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Resilience Metrics 2015 |
Quantitative measurement is a key to sharing understanding of resilience in cyber physical systems. The work cited here looks at the development of predictive and analytical metrics to help achieve this end. The work was presented in 2015.
Alenazi, M.J.F.; Sterbenz, J.P.G., “Comprehensive Comparison and Accuracy of Graph Metrics in Predicting Network Resilience,” in Design of Reliable Communication Networks (DRCN), 2015 11th International Conference on the, vol., no.,
pp. 157–164, 24–27 March 2015. doi:10.1109/DRCN.2015.7149007
Abstract: Graph robustness metrics have been used largely to study the behavior of communication networks in the presence of targeted attacks and random failures. Several researchers have proposed new graph metrics to better predict network resilience and survivability against such attacks. Most of these metrics have been compared to a few established graph metrics for evaluating the effectiveness of measuring network resilience. In this paper, we perform a comprehensive comparison of the most commonly used graph robustness metrics. First, we show how each metric is determined and calculate its values for baseline graphs. Using several types of random graphs, we study the accuracy of each robustness metric in predicting network resilience against centrality-based attacks. The results show three conclusions. First, our path diversity metric has the highest accuracy in predicting network resilience for structured baseline graphs. Second, the variance of node-betweenness centrality has mostly the best accuracy in predicting network resilience for Waxman random graphs. Third, path diversity, network criticality, and effective graph resistance have high accuracy in measuring network resilience for Gabriel graphs.
Keywords: graph theory; telecommunication network reliability; telecommunication security; Gabriel graphs; Waxman random graphs; baseline graphs; centrality-based attacks; communication network behavior; comprehensive comparison; effective graph resistance; graph robustness metrics accuracy; network criticality; network resilience measurement; network resilience prediction; node-betweenness centrality variance; path diversity metric; random failures; survivability prediction; targeted attacks; Accuracy; Communication networks; Joining processes; Measurement; Resilience; Robustness; Connectivity evaluation; Fault tolerance; Graph robustness; Graph spectra; Network design; Network resilience; Network science; Reliability; Survivability (ID#: 15-7263)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7149007&isnumber=7148972
Schneider, J.; Romanowski, C.; Raj, R.K.; Mishra, S.; Stein, K., “Measurement of Locality Specific Resilience,” in Technologies for Homeland Security (HST), 2015 IEEE International Symposium on, vol., no., pp. 1–6, 14–16 April 2015. doi:10.1109/THS.2015.7225332
Abstract: Resilience has been defined at the local, state, and national levels, and subsequent attempts to refine the definition have added clarity. Quantitative measurements, however, are crucial to a shared understanding of resilience. This paper reviews the evolution of resiliency indicators and metrics and suggests extensions to current indicators to measure functional resilience at a jurisdictional or community level. Using a management systems approach, an input/output model may be developed to demonstrate abilities, actions, and activities needed to support a desired outcome. Applying systematic gap analysis and an improvement cycle with defined metrics, the paper proposes a model to evaluate a community’s operational capability to respond to stressors. As each locality is different—with unique risks, strengths, and weaknesses—the model incorporates these characteristics and calculates a relative measure of maturity for that community. Any community can use the resulting model output to plan and improve its resiliency capabilities.
Keywords: emergency management; social sciences; community operational capability; functional resilience measurement; locality specific resilience measurement; quantitative measurement; resiliency capability; resiliency indicators; resiliency metrics; systematic gap analysis; Economics; Emergency services; Hazards; Measurement; Resilience; Standards; Training; AHP; community resilience; operational resilience modeling; resilience capability metrics (ID#: 15-7264)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7225332&isnumber=7190491
Eshghi, K.; Johnson, B.K.; Rieger, C.G., “Power System Protection and Resilient Metrics,” in Resilience Week (RWS), 2015, vol., no., pp. 1–8, 18–20 Aug. 2015. doi:10.1109/RWEEK.2015.7287448
Abstract: During a real-time power system event, a system operator needs to conservatively reduce operating limits while the changing system conditions are analyzed. The time it takes to develop new operating limits could affect millions of transmission system users, especially if this event is classified by NERC as a Category D type event (extreme events resulting in the loss of two or more bulk electric system elements). Controls for the future grid must be able to perform real-time analysis, identify new reliability risks, and set new SOLs (System Operating Limit) for real-time operations. In this paper we are developing “Resilience Metrics” requirements that describe how systems operate at an acceptable level of normalcy despite disturbances or threats. We consider the interdependencies inherent in critical infrastructure systems and discuss some distributed resilience metrics that can be in current supervisory control and data acquisition (SCADA) to provide a level of state awareness. This level of awareness provides knowledge that can be used to characterize and reduce the risk of cascading events. A “resilience power system agent” is proposed that provides attributes to measure and perform this metrics.
Keywords: Control systems; Measurement; Power system stability; Resilience; Stability analysis; Transient analysis (ID#: 15-7265)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7287448&isnumber=7287407
Yabin Ye; Arribas, F.J..; Elmirghani, J.; Idzikowski, F.; Vizcaino, J.L.; Monti, P.; Musumeci, F.; Pattavina, A.; Van Heddeghem, W., “Energy-Efficient Resilient Optical Networks: Challenges and Trade-Offs,” in Communications Magazine, IEEE, vol. 53, no. 2, pp. 144–150, Feb. 2015. doi:10.1109/MCOM.2015.7045403
Abstract: Energy efficiency and resilience are two well established research topics in optical transport networks. However, their overall objectives (i.e., power minimization and resource utilization/availability maximization) conflict. In fact, provisioning schemes optimized for best resilience performance are in most cases not energy-efficient in their operations, and vice versa. However, very few works in the literature consider the interesting issues that may arise when energy efficiency and resilience are combined in the same networking solution. The objective of this article is to identify a number of research challenges and trade-offs for the design of energy-efficient and resilient optical transport networks from the perspective of long-term traffic forecasts, short-term traffic dynamics, and service level agreement requirements. We support the challenges with justifying numbers based on lessons learned from our previous work. The article also discusses suitable metrics for energy efficiency and resilience evaluation, in addition to a number of steps that need to be taken at the standardization level to incorporate energy efficiency into already existing and well established protocols.
Keywords: optical fibre networks; standardisation; telecommunication power management; telecommunication traffic; availability maximization; energy efficiency; energy-efficient resilient optical transport networks; long-term traffic forecasts; power minimization; resilience evaluation; resource utilization; service level agreement requirements; short-term traffic dynamics; standardization level; Energy consumption; Energy efficiency; Optical fiber networks; Optical fibers; Optical transmitters (ID#: 15-7266)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7045403&isnumber=7045380
Backhaus, S.; Swift, G.W., “DOE DC Microgrid Scoping Study — Opportunities and Challenges,” in DC Microgrids (ICDCM), 2015 IEEE First International Conference on, vol., no., pp. 43–44, 7–10 June 2015. doi:10.1109/ICDCM.2015.7152007
Abstract: For the Department of Energy, several national labs (Los Alamos, Lawrence Berkeley, Oakridge, Sandia, Argonne, and Pacific Northwest) collaborated on a scoping study1 to provide a preliminary examination of the benefits and drawbacks of potential DC microgrid applications relative to their AC counterparts. The performance of notional AC and DC microgrids are estimated and compared using several metrics: safety and protection, reliability, capital cost, energy efficiency, operating cost, engineering costs, environmental impact, power quality, and resilience. The initial comparison is done using several generic microgrid architectures (see Fig. 1) to reveal the importance of the different metrics. Then, these metrics were compared for several specific microgrid applications to draw out possible unique advantages of DC microgrids. In this manuscript, we focus on the comparison using the generic architectures in Fig.1. The draft report provides recommendations for potential future research and deployment activities. The draft report provides recommendations for potential future research and deployment activities.
Keywords: distributed power generation; energy conservation; power generation protection; power generation reliability; power supply quality; DOE DC microgrid reliability; department of energy; energy efficiency; microgrid protection; power quality; Energy efficiency; Measurement; Microgrids; Power electronics; Power system reliability; Reliability (ID#: 15-7267)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7152007&isnumber=7151990
Kumar, N.; Misra, S.; Chilamkurti, N.; Lee, J.H.; Rodrigues, J.J.P.C., “Bayesian Coalition Negotiation Game as a Utility for Secure Energy Management in a Vehicles-to-Grid Environment,” in Dependable and Secure Computing, IEEE Transactions on, vol. 13, no. 1, pp. 133–145, Jan.–Feb.1 2016. doi:10.1109/TDSC.2015.2415489
Abstract: In recent times, Plug-in Electric Vehicles (PEVs) have emerged as a new alternative to increase an efficiency of smart grids (SGs) in a vehicles-to-grid (V2G) environment. The V2G environment provides a bidirectional power and information flow, so that users can have an optimized usage as per their requirements. However, uncontrolled and unmanaged power distribution may lead to an overall performance degradation in the V2G environment. One reason for this uncontrolled and unmanaged flow may be due to the usage of power by unauthorized users. To address this issue, we propose a Bayesian Coalition Negotiation Game (BCNG) as a utility for secure energy management for PEVs in the V2G environment. We have used a BCNG along with Learning Automata (LA), wherein LA are stationed on PEVs and are assumed as the players in the game. To provide an approach based on resilience for any misuse of electricity consumption, a new Secure Payoff Function (SPF) is proposed. The players take actions and update their action probability vector using SPF. Nash Equilibrium (NE) is also achieved in the game using convergence theory. Our proposal is evaluated with various metrics. The proposed scheme also provides mutual authentication and resilience against various attacks during power distribution.
Keywords: Automata; Bayes methods; Equations; Games; Learning automata; Vectors; Vehicles; Bayesian Coalition; Learning Automata; Plug-in Electric Vehicles (ID#: 15-7268)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7064718&isnumber=4358699
Klöti, R.; Kotronis, V.; Ager, B.; Dimitropoulos, X., “Policy-Compliant Path Diversity and Bisection Bandwidth,” in Computer Communications (INFOCOM), 2015 IEEE Conference on, vol., no., pp. 675–683, April 26 2015–May 1 2015. doi:10.1109/INFOCOM.2015.7218436
Abstract: How many links can be cut before a network is bisected? What is the maximal bandwidth that can be pushed between two nodes of a network? These questions are closely related to network resilience, path choice for multipath routing or bisection bandwidth estimations in data centers. The answer is quantified using metrics such as the number of edge-disjoint paths between two network nodes and the cumulative bandwidth that can flow over these paths. In practice though, such calculations are far from simple due to the restrictive effect of network policies on path selection. Policies are set by network administrators to conform to service level agreements, protect valuable resources or optimize network performance. In this work, we introduce a general methodology for estimating lower and upper bounds for the policy-compliant path diversity and bisection bandwidth between two nodes of a network, effectively quantifying the effect of policies on these metrics. Exact values can be obtained if certain conditions hold. The approach is based on regular languages and can be applied in a variety of use cases.
Keywords: channel estimation; computer network reliability; telecommunication network routing; bisection bandwidth estimations; data center; edge disjoint paths; multipath routing; network policies; network resiliency; policy compliant path diversity; Approximation methods; Automata; Bandwidth; Internet; Routing; Tensile stress; Transforms (ID#: 15-7269)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7218436&isnumber=7218353
Poslad, S.; Middleton, S.E.; Chaves, F.; Ran Tao; Necmioglu, O.; Bügel, U., “A Semantic IoT Early Warning System for Natural Environment Crisis Management,” in Emerging Topics in Computing, IEEE Transactions on, vol. 3, no. 2, pp. 246–257, June 2015. doi:10.1109/TETC.2015.2432742
Abstract: An early warning system (EWS) is a core type of data driven Internet of Things (IoTs) system used for environment disaster risk and effect management. The potential benefits of using a semantic-type EWS include easier sensor and data source plug-and-play, simpler, richer, and more dynamic metadata-driven data analysis and easier service interoperability and orchestration. The challenges faced during practical deployments of semantic EWSs are the need for scalable time-sensitive data exchange and processing (especially involving heterogeneous data sources) and the need for resilience to changing ICT resource constraints in crisis zones. We present a novel IoT EWS system framework that addresses these challenges, based upon a multisemantic representation model. We use lightweight semantics for metadata to enhance rich sensor data acquisition. We use heavyweight semantics for top level W3C Web Ontology Language ontology models describing multileveled knowledge-bases and semantically driven decision support and workflow orchestration. This approach is validated through determining both system related metrics and a case study involving an advanced prototype system of the semantic EWS, integrated with a deployed EWS infrastructure.
Keywords: Internet of Things; emergency management; ontologies (artificial intelligence); semantic Web; ICT resource constraints; W3C Web ontology language; data exchange; data processing; data source plug-and-play; environment disaster risk and effect management; information and communication technology; meta data-driven data analysis; multisemantic representation model; natural environment crisis management; ontology models; semantic IoT early warning system; semantic-type EWS; semantically driven decision support; sensor plug-and-play; service interoperability; service orchestration; workflow orchestration; Data models; Data processing; Hazards; Method of moments; Ontologies; Semantics; Tsunami; Crisis Management; Early Warning System; Early warning system; Resilience; Time-critical; crisis management; resilience; scalable; semantic Web; time-critical (ID#: 15-7270)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7109842&isnumber=7118282
Bulbul, R.; Sapkota, P.; C.-W. Ten; L. Wang; Ginter, A., “Intrusion Evaluation of Communication Network Architectures for Power Substations,” in Power Delivery, IEEE Transactions on, vol. 30, no. 3, pp. 1372–1382, June 2015. doi:10.1109/TPWRD.2015.2409887
Abstract: Electronic elements of a substation control system have been recognized as critical cyberassets due to the increased complexity of the automation system that is further integrated with physical facilities. Since this can be executed by unauthorized users, the security investment of cybersystems remains one of the most important factors for substation planning and maintenance. As a result of these integrated systems, intrusion attacks can impact operations. This work systematically investigates the intrusion resilience of the ten architectures between a substation network and others. In this paper, two network architectures comparing computer-based boundary protection and firewall-dedicated virtual local-area networks are detailed, that is, architectures one and ten. A comparison on the remaining eight architecture models was performed. Mean time to compromise is used to determine the system operational period. Simulation cases have been set up with the metrics based on different levels of attackers’ strength. These results as well as sensitivity analysis show that implementing certain architectures would enhance substation network security.
Keywords: firewalls; investment; local area networks; maintenance engineering; power system planning; safety systems; substation automation; substation protection; automation system; communication network architectures; computer-based boundary protection; cybersystems; electronic elements; firewall-dedicated virtual local-area networks; intrusion attacks; intrusion evaluation; intrusion resilience; power substations; security investment; sensitivity analysis; substation control system; substation maintenance; substation network security; substation planning; unauthorized users; Computer architecture; Modems; Protocols; Security; Servers; Substations; Tin; Cyberinfrastructure; electronic intrusion; network security planning; power substation (ID#: 15-7271)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7054545&isnumber=7110680
Guner, S.; Selvi, H.; Gür, G.; Alagöz, F., “Controller Placement in Software-Defined Mobile Networks,” in Signal Processing and Communications Applications Conference (SIU), 2015 23rd, vol., no., pp. 2619–2622, 16–19 May 2015. doi:10.1109/SIU.2015.7130425
Abstract: In this paper, important aspects of the controller placement problem (CPP) in Software Defined Mobile Networks (SDMN) are discussed. To find an efficient and optimal controller placement, we must clarify how many controllers we need, where we place them in topology, and how they interact with each other. We take into consideration reliability, latency, resilience, and scalability metrics to answer related questions.
Keywords: controllers; mobile communication; software defined networking; controller placement; software-defined mobile networks; Conferences; IEEE standards; Mobile communication; Mobile computing; Network topology; Reliability; Software;
number of controllers; placement algorithms (ID#: 15-7272)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7130425&isnumber=7129794
Mittal, S.; Vetter, J.S., “A Survey of Techniques for Modeling and Improving Reliability of Computing Systems,” in Parallel and Distributed Systems, IEEE Transactions on, vol. 27, no. 4, pp.1226–1238, April 1 2016. doi:10.1109/TPDS.2015.2426179
Abstract: Recent trends of aggressive technology scaling have greatly exacerbated the occurrences and impact of faults in computing systems. This has made ‘reliability’ a first-order design constraint. To address the challenges of reliability, several techniques have been proposed. This paper provides a survey of architectural techniques for improving resilience of computing systems. We especially focus on techniques proposed for microarchitectural components, such as processor registers, functional units, cache and main memory etc. In addition, we discuss techniques proposed for non-volatile memory (NVM), GPUs and
3D-stacked processors. To underscore the similarities and differences of the techniques, we classify them based on their key characteristics. We also review the metrics proposed to quantify vulnerability of processor structures. We believe that this survey will help researchers, system-architects and processor designers in gaining insights into the techniques for improving reliability of computing systems.
Keywords: Circuit faults; Computational modeling; Integrated circuit reliability; Measurement; Nonvolatile memory; Registers; Review; architectural techniques; architectural vulnerability factor; classification; fault-tolerance; reliability; resilience; soft/transient error; vulnerability (ID#: 15-7273)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7094277&isnumber=4359390
Chung, Chun-Jen; Xing, Tianyi; Huang, Dijiang; Medhi, Deep; Trivedi, Kishor, “SeReNe: On Establishing Secure and Resilient Networking Services for an SDN-based Multi-tenant Datacenter Environment,” in Dependable Systems and Networks Workshops (DSN-W), 2015 IEEE International Conference on, vol., no., pp. 4–11, 22–25 June 2015. doi:10.1109/DSN-W.2015.25
Abstract: In the current enterprise data enter networking environment, a major hurdle in the development of network security is the lack of an orchestrated and resilient defensive mechanism that uses well-established quantifiable metrics, models, and evaluation methods. In this position paper, we describe an emerging Secure and Resilient Networking (SeReNe) service model to establish a programmable and dynamic defensive mechanism that can adjust the system’s networking resources such as topology, bandwidth allocation, and traffic/flow forwarding policies, according to the network security situations. We posit that this requires addressing two interdependent technical areas: (a) a Moving Target Defense (MTD) framework both at networking and software levels, and (b) an Adaptive Security-enabled Traffic Engineering (ASeTE) approach to select optimal countermeasures by considering the effectiveness of countermeasures and network bandwidth allocations while minimizing the intrusiveness to the applications and the cost of deploying the countermeasures. We believe that our position can greatly benefit the virtual networking system established in data Centerior enterprise virtual networking systems that have adopted latest Open Flow technologies.
Keywords: Bridges; Cloud computing; Computational modeling; Computer bugs; Home appliances; Security; multi-tenant datacenter; security and resilience (ID#: 15-7274)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7272544&isnumber=7272533
Amarù, L.; Gaillardon, P.-E.; De Micheli, G., “Boolean Logic Optimization in Majority-Inverter Graphs,” in Design Automation Conference (DAC), 2015 52nd ACM/EDAC/IEEE, vol., no., pp. 1–6, 7-11 June 2015. doi:10.1145/2744769.2744806
Abstract: We present a Boolean logic optimization framework based on Majority-Inverter Graph (MIG). An MIG is a directed acyclic graph consisting of three-input majority nodes and regular/complemented edges. Current MIG optimization is supported by a consistent algebraic framework. However, when algebraic methods cannot improve a result quality, stronger Boolean methods are needed to attain further optimization. For this purpose, we propose MIG Boolean methods exploiting the error masking property of majority operators. Our MIG Boolean methods insert logic errors that strongly simplify an MIG while being successively masked by the voting nature of majority nodes. Thanks to the data-structure/methodology fitness, our MIG Boolean methods run in principle as fast as algebraic counterparts. Experiments show that our Boolean methodology combined with state-of-art MIG algebraic techniques enable superior optimization quality. For example, when targeting depth reduction, our MIG optimizer transforms a ripple carry adder into a carry look-ahead one. Considering the set of IWLS’05 (arithmetic intensive) benchmarks, our MIG optimizer reduces by 17.98% (26.69%) the logic network depth while also enhancing size and power activity metrics, with respect to ABC academic optimizer. Without MIG Boolean methods, i.e., using MIG algebraic optimization alone, the previous gains are halved. Employed as front-end to a delay-critical 22-nm ASIC flow (logic synthesis + physical design) our MIG optimizer reduces the average delay/area/power by (15.07%, 4.93%, 1.93%), over 27 academic and industrial benchmarks, as compared to a leading commercial ASIC flow.
Keywords: Boolean functions; directed graphs; optimisation; Boolean logic optimization framework; MIG Boolean methods; MIG optimization; consistent algebraic framework; data-structure; directed acyclic graph; majority-inverter graphs; methodology fitness; three-input majority nodes; Adders; Application specific integrated circuits; Benchmark testing; Hardware design languages; Measurement; Optimization; Resilience; Boolean Optimization; Logic Synthesis; Majority Logic (ID#: 15-7275)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7167312&isnumber=7167177
Soule, N.; Simidchieva, B.; Yaman, F.; Watro, R.; Loyall, J.; Atighetchi, M.; Carvalho, M.; Last, D.; Myers, D.; Flatley, B., “Quantifying & Minimizing Attack Surfaces Containing Moving Target Defenses,” in Resilience Week (RWS), 2015 , vol., no., pp.1–6, 18–20 Aug. 2015. doi:10.1109/RWEEK.2015.7287449
Abstract: The cyber security exposure of resilient systems is frequently described as an attack surface. A larger surface area indicates increased exposure to threats and a higher risk of compromise. Ad-hoc addition of dynamic proactive defenses to distributed systems may inadvertently increase the attack surface. This can lead to cyber friendly fire, a condition in which adding superfluous or incorrectly configured cyber defenses unintentionally reduces security and harms mission effectiveness. Examples of cyber friendly fire include defenses which themselves expose vulnerabilities (e.g., through an unsecured admin tool), unknown interaction effects between existing and new defenses causing brittleness or unavailability, and new defenses which may provide security benefits, but cause a significant performance impact leading to mission failure through timeliness violations. This paper describes a prototype service capability for creating semantic models of attack surfaces and using those models to (1) automatically quantify and compare cost and security metrics across multiple surfaces, covering both system and defense aspects, and (2) automatically identify opportunities for minimizing attack surfaces, e.g., by removing interactions that are not required for successful mission execution.
Keywords: Analytical models; Computational modeling; IP networks; Measurement; Minimization; Security; Surface treatment; cyber security analysis; modeling; threat assessment (ID#: 15-7276)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7287449&isnumber=7287407
Pinnaka, S.; Yarlagadda, R.; Çetinkaya, E.K., “Modelling Robustness of Critical Infrastructure Networks,” in Design of
Reliable Communication Networks (DRCN), 2015 11th International Conference on the, vol., no., pp. 95–98, 24–27 March 2015. doi:10.1109/DRCN.2015.7148995
Abstract: Critical infrastructure networks are becoming increasingly interdependent. An attack or disaster in a network or on a single node in a network will affect the other networks dependent on it. Therefore, it is important to assess and understand the vulnerability of interdependent networks in the presence of natural disasters and malicious attacks that lead to cascading failures. We develop a framework to analyse the robustness of interdependent networks. Nodes and links in the interdependent networks are attacked based on the graph centrality metrics. We apply our framework on critical infrastructure network data. Our results indicate that the importance of critical infrastructure varies depending on the attack strategy.
Keywords: critical infrastructures; graph theory; critical infrastructure networks; graph centrality metrics; interdependent networks; malicious attacks; natural disasters; Measurement; Power system faults; Power system protection; Reliability engineering; Robustness; Transportation; cascading failures; centrality; critical infrastructure; directed graph; resilience; robustness
(ID#: 15-7277)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7148995&isnumber=7148972
Lange, S.; Gebert, S.; Zinner, T.; Tran-Gia, P.; Hock, D.; Jarschel, M.; Hoffmann, M., “Heuristic Approaches to the Controller Placement Problem in Large Scale SDN Networks,” in Network and Service Management, IEEE Transactions on, vol. 12, no.1, pp. 4–17, March 2015. doi:10.1109/TNSM.2015.2402432
Abstract: Software Defined Networking (SDN) marks a paradigm shift towards an externalized and logically centralized network control plane. A particularly important task in SDN architectures is that of controller placement, i.e., the positioning of a limited number of resources within a network to meet various requirements. These requirements range from latency constraints to failure tolerance and load balancing. In most scenarios, at least some of these objectives are competing, thus no single best placement is available and decision makers need to find a balanced trade-off. This work presents POCO, a framework for Pareto-based Optimal COntroller placement that provides operators with Pareto optimal placements with respect to different performance metrics. In its default configuration, POCO performs an exhaustive evaluation of all possible placements. While this is practically feasible for small and medium sized networks, realistic time and resource constraints call for an alternative in the context of large scale networks or dynamic networks whose properties change over time. For these scenarios, the POCO toolset is extended by a heuristic approach that is less accurate, but yields faster computation times. An evaluation of this heuristic is performed on a collection of real world network topologies from the Internet Topology Zoo. Utilizing a measure for quantifying the error introduced by the heuristic approach allows an analysis of the resulting trade-off between time and accuracy. Additionally, the proposed methods can be extended to solve similar virtual functions placement problems which appear in the context of Network Functions Virtualization (NFV).
Keywords: Internet; Pareto optimisation; optimal control; software defined networking; telecommunication network topology; Internet topology zoo; NFV; SDN architectures; centralized network control plane; controller placement problem; decision makers; failure tolerance; large scale SDN networks; load balancing; network functions virtualization; pareto based optimal controller placement; small and medium sized networks; software defined networking; Context; Equations; Graphical user interfaces; Mathematical model; Measurement; Optimization; Resilience; Controller Placement; OpenFlow; POCO; SDN; controller placement; failure tolerance; latency; multiobjective optimization; resilience; simulated annealing (ID#: 15-7278)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7038177&isnumber=7061568
Chanda, Sayonsom; Srivastava, Anurag K., “Quantifying Resiliency of Smart Power Distribution Systems with Distributed Energy Resources,” in Industrial Electronics (ISIE), 2015 IEEE 24th International Symposium on, vol., no., pp. 766–771, 3–5 June 2015. doi:10.1109/ISIE.2015.7281565
Abstract: The purpose of smart grid projects worldwide is to revitalize the aging power system infrastructure, and make it more reliable, more resilient and more sustainable. Technological advances has led to diversity of power sources and lesser dependence on fossil fuels; however, it has also increased the complexity of control of the network, which may have a counter-effect on its resiliency and reliability. Also, weather induced power disruptions or targeted attacks on critical power system infrastructure have increased in numbers. Thus there is a need for formal metrics to quantify resiliency of the different distribution system, or different configurations of same network. This paper presents definitions of resiliency of power distribution system, and approach towards resilient design of future power distribution systems with distributed energy resources. These are eventually used to identify parameters for quantification of resiliency. Simulation results for several test cases have been presented to validate the developed resiliency metrics.
Keywords: Measurement; Meteorology; Microgrids; Power system reliability; Reliability; Resilience (ID#: 15-7279)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7281565&isnumber=7281431
Lew, R.; Boring, R.L.; Ulrich, T.A., “A Tool for Assessing the Text Legibility of Digital Human Machine Interfaces,” in Resilience Week (RWS), 2015, vol., no., pp. 1–5, 18–20 Aug. 2015. doi:10.1109/RWEEK.2015.7287437
Abstract: A tool intended to aid qualified professionals in the assessment of the legibility of text presented on a digital display is described. The assessment of legibility is primarily for the purposes of designing and analyzing human machine interfaces in accordance with NUREG-0700 and MIL-STD 1472G. The tool addresses shortcomings of existing guidelines by providing more accurate metrics of text legibility with greater sensitivity to design alternatives.
Keywords: Ergonomics; Guidelines; Sociology; Standards; Statistics; Testing; Workstations; Human Factors; Human Machine Interface; Text Legibility (ID#: 15-7280)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7287437&isnumber=7287407
Lei Sun; Wenye Wang; Zhuo Lu, “On Topology and Resilience of Large-Scale Cognitive Radio Networks Under Generic Failures,” in Wireless Communications, IEEE Transactions on, vol. 14, no. 6, pp. 3390–3401, June 2015. doi:10.1109/TWC.2015.2404919
Abstract: It has been demonstrated that in wireless networks, blackholes, which are typically generated by isolated node failures, and augmented by failure correlations, can easily result in devastating impact on network performance. In order to address this issue, we focus on the topology of Cognitive Radio Networks (CRNs) because of their phenomenal benefits in improving spectrum efficiency through opportunistic communications. Particularly, we first define two metrics, namely the failure occurrence probability p and failure connection function g(·), to characterize node failures and their spreading properties, respectively. Then we prove that each blackhole is exponentially bounded based on percolation theory. By mapping failure spreading using a branching process, we further derive an upper bound on the expected size of blackholes. With the observations from our analysis, we are able to find a sufficient condition for a resilient CRN in the presence of blackholes through analysis and simulations.
Keywords: cognitive radio; telecommunication network topology; blackholes; failure connection function; failure correlations; failure occurrence probability; generic failures; large-scale cognitive radio networks resilience; large-scale cognitive radio networks topology; network performance; node failures; opportunistic communications; percolation theory; wireless networks; Interference; Network topology; Routing; Routing protocols; Topology; Wireless networks; Resilience; cognitive radio networks; topology (ID#: 15-7281)
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7046409&isnumber=7119638
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