With the growing demand for high-bandwidth applications, traditional optical networks are reaching their capacity limits. Multi-band elastic optical networks (MB-EONs) have emerged as a cost-effective and promising solution to enhance spectral efficiency by utilizing spectrum slots across multiple bands beyond the C-band. However, the performance of MBEONs is significantly affected by physical layer impairments (PLIs), including amplified spontaneous emission (ASE), nonlinear interference (NLI), and inter-channel stimulated Raman scattering (ISRS), which complicate dynamic resource allocation and degrade the quality of transmission (QoT). To address these challenges, we propose an ISRS-Enhanced PLI-Aware (IE-PLIA) routing algorithm for MB-EON resource allocation, explicitly accounting for PLIs under the influence of ISRS. Unlike prior approaches, IE-PLIA dynamically adjusts routing costs based on link conditions, self-channel interference (SCI), and cross-channel interference (XCI) variations induced by ISRS. Furthermore, we investigate the network performance under various traffic load conditions to determine when transitioning from single-band to multi-band EONs becomes advantageous. Our results show that IE-PLIA significantly lowers the blocking probability, achieving a 60% reduction compared to the benchmark algorithm in the Pan-European network at 2000 Erlangs.

This paper proposes a machine learning-based bandwidth slicing approach for crosstalk-aware routing, modulation level, core, and spectrum allocation in space division multiplexed elastic optical networks, implemented within a software-defined elastic optical network controller. Our method aims to mitigate blocking probability due to spectrum fragmentation and optical transmission reach while improving the time efficiency of traditional slicing approaches. We implemented and evaluated three classification models, logistic regression, K-nearest neighbors, and decision tree, on a Pan-European topology. The logistic regression model, when deployed, performed the best, reducing the blocking probability by an average of 46% and 4.3% compared to baseline models and further improving time complexity post-training.

The cyber resilience of cyber-physical power grids relies on swift restoration of cyber domain components following major disturbances such as, natural disasters or man-made attacks. The cyber domain restoration problem is inherently stochastic due to uncertainties surrounding initial outage conditions and restoration action failures. Traditionally, optimization-based methods, such as heuristics and mixed-integer linear programming (MILP), are utilized for solving restoration problems. However, these methods suffer from time-consuming processes and limited adaptability to dynamic conditions. To address these challenges, this paper formulates the observability recovery problem (ORP) as a Markov decision process and uses deep reinforcement learning (DRL) to solve the problem. Numerical simulations on the IEEE 30-bus system demonstrate that our proposed approach outperforms the heuristic approach in terms of both performance and computational efficiency. Moreover, when compared to the MILP approach, our method achieves comparable performance while requiring significantly less computation time.

Elastic optical networks (EONs) will not be able to satisfy the ever-increasing demand of the next-generation Internet applications. Thus, space-division multiplexing (SDM) technology is introduced to increase the fiber capacity and incorporate multiple EONs (SDM-EONs), specifically through implementing multi-core fibers (MCFs). Inter-core crosstalk (XT) is the fundamental issue in MCF, leading to lower utilization and lower optical signal quality. Due to the presence of significant XT, the traditional resource allocation problem in SDM-EONs needs to incorporate dynamic XT values. This paper describes a comprehensive solution that incorporates the XT constraint during routing, modulation, core, and spectrum allocation in the software-defined networking controller. First, we present a dynamic XT-aware routing (XTAR) algorithm with two policies in which link costs are dynamically calculated based on the XT effect and length of the links. Next, we introduce a new XT-aware bandwidth-slicing resource allocation approach that considers both XT limitations and simultaneously addresses blocking of large demands due to fragmentation and optical reach. Extensive simulations on several well-known network topologies reveal that the average request blocking for both the proposed policies significantly outperforms traditional shortest-path based benchmark.

The ability of phasor measurement units (PMUs) to precisely measure time-synchronized voltage and current phasors has made them a vital component of power grid monitoring systems. In a PMU-measured power grid, the measurement data is transferred via a communication network to the data monitoring station known as the phasor data concentrator (PDC) for data analysis. The PMU measurement-based applications depend on the observability of the power grid which relies on the availability of the PMU network (PMUs and their corresponding CNs). Multiple component (PMU and communication link) failure is a potential threat during high-impact events such as natural disasters or major cyber attacks, which could result in partial observability (in the worst case full unobservability) of the grid. Since it is not possible to maintain full grid observability during disasters when multiple components fail simultaneously, this paper proposes an observability-risk- aware resilient PMU network (ORARN) design framework that maximizes the expectation of the observability of the power grid buses. The proposed framework provides a disaster-resilient PMU network design that considers the probabilities of failures of the PMUs and the communication links and is constrained by a fixed total budget. Numerical studies are conducted on the IEEE 57-bus system to demonstrate the effectiveness of the proposed ORARN framework. The results obtained in the paper prove the effectiveness of the ORARN framework since it achieves a statistically higher power grid observability level under high-impact disasters when compared to an observability- risk-unaware baseline method.

Smart grid technologies have been transforming the power grid operation paradigms by integrating smart sensing devices, advanced communication networks, and powerful computing resources. In addition, data-driven applications have significantly increased in recent years, accelerating the use of smart sensors, such as phasor measurement units (PMU), in power grid monitoring. It necessitates a well-functioning communication network (CN) for PMU measurement data transfer to the control center even in the event of failures. This paper proposes a PMU network routing algorithm to ensure data transfer for control center's resilient observability to the power grid. The interdependent roles of PMUs in power grid observability is first identified based on the power grid topology. Then, a failure-tolerant routing algorithm is proposed to find data transfer paths in the CN that meets the power grid monitoring needs. The resultant routing paths ensure resilience against single link failure, where the resilience is defined in terms of grid observability. Besides, a cost metric is defined to minimize end-to-end delay in the network to facilitate real-time data transfer. Simulation results verify the superiority of the proposed routing algorithm compared with conventional fault-tolerant routing algorithms that are agnostic to the domain knowledge of power grid observability.

Phasor measurement units (PMUs) play a crucial role in real-time monitoring and control of power grids. They rely on a communication network to transfer measurement data to the phasor data concentrator (PDC) for further processing and analysis. In this article, a resilient cross-domain PMU and communication link placement method for minimizing the overall installation cost of the wide-area measurement system (WAMS) is proposed. The main idea is to break down the barrier between the power grid domain and the communication domain and consider the impact of one when designing the other. The PMU placement in the power grid domain takes into account the cost of communication links by generating multiple solutions with equally minimum PMU costs for communication link placement evaluation. On the other hand, the communication link placement problem reduces the cost by customizing the routing policies based on the different roles of PMUs in grid observability. The proposed WAMS design is capable of withstanding any single component failure in the power domain (PMU failure or power branch failure) or in the communication domain (communication link failure or PDC failure). The numerical study on the IEEE 57-bus system reveals that the developed cross-domain optimization framework can significantly reduce the overall installation cost of WAMS while attaining multidomain resiliency.

In order to have a properly functioning cyber–physical power system, the operational data need to be properly measured, transmitted, and processed. In case of a malicious event on the cyber layer of the power system, such as the wide-area monitoring system, cyber components, such as phasor measurement units (PMUs), communication routers, and phasor data concentrators (PDCs) may be compromised, leading to an unobservable power system. This article proposes the concept of cyber restoration of power systems, and an optimal restoration scheme to recover the system observability swiftly after massive interruptions. The cyber restoration problem is formulated as a mixed integer linear programming (MILP) problem considering PMU measurability, communication network connectivity, and PDC processability conditions, as well as cyber restoration resources as constraints. Results in the IEEE 57-bus system validate that the proposed optimization method can provide solutions that recover system observability much faster than heuristic methods, demonstrating the need for systematic cyber restoration planning research and implementation.

Due to the modern bandwidth-intensive, ever heterogeneous, and evolving network traffic, exhaustion of network resources under current technologies is foreseeable. In order to provision high quality network services for the next-generation network users, emerging network technologies must be relied on. Elastic optical networks (EON) and space division multiplexing (SDM) are the two preferred emerging optical network architectures to solve the future challenge of network demands. However, the spectrum contiguity constraint introduced by EON may lead to significant fragmentation. Slice-ability is an effective allocation framework that can mitigate spectrum fragmentation by dividing the lightpath into a set of sub-lightpaths, where each sub-lightpath consists of a fraction of the original lightpath bandwidth for the entire duration of the original request. Sliceability is conventionally used to solve routing, modulation, and spectrum assignment (RMSA) problems in EON. In this paper, we propose SDM sliceable framework that is crosstalk-and modulation-aware for solving the routing, modulation, core, and spectrum assignment (RMCSA) problems in SDM-EON. We refer each sub-lightpath as tight-segment. SDM slice-ability framework is compatible with all core and spectrum assignment (CSA) algorithms in literature. We evaluate light-segment based RMCSA algorithms using three existing CSA algorithms: First-Fit, Largest-First, and Best-Fit. Based on extensive performance evaluations, we observe significant improvement of RMCSA algorithms with SDM slice-ability compared to conventional approaches without SDM slice-ability.

The manycast communication paradigm is becoming increasingly important in today's optical networks, wherein connection requests from a source node can be routed to a subset of a candidate destination set. This flexibility in choosing different destinations from a larger candidate destination set helps improve the network performance. In this paper, we develop a new analytical model to compute the network-wide blocking performance for generalized manycast routing and wavelength assignment (MRWA) in optical wavelength division multiplexed (WDM) networks. Specifically, we calculate the request blocking on full-wavelength convertible optical networks based on Markov chains and conditional probability analysis. Performance results show that our model is accurate and is verified by extensive simulation results.

Literature has indicated that accurate dietary assessment is very important for assessing the effectiveness of weight loss interventions. However, most of the existing dietary assessment methods rely on memory. With the help of pervasive mobile devices and rich cloud services, it is now possible to develop new computer-aided food recognition system for accurate dietary assessment. However, enabling this future Internet of Things-based dietary assessment imposes several fundamental challenges on algorithm development and system design. In this paper, we set to address these issues from the following two aspects: (1) to develop novel deep learning-based visual food recognition algorithms to achieve the best-in-class recognition accuracy; (2) to design a food recognition system employing edge computing-based service computing paradigm to overcome some inherent problems of traditional mobile cloud computing paradigm, such as unacceptable system latency and low battery life of mobile devices. We have conducted extensive experiments with real-world data. Our results have shown that the proposed system achieved three objectives: (1) outperforming existing work in terms of food recognition accuracy; (2) reducing response time that is equivalent to the minimum of the existing approaches; and (3) lowering energy consumption which is close to the minimum of the state-of-the-art.

The Department of Energy (DOE) supports scientific collaboration in six program areas, ranging from nuclear physics, to biological and environmental research. To enable these data intensive large scale collaborations, the Energy Sciences Network (ESnet) is used to move upwards of 50 Petabytes a month between sites within the US and Europe. Bandwidth within ESnet can be requested, reserved, and utilized through the On-demand Secure Circuits and Advance Reservation System (OSCARS), which provisions network resources with guaranteed bandwidth over a known reservation schedule. Traditionally, OSCARS has only supported simple point-to-point connections between endpoints (e.g. universities, research laboratories), which has limited how efficiently the network may be harnessed by users. This paper details recent extensive enhancements prototyped for OSCARS, to be incorporated into a future release, which enable users to select novel service types including survivability, asymmetric bandwidth or routes, and anycast/manycast. We quantitatively compare several of these enhancements to the baseline point-to-point service, and find that the new services provide not only greater flexibility for the end-user, but savings for network administrators in terms of blocking and network resource usage as well.

Optical wavelength-routed networks enable parallel transmission of massive datasets on non-overlapping wavelength channels. However, as the sizes of scientific workflows increase, the simple availability of multi-wavelength resources will fall short of supporting application needs. Rather, these resources must be allocated intelligently, efficiently, and flexibly to bear the burden of high-volume science. We propose time-slotted wavelength-switching to support modifying the wavelength that carries a lightpath throughout its lifetime, exposing flexible consumption of available resources during the request schedule. We explore the efficacy of wavelength-switching in combination with adaptive path selection flexibility and attempt to approach previously determined optimality benchmarks. Results from quantitative evaluations show tremendous savings opportunity via wavelength-switching support, and indicate that efficient invocation of spectral flexibility in this manner may even be more impactful than spatial flexibility on network-wide performance.

Today's extreme-scale science applications involve the processing of bandwidth-intensive scientific workflows consisting of several inter-dependent tasks executing on heterogeneous clusters of computational resources and storage resources, which are interconnected by high-speed networks. An important challenge in such applications is the joint scheduling of computational, storage, and network resources. The tasks in each workflow can be scheduled and assigned computing and storage resources as an inseparable part (i.e., sequential scheduling); on the other hand, for some applications, tasks can be divided into small subtasks and parallel scheduling is applied. Elastic optical networks are a promising backbone for next-generation networks, since they are capable of allocating the huge fiber bandwidth more efficiently and flexibly to applications with various requirements. This is enabled by partitioning the fiber bandwidth into hundreds of subcarriers with fine granularity that may be allocated to services. In this paper, we study the problem of scheduling computational, storage, and networking resources to dynamic workflows in elastic optical networks. Four heuristics for sequential task scheduling and parallel task scheduling are proposed and compared. Simulation results are presented to demonstrate the effectiveness of the proposed approaches.

With advances in Internet of Things (IoT), intelligent data sensors are being added to more and more devices that interact with human's daily life in areas, such as medical services, smart grids, and financial services. IoT has made big contributions to data growth, requiring highly reliable data storage solutions. Storage area networks (SANs) are one of such solutions. To meet high reliability and availability requirements, SANs have to provide fault tolerance through redundancy to minimize or eliminate system downtime, thus preventing business discontinuity due to catastrophic events. Mesh is one of the common SAN topologies that have been applied to implement a fault tolerant SAN in practice. In this paper, failure behavior of a mesh SAN is modeled using a dynamic fault tree (DFT) in the case of perfect links, or a network graph in the case of imperfect links. Based on the constructed DFT or network graph model, reliability of the mesh SAN is evaluated using a binary decision diagram-based method. Results obtained from the case study can provide insights into the behavior of general mesh SAN systems, providing guidelines in the reliable design and operation of SANs.

This paper models 1-out-of-N standby computing systems with a dynamic checkpointing policy. The system performs a real-time mission task that has to be accomplished within an allowed mission time. During the mission, to facilitate an effective failure recovery the system undergoes checkpointing procedures according to a policy that dynamically determines a checkpointing frequency based on the activated element and remaining work for completing the mission. System elements are heterogeneous; they can follow different, arbitrary types of time-to-failure distributions, have different performance and wait in different standby modes before their activation. A new numerical algorithm based on state space event transitions is first proposed to evaluate mission success probability of the real-time standby systems considered in this work. Additional new contributions are made by formulating and solving optimal dynamic checkpointing policy problems, as well as an integrated optimization problem that finds the optimal combination of checkpointing policy and element activation sequence maximizing mission success probability. Advantages of using the dynamic checkpointing policy over fixed even checkpoints are demonstrated through examples. Examples and results are also provided to illustrate effects of different mission and element parameters on mission success probability as well as on the optimal dynamic checkpointing policy.

Recent trends in science applications call for long-range and large-scale collaboration among laboratories and super-computing sites. Long gone are the days of entering data manually into a spreadsheet on a local workstation. The world's most powerful and ground-breaking experiments generate exabytes of information, which must be distributed to multiple labs for analysis and interpretation. Such trends reveal the unwavering importance of new communication paradigms, like multicasting and manycasting, which provide point-to-multipoint data transfers. Typically, these all-important mechanisms are provided at the optical layer, where split-capable cross-connects split input signals into multiple output signals all-optically. Unfortunately, some of the world's largest and most powerful networks do not have the hardware infrastructure to support such functionality, but allow for point-to-point communication exclusively. In such split-incapable (SI) networks, multicast and manycast must be provided as a logical overlay to the pre-existing and limited unicast infrastructure. In this paper, we present two overlay models for providing manycast support in SI networks: Manycasting with Drop at Member Node (MA-DMN) and Manycasting with Drop at Any Node (MA-DAN). Through the development of integer linear programs (ILPs) and heuristics, we evaluate these models in terms of both optimal solutions and efficient approximations for both small-scale and large-scale networks and consider both static and dynamic traffic scenarios. Our results demonstrate that despite a small tradeoff in additional complexity and delay from signal conversion to the optical domain, our models provide efficient utilization of network resources and greatly surpass the standard naive approach of establishing paths to every destination.

In anycast, connection requests are routed to one of multiple destination candidates, thus helping improve the overall acceptance of service requests in the network when compared to traditional unicast. In this paper we develop a new analytical model to compute the network-wide blocking performance for anycast routing and wavelength assignment (ARWA) in wavelength division multiplexing (WDM) optical networks using the reduced-load fixed-point approximation analysis. This model is based on conventional queuing theory for loss systems combined with a joint probability analysis of the anycast service alternatives. Performance results show that our model provides good accuracy compared to simulation results.

Critical data transmissions are often scheduled hours or days in advance of the actual acquirement of network resources, allowing for efficient allocation and scheduling among a set of competing or temporally overlapping lightpath demands. Many periodic applications may not only desire service at some future time, but may further require repeatable and predictable scheduling services. Typically, such application demands are deadline-driven and therefore mutable within some sliding window depending on congestion, competition, or load. This paper considers Sliding Scheduled Lightpath Establishment (SSLE) in time-slotted optical networks and enhances scheduling by incorporating spectral flexibility at wavelength/time-slot granularity. A novel wavelength-switching integer linear program and two conservative heuristics are presented to describe and evaluate the SSLE problem under various degrees of temporal conflict and flexibility.

Resources in a network are imperfect, and equipment failure can have detrimental effects on data and transmission success rates. Attempts to improve the survivability of network communications when these failures occur focus primarily on protection against the common occurrence of link failures, while nodal failure has been largely overlooked. In data-critical infrastructures, such as cloud computing or data center networks, wherein the critical points of interest are at the nodes, a natural disaster or directed attack could have catastrophic consequences for the localized data. To overcome single points of failure, replicated multicast transmissions can be used to distribute copies of critical data to various geographically dispersed locations on the grid. We therefore explore strategies to protect against single critical node failures during multicast transmissions. We propose three novel multicast survivable heuristics and quantitatively analyze and then compare them to traditional multicast provisioning schemes through extensive simulation1.

Traffic grooming is necessary for the efficient use of optical networks. It generally requires a signal-conversion from the optical to the electrical domain and back. Planners have some freedom in selecting the location where this energy-intensive process takes place. A subset of nodes in a network may be powered by renewable energy sources. Those green nodes cause lower green house gas (GHG) emissions than others. We suggest to choose these sites for grooming. We propose a model for GHG emissions caused by network operations. Depending on the level of penetration of renewable sources in the power supplies across the network, emissions can be reduced significantly. Potentially spanning different network domains, we introduce a hierarchical grooming approach to collect and multiplex traffic at those green nodes, groom it there and therefore save emissions. We evaluate the emission model and the hierarchical approaches' performance. Further, we apply them to various network/demand scenarios in an effort to identify favorable conditions for this scheme. We find that by relaxing energy-efficiency requirements in green nodes, and being more stringent in black nodes, we can reduce overall network emissions. The hierarchical approach is scalable and efficiently applicable to operating and future networks.

Today, large amounts of data, growing from terabytes to petabytes, need to be transferred across the globe in a timely manner. To accommodate this efficiently, network operators are augmenting their networks to 100 Gbps links and beyond. The spectrum-sliced elastic optical path network (SLICE) architecture enables accommodation of variable-rate data traffic in a highly spectrum-efficient manner. The blocking in SLICE networks observed in literature is much lower than on traditional fixed grid WDM networks. Still, the current routing and spectrum allocation (RSA) algorithms have potential for blocking performance improvements. To increase the spectral efficiency, we introduce a concept called routing, spectrum, and segment allocation (RSSA). We propose several novel continuous and non-continuous time heuristics based on the concept of RSSA. We consider dynamic advance reservation traffic requests over SLICE networks and evaluate the performance of the proposed RSSA heuristics. Through extensive simulations, we observe that our continuous-time, non-contiguous spectrum RSSA heuristics outperform existing heuristics in terms of both blocking probability and spectral utilization.

While personal data privacy is threatened by online social networks, researchers are seeking for privacy protection tools and methods to assist online social network providers and users. In this paper, we aim to address this problem by investigating how to quantitatively evaluate the privacy risk, as a function of people's awareness of privacy risks as well as whether their friends can be trusted to protect their personal data. We present a trust-aware privacy evaluation framework, called TAPE. Simulations are performed to illustrate the key concepts and calculations in TAPE, as well as demonstrate the advantages of TAPE.

Manycasting allows a single source to reach multiple destinations while providing flexibility in destination selection. Our goal in this paper is to improve the cost of the manycast drop at member node (MA-DMN) overlay algorithm in terms of energy consumption and associated greenhouse gas (GHG) emissions. To reduce the environmental impact, ideally, a large percentage of the network nodes along the transmission and the chosen destinations need to be green. We present a novel energy-conservative emission-aware variant of the MA-DMN algorithm. We then propose further modifications to increase the utilization of those destinations that are powered by renewable energy sources: manycast drop at greenest nodes (MA-DGN). The potential for emission reduction by those algorithms is two-fold: The data are transported in the most efficient way and processed at the greenest available data centers. We compare the approaches by simulating realistic quantities of dynamic traffic. We assume heterogeneously distributed and time-dependent availability of renewable energy sources to power nodes throughout the network. We find that the energy-source-aware algorithms lower both energy-consumption and GHG emissions at stable network performance levels, in some cases even lowers blocking rate.

Application communication in wireless sensor networks (WSN) depends on two important factors: acquisition of sensed data from a specific area, and network connectivity that concerns the reliable delivery of the observed data from sensor nodes to the sink node. In this paper, we consider the application communication reliability (ACR) of WSN supporting K-coverage in the presence of shadowing for a specific monitored area. The analytical evaluation of ACR involves two steps. We first identify all the K-coverage sets. Then, we evaluate the communication reliability of delivering the observed data from sensor nodes within the identified K-coverage sets to the sink node. Two single-path routing algorithms, shortest-path distance algorithm and shortest-path hop algorithm, are considered for evaluating the communication reliability during the second step; their performances in terms of ACR and energy consumptions are compared through an empirical analysis of several examples. Different scenarios are considered to evaluate the impact of node density, channel condition and different monitored areas on ACR. Simulation and analytical results show that WSN using the shortest-path distance algorithm is more reliable than that using the shortest-path hop algorithm in most cases, but WSN using the shortest-path hop algorithm consumes less energy for delivering the sensed data to the sink node.

Manycasting is an emerging communication paradigm which allows a single source to reach multiple destinations while providing flexibility in the selection of which destinations to connect with. Traditional wavelength division multiplexed (WDM) networks do not support the all-optical splitting of signals to multiple output ports as required by point-to-multipoint communication schemes. Previous work has proposed an overlay approach known as Manycasting with Drop at Member Node (MA-DMN) to provide manycast support as a logical overlay to basic point-to-point lightpath connections. This approach has been studied extensively and compared to alternative overlay models, and has emerged the obvious candidate for supporting manycast overlays. Throughout its evaluation though, MA-DMN has never been scrutinized in terms of its costs for energy consumption and associated greenhouse gas (GHG) emissions. In this work, we subject MA-DMN to these evaluations, while also proposing a new more energy-conservative emission-aware variant known as MA-DMN using Least Impact Trees (MA-DMN-LIT). We compare these two approaches by simulating realistic quantities of dynamic traffic, and uniformly distributing renewable energy sources to power nodes throughout the network. We find that MA-DMN-LIT reduces energy consumption over MA-DMN by 6-10% across the network, while also reducing CO2emissions by as much as 27%. We further conclude that MA-DMN-LIT also provides lower connection blocking by not over-subscribing shorter paths in the network as its emission-blind counterpart does.

Recent explosion of high-bandwidth applications and scientific collaboration has expedited the need for scheduled transmission of data to multiple scientific sites around the world. Advance reservations (AR) promote efficient bandwidth utilization, particularly when demands are high. The collaborative nature of modern science calls for more flexible point-to-multipoint distribution paradigms, such as manycasting. Combining AR and manycast communication mechanisms enables intelligent resource utilization in optical networks to support future e-science applications. Limiting the adoption of point-to-multipoint communication is the physical handicap that many optical crossconnects are Split-Incapable (SI), i.e., all-optical splitting of signals is not supported, making optical AR manycasting infeasible. In this paper, we adapt solutions which have previously only been considered in immediate reservation (IR) scenarios to provide manycasting as a multi-hop logical overlay to the unicast-only optical layer. We develop ILPs and heuristics to evaluate the resource consumption for various AR traffic scenarios1.

Immediate reservation (IR) and advance reservation (AR) are the two main reservation mechanisms currently implemented on large-scale scientific optical networks. They can be used to satisfy both provisioning delay and low blocking for delay-tolerant applications. Therefore, it seems reasonable that future optical network provisioning systems will provide both mechanisms in hybrid IR/AR scenarios. Nonetheless, such scenarios can increase the blocking of IR if no quality-of-service (QoS) policies are implemented. A solution could be to quantify such blocking performance based on the current network load and implement mechanisms that would act accordingly. However, current blocking analytical models are not able to deal with both IR and AR. In this paper, we propose an analytical model to compute the network-wide blocking performance of different IR/AR classes within the scope of a multiservice framework for optical wavelength-division multiplexing (WDM) networks. Specifically, we calculate the blocking on two common optical network scenarios using the fixed-point approximation analysis: on wavelength conversion capable and wavelength-continuity constrained networks. Performance results show that our model provides good accuracy compared to simulation results, even in a scenario with multiple reservation classes defined by different book-ahead times.

In this paper we investigate techniques for provisioning advanced reservation multicast requests in Multicast-Incapable (MI) networks, which lack the ability to split an incoming signal to multiple output ports, without performing an O-E-O conversion. To implement the multicasting functionality in a MI network, we propose implementing it as a logical overlay to the optical layer. One such method is to reserve unicast lightpaths from the source node to each destination node of the multicast request. Referred to as Multicast Via WDM Unicast (MVWU), this solution tends to utilize the network resources in an inefficient manner. To address this problem we propose two novel overlay solutions: Drop At Member Node (DAMN) and Drop At Any Node (DAAN), wherein we create a set of lightpath routes (possibly multiple-hop) in the overlay layer to reach all the destinations of a multicast request. In DAMN, we allow a lightpath to terminate/originate only at nodes which belong to the set of destination nodes of the multicast request. DAAN relaxes this constraint and allows a lightpath to be terminated at any node in the network. We refer to the set of lightpath routes created in the overlay layer as overlay-trees. We consider dynamic traffic and present efficient heuristics to solve the MVWU, DAMN, and DAAN problems with a goal of minimizing the blocking probability of a request. Our results indicate that DAMN and DAAN outperform the MVWU approach. Further, we present different mechanisms to generate the overlay-trees and compare their relative performance on a real-world large-scale network.

In this paper, we investigate the static multicast advance reservation (MCAR) problem for all-optical wavelength-routed WDM networks. Under the advanced reservation traffic model, connection requests specify their start time to be some time in the future and also specify their holding times. We investigate the static MCAR problem where the set of advance reservation requests is known ahead of time. We prove the MCAR problem is NP-complete, formulate the problem mathematically as an integer linear program (ILP), and develop three efficient heuristics, seqRWA, ISH, and SA, to solve the problem for practical size networks. We also introduce a theoretical lower bound on the number of wavelengths required. To evaluate our heuristics, we first compare their performances to the ILP for small networks, and then simulate them over real-world, large-scale networks. We find the SA heuristic provides close to optimal results compared to the ILP for our smaller networks, and up to a 33% improvement over seqRWA and up to a 22% improvement over ISH on realistic networks. SA provides, on average, solutions 1.5-1.8 times the cost given by our conservative lower bound on large networks.

With the increasing number of high-bandwidth applications, energy consumption of networks has become an important issue that needs to be addressed. Manycasting is a communication paradigm that finds applications in such high-bandwidth environments. To support manycasting functionality in an optical network that is Split-Incapable (SI), i.e., the optical cross connects are incapable of switching an incoming optical signal to more than one output interface, manycasting must be implemented as an overlay to the optical layer. We propose two such overlay approaches: Manycasting with Drop at Member Node (MA-DAMN) and Manycasting with Drop at Any Node (MA-DAAN) which employ Steiner tree routing. We subject these approaches to a static traffic model, and present integer linear programs (ILPs) and heuristic approximations which aim to minimize the total number of wavelengths required to service the manycast request set in an effort to reduce network-wide energy consumption. Through extensive simulation, we show that MA-DAMN and MA-DAAN achieve 25-45% wavelength reduction as compared to a baseline overlay approach which employs single-hop lightpaths to each manycast destination individually.

Current Internet and large-scale experimentation applications need to satisfy short provisioning delay and low blocking demands. Both can be guaranteed by using immediate reservation (IR) and advance reservation (AR), respectively. However, the scheduling of both reservation types in the same network can especially degrade the performance of IR if no extra policies are applied. In order to enhance such class-based policies, we need to quantify the future performance of the system, thus requiring to model its behavior. In this paper, we propose the use of a two-fold probability transition Markov chain successfully applied in the past in offset-based reservation systems. Results show the good accuracy of the model to simulation results, even in an scenario with multiple traffic classes defined by different book-ahead times. Such a performance validates its applicability to a wide range of immediate and advance reservation systems.

In this paper we investigate the problem of provisioning dynamic anycast holding-time-aware (HTA) lightpaths in all-optical wavelength division multiplexed (WDM) networks. We employ a technique called lightpath switching (LPS) wherein the data transmission may begin on one lightpath and switch to a different lightpath at a later time. We propose two heuristics to solve the anycast routing and wavelength assignment (RWA) problem: anycast with continuous segment (ACS) and anycast with lightpath switching (ALPS). We first compare the performance of ACS to ALPS and observe that ALPS achieves better blocking than ACS. Furthermore, we also compare the performance of these two anycast RWA algorithms to the traditional unicast RWA algorithm. We show that the anycast RWA algorithms presented here significantly out-perform the traditional unicast RWA algorithms.

In this work we propose anycast routing methods to improve the performance of reconfigurable WDM networks under the variations in the IP traffic. We first investigate anycast communication via impairment-aware anycast routing (IAAR); our simulation results show significant improvement in the blocking probability. We also investigate the proposed load-aware anycast routing (LAAR) for the varying traffic model. From the results we observe that LAAR minimizes the lightpath request loss, by dynamically choosing the anycast configuration based on the network load.

Ant colony optimization (ACO) is a probabilistic technique used for solving complex computational problems, such as finding optimal routes in networks. It has been proved to perform better than simulated annealing and genetic algorithm approaches for solving dynamic problems. ACO algorithms can quickly adapt to real-time changes in the system. In this paper, we propose an ACO-based algorithm to solve the dynamic anycast routing and wavelength assignment (RWA) problem in wavelength-routed WDM networks. Using extensive simulations, we show that ACO-based anycast RWA significantly reduces blocking probability compared to the fixed shortest-path first (SPF) and other dynamic algorithms.

Some current Internet applications (e.g., Grid/Cloud computing storage, video-conference) demand service differentiation, not only in terms of packet forwarding, but also at the connection level. To satisfy the demands for delay-sensitive and low-blocking applications, immediate reservation (IR) and advance reservation (AR) can be performed. Independent resource reservation of each type of network resources is well-investigated. Nevertheless, it is very likely that both types of requests will need to share network resources. There is also significant demand for a service framework that is able to provide application-aware quality of service (QoS). By using existing scheduling algorithms for IR/AR, we develop a service framework to guarantee relative QoS among different application requests, with and without tolerance to delay and service blocking. Simulation results demonstrate the feasibility of our approach and provide a basis for future development of enhanced IR/AR QoS policies within the control plane of future high-speed networks.

In this paper we introduce the static multicast advance reservation (MCAR) problem for all-optical wavelength-routed WDM networks. Advance reservation connection requests specify their start time to be some time in the future and also specify their holding times. We investigate the static MCAR problem where the set of advance reservation requests is known ahead of time. We develop two efficient heuristics, ISH and SA, to solve the problem for practical size networks. We also introduce a theoretical lower bound on the number of wavelengths required. To evaluate our heuristics we run simulations over real-world, large scale networks and compare them to our lower bound. We find the SA heuristic provides up to a 21% improvement over ISH (14% on average) on realistic networks. SA provides, on average, solutions 1.5-1.8x times the cost given by our conservative lower bound on large networks.

Random contentions occur in optical burst-switched (OBS) networks because of one-way signaling and lack of optical buffers. These contentions can occur at low loads and are not necessarily an indication of congestion. The loss caused by them, however, causes TCP at the transport layer to reduce its send rate drastically, which is unnecessary and reduces overall performance. In this paper, we propose coordinated burst cloning and forward segment redundancy, a proactive technique to prevent data loss during random contentions in the optical core. With forward segment redundancy (FSR), redundant segments are appended to each burst at the edge and redundant burst segmentation (RBS) is implemented in the core so that when a contention occurs, primarily redundant data is dropped. With burst cloning, an entire redundant burst is created at the edge and sent at the same time as the original burst. Coordinated burst cloning and FSR creates clones of bursts (with FSR) and transmits them independently, creating a second-level of redundancy. We evaluate the performance of our proposed loss recovery technique through extensive simulations. We observe that the proposed hybrid technique significantly improves TCP performance at both low and high network loads.

It is well-known that the bufferless nature of OBS networks causes random burst loss even at low traffic loads. When TCP is used over OBS, these random losses make the TCP sender decrease its congestion window even though the network may not be congested. This results in significant TCP throughput degradation. In this paper, we propose a coordinated multi-layer loss-recovery approach for TCP over OBS networks using Snoop and ARQ. We developed an analytical model for end-to-end TCP throughput using the hybrid approach over OBS and verified the results using simulations. We evaluate the performance of independent and coordinated Snoop and ARQ over an OBS network. Based on the numerical results, the proposed coordinated multi-layer Snoop and ARQ approach outperforms all other approaches at all traffic loads.

This paper presents a tabu search meta-heuristic to solve the static manycast routing and wavelength assignment problem (MA-RWA). The problem is to route a set of manycast requests over a wavelength-routed WDM network such that the number of wavelengths required is minimized. We present the details of a tabu search meta-heuristic for this problem and compare it to two other MA-RWA heuristics called lambda path heuristic (LPH) and shortest path tree (SPT) heuristic. The tabu search meta-heuristic shows a 10% improvement over LPH and a 30-40% improvement over SPT for various realistic networks.

In this paper we discuss the effect of physical impairments on manycasting service over the optical burst- switched (OBS) networks. Signal quality degradation in manycast networks is an important issue and it can occur due to fiber attenuation, splitter switch and amplified spontaneous noise in EDFA. These physical layer impairments causes the signal quality to be weak at the receiver and hence burst may not be detected or lost. Our objective is to select the manycast destinations based on the quality of signal received. We propose a new algorithm,impairmentaware-dynamicmembership(IADM) that takes into account of the physical layer impairments. Based on the simulation results we observe that IADM is more robust and practical, as bursts are scheduled not just on contention but also on the physical layer constraints.

We discuss the effect of physical impairments on manycasting service over optical burst-switched (OBS) networks. Signal quality degradation in manycast networks is an important issue and it can occur due to fiber attenuation, splitter switch, and amplified spontaneous noise in EDFA. These physical layer impairments causes the signal quality to be weak at the receiver and hence burst may not be detected. Our objective is to select the manycast destinations based on resource unavailability and the quality of signal received. We propose three impairment- aware algorithms that take into account of the physical layer impairments. Using extensive simulation results we compute average burst loss probability, both due to contention and signal degradation. These simulation results are verified by the analytical model. We have also compared our results with random destination selection using binomial model and observe that our methods perform better than the random selection method.

TCP-based applications account for a majority of data traffic in the Internet; thus understanding and improving the performance of TCP over OBS network is critical. In this paper, we identify the ill-effects of implementing TCP over a hybrid network (IP-access and OBS-core). We purpose a Split- TCP approach for a hybrid IP-OBS network to improve TCP performance. We propose two Split-TCP approaches, namely, 1:1:1 and N:1:N. We evaluate the performance of the proposed approaches over an IP-OBS hybrid network. Based on the simulation results, N:1:N Split-TCP approach outperforms all other approaches.

Recent advances in optical switching technology allows for the creation of networks in which data bursts are switched optically at each node, offering a greater degree of flexibility suitable for handling bursty Internet traffic. TCP-based applications account for a majority of data traffic in the Internet; thus understanding and improving the performance of TCP implementations over OBS networks is critical. Previously, several articles show that load-balanced routing improves lossperformance in OBS. In this paper, we identify the ill-effects of load-balanced OBS on TCP performance caused due to false time-outs and false fast-retransmit. We propose source-ordering mechanism that significantly improves TCP throughput. We evaluate the performance of the proposed mechanism over different TCP flavors, such as TCP Tahoe, TCP Reno, TCP SACK, and TCP Vegas over a load-balanced OBS network.

In this paper, we discuss for the first time the issue of supporting manycasting service over optical burst- switched (OBS) networks. One of the primary challenges in providing manycasting service over OBS networks is to reduce data loss due to burst contentions. We propose two new schemes, static over-provisioning (SOP) and dynamic membership (DM), to alleviate this data loss problem. The proposed schemes take into consideration the specific properties of manycasting, and the schemes may complement existing contention resolution schemes. The effectiveness of the proposed schemes is verified through simulation.

With the rapid deployment of wireless sensor networks, there are several new sensing applications with specific requirements. Specifically, target tracking applications are fundamentally concerned with the area of coverage across a sensing site in order to accurately track the target. We consider the problem of maintaining a minimum threshold-coverage in a wireless sensor network, while maximizing network lifetime and minimizing additional resources. We assume that the network has failed when the sensing coverage falls below the minimum threshold-coverage. We develop three node-replacement policies to maintain threshold-coverage in wireless sensor networks. These policies assess the candidature of each failed sensor node for replacement. Based on different performance criteria, every time a sensor node fails in the network, our replacement policies either replace with a new sensor or ignore the failure event. The node-replacement policies replace a failed node according to a node weight. The node weight is assigned based on one of the following parameters: cumulative reduction of sensing coverage, amount of energy increase per node, and local reduction of sensing coverage. We also implement a first-fail-first-replace policy and a no-replacement policy to compare the performance results. We evaluate the different node-replacement polices through extensive simulations. Our results show that given a fixed number of replacement sensor nodes, the node-replacement policies significantly increase the network lifetime and the quality of coverage, while keeping the sensing-coverage about a pre-set threshold.

Sensor networks are fundamentally deployed to handle extreme behaviors across sensing sites. Service differentiation in information-aware wireless sensor network refers to the ability to provide reliable and low-latency transmissions of critical data. In this paper, we present remote-homing based solutions to support service differentiation in wireless sensor network. For each sensor (source), we designate remote homes that bypass certain layers in a multi-layered sensor network in order to reduce transmission delay, and also identify node-disjoint remote homes in order to provide high reliability. We develop algorithms that identify optimal remote homes, which minimize the total energy consumed for data transmission given a delay and a loss constraint. We evaluate the effectiveness of our dynamic programming-based optimal algorithms using simulation results.

Abstract — In this paper, we study the survivability problem in hierarchical wireless access networks with dual-homed end users, who are connected to two base stations (BSs), a primary BS and a backup BS. The dual homing mechanism is resilient to a single failure of a BS. However, if a failure occurs at the base station controller (BSC) layer or at the mobile switching center (MSC) layer, dual-homing may not prevent connection loss. We address the problem of routing from BSs to BSCs and from BSCs to MSCs, with the objective of minimizing the maximum number of connections lost due to a single failure of BS, BSC, or MSC. We first formulate the problem using Integer Linear Programming (ILP). We then prove that this optimization problem is NP-hard by showing some of its subproblems with relaxed constraints are still NP-hard. A Tabu Search (TS) based heuristic is then proposed for the problem, which provides near optimal results in most cases. I.

The current state of the art in detecting immediate and long-term railway track problems involves both inspectors walking the track lines and train cars instrumented with accelerometers and ultrasonic sensors that are capable of detecting wear of the rail and breakages. Additionally, a widespread practice of sensing rail continuity by using the tracks to complete simple circuits is in place. In this paper, we propose a fundamentally different approach to improve the current practices in railway operations using wireless sensor network (WSN). The primary technical and scientific objectives of the system introduced in this paper are to generate innovative solutions for a number of the issues facing the railroad community through the development of a system based on WSN. The objectives from a railroad perspective include finding new approaches to reduce the occurrence rate of accidents and improving the efficiency of railroad maintenance activities.

Dual homing is a fault-tolerance mechanism generally used in IP-based access networks to increase the survivability of the network. In a dual-homing architecture, a host is connected to two different access routers; therefore, it is unlikely that the host will be denied access to the network as the result of a failure in the access network, a failure of the access router, or congestion at the access router. However, dual homing cannot provide survivability with respect to possible failures in the optical core network. To provide survivability in the core network, optical protection and restoration techniques must be used. In the past, dual homing architectures and optical protection schemes have been studied independently of one another. This paper studies coordinated multi-layer survivability techniques that use both dual-homing schemes and optical protection schemes in an IP-based access network over a WDM-based optical core network. Specifically, we investigate the protection design problem in the WDM core network, given that a dual-homing infrastructure is implemented in the access network. Several solutions are proposed, and it is shown that the proposed coordinated survivability schemes can reduce cost compared to the case in which the survivability mechanisms arc not coordinated between the IP layer and the optical layer.

In this paper, we evaluate the performance of a burst retransmission scheme in which the bursts lost due to contentions in an OBS network are retransmitted at the OBS layer. The retransmission scheme aims to reduce burst loss probability in OBS networks. We develop an analytical model for obtaining the burst loss probability over an OBS network that uses the retransmission scheme. We also compare the performance of the burst retransmission scheme with the deflection scheme. Simulation results also show that at a moderate traffic load, the retransmission scheme provides an improvement of up to four times the burst loss probability with the deflection scheme. Results also show that the retransmission scheme significantly improves the burst loss probability compared to an OBS network without the retransmission scheme.

Due to the bufferless nature of OBS networks, random burst losses may occur, even at low traffic loads. For optical burst-switched (OBS) networks in which TCP is implemented at a higher layer, these random burst losses may be mistakenly interpreted by the TCP layer as congestion in the network, leading to serious degradation of the TCP performance. In this paper, we reduce random burst losses by a burst retransmission scheme in which the bursts lost due to contention in the OBS network are retransmitted at the OBS layer. The OBS retransmission scheme can then reduce the probability that the TCP layer falsely detects congestion, thereby improving the TCP throughput. We analyze the TCP throughput when OBS networks employ the burst retransmission scheme and develop a simulation model to validate the analytical results. Based on our simulation results, we show that an OBS layer with burst retransmission provides an improvement of up to ten times the TCP throughput over an OBS layer without burst retransmission. This significant improvement is primarily because the TCP layer triggers fewer time-out based retransmissions when the OBS retransmission scheme is used

In this paper, we propose a novel proactive scheme, burst cloning, to reduce data loss due to burst contention in optical burst-switched (OBS) networks. The idea is to replicate a burst and send duplicated copies of the burst through the network simultaneously. If the original burst is lost, the cloned burst way still be able to reach the destination. Primary design issues in burst cloning are to select the optimal nodes at which to do cloning and to prevent cloned bursts from contending for resources with original bursts. An analytical model is developed to evaluate the proposed scheme. The model is verified through extensive simulations. We observe that burst cloning could significantly reduce data loss in OBS networks.

Several schemes have been proposed recently in the literature for providing absolute QoS differentiation in OBS networks, such as early drop and wavelength grouping schemes. However, these schemes only provide loss guarantees at a per-hop level. In this paper, we propose a path clustering technique to implement these per-hop schemes over an entire network. The path clustering technique provides a solution to prioritizing the traffic based on hop-distances between source and destination pairs. We develop an analytical model for obtaining the optimal path clustering for a given network. By using the path clustering technique, we can improve the end-to-end loss performance of nonguaranteed traffic, and also provide absolute end-to-end loss probability of guaranteed traffic.

A fault-tolerant scheme, called dual homing, is generally used in IP-based access networks to increase the survivability of the network. However, dual homing itself cannot provide survivability with respect to possible failures in the wavelength division multiplexed (WDM) core network. To provide survivability in the core network, protection and restoration techniques must be used. In the past, dual homing architecture and protection are studied separately. This paper observes that the dual homing architecture introduces new issues for protection and restoration design, especially when providing survivability against two independent failures, one in the access network and the other in the core network. This paper provides an integrated solution and studies the protection design problem in the WDM core network, given a dual-homing infrastructure in the access network. Several algorithmic solutions are proposed, and performance of the solutions is compared.

A number of schemes have been proposed for providing quality-of-service (QoS) differentiation in optical burst-switched (OBS) networks. Most existing schemes are based on a relative QoS model in which the service requirements for a given class of traffic are defined relative to the service requirements of another class of traffic. In this paper, we propose an absolute QoS model in OBS networks which ensures that the loss probability of the guaranteed traffic does not exceed a certain value. We describe two mechanisms for providing loss guarantees at OBS core nodes: an early dropping mechanism, which probabilistically drops the nonguaranteed traffic, and a wavelength grouping mechanism, which provisions necessary wavelengths for the guaranteed traffic. It is shown that integrating these two mechanisms outperforms the stand-alone schemes in providing loss guarantees, as well as reducing the loss experienced by the nonguaranteed traffic. We also discuss admission control and resource provisioning for OBS networks, and propose a path clustering technique to further improve the network-wide loss performance. We develop analytical loss models for the proposed schemes and verify the results by simulation.

In optical burst-switched networks, data loss may occur when bursts contend for network resources. There have been several proposed solutions to resolve contentions in order to minimize loss. These localized contention resolution techniques react to contention, but do not address the more fundamental problem of congestion. Hence, there is a need for network level contention avoidance using load balanced routing techniques in order to minimize the loss. In this paper, we propose two dynamic congestion-based load balanced routing techniques to avoid congestion. Our simulation results show that the proposed contention avoidance techniques improve the network utilization and reduce the packet loss probability.

A number of schemes have been proposed to support QoS in optical burst-switched (OBS) networks. Most schemes only support relative QoS differentiation instead of absolute QoS guarantee. However, absolute QoS differentiation is a basic requirement for many delay and loss sensitive applications. In this paper, we propose two mechanisms for providing absolute QoS differentiation in OBS networks, an early drop mechanism, which selectively drops non-guaranteed traffic, and a wavelength grouping mechanism, which manages wavelengths for guaranteed traffic. We show that the combination of these two mechanisms not only outperforms other schemes in providing loss guarantees, but also improves the loss performance of non-guaranteed traffic.

Optical burst switching is a promising solution for terabit transmission of IP data bursts over WDM networks. One of the key components in the design of optical burst-switched nodes is the development of channel scheduling algorithms that can efficiently handle data burst contentions. Currently, traditional scheduling techniques use wavelength conversion and buffering to resolve burst contention. In this paper, we reduce packet losses by proposing a number of data channel scheduling algorithms that use burst segmentation and fiber delay lines (FDLs). The proposed scheduling algorithms are classified based on the placement of the FDL buffers in the optical burst-switched node and are referred to as delay-first or segment-first schemes. Simulation results show that these algorithms can effectively reduce the packet loss probability compared to existing scheduling techniques.

We address the issue of providing quality-of-service (QoS) in an optical burst-switched network. QoS is provided by introducing prioritized contention resolution policies in the network core and a composite burst-assembly technique at the network edge. In the core, contention is resolved through prioritized burst segmentation and prioritized deflection. The burst segmentation scheme allows high-priority bursts to preempt low-priority bursts and enables full class isolation between bursts of different priorities. At the edge of the network, a composite burst-assembly technique combines packets of different classes into the same burst, placing lower class packets toward the tail of the burst. By implementing burst segmentation in the core, packets that are placed at the tail of the burst are more likely to be dropped than packets that are placed at the head of the burst. The proposed schemes are evaluated through analysis and simulation, and it is shown that significant differentiation with regard to packet loss and delay can be achieved.

We address the issue of providing differentiated services to IP packets over an optical burst switched core network, and we introduce a new approach for assembling packets into a burst. In this technique, a composite burst is created by combining packets of different classes into the same burst. The packets are placed from the head of the burst to the tail of the burst in order of decreasing class. The performance of this approach is enhanced by using a burst segmentation technique in which, during burst contention, only the packets in the tail of a burst are dropped. We describe a generalized model for burst assembly and burst scheduling, and we propose several composite burst assembly methods. We observe that having multiple classes of packets in a burst performs better than having a single class of packets in a burst.

We address the issue of contention resolution in optical burst switched networks, and we introduce an approach for reducing packet losses which is based on the concept of burst segmentation. In burst segmentation, rather than dropping the entire burst during contention, the burst may be broken into multiple segments, and only the overlapping segments are dropped. The segmentation scheme is investigated by simulation in conjunction with a deflection scheme, and it is shown that segmentation with deflection can achieve a significantly reduced packet loss rate.