Technology-related disasters:a survey towards disaster-resilient software defined networks

Resilience against disaster scenarios is essential to network operators, not only because of the potential economic impact of a disaster but also because communication networks form the basis of crisis management. COST RECODIS aims at studying measures, rules, techniques and prediction mechanisms for different disaster scenarios. This paper gives an overview of different solutions in the context of technology-related disasters. After a general overview, the paper focuses on resilient Software Defined Networks

Future Internet Routing Design for Massive Failures and Attacks

Given the high complexity and increasing traffic load of the Internet, geo-correlated challenges caused by large-scale disasters or malicious attacks pose a significant threat to dependable network communications. To understand its characteristics, we propose a critical-region identification mechanism and incorporate its result into a new graph resilience metric, compensated Total Geographical Graph Diversity. Our metric is capable of characterizing and differentiating resiliency levels for different physical topologies. We further analyze the mechanisms attackers could exploit to maximize the damage and demonstrate the effectiveness of a network restoration plan. Based on the geodiversity in topologies, we present the path geodiverse problem and two heuristics to solve it more efficiently compared to the optimal algorithm. We propose the flow geodiverse problem and two optimization formulations to study the tradeoff among cost, end-to-end delay, and path skew with multipath forwarding. We further integrate the solution to above models into our cross-layer resilient protocol stack, ResTP–GeoDivRP. Our protocol stack is prototyped and implemented in the network simulator ns-3 and emulated in our KanREN testbed. By providing multiple GeoPaths, our protocol stack provides better path restoration performance than Multipath TCP

ResTP: A Configurable and Adaptable Multipath Transport Protocol for Future Internet Resilience

Motivated by the shortcomings of common transport protocols, e.g., TCP, UDP, and MPTCP, in modern networking and the belief that a general-purpose transport-layer protocol, which can operate efficiently over diverse network environments while being able to provide desired services for various application types, we design a new transport protocol, ResTP. The rapid advancement of networking technology and use paradigms is continually supporting new applications. The configurable and adaptable multipath-capable ResTP is not only distinct from the standard protocols by its flexibility in satisfying the requirements of different traffic classes considering the characteristics of the underlying networks, but by its emphasis on providing resilience. Resilience is an essential property that is unfortunately missing in the current Internet. In this dissertation, we present the design of ResTP, including the services that it supports and the set of algorithms that implement each service. We also discuss our modular implementation of ResTP in the open-source network simulator ns-3. Finally, the protocol is simulated under various network scenarios, and the results are analyzed in comparison with conventional protocols such as TCP, UDP, and MPTCP to demonstrate that ResTP is a promising new transport-layer protocol providing resilience in the Future Internet (FI)

Finding and Mitigating Geographic Vulnerabilities in Mission Critical Multi-Layer Networks

Title from PDF of title page, viewed on June 20, 2016Dissertation advisor: Cory BeardVitaIncludes bibliographical references (pages 232-257)Thesis(Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2016In Air Traffic Control (ATC), communications outages may lead to immediate loss of communications or radar contact with aircraft. In the short term, there may be safety related issues as important services including power systems, ATC, or communications for first responders during a disaster may be out of service. Significant financial damage from airline delays and cancellations may occur in the long term. This highlights the different types of impact that may occur after a disaster or other geographic event. The question is How do we evaluate and improve the ability of a mission-critical network to perform its mission during geographically correlated failures? To answer this question, we consider several large and small networks, including a multi-layer ATC Service Oriented Architecture (SOA) network known as SWIM. This research presents a number of tools to analyze and mitigate both long and short term geographic vulnerabilities in mission critical networks. To provide context for the tools, a disaster planning approach is presented that focuses on Resiliency Evaluation, Provisioning Demands, Topology Design, and Mitigation of Vulnerabilities. In the Resilience Evaluation, we propose a novel metric known as the Network Impact Resilience (NIR) metric and a reduced state based algorithm to compute the NIR known as the Self-Pruning Network State Generation (SP-NSG) algorithm. These tools not only evaluate the resiliency of a network with a variety of possible network tests, but they also identify geographic vulnerabilities. Related to the Demand Provisioning and Mitigation of Vulnerabilities, we present methods that focus on provisioning in preparation for rerouting of demands immediately following an event based on Service Level Agreements (SLA) and fast rerouting of demands around geographic vulnerabilities using Multi-Topology Routing (MTR). The Topology Design area focuses on adding nodes to improve topologies to be more resistant to geographic vulnerabilities. Additionally, a set of network performance tools are proposed for use with mission critical networks that can model at least up to 2nd order network delay statistics. The first is an extension of the Queueing Network Analyzer (QNA) to model multi-layer networks (and specifically SOA networks). The second is a network decomposition tool based on Linear Algebraic Queueing Theory (LAQT). This is one of the first extensive uses of LAQT for network modeling. Benefits, results, and limitations of both methods are described.Introduction -- SWIM Network - Air traffic Control example -- Performance analysis of mission critical multi-layer networks -- Evaluation of geographically correlated failures in multi-layer networks -- Provisioning and restoral of mission critical services for disaster resilience -- Topology improvements to avoid high impact geographic events -- Routing of mission critical services during disasters -- Conclusions and future research -- Appendix A. Pub/Sub simulation model description -- Appendix B. ME Random Number Generatio

Heterogeneous Cloud Systems Based on Broadband Embedded Computing

Computing systems continue to evolve from homogeneous systems of commodity-based servers within a single data-center towards modern Cloud systems that consist of numerous data-center clusters virtualized at the infrastructure and application layers to provide scalable, cost-effective and elastic services to devices connected over the Internet. There is an emerging trend towards heterogeneous Cloud systems driven from growth in wired as well as wireless devices that incorporate the potential of millions, and soon billions, of embedded devices enabling new forms of computation and service delivery. Service providers such as broadband cable operators continue to contribute towards this expansion with growing Cloud system infrastructures combined with deployments of increasingly powerful embedded devices across broadband networks. Broadband networks enable access to service provider Cloud data-centers and the Internet from numerous devices. These include home computers, smart-phones, tablets, game-consoles, sensor-networks, and set-top box devices. With these trends in mind, I propose the concept of broadband embedded computing as the utilization of a broadband network of embedded devices for collective computation in conjunction with centralized Cloud infrastructures. I claim that this form of distributed computing results in a new class of heterogeneous Cloud systems, service delivery and application enablement. To support these claims, I present a collection of research contributions in adapting distributed software platforms that include MPI and MapReduce to support simultaneous application execution across centralized data-center blade servers and resource-constrained embedded devices. Leveraging these contributions, I develop two complete prototype system implementations to demonstrate an architecture for heterogeneous Cloud systems based on broadband embedded computing. Each system is validated by executing experiments with applications taken from bioinformatics and image processing as well as communication and computational benchmarks. This vision, however, is not without challenges. The questions on how to adapt standard distributed computing paradigms such as MPI and MapReduce for implementation on potentially resource-constrained embedded devices, and how to adapt cluster computing runtime environments to enable heterogeneous process execution across millions of devices remain open-ended. This dissertation presents methods to begin addressing these open-ended questions through the development and testing of both experimental broadband embedded computing systems and in-depth characterization of broadband network behavior. I present experimental results and comparative analysis that offer potential solutions for optimal scalability and performance for constructing broadband embedded computing systems. I also present a number of contributions enabling practical implementation of both heterogeneous Cloud systems and novel application services based on broadband embedded computing

Network Resilience Architecture and Analysis for Smart Homes

The Internet of Things (IoT) is evolving rapidly to every aspect of human life including, healthcare, homes, cities, and driverless vehicles that makes humans more dependent on the Internet and related infrastructure. While many researchers have studied the structure of the Internet that is resilient as a whole, new studies are required to investigate the resilience of the edge networks in which people and “things” connect to the Internet. Since the range of service requirements varies at the edge of the network, a wide variety of technologies with different topologies are involved. Though the heterogeneity of the technologies at the edge networks can improve the robustness through the diversity of mechanisms, other issues such as connectivity among the utilized technologies and cascade of failures would not have the same effect as a simple network. Therefore, regardless of the size of networks at the edge, the structure of these networks is complicated and requires appropriate study. In this dissertation, we propose an abstract model for smart homes, as part of one of the fast-growing networks at the edge, to illustrate the heterogeneity and complexity of the network structure. As the next step, we make two instances of the abstract smart home model and perform a graph-theoretic analysis to recognize the fundamental behavior of the network to improve its robustness. During the process, we introduce a formal multilayer graph model to highlight the structures, topologies, and connectivity of various technologies at the edge networks and their connections to the Internet core. Furthermore, we propose another graph model, technology interdependence graph, to represent the connectivity of technologies. This representation shows the degree of connectivity among technologies and illustrates which technologies are more vulnerable to link and node failures. Moreover, the dominant topologies at the edge change the node and link vulnerability, which can be used to apply worst-case scenario attacks. Restructuring of the network by adding new links associated with various protocols to maximize the robustness of a given network can have distinctive outcomes for different robustness metrics. However, typical centrality metrics usually fail to identify important nodes in multi-technology networks such as smart homes. We propose four new centrality metrics to improve the process of identifying important nodes in multi-technology networks and recognize vulnerable nodes. We perform the process of improvement through modifying topology, adding extra nodes, and links when necessary. The improvement process would be verified by calculation of the proper graph metrics and introducing new metrics when it is appropriate. Finally, we study over 1000 different smart home topologies to examine the resilience of the networks with typical and the proposed centrality metrics

Guidelines for geoconservation in protected and conserved areas

These Guidelines are to help all of those involved in any aspect of protected area establishment and management and the stewardship of conserved areas to understand and address the conservation of geoheritage (termed geoconservation throughout these Guidelines)