disconnection and/or outage due to disasters. After a disaster occurs, the network operator should determine a repair schedule and then send repairmen to repair failures following the schedule. The schedule can change the overall effect of a disaster by changing the restoration order of failed components. In this study, we introduce the traveling repairman problem to help the network operator make the schedule after a disaster. We measure the overall effect of a disaster from the damage it caused, and we define the damage as the numbers of disconnected virtual networks, failed virtual links, and failed physical links. Our objective is to find an optimal schedule for a repairman to restore the optical network with minimum damage. We first state the problem; then a mixed integer linear program (MILP) and three heuristic algorithms, namely dynamic programming (DP), the greedy algorithm (GR), and simulated annealing (SA), are proposed. Finally, simulation results show that the repair schedules using MILP and DP results get the least damage but the highest complexity; GR gets the highest damage with the lowest complexity, while SA has a good balance between damage and complexity.

Global versus essential post-disaster re-provisioning in telecom mesh networks

Telecommunication networks face large-scale threats, such as natural disasters (earthquake, hurricane, tsunami, etc.) and targeted attacks (weapons of mass destruction). These disasters may simultaneously destroy many network components (nodes and/or links) and cause multi-failure events. Although existing protection schemes can handle some given multi-failure scenarios, it is extremely challenging to solve all possible disaster-failure scenarios with reasonable resource costs and a 100% reliability guarantee. In this paper, we investigate postdisaster restoration strategies for telecom backbone mesh networks (such as wavelength-division multiplexed networks), whose objective is two-fold: to maintain network connectivity (i.e., guarantee a minimal degree of service for the survived connections) and to maximize the traffic flow in the post-disaster network. We study three postdisaster re-provisioning schemes employing different policies for connection rerouting and admissible bandwidth degradation (i.e., provisioning partial bandwidth). These schemes, whose services range from essential to global post-disaster re-provisioning, are the no-degradation reprovisioning (NDR) scheme, the degradation-as-needed re-provisioning (DAN) scheme, and the fairness-aware degradation re-provisioning (FAD) scheme. Corresponding mixed integer linear program models are developed and applied on two representative mesh topologies. Numerical results show that NDR can effectively decrease the connection loss ratio by rerouting some survived connections. However, both DAN and FAD can achieve optimal performance on maintaining connectivity even without rerouting any survived connections. DAN outperforms the other schemes in terms of traffic loss ratio, but it may cause a large difference between the maximum and minimum degradation ratios. FAD can improve the performance in terms of traffic loss ratio by rerouting a few survived connections. In particular, compared with DAN, FAD can provide balanced bandwidth degradation for all connections by sacrificing a certain amount of traffic flow, but avoiding extreme deterioration of the bandwidth capacity on some connections.

Heterogeneous bandwidth provisioning for virtual machine migration over SDN-enabled optical networks

Virtual machine migration in cloud-computing environments is an important operational technique, and requires significant network bandwidth. We demonstrate that heterogeneous bandwidth (vs. homogeneous bandwidth) for migration reduces significant resource consumption in SDN-enabled optical networks.

Disaster-aware service provisioning with manycasting in cloud networks

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.