Advanced Metering Infrastructure (AMI) comprises several smart meters (SM) that use wireless technologies such as ZigBee to exchange data and commands between each other and the backend systems. The wireless broadcast nature and smart meters' physical vulnerability make them prone to cyberattacks like spoofing, masquerading, and man-in-the-middle. This paper addresses the secret-free smart meter identification challenge in AMI systems, focusing on the widely used Zigbee communication standard. Specifically, we introduce an ensemble device fingerprinting framework, integrating the physical and the medium access control (MAC) layer with multiple machine learning models (Convolutional Neural Network, Logistic Regression, and Decision Tree). Our analysis shows that the ensemble framework outperforms individual fingerprinting models, with a mean accuracy of 83.33 %.

Communication networks are heterogeneous, distributed, and often lack centralized raw training data, making traditional Machine Learning (ML) difficult to adopt. Although Federated Learning (FL) addressed some of these drawbacks, FL, just like traditional (offline) ML, assumes that local data arrives in a statistically known manner, which makes them unable to adapt to the evolving statistics in communication patterns. To address this gap, we present a novel paradigm called Runtime Online Federated Learning (ROFL) for communication networks by modifying the FL paradigm into an online variant using continual/incremental learning principles of Online Learning (OL) to achieve just-in-time results i.e. in “runtime”. Specifically, we make the following contributions. (1) Our ROFL adopts an asynchronous aggregation for Global Model updates and adaptive activation rates and update periods for each node. (2) Unlike existing federated online approaches, ROFL is designed for previously unknown data to be available at runtime. We implement functionalities to listen for incoming packets at runtime, preprocess them and feed into the learning models. (3) As part of ROFL, we present a lighweight traffic classification model based on Natural Language Principles (NLP). When designed as a local model for each local node in ROFL paradigm, our classifier was able to seamlessly classify packets at runtime and continued to adapt to newer traffic in online fashion. (3) We evaluate our framework by emulating a real production-level network communication scenario. We show that our proposed framework is not only able to classify packets at runtime, but can also learn/train continuously once deployed, induce minimal communication overhead, and adapt to varying communication patterns. With modifications to the Local Model, our framework can be theoretically extended to any runtime federated task(s) which need to learn from continuous distributed data to make runtime inferences.

Machine Learning (ML) is extensively used for predicting transfer times for general purpose Wide Area Networks (WANs) or public Internet applications, but for Research and Education Networks (RENs) two major gaps exist in literature. First, RENs i.e. networks carrying large data flows have received limited attention by the networking community. RENs behave differently compared to the general purpose Internet applications and other network types. Hence, ML models from other network types cannot be used interchangeably for large data transfers. Second, the ML models are used as blackboxes to train on measured network values and then used to predict transfer times or other runtime network parameters. In this paper, we present a dynamical systems model of the large data transfers typical of RENs in the form of a system of Ordinary Differential Equations (ODEs) inspired by the Lotka-Volterra competition model. We present a transfer time prediction component called Dynamic Transfer Time Predictor (DTTP) which solves the ODEs and predicts the future transfer times. Second we formulate a loss function based on Lyapunov function called Lyapunov Drift Correction (LDC) that self-corrects the transfer time prediction errors dynamically.To design and develop our model, we studied real-world datasets consisting of over 100 million transfer records collected from platforms such as Open Science Grid (OSG), Large Hadron Collider Optical Private Network (LHCOPN), Worldwide LHC Grid (WLCG), as well as the RENs of Internet2 and ESNet. We integrate our model into well-known neural network models and regressors and present evaluation results.

Increasingly, academic campus networks support large-scale data transfer workflows for data-intensive science. These data transfers rely on high-performance, scalable, and reliable protocols for moving large amounts of data over a high-bandwidth, high-latency network. GridFTP is a widely used protocol for wide area network (WAN) data movement. However, as the GridFTP protocol does not share connection information with the network-layer, network operators have reduced flexibility, particularly in identifying/managing flows across the network. We address this problem by deploying a production “application-aware” software defined network (SDN) for managing GridFTP transfers for data-intensive science workflows. We first propose a novel application-aware architecture called SNAG (SDN-managed Network Architecture for GridFTP transfers). SNAG combinesapplication-layer and network-layer collaboration(termed “application-awareness”) with SDN-enabled network management to classify, monitor and to manage network resources actively. Until now, our SNAG deployment has successfully classified over1.5 BillionGridFTP connections at the Holland Computing Center (HCC), University of Nebraska-Lincoln (UNL). Next, we develop an application-aware SDN system to provide differentiated network services for distributed computing workflows. At HCC, we also demonstrate how our system ensures the quality of service (QoS) for high-throughput workflows such as Compact Muon Solenoid (CMS) and Laser Interferometer Gravitational-Wave Observatory (LIGO). Further, we also demonstrate how application-aware SDN can be exploited to createpolicy-drivenapproaches to achieve accurate resource accounting for each workflow. We present strategies for implementing differentiated network services and discuss their capacity improvement benefits. Lastly, we provide some guidelines and recommendations for developing application-aware SDN architectures for general-purpose applications.

Network availability is an important requirement in an optical telecommunication network. To overcome a disconnection, preparing a backup path before failure happens is required to reroute the affected traffic. This prevents any failure causing a significant amount of data loss or interruption in Wavelength Division Multiplexing (WDM) networks. Resource Delayed Release (RDR) is a new idea to improve the Service Provisioning Time (SPT) by adding the concept of idle optical channels. In earlier work [1] we proved that the delay in the removal of an idle optical channel helps the next service request to be carried immediately. In this paper, we address the problem of single link failure in WDM networks by comparing different protection methods when applied to the RDR strategy. We investigate and compare three algorithms that are mostly intended for maximization of the amount of remaining bandwidth over a damaged network. They are: Path Protection (PP), Link Protection (LP), and Partial Path Protection (PPP) [2]. The objective of this work is to apply the above protection methods on the RDR strategy to determine which method provides the best network performance in terms of Bandwidth Blocking Probability (BBP), Blocking Probability (BP), Service Provisioning Time (SPT), and recovery time (RT). Our simulation results show high network efficiency when using the RDR strategy with the PPP method for uniform traffic distribution. The highest BBP is when we do not apply any protection on RDR. When PPP is utilized there is a reduction of 58% in BBP, of 64% in BP, and of 40% in SPT. Additionally RDR with PPP results in the lowest RT measured.

In this paper, we propose ERGO (edge architecture for Ag-IoT), an edge-computing architecture for infrastructureless smart agriculture environments. We also develop Ag-IoT application APIs and the associated microservice infrastructure. Our implementation and evaluations show that ERGO can operate independently of cloud-backed assistance, is highly scalable, modular, and affords composability benefits to Ag-IoT systems. We also demonstrate that ERGO outperforms traditional infrastructure in response latencies and transactional throughput, on average, by over 54% and 77%, respectively.

The Interplanetary Network (IPN) or the Interplanetary Internet is a network composed of interconnected space objects, which are in turn connected to mission control stations on the surface of Earth. The IPN is our only portal to the deep space, and yet it has been relatively sparse, until recently. With the ongoing and the planned missions to the outer space, the Delay Tolerant Networking (DTN) based network infrastructure will require more scalable routing and scheduling algorithms. In this paper, we propose the first Mixed Integer Linear Programming (MILP) model for message routing and scheduling in the IPN using Multi-Attribute Decision Making (MADM) principles. Based on this model, we propose a novel MADM-based algorithm called Multi-Attribute Routing and Scheduling (MARS) algorithm. This algorithm uses a sliding window of size n to schedule the first n messages in the buffer based on multiple attributes. After finding the optimal schedule for these messages (in terms of delivery rate), they are routed using our proposed Dijkstra-based routing algorithm. We use an existing MADM technique, PROMETHEE II, and consider the four main attributes of a message: size, priority, time to live (TTL), and time in buffer (TiB). Finally, we run multiple simulation experiments in order to test the performance of the proposed MARS and show that MADM coupled with scheduling and routing in IPN delivers at least three times more messages than a previously proposed technique, the Contact Graph Routing (CGR), while significantly reducing the average end-to-end delay and overhead.

In this paper, we propose an application-aware intelligent load balancing system for high-throughput, distributed computing, and data-intensive science workflows. We leverage emerging deep learning techniques for time-series modeling to develop an application-aware predictive analytics system for accurately forecasting GridFTP connection loads. Our solution integrates with a major U.S. CMS Tier-2 site; we use a real dataset representing 670 million GridFTP transfer connections measured over 18 months to drive our predictive analytics solution. First, we perform extensive analysis on this dataset and use the connection loads as an example to study the temporal dependencies between various user-roles and workflow memberships. We use the analysis to motivate the design of a gated recurrent unit (GRU) based deep recurrent neural network (RNN) for modeling long-term temporal dependencies and predicting connection loads. We develop a novel application-aware, predictive and intelligent load balancer, APRIL, that effectively integrates application metadata and load forecast information to maximize server utilization. We conduct extensive experiments to evaluate the performance of our deep RNN predictive analytics system and compare it with other approaches such as ARIMA and multi-layer perceptron (MLP) predictors. The results show that our forecasting model, depending on the user-role, performs between 5.88%-92.6% better than the alternatives. We also demonstrate the effectiveness of APRIL by comparing it with the load balancing capabilities of an existing production Linux Virtual Server (LVS) cluster. Our approach improves server utilization, on an average, between 0.5 to 11 times, when compared with its LVS counterpart.

The IT infrastructure of large organizations consists of devices and software services purchased from multiple vendors. The problem of measuring the quality of service (QoS) of each of these vendor devices (and services) is challenging since the vendors may tamper with the measurements for monetary benefits or saving debugging efforts. Existing solutions for QoS measurement in trusted environments cannot be extended for this problem since the vendors can easily circumvent them. Solutions borrowed from other areas such as client-server QoS measurement do not help either since they incur unreasonable storage and network overheads, or require extensive modifications to the packet headers. In this paper, we propose the Measuring Tape scheme, comprised of (1) a novel data structure called evidence Bloom filter (e-BF) that can be deployed at the vendor devices (and services), and (2) unique querying techniques, which can be used by the administrator to query the e-BF to measure QoS. While e-BF uses storage and computational resources judiciously, the querying techniques ensure resilience to adversarial behavior. We evaluate our solution based on a few real-world and synthetic traces and with different adversaries. Our results highlight the trade-off between resources (i.e., storage and computation) and the accuracy of QoS predictions, as well as its implications on security. We also present an analytical model of e-BF that establishes the relationship between storage, prediction accuracy, and security. Further, we present security arguments to illustrate how our solution thwarts adversarial attempts to tamper QoS.

Humans' deep space exploration missions have attracted great interest in the past decade. The Interplanetary Network (IPN), hence, has to undergo many structural changes, as the traffic loads and types will drastically increase. In this paper, we propose N-Look Ahead Routing and Scheduling (N-LARS), a novel scheduling and routing technique for DTN-based IPNs with these new challenges. Our N-LARS model for Delay Tolerant Networking (DTN)-based IPNs provides scheduling of bundles (also called requests or messages) and efficient routing across the overall network. We develop a mixed integer linear programming (MILP) formulation for N-LARS problem and solve it using CPLEX. We further derive a heuristic that scales better than the MILP for large networks. We run experiments on networks mimicking the proposed Mars project by the European Space Agency. Finally, we compare the performance of the network using our scheduling model to its performance using the usual routing technique such as the Contact Graph Routing (CGR). Our simulation results show that the overall performance of the network using N-LARS for bundle scheduling and routing is four times better than CGR, in terms of delivered bundles, and 13.8% closer to the sub- optimal schedule generated by the CPLEX solver.

As the deployment of software-defined networks increases, so does the manageability of local and wide area networks. Designing intelligent solutions that respond to traffic changes automatically will soon become a mandatory requirement in production networks. In this paper, we focus on designing an intelligent control plane for the MobilityFirst Future Internet architecture. This architecture proposes novel mechanisms to replace the Internet Protocol to better support content delivery and mobility, such as hop-by-hop transfer, storage-aware routing and separation of identifiers and network addresses. In earlier work, we have argued that these mechanisms can be bypassed for certain data flows. Indeed, when there is no mobility involved, it is more convenient to implement cut-through switching at lower layers to bypass the routing mechanisms. In this paper, we propose an inter-domain framework capable of cut-through switching in MobilityFirst. The proposed framework is capable of adding and removing flows from tunnels automatically. It is also capable of creating inter-domain tunnels based on flow behavior and inter-domain latency. Our implementation experiments show that the control plane delay can be reduced by 75% when using inter-domain tunnels. Furthermore, the results also show how our framework needs fewer messages than current protocols such as label distribution protocol to setup intra-domain and inter-domain tunnels.

Named Data Networking (NDN) is one of the promising future internet architectures, which focuses on the data rather than its location (IP/host-based system). NDN has several characteristics which facilitate addressing and routing the data: fail-over, in-network caching and load balancing. This makes it useful in areas such as managing scientific data. The CMS experiment on the Large Hadron Collider (LHC) has a data access problem amenable to content-centric networking. CERN Virtual Machine File System (CVMFS) is used by High Energy Physics (HEP) community for worldwide software distribution. CVMFS maintain its data by using content-addressable storage, which makes it suitable for NDN. n this paper, we investigate the possibilities of using a content-centric networking architecture such as NDN on distributing CMS software.

Interplanetary Networks (IPN) are classified among challenged networks and hence are hard to model using static graphs. Furthermore, they do not behave optimally when operated using the standards and techniques of static networks. Delay Tolerant Networking (DTN) is one of the suggested solutions to overcome these networks' challenges. The more widely used implementation of DTN uses Contact Graph Routing (CGR) to find the path from source to destination. In this paper, we identify the shortcoming of CGR that results from overlooking the future contacts and propose the Earliest Arrival Optimal Delivery Ratio (EAODR) Routing that examines all the paths both with the desired earliest departure time and in the future in order to choose the earliest arrival path from a given node. EAODR finds the route that delivers the exchanged message (a.k.a. bundle) at most at the same time as CGR's route. We propose a Modified Temporal Graph (MTG) model that provides a near-real-time representation of the deterministic dynamic networks. We base EAODR routing algorithm on the MTG model. Our results show that we can reduce the delay by 12.9% compared to CGR when we apply our algorithm to over 50 combinations of bundle sizes and transmission times.

Future Internet projects such as MobilityFirst and Named Data Networking have proposed novel mechanisms to replace the Internet Protocol to better support content delivery and mobility. However, the problem of efficient data transfer across the network core has not been adequately investigated. We tackle the challenge of inter-domain cut-through switching using software-defined networking (SDN). First, we propose and solve an optimization problem that minimizes the total transfer time using inter-domain tunnels. Second, we propose an SDN-based routing framework for the MobilityFirst architecture capable of dynamically creating such tunnels. The main novelty of this framework is to name tunnels as network objects to simplify how tunnels are created and maintained. To validate our framework, we implement on the GENI (Global Environment for Network Innovations) testbed a prototype for the MobilityFirst architecture. Our experiments with the optimization problem show that the inter-domain latency between controllers plays a key role on how tunnels are setup. Furthermore, our implementation experiments show that the control plane delay can be reduced by 75% when using inter-domain tunnels. Finally, we show how our framework needs fewer messages than current protocols such as label distribution protocol (LDP) to setup intra-domain and inter-domain tunnels.

As the popularity of software-defined networks (SDN) and OpenFlow increases, policy-driven network management has received more attention. Manual configuration of multiple devices is being replaced by an automated approach where a software-based, network-aware controller handles the configuration of all network devices. Software applications running on top of the network controller provide an abstraction of the topology and facilitate the task of operating the network. We propose OpenSec, an OpenFlow-based security framework that allows a network security operator to create and implement security policies written in human-readable language. Using OpenSec, the user can describe a flow in terms of OpenFlow matching fields, define which security services must be applied to that flow (deep packet inspection, intrusion detection, spam detection, etc.) and specify security levels that define how OpenSec reacts if malicious traffic is detected. In this paper, we first provide a more detailed explanation of how OpenSec converts security policies into a series of OpenFlow messages needed to implement such a policy. Second, we describe how the framework automatically reacts to security alerts as specified by the policies. Third, we perform additional experiments on the GENI testbed to evaluate the scalability of the proposed framework using existing datasets of campus networks. Our results show that up to 95% of attacks in an existing data set can be detected and 99% of malicious source nodes can be blocked automatically. Furthermore, we show that our policy specification language is simpler while offering fast translation times compared to existing solutions.

Interplanetary Internet or Interplanetary Networking is envisaged as a space network which interconnects spacecrafts, satellites, rovers and orbiters of different planets and comets for efficient exchange of scientific data such as telemetry and images. In this paper, we implement a layout of the Interplanetary Internet (IPN) with the Interplanetary Overlay Network (ION) software module that uses Contact Graph Routing (CGR). The experiments are then implemented on the Global Environment for Network Innovations (GENI) testbed. Along with realistic contact plans (CP) of the nodes, this network implementation was used to run experiments testing the performance of Delay Tolerant Networking (DTN) with and without cross links between Mars orbiters. The experiments showed that in an Earth-Mars communication network using two Mars orbiters, allowing cross links between the orbiters results in increasing the amount of data transferred by roughly 9.2%. Data sent from Mars Rover to the Earth stations also increases by 35.7% when a third satellite (Mars Express) was added to the network without cross links. Finally, when cross links are allowed across all satellites orbiting Mars and serving as relay nodes between the Earth stations and Mars rover, the communication was enhanced by almost 46%. We conclude that by adding cross links, the performance of the network is enhanced for a better transmission of data from Mars to the Earth, which is very pertinent for the scalability of the network.

As the popularity of software defined networks (SDN) and OpenFlow increases, policy-driven network management has received more attention. Manual configuration of multiple devices is being replaced by an automated approach where a software-based, network-aware controller handles the configuration of all network devices. Software applications running on top of the network controller provide an abstraction of the topology and facilitate the task of operating the network. We propose OpenSec, an OpenFlow-based security framework that allows a network security operator to create and implement security policies written in human-readable language. Using OpenSec, the user can describe a flow in terms of OpenFlow matching fields, define which security services must be applied to that flow (deep packet inspection, intrusion detection, spam detection, etc) and specify security levels that define how OpenSec reacts if malicious traffic is detected. We implement OpenSec in the GENI testbed to evaluate the flexibility, accuracy and scalability of the framework. The experimental setup includes deep packet inspection, intrusion detection and network quarantining to secure a web server from network scanners. We achieve a constant delay when reacting to security alerts and a detection rate of 98%.

To address reliability challenges due to failures and planned outages, Internet Service Providers (ISPs) typically use two backbone routers (BRs) at each central office. Access routers (ARs) are connected to these BRs in a dual-homed configuration. To provide reliability through node and path diversity, redundant backbone routers and redundant transport equipment to interconnect them are deployed. However, deploying such redundant resources increases the overall cost of the network. Hence, to avoid such redundant resources, a fundamental redesign of the backbone network leveraging the capabilities of an agile optical transport network is highly desired. In this paper, we propose a fundamental redesign of IP backbones. Our alternative design uses only a single router at each office. To survive failures or outages of a single local BR, we leverage the agile optical transport layer to carry traffic to remote BRs. Optimal mapping of local ARs to remote BRs is determined by solving an Integer Linear Program (ILP). We describe how our proposed design can be realized using current optical transport technology. We evaluate network designs for cost and performability, the latter being a metric combining performance and availability. We show significant reduction in cost for approximately the same level of reliability as current designs.

Future space exploration demands a space network that will be able to connect spacecrafts with one another and in turn with Earth's terrestrial Internet and hence efficiently transfer data back and forth. The feasibility of this technology would enable everyone to directly access telemetric data from distant planets and satellites. The concept of an Interplanetary Internet (IPN) is only in its incubation stage and considerable amount of common standards and research is required before widespread deployment can occur to make IPN feasible. Delay is an important factor in space communication and its nature is completely different from terrestrial delay environments. Moreover, space deployments and testing in space environments are very costly and time consuming. We propose a design of the IPN and implement it with the Interplanetary Overlay Network (ION) software module on physical nodes on the terrestrial ORBIT testbed. Two space network scenarios are designed and experimentally evaluated to verify the correctness of the network implementation. We also focus on the study of bundle transmission delay and separately evaluate the effect of bundle size and number of bundles. The experimental evaluation provides insights into the factors which caused delay in bundle transmission such as custody refusal, expiration of bundle lifetime and congestion.

The need for large-scale computing, storage and network capabilities by the scientific or business community has resulted in the development of cloud networks. Grid/Clouds users are provided with IT infrastructure (servers, storage, networks, etc.) as services called Infrastructure as a Service (IaaS). In this case, an efficient resource scheduling mechanism for allocating the infrastructure resources across the network will improve the resource efficiency in the cloud significantly. In this paper, we investigate the budget optimization of joint resources (storage, processor and network) allocation for IaaS model in distributed Grid/Clouds from the consumer's perspective. We develop a Mixed Integer Linear Programming (MILP) formulation along with a new resource model and propose a Best-Fit heuristic algorithm with different job scheduling policies. Our goal is to minimize the expenditure for each user to obtain enough resources to execute their submitted jobs, while enabling the Grid/Cloud provider to accept as many job requests from the users as possible. Both MILP and heuristic are tested on a 10- node topology and the Google Datacenter topology. The results show that the heuristic method can achieve approximate optimal solutions to MILP; it can reduce the user expense by at least 30%. In addition, Best-Fit algorithm with SSF (simple job structure first) job scheduling policy has the lowest blocking rate, which is 5%~25% less than other job scheduling policies.

Connection requests for data-intensive applications often require specific start time and end time/duration when they are submitted. With the additional time domain information, cost efficient connections can be established. In this paper, we propose two capital expenditure (CapEx) optimized approaches: Multi-Layer (ML) approach and Transponder/Regenerator Reuse (TRR) approach. Integer Linear Programming (ILP) is used to formulate the routing, wavelength assignment and regenerator/multiplexer placement problem in a complex multi-layer optical network and provide lower bounds for the optimized CapEx value. Due to the time and space complexity of ILP, we also propose a greedy algorithm and a tabu-search algorithm to solve the same problem in a less time and resource consuming way. Finally, we compare the results in terms of computing time and optimized CapEx value across the ILP, greedy heuristic and tabu search heuristic methods with the ML approach for the Internet2 topology and a 6-node ring topology. The performance of all three methods with TRR approach is also tested with the same input traffic. The results show 30% to 40% less CapEx when comparing ML with TRR. Further, our tabu search heuristic can achieve near optimal results compared to ILP.

The 19th IEEE LANMAN 2013 Workshop on Local and Metropolitan Area Networks has a long tradition as a leading forum for showcasing the latest technical advances in networking in the local and metropolitan areas. This year's LANMAN features the theme of seamless services, particularly within the context of recent explosion of cloud, mobile, heterogeneous, and wireless systems.

Most of the commercial peer-to-peer (P2P) video streaming deployments support hundreds of channels and are referred to as multichannel systems. Recent research studies have proposed specific protocols to improve the streaming quality for all channels by enabling cross-channel cooperation among multiple channels. In this paper, we focus on the following fundamental problems in designing cooperating multichannel systems: 1) what are the general characteristics of existing and potential designs? and 2) under what circumstances should a particular design be used to achieve the desired streaming quality with the lowest implementation complexity? To answer the first question, we propose simple models based on linear programming and network-flow graphs for three general designs, namely Naive Bandwidth allocation Approach (NBA), Passive Channel-aware bandwidth allocation Approach (PCA), and Active Channel-aware bandwidth allocation Approach (ACA), which provide insight into understanding the key characteristics of cross-channel resource sharing. For the second question, we first develop closed-form results for two-channel systems. Then, we use extensive numerical simulations to compare the three designs for various peer population distributions, upload bandwidth distributions, and channel structures. Our analytical and simulation results show that: 1) the NBA design can rarely achieve the desired streaming quality in general cases; 2) the PCA design can achieve the same performance as the ACA design in general cases; and 3) the ACA design should be used for special applications.

It is challenging to provide delay-bounded service in a large-scale P2P live streaming system since a P2P streaming system is not scalable from the perspective of playback delay. However, certain peers called subscribers are more sensitive to playback delay than other peers, and the violation of the delay bound dramatically affects their satisfaction. In this paper, we study subscriber bounded delay (SBD) problem, which aims to provide bounded delay service to subscribers and best-effort delay service to ordinary peers in a large-scale single channel P2P live streaming system. We formulate the SBD as a decision problem and prove that it is NP-Complete. Then we propose a decentralized heuristic called the high fanout promotion (HFP) algorithm, which helps the system to serve the maximum number of subscribers with delay-bounded service, and to provide best-effort delay service to remaining subscribers and ordinary peers. We evaluate its performance using simulation experiments and compare our approach with the naive greedy algorithm and the general delay minimization approaches in the literature. Our extensive packet-level simulations show that our distributed solution can serve more subscribers with bounded delay video service compared to the other two methods (17%-50% in our simulations). Our distributed algorithm works well in both homogeneous and heterogeneous environments, and it converges very fast.

Current core networks are composed of high-end routers which are connected by high-speed fibers. These optical connections are commonly overprovisioned and in low utilization. Many of them are combined together to form bundle links or composite links and the component links are referred to as sublinks. These physical sublinks could be SONET connections, Ethernet circuits, wavelengths on a fiber, etc. And they could be shut down or brought up independently. Selectively shutting down sublinks during low traffic periods could save a large amount of energy while keeping the network topology unchanged. Based on this concept, we propose a local heuristical threshold- based method to explore the potential energy- savings in the backbone network by adjusting the number of active sublinks in bundle links. An experiment based on an Internet2 derived synthetic network was conducted to verify the performance of our method and the results show that 86% of energy consumed on ports of core routers could be saved when setting 90.0% as the link utilization threshold. The experiment also shows that setting 90.0% as threshold is safe enough to avoid data loss during extreme traffic increases in this case. Compared to previous proposed ILP (Integer linear programming) based global heuristic algorithms, our local heuristic algorithm can achieve energy-savings close to the optimum and greatly reduce the response time and the risk of data loss.

Nowadays, millions of Internet users watch and upload a large number of videos on User Generated Content (UGC) sites (e.g., Youtube) everyday. Moreover, online videos about hot events, such as breaking news and Olympic games, attract lots of users. In this paper, we study the characteristics of hot-event videos by collecting video traces of the largest UGC site in China for 28 days. We first empirically study statistical properties of such videos and find that hot-event videos contribute a large number of views, even though the total number of hot-event videos is relatively small. In addition, there exist extremely active uploaders and top 10% active uploaders upload over 60% videos. The video popularity demonstrates high skewness, where top 5% the most popular videos contribute over 80% views. Finally, we analyze the popularity evolution of hot-event videos using the consecutive 28-day video traces. The popularity of the studied videos decays very fast and most of these videos remain popular for only a week. Our findings reflect the most recent developments of UGC sites, which provide technical and commercial insights for engineers and UGC site owners.

Digital video recorder (DVR) style and non-prerecording (NPR) style are two possible implementations for P2P-based time-shifted streaming, but existing P2P streaming solutions are not suitable to implement the NPR method. Since peers can view any arbitrary video segments which have been broadcasted, they might encounter severe video quality problems and the server bandwidth consumption can become high. In this paper, we focus on minimizing the server bandwidth consumption to maintain smooth streaming service in NPR-style P2P-based time-shifted streaming. To reduce the server cost, peers prefetch segments which are not required for their current viewing. Hence even if they are viewing different parts of the video, they can exchange segments with one another. However, segment prefetching competes for bandwidth with ordinary segment fetching, and it might bring negative impact. A good prefetching solution should not affect peers' viewing experience. We formulate the problem of finding a prefetching solution as an optimization problem, with the objective to minimize the server bandwidth consumption. Then we propose a heuristic algorithm by decomposing the global optimization problem into a set of smaller problems. Each peer runs this algorithm to determine which segments to prefetch and how to serve other peers. Simulation experiments demonstrate that our design provides P2P-based time-shifted streaming at low server bandwidth consumption.

To accommodate the increasing demands for bandwidth, Internet Service Providers (ISPs) have deployed higher-speed links and reconfigurable optical add drop multiplexers (ROADMs) in their backbone networks. To address the reliability challenges due to failures and planned outages, ISPs typically use two backbone routers at each central office in a dual-home configuration. Thus at the IP layer, redundant backbone routers as well as redundant transport equipment to interconnect them are deployed to provide reliability through node and path diversity. However, adding such redundant resources increases the overall cost of the network. Hence, a fundamental redesign of the backbone network which avoids such redundant resources by leveraging the capabilities of an intelligent optical transport network is a highly desirable objective. It is clear that such a redesign must lower costs without compromising on the reliability achieved by today's backbone networks. Modeling the costs and reliability of the network at all layers is an important step in achieving this objective. In this paper, we undertake an in-depth investigation of the cost and reliability considerations involved in designing the next-generation backbone network. Our work includes a detailed analysis of the operation, cost and reliability of the network at the IP layer and the multiple layers below it. We discuss alternative backbone network designs which use only a single router at each central office but use the optical transport layer to carry traffic to routers at other offices in order to survive failures or outages of the single local router. We discuss trade-offs involved in using these designs.

Many scientific and Grid applications require high-speed circuits of guaranteed bandwidth for scheduled transfers. Offline optimization of dynamic scheduled bandwidth demands is an efficient way of finding the near-optimal solution to the bandwidth scheduling problem. In this paper, we propose a continuous and parallel optimization method to address the dynamic and deterministic bandwidth scheduling problem in next generation wavelength-division multiplexing (WDM) networks. In this method a greedy algorithm and genetic algorithm are run in parallel in separate threads and both of them take the Dynamic Scheduled Bandwidth Demand (D-SBD) as their input. The user gets his response only from the greedy algorithm and hence he will get a deterministic answer in a short amount of time. The genetic algorithm takes as one of its inputs the output of the greedy algorithm and does the optimization of the D-SBDs with minimizing blocking probability as its fitness function. The greedy algorithm copies the optimized reservation database of the genetic algorithm at regular intervals. The user submitting a D-SBD request is unaware of the optimization done by the genetic algorithm. This method is evaluated using both trace-driven simulation of real network traffic from the DOE ESnet network and stochastic traffic in ESnet network topology and a 24 node network topology. We also compare our approach with an earlier proposed method called re-optimization at blocking. Adding the genetic algorithm improves the performance of the network (in terms of blocking probability) compared to using only the greedy approach or the re-optimization at blocking method.

Advanced distributed applications in engineering, scientific and business domains that are highly data-intensive demand high-performance computing platforms. Grid networks based on optical technology provide a promising approach to create efficient infrastructure to support such applications. These networks, termed in general as Lambda Grid networks, are based on optical circuit switching and employ wavelength division multiplexing and optical lightpaths. In this paper, we propose an approach based on Tabu Search heuristic for joint scheduling of computing, network and storage resources in a Lambda Grid network. The objectives are to minimize cost by efficient usage of resources and to minimize total completion time of job execution. The results are compared to a Greedy approach. Simulation results from both the methods show that the Tabu search heuristic performed better than the greedy approach in optimizing both the cost and completion time objectives.

Peer-to-peer (P2P) technology has become an attractive approach for enabling large-scale video streaming applications, but the factor of users' subjective preferences is usually ignored in such networks. As users have different demands on video quality, we have proposed several schemes, to address the design challenge of providing all users uninterrupted video with their desired qualities in case their demands change dynamically. However, there is still a lack of theoretical analysis of how good we can achieve, and what guidelines we should follow when designing schemes in case of demand heterogeneity. To shed more light on demand heterogeneity problem, we model the problem as a resource demand and supply problem. We propose an optimization method to improve bandwidth efficiency through efficient bandwidth allocation. We develop a tiered overlay and a price-rated mechanism to implement cooperation among peers, and present a framework to address the challenge via efficient bandwidth allocation and group cooperation. Through complementary simulations, we evaluate the effectiveness of the proposed framework, and show that it effectively helps existing solutions, such as the Partial Participation Scheme (PPS), achieve better performance.

Most of the commercial P2P video streaming deployments support hundreds of channels and are referred to as multichannel systems. Measurement studies show that bandwidth resources of different channels are highly unbalanced and thus recent research studies have proposed various protocols to improve the streaming qualities for all channels by enabling cross-channel cooperation among multiple channels. However, there is no general framework for comparing existing and potential designs for multi-channel P2P systems. The goal of this paper is to establish tractable models for answering the fundamental question in multi-channel system designs: Under what circumstances, should a particular design be used to achieve the desired streaming quality with the lowest implementation complexity? To achieve this goal, we first classify existing and potential designs into three categories, namely Naive Bandwidth allocation Approach (NBA), Passive Channel-aware bandwidth allocation Approach (PCA) and Active Channel-aware bandwidth allocation Approach (ACA). Then, we define the bandwidth satisfaction ratio as a performance metric to develop linear programming models for the three designs. The proposed models are independent of implementations and can be efficiently solved due to the linear property, which provides a way of numerically exploring the design space of multi-channel systems and developing closed-form solutions for special systems.

The success of commercial Peer-to-Peer (P2P) video streaming systems has triggered interest in exploiting end users' bandwidth to reduce the operating costs of IPTV and Content Distribution Networks (CDN) and to improve the user-perceived service quality. Traditionally, users watching different channels are organized into separate overlays, where there is no cooperation among different channels. However, based on measurement studies, cross-channel cooperation is found to be desirable due to the bandwidth imbalance among different channels. In this paper, we focus on studying the characteristics of existing and potential designs to help system designers choose proper cross-channel cooperation strategies considering efficiency and implementation complexity. Specifically, we propose simple models based on network flow graphs for three general designs, namely Naive Bandwidth allocation Approach (NBA), Passive Channel-aware bandwidth allocation Approach (PCA) and Active Channel-aware bandwidth allocation Approach (ACA) respectively, which capture the key characteristics of different designs. We develop closed-form results for two-channel systems. Then, we use extensive numerical simulations to compare the three designs for various peer population distributions, upload bandwidth distributions and channel structures. Our analytical and simulation results show that: 1) Though the NBA design can be implemented with low complexity, it cannot efficiently use user's bandwidth in general cases; 2) the PCA design can achieve the same bandwidth utilization efficiency as the ACA design in general cases; and 3) the ACA design should be used for special applications and systems in which a user is restricted to watch only one channel at a time.

In this paper, we describe the design, implementation and deployment details of a two-tier real-time environmental monitoring network in Nebraska. Our state-wide sensor network infrastructure uses typical Wireless Sensor Network (WSN) structure at tier-two to conduct dynamic sensing tasks with high resolution and flexibility. The satellite communication technology is used at tier-one to provide reliable and low-cost long-haul connectivity between each local WSN and the central base station. By the end of 2009, the entire tier-one infrastructure has been designed and deployed to provide state-wide wireless connectivity for 54 monitoring sites equipped with 1-4 water level transducers. A data and network management framework has also been developed to enable the remote network retasking and network performance analysis from a central base station. The network web portal offers integrated real-time and historical groundwater data to worldwide users. The deployed infrastructure will serve as the prototype network to expedite the commercial adoption of large-scale WSN design for long-term environmental monitoring applications.

Anycasting has been proposed recently as an efficient communication method for asynchronous duty-cycled wireless sensor networks. However, the interdependencies between end-to-end communication cost and the anycasting design parameters have not been systematically studied. In this paper, a statistical end-to-end cost model is presented to capture the end-to-end latency and energy consumption of anycasting operation under a realistic wireless channel model. By exploring the relationship between the end-to-end cost efficiency and the forwarding decision dependent anycasting design parameters, two anycasting forwarding metrics are proposed for fully distributed forwarding decision. By exploring the relationship among the preamble length, the size of the forwarding set and the achievable end-to-end cost efficiency, a series of preamble length control guidelines are proposed for low and extremely low duty-cycled WSNs. According to our analytical results and simulation validation, the proposed forwarding metrics help reduce the end-to-end latency and energy consumption by about 55% for anycasting with moderate preamble length, compared with the existing heuristic forwarding metrics. The proposed preamble length control guidelines help reduce, by more than half, the end-to-end energy and latency costs in low and extremely-low duty-cycled WSNs.

Abstract The goal of key management is to establish the required keys between sensor nodes which exchange data. A key management protocol includes two aspects: key distribution and key revocation. Key distribution has been extensively studied in the context of sensor networks. However, key revocation has received relatively little attention. In this paper, we first review and summarize the current key revocation schemes for sensor networks. Then, we present an efficient scheme, KeyRev, for removing compromised sensor nodes from a wireless sensor network (WSN). Unlike most proposed key revocation schemes focusing on removing the compromised keys on the sensor nodes, the KeyRev scheme uses key update techniques to obsolesce the keys owned by the compromised sensor nodes and thus remove the nodes from the network. We analyze the security of the KeyRev scheme and compare its performance against another centralized key revocation scheme and a distributed key revocation scheme. Our analyses show that the KeyRev scheme is secure in spite of not removing the pre‐distributed key materials at compromised sensor nodes. Simulation results also indicate that the KeyRev scheme is scalable and performs very well compared with other key revocation schemes in WSNs. Copyright © 2008 John Wiley & Sons, Ltd.

Data-intensive grid applications require huge data transfers between grid computing nodes. These computing nodes, where computing jobs are executed, are usually geographically separated. A grid network that employs optical wavelength division multiplexing (WDM) technology and optical switches to interconnect computing resources with dynamically provisioned multigigabit rate bandwidth lightpath is called a lambda grid network. A computing task may be executed on any one of several computing nodes which possesses the necessary resources. In order to reflect the reality in job scheduling, allocation of network resources for data transfer should be taken into consideration. However, few scheduling methods consider the communication contention on lambda grids. In this paper, we investigate the joint scheduling problem while considering both optical network and computing resources in a lambda grid network. The objective of our work is to maximize the total number of jobs that can be scheduled in a lambda grid network. An adaptive routing algorithm is proposed and implemented for accomplishing the communication tasks for every job submitted in the network. Four heuristics (FIFO, ESTF, LJF, RS) are implemented for job scheduling of the computational tasks. Simulation results prove the feasibility and efficiency of the proposed solution.

Due to their widespread popularity, peer-to-peer (P2P) live streaming systems have become a great challenge for Internet service providers (ISPs) as they consume huge amount of Internet bandwidth. By observing that different users may watch a channel with different window sizes, we propose a cooperative scheme called partial participation scheme (PPS) in which different peers request a video stream at different rates based on their window sizes, and a subset of peers viewing the video stream using a small window work as helpers to forward extra data to help other peers using a large window. By reducing streaming rate received by small-window peers, the total amount of consumed bandwidth decreases without sacrificing users' satisfaction. PPS includes peer cooperative bandwidth allocation algorithms and neighbor maintenance mechanisms to achieve short resizing delay when a peer changes its window between different sizes. We evaluate the performance of PPS via a comprehensive set of metrics generated from extensive simulations. Our simulation results show that PPS greatly reduces the bandwidth consumption, achieves short resizing delay, and maintains high and stable streaming quality.

Most of the literature on peer-to-peer (P2P) live streaming focuses on how to provide best-effort streaming quality by efficiently using the system bandwidth; however, there is no guarantee about the provided streaming quality. This paper considers how to provide statistically guaranteed streaming quality to a P2P live streaming system. We study a class of admission control algorithms which statistically guarantee that a P2P live streaming system has sufficient overall bandwidth. Our results show that there is a tradeoff between the user blocking rate and user-behavior insensitivity (i.e., whether the system performance is insensitive to the fine statistics of user behaviors). We also find that the system performance is more sensitive to the distribution change of user inter-arrival times than to that of user lifetimes.

Multi-view peer-to-peer (P2P) live streaming systems have recently emerged, where a user can simultaneously watch multiple channels. Previous work on multi-view P2P streaming solves the fundamental inter-channel bandwidth competition problem at the individual peer level, and thus can be used with very limited types of streaming protocols. In this paper, we propose a new protocol for multi-view P2P streaming, called divide-and-conquer (DAC), which efficiently solves the inter-channel bandwidth competition problem using a divide-and conquer strategy at the channel level, and thus is flexible to work with various streaming protocols. This makes DAC more suitable for upgrading current single-view P2P live streaming systems to multi-view P2P live streaming systems. Our extensive packetlevel simulations show that DAC is efficient in allocating the overall system bandwidth among competing channels, is flexible in working with various streaming protocols, and is scalable in supporting a large number of users and channels.

Data-driven (or swarming based) streaming is one of the popular ways to distribute live multimedia streaming traffic over peer-to-peer (P2P) networks. The efficiency and user satisfaction highly depend on the constructed overlays. The common neighbor selection algorithms in existing overlay construction schemes usually randomly select a fixed number of neighbors which satisfy the selection requirements, such as end-to-end delay or a peerpsilas sojourn time. However, this fixed random neighbor-selection algorithm (FRNS) neglects the peerspsila upload bandwidth heterogeneity and therefore, the upload bandwidth cannot be efficiently used. In this paper, we propose a variable random neighbor-selection (VRNS) scheme to alleviate the problems due to bandwidth heterogeneity, and in which the number of neighbors with different upload bandwidths is dynamically determined by the statistical bandwidth information of the system. Our proposed scheme is shown to outperform FRNS based upon a large volume of carefully designed simulations.

Key management is a core mechanism to ensure the security of applications and network services in wireless sensor networks. It includes two aspects: key distribution and key revocation. Many key management protocols have been specifically designed for wireless sensor networks. However, most of the key management protocols focus on the establishment of the required keys or the removal of the compromised keys. The design of these key management protocols does not consider the support of higher level security applications. When the applications are integrated later in sensor networks, new mechanisms must be designed. In this paper, we propose a security framework, uKeying, for wireless sensor networks. This framework can be easily extended to support many security applications. It includes three components: a security mechanism to provide secrecy for communications in sensor networks, an efficient session key distribution scheme, and a centralized key revocation scheme. The proposed framework does not depend on a specific key distribution scheme and can be used to support many security applications, such as secure group communications. Our analysis shows that the framework is secure, efficient, and extensible. The simulation and results also reveal for the first time that a centralized key revocation scheme can also attain a high efficiency.

Peer-to-peer (P2P) streaming systems, in which individual nodes or peers operated by ordinary Internet users collaborate to serve video streams, have recently aroused considerable interest in both academia and industry. An important problem in P2P streaming systems is how to reduce their consumed bandwidth, which is a major concern of Internet service providers. Our work is motivated by the fact that a user may dynamically change the size of a window displaying a video stream according to his/her personal choice, a scenario we refer to as dynamic window resizing. In this paper, we propose a scheme called the partial forwarding scheme (PFS) based on layered coding, in which users with small windows help in forwarding a part of the enhancement layer. PFS significantly reduces the total consumed bandwidth while still maintaining the desired streaming quality. Our extensive simulation results show that PFS can reduce the total consumed bandwidth by up to 40% while still maintaining satisfactory streaming quality.

Most of the proposed key management protocols for wireless sensor networks (WSNs) in the literature assume that a single base station is used and that the base station is trustworthy. However, there are applications in which multiple base stations are used and the security of the base stations must be considered. This paper investigates a key management protocol in wireless sensor networks which include multiple base stations. We consider the situations in which both the base stations and the sensor nodes can be compromised. The proposed key management protocol, mKeying, includes two schemes, a key distribution scheme, mKeyDist, supporting multiple base stations in the network, and a key revocation scheme, mKeyRev, used to efficiently remove the compromised nodes from the network. Our analyses show that the proposed protocol is efficient and secure against the compromise of the base stations and the sensor nodes.

In this paper, we propose a loss tolerant reliable (LTR) data transport mechanism for dynamic event sensing (LT-RES) in WSNs. In LTRES, a reliable event sensing requirement at the transport layer is dynamically determined by the sink. A distributed source rate adaptation mechanism is designed, incorporating a loss rate based lightweight congestion control mechanism, to regulate the data traffic injected into the network so that the reliability requirement can be satisfied. An equation based fair rate control algorithm is used to improve the fairness among the LTRES flows sharing the congestion path. The performance evaluations show that LTRES can provide LTR data transport service for multiple events with short convergence time, low lost rate and high overall bandwidth utilization.

Motivated by the success of the Picture in Picture feature of the traditional TV, several commercial Peer-to-Peer MultiMedia Streaming (P2PMMS) applications now support the multi-view feature, with which a user can simultaneously watch multiple channels on its screen. This paper considers the peer selection problem in multi-view P2PMMS. This problem has been well studied in the traditional single-view P2PMMS; however, it becomes more complicated in multi-view P2PMMS, mainly due to the fact that a peer watching multiple channels joins multiple corresponding overlays. In this paper, we propose a novel peer selection algorithm, called Channel-Aware Peer Selection (CAPS), where a peer selects its neighboring peers based on the channel subscription of the system, in order to efficiently utilize the bandwidth of all peers in the system, especially those peers watching multiple channels. The results of a large-scale simulation with 10,000 peers and 4 channels shows that CAPS can significantly improve the system performance over the straightforward Random Peer Selection (RPS), which is widely used in single-view P2PMMS networks.

Supporting end-to-end real-time communication is important for wireless sensor networks (WSNs) to acomplish the collaborative sensing tasks with specific timing constraints. However, without considering the unique constraints for WSNs, many existing real-time communication protocols prove to be infeasible for low-cost WSNs. In this paper, we propose a novel real-time communication scheme (RCS) to provide service-differentiated soft real-time guarantees for end-to-end communication in WSNs. We use hop-based geographic grouping to enable location awareness for sensor nodes with extremely low control overhead.We use dynamic forwarding with load-balanced receiver contention to provide a light-weight, yet efficient, routing technique, which can be easily adapted for duty cycle design. We use polling contention period based real-time MAC support to improve the service-differentiation granularity with better bandwidth utilization. The performance evaluation shows that our scheme can achieve low end-to-end latency, high on-time delivery ratio, fine services-differentiation granularity with load-balance for real-time traffic in unsynchronized low-cost WSNs.

Abstract As a result of the growing popularity of wireless networks, in particular mobile ad hoc networks (MANET), security over such networks has become very important. Trust establishment, key management, authentication, and authorization are important areas that need to be thoroughly researched before security in MANETs becomes a reality. This work studies the problem of secure group communications (SGCs) and key management over MANETs. It identifies the key features of any SGC scheme over such networks. AUTH‐CRTDH, an efficient key agreement scheme with authentication capability for SGC over MANETs, is proposed. Compared to the existing schemes, the proposed scheme has many desirable features such as contributory and efficient computation of group key, uniform work load for all members, few rounds of rekeying, efficient support for user dynamics, key agreement without member serialization and defense against the Man‐in‐the‐Middle attack, and the Least Common Multiple (LCM) attack. These properties make the proposed scheme well suited for MANETs. The implementation results show that the proposed scheme is computationally efficient and scales well to a large number of mobile users. Copyright © 2007 John Wiley & Sons, Ltd.

This paper considers the problem of dedicated path-protection in a wavelength-division multiplexing (WDM) mesh network with waveband switching (WBS) functionality under shared risk link group (SRLG) constraints. Two protection schemes are proposed, namely the Protecting-waveBand-At-waveBand-Level-only (PBABL) and the Mixed-Protection-At-waveBand-and-Wavelength-Level (MPABWL). The PBABL protects each working waveband-path by a backup waveband-path. While the MPABWL protects each working waveband-path by either a backup waveband-path or multiple backup lightpaths. The performances of the two protection schemes in terms of gained revenue and cost saving are studied and compared. Integer linear programming (ILP) formulations are presented to solve the problems for each protection scheme. Numerical results of the ILPs and the experimental results of previously proposed heuristics are presented, which show that both heuristics can obtain optimum solutions. According to the results, under heavy load traffic the MPABWL scheme provides solutions with higher revenues than the PBABL scheme does. Under light load traffic, where network resources are sufficient to accommodate all the traffics, the PBABL scheme leads to less switching and transmission costs than the MPABWL scheme does.

Wireless sensor networks (WSNs) use sensors to monitor phenomena such as temperature, humidity, groundwater levels and transmit this information to a base station using wireless channels. WSNs find applications in military, ecological, and health-related areas. A hybrid wireless sensor network includes two networks: an ad hoc wireless network and a wireless sensor network. The nodes in the ad hoc network act as base stations conducting surveillance on the WSN. In this dissertation, we focus on the key management issues in hybrid wireless sensor networks. The key management issues in hybrid wireless sensor networks can be divided into three categories according to which layer they affect: ad hoc network layer, wireless sensor network layer, and integrated cross layer. At the ad hoc network layer, we propose two elliptic curve discrete logarithm problem (ECDLP) based schemes for secure group communication (SGC). Unlike the vast majority of secure group communication protocols using the discrete logarithm problem (DLP) based Diffie-Hellman as the basic key agreement protocol, our solutions use the ECDLP-based Diffie-Hellman protocol. We also extend our research on secure group communication to the wireless sensor network layer. We formally define the grouping and secure group communication problems in WSNs. We further propose and evaluate four centralized group rekeying (CGK) schemes for SGC in WSNs. Our proposed key management protocol at the integrated cross layer, mKeying, includes two schemes, a key distribution scheme, KeyDist, supporting multiple base stations in the network, and a centralized key revocation scheme, KeyRev, for removing compromised sensor nodes from the sensor network. Through these protocols for key distribution, key revocation, and group communication, we present an integrated approach to provide security in hybrid wireless sensor networks.

Lightpath scheduling is an important capability in next-generation wavelength-division multiplexing (WDM) optical networks to reserve resources in advance for a specified time period while provisioning end-to-end lightpaths. In a dynamic environment, the end user requests for dynamic scheduled lightpath demands (D-SLDs) need to be serviced without the knowledge of future requests. Even though the starting time of the request may be hours or days from the current time, the end-user however expects a quick response as to whether the request could be satisfied. We propose a two- phase approach to dynamically schedule and provision D-SLDs. In the first phase, termed the deterministic lightpath scheduling phase, upon arrival of a lightpath request, the network control plane schedules a path with guaranteed resources so that the user can get a quick response with a deterministic lightpath schedule. In the second phase, termed the lightpath re-optimization phase, we re-provision some already scheduled lightpaths to re-optimize for improving network performance. We study two re- optimization scenarios to reallocate network resources while maintaining the existing lightpath schedules. Experimental results show that our proposed two-phase dynamic lightpath scheduling approach can greatly reduce network blocking.

Wireless sensor networks are promising solutions for many applications. However, wireless sensor nodes suffer from many constraints such as low computation capability, small memory, limited energy resources, and so on. Grouping is an important technique to localize computation and reduce communication overhead in wireless sensor networks. In this paper, we use grouping to refer to the process of combining a set of sensor nodes with similar properties. We propose two centralized group rekeying (CGK) schemes for secure group communication in sensor networks. The lifetime of a group is divided into three phases, i.e., group formation, group maintenance, and group dissolution. We demonstrate how to set up the group and establish the group key in each phase. Our analysis shows that the proposed two schemes are computationally efficient and secure.

Key management is a core mechanism to ensure the security of applications and network services in wireless sensor networks. It includes two aspects: key distribution and key revocation. Key distribution has been extensively studied in the context of sensor networks. However, key revocation has received relatively little attention. Existing key revocation schemes can be divided into two categories: centralized key revocation scheme and distributed key revocation scheme. In this paper, we first summarize the current key revocation schemes for sensor networks. Then, we propose an efficient centralized key revocation scheme, KeyRev, for wireless sensor networks. Unlike most proposed key revocation schemes focusing on removing the compromised keys, we propose to use key updating techniques to obsolesce the keys owned by the compromised sensor nodes and thus remove the nodes from the network. Our analyses show that the KeyRev scheme is secure inspite of not removing the pre-distributed key materials at compromised sensor nodes. Simulation results also indicate that the KeyRev scheme is scalable and performs very well in wireless sensor networks.

In this paper, we propose a layered clustering hierarchy (LCH) communication protocol for wireless sensor networks (WSNs). The design of LCH has two goals: scalability and energy-efficiency. In LCH, the sensor nodes are organized as a layered clustering structure. Each layer runs a distributed clustering protocol. By randomizing the rotation of cluster heads in each layer, the energy load is distributed evenly across sensors in the network. Our simulations show that LCH is effective in densely deployed sensor networks. On average, 70% of live sensor nodes are involved directly in the clustering communication hierarchy. Moreover, the simulations also show that the energy load and dead nodes are distributed evenly over the network. As studies prove that the performance of LCH depends mainly on the distributed clustering protocol, the location of cluster heads and cluster size are two critical factors in the design of LCH.

The survivable virtual topology routing problem is to route a virtual topology graph on a optical fiber physical topology such that the virtual topology remains connected when failures occur in the physical topology. In this work we study the problem of survivable virtual topology routing under single node/SRLG (Shared Risk Link Group) failure model. We prove that the survivable virtual topology routing problem under node/SRLG failures is NP-complete. We present an improved integer linear programming (ILP) formulation for computing the survivable routing of a virtual topology graph. However, ILP is not scalable when the network size scales more than a few tens of nodes. In this work, we present sub-classes of graphs which more accurately model an actual network and for which a survivable routing can be easily computed solving an ILP. We successfully computed the survivable routing of virtual topologies belonging to these sub-classes against link/SRLG failures for topologies of size up to 24 nodes.

As more reliance is placed on computing and networking systems, the need for redundancy increases. The Common Address Redundancy Protocol (CARP) protocol and OpenBSD's pfsync utility provide a means by which to implement redundant routers and firewalls. This paper details how CARP and pfsync work together to provide this redundancy and explores the performance one can expect from the open source solutions. Two experiments were run: one showing the relationship between firewall state creation and state synchronization traffic and the other showing how TCP sessions are transparently maintained in the event of a router failure. Discussion of these simulations along with background information gives an overview of how OpenBSD, CARP, and pfsync can provide redundant routers and firewalls for today's Internet.

Dynamic conferencing refers to a scenario wherein any subset of users in a universe of users form a conference for sharing confidential information among themselves. The key distribution (KD) problem in dynamic conferencing is to compute a shared secret key for such a dynamically formed conference. In literature, the KD schemes for dynamic conferencing either are computationally unscalable or require communication among users, which is undesirable. The extended symmetric polynomial based dynamic conferencing scheme (ESPDCS) is one such KD scheme which has a high computational complexity that is universe size dependent. In this paper we present an enhancement to the ESPDCS scheme to develop a KD scheme called universe-independent SPDCS (UI-SPDCS) such that its complexity is independent of the universe size. However, the UI-SPDCS scheme does not scale with the conference size. We propose a relatively scalable KD scheme termed as DH-SPDCS that uses the UI-SPDCS scheme and the tree-based group Diffie-Hellman (TGDH) key exchange protocol. The proposed DH-SPDCS scheme provides a configurable trade-off between computation and communication complexity of the scheme.

Employing waveband switching (WBS) in WDM networks can reduce the network operational cost and the call blocking probability. However, upgrading the existing optical switching architecture requires time and money. It is expected that a heterogeneous waveband switching (HeteroWBS) architecture would be desirable, where some nodes can support WBS functions and some cannot. We study the performance of HeteroWBS networks in terms of call blocking probability and cost savings under dynamic traffic requests. We propose an autonomous clustering-based HeteroWBS (AS-HeteroWBS) architecture to clusters the network into multiple autonomous systems (ASs). An AS may contain some specific nodes that provide WBS functions for all the nodes in the AS. Based on the architecture, three HeteroWBS algorithms are proposed. Our simulation results show that the HeteroWBS algorithms can achieve optimal cost savings while maintaining the same network throughput compared with the algorithm without WBS.

The security of the two party Diffie-Hellman key exchange protocol is currently based on the discrete logarithm problem (DLP). However, it can also be built upon the elliptic curve discrete logarithm problem (ECDLP). Most proposed secure group communication schemes employ the DLP-based Diffie-Hellman protocol. This paper proposes the ECDLP-based Diffie-Hellman protocols for secure group communication and evaluates their performance on wireless ad hoc networks. The proposed schemes are compared at the same security level with DLP-based group protocols under different channel conditions. Our experiments and analysis show that the Tree-based Group Elliptic Curve Diffie-Hellman (TGECDH) protocol is the best in overall performance for secure group communication among the four schemes discussed in the paper. Low communication overhead, relatively low computation load and short packets are the main reasons for the good performance of the TGECDH protocol.

Abstract — As wavelength-division multiplexing (WDM) evolves towards practical applications in optical transport networks, waveband switching (WBS) has been introduced to cut down the operational costs and to reduce the complexities and sizes of network components, e.g., optical cross-connects (OXCs). This paper considers the routing, wavelength assignment and waveband assignment (RWWBA) problem in a WDM network supporting mixed waveband and wavelength switching. First, the techniques supporting waveband switching are studied, where a node architecture enabling mixed waveband and wavelength switching is proposed. Second, to solve the RWWBA problem with reduced switching costs and improved network throughput, the cost savings and call blocking probabilities along intermedi-ate waveband-routes are analyzed. Our analysis reveals some important insights about the cost savings and call blocking

Lightpath scheduling is an important capability in next-generation wavelength-division multiplexing (WDM) optical networks to reserve resources in advance for a specified time period while provisioning end-to-end lightpaths. In this study, we propose an approach to support dynamic lightpath scheduling in such networks. To minimize blocking probability in a network that accommodates dynamic scheduled lightpath demands (D- SLDs), resource allocation should be optimized in a dynamic manner. However, for the network users who desire deterministic services, resources must be reserved in advance and guaranteed for future use. These two objectives may be mutually incompatible. Therefore, we propose a two-phase dynamic lightpath scheduling approach to tackle this issue. The first phase is the deterministic lightpath scheduling phase. When a lightpath request arrives, the network control plane schedules a path with guaranteed resources so that the user can get a quick response with the deterministic lightpath schedule. The second phase is the lightpath re-optimization phase, in which the network control plane re-provisions some already scheduled lightpaths. Experimental results show that our proposed two-phase dynamic lightpath scheduling approach can greatly reduce WDM network blocking.

Abstract — Multicommodity flow (MF) problems have a wide variety of applications in areas such as VLSI circuit design, network design, etc., and are therefore very well studied. The fractional MF problems are polynomial time solvable while integer versions are N Pcomplete. However, exact algorithms to the fractional MF problems have high computational complexity. Therefore approximation algorithms to fractional MF problems have been explored in the literature to reduce their computational complexity. Using these approximation algorithms and the randomized rounding technique, polynomial time approximation algorithms have been explored in the literature. In the design of high-speed networks, such as optical wavelength division multiplexing (WDM) networks, providing survivability carries great significance. Survivability is the ability of the network to recover from failures. It further increases the complexity of the network design and presents network designers with more formidable challenges. In this work we formulate the survivable versions of the MF problems. We build approximation algorithms for the survivable multicommodity flow (SMF) problems based on the framework of the approximation algorithms for the MF problems presented in [1] and [2]. We discuss applications of the SMF problems to solve survivable routing in capacitated networks.

No abstract available.

Providing fault tolerance against network failures in an optical WDM network is of prime importance. In this work we study the problem of computing optimal disjoint paths for providing shared protection in fully wavelength-convertible networks. We introduce and formalize the concept of dependent cost structure of a protection path on its working path and current network status. We formulate the problem of computing optimal disjoint paths for providing shared protection in fully wavelength-convertible networks as the problem of computing least-cost disjoint paths with dependent cost structure (LDP-DCS). We prove that LDP-DCS is NP-complete and is also hard to approximate. We present an iterative modified network-flow heuristic for the problem. We provide an approach to measure the optimality of the solution computed by the heuristic. Simulation results demonstrate the superior performance of our proposed heuristic in comparison to earlier heuristic approaches which did not consider the dependent cost structure.

Traffic grooming is an essential functionality of WDM optical networks to provision multi-granularity subwave-length connections. Depending on the number of lightpaths allowed in a connection route, traffic grooming can be classified as single-hop traffic grooming (SH-TG) and multi-hop traffic grooming (MH-TG). MH-TG is more general and resource-efficient than SH-TG, because it allows connections from different source-destination pairs to share the bandwidth of a lightpath. In this paper, we propose a MH-TG algorithm, namely the fixed-order multi-hop (FOMH) grooming algorithm, based on the fixed-alternate routing approach. We introduce the grooming node selection (GNS) problem in MH-TG and propose three grooming policies, namely exhaustive sequential (ES), limited-hop sequential (LHS) and load sharing (LS) policies, to address the GNS problem. Given that the analysis of MH-TG is a relatively unexplored area, we propose an analytical model to evaluate the blocking performance of MH-TG using FOMH and the LS grooming policy. To address the multi-layered routing and multi-rate connection characteristics of traffic grooming, we introduce a novel multi-level decomposition approach in our analytical model which decomposes traffic at four different levels, namely alternate path, connection route, lightpath and link levels. The Erlang fixed-point approximation method is used to solve the analytical model. Numerical results show that analytical results matches well with simulation results. We also evaluate the effect of the grooming policies, the number of virtual hops (lightpaths) within a connection route and the number of alternate paths on the performance of the grooming algorithm.

This paper considers the problem of dedicated path-protection in wavelength-division multiplexed (WDM) mesh networks with waveband switching functionality under shared risk link group (SRLG) constraints. Two dedicated path-protection schemes are proposed, namely the PBABL scheme and the MPABWL scheme. The PBABL scheme protects each working waveband-path through a backup waveband-path. The MPABWL scheme protects each working waveband-path by either a backup waveband-path or multiple backup lightpaths. Heuristic algorithms adopting random optimization technique are proposed for both the schemes. The performance of the two protection schemes is studied and compared. Simulation results show that both the heuristics can obtain optimum solutions and the MPABWL scheme leads to less switching and transmission costs than the PBABL scheme.

Waveband switching (WBS) is an important technique to save switching and transmission cost in wavelength-division multiplexed (WDM) optical networks. A cost-efficient WBS scheme would enable network carriers to increase the network throughput (revenue) while achieving significant cost savings. We identify the critical factors that determine the WBS network throughput and switching cost and propose a novel intermediate waveband switching (IT-WBS) algorithm, called the minimizing-weighted-cost (MWC) algorithm. The MWC algorithm defines a cost for each candidate route of a call. By selecting the route with the smallest weighted cost, MWC balances between minimizing the call blocking probability and minimizing the network switching cost. Our simulations show that MWC outperforms other wavelength/waveband switching algorithms and can enhance the network throughput at a reduced cost.

Establishing a fault-tolerant connection in a network involves computation of diverse working and protection paths. The shared risk link group (SRLG) (J. Strand et al. (2001) concept is used to model several types of failure conditions such as link, node, fiber conduit, etc. In this work we focus on the problem of computing optimal SRLG/link diverse paths under shared protection. Shared protection technique improves network resource utilization by allowing protection paths of multiple connections to share resources. In this work we propose an iterative heuristic for computing SRLG/link diverse paths. We present a method to calculate a quantitative measure that provides a bounded guarantee on the optimality of the diverse paths computed by the heuristic. The experimental results on computing link diverse paths show that our proposed heuristic is efficient in terms of number of iterations required (time taken) to compute diverse paths when compared to other previously proposed heuristics

As a result of the growing popularity of wireless networks, in particular ad hoc networks, security over such networks has become very important. In this paper, we study the problem of secure group communications (SGC) and key management over ad hoc networks. We identify the key features of any SGC protocol for such networks. We also propose an efficient key agreement scheme for SGC. The scheme solves two important problems that exist in most current SGC schemes: requirement of member serialization and existence of a central entity. Besides this, the protocol also has many highly desirable properties such as contributory and efficient computation of group key, uniform work load for all the members, few rounds of rekeying (2 rounds for the initial key formation and join and 1 round for leave), and efficient support for high dynamics. These properties make the protocol well suited for wireless ad hoc networks.

We investigate waveband switching (WBS) with different grouping strategies in wavelength-division multiplexing (WDM) mesh networks. End-to-end waveband switching (ETE-WBS) and same-destination-intermediate waveband switching (SD-IT-WBS) are analyzed and compared in terms of blocking probability and cost savings. First, an analytical model for ETE-WBS is proposed to determine the network blocking probability in a mesh network. For SD-IT-WBS, a simple waveband switching algorithm is presented. An analytical model to determine the network blocking probability is proposed for SD-IT-WBS based on the algorithm. The analytical results are validated by comparing with simulation results. Both results match well and show that ETE-WBS slightly outperforms SD-IT-WBS in terms of blocking probability. On the other hand, simulation results show that SD-IT-WBS outperforms ETE-WBS in terms of cost savings.

Sparse traffic grooming is a practical problem to be addressed in heterogeneous multi-vendor optical WDM networks where only some of the optical cross-connects (OXCs) have grooming capabilities. Such a network is called as a sparse grooming network. The sparse grooming problem under dynamic traffic in optical WDM mesh networks is a relatively unexplored problem. In this work, we propose the maximize-lightpath-sharing multi-hop (MLS-MH) grooming algorithm to support dynamic traffic grooming in sparse grooming networks. We also present an analytical model to evaluate the blocking performance of the MLS-MH algorithm. Simulation results show that MLS-MH outperforms an existing grooming algorithm, the shortest-path single-hop (SPSH) algorithm. The numerical results from analysis show that it matches closely with the simulation. The effect of the number of grooming nodes in the network on the blocking performance is also analyzed.

Survivable traffic grooming (STG) is a promising approach to provide reliable and resource-efficient multi-granularity connection services in optical networks. In this paper, we study the static STG problem in WDM mesh networks employing path protection at the lightpath level. To make connections survivable under various failures such as fiber cut and duct cut, we consider the general shared risk link group (SRLG) diverse routing constraints. In addition to providing the results from the integer linear programming (ILP) approach, we propose three efficient heuristics, namely separated grooming algorithm (SGA), integrated grooming algorithm (IGA) and tabu search grooming algorithm (TSGA). While SGA and IGA correspond to an overlay model and a peer model respectively, TSGA further improves SGA and IGA by incorporating the tabu search method. Numerical results show that the heuristics use much shorter running times to generate network throughputs close to those of the ILP formulations.

Logical key hierarchy (LKH) is a promising solution to handle group key distribution in secure group communication. Several recent studies have investigated different approaches to reduce the re-keying cost of LKH. For certain group communication applications, such as the subscription pay TV; a member's departure time is available when the member joins the group. The proposed scheme aims to improve the re-keying cost for such applications. It uses a combination of an AVL tree and a binary search tree called the leaving tree as the topology of its key tree. Both the AVL tree and the leaving tree are searchable by members' departure times. Our analysis shows that the average costs in terms of the number of key updates for the member join and leave are O(logn) and O(loglog n), respectively. Our simulation results show that the proposed scheme achieves better performance than other balanced tree based solutions.

One of the important issues in establishing a fault tolerant connection in a wavelength division multiplexing optical network is computing a pair of disjoint working and protection paths and a free wavelength along the paths. While most of the earlier research focused only on computing disjoint paths, in this work we consider computing both disjoint paths and a free wavelength along the paths. The concept of dependent cost structure (DCS) of protection paths to enhance their resource sharing ability was proposed in our earlier work. In this work we extend the concept of DCS of protection paths to wavelength continuous networks. We formalize the problem of computing disjoint paths with DCS in wavelength continuous networks and prove that it is NP-complete. We present an iterative heuristic that uses a layered graph model to compute disjoint paths with DCS and identify a free wavelength.

This paper addresses the two-layer dynamic traffic grooming problem in wavelength-division-multiplexed (WDM) mesh optical networks subject to resource constraints and the generalized wavelength continuity (GWC) constraint. The GWC constraint is a relaxed wavelength continuity constraint which incorporates various kinds of wavelength conversion capabilities that exist in optical networks. As an improvement over the existing layered auxiliary graph (layered-AG) approach which represents each wavelength separately in the auxiliary graph, we introduce a largely simplified link bundled auxiliary graph (LBAG) model and propose the SAG-LB method to find paths and assign wavelengths for new lightpaths subject to the GWC constraint. We propose the constrained integrated grooming algorithm (CIGA) based on the LBAG model. A grooming policy influences the resource utilization by determining the weight function of the auxiliary graph. We propose the least resource path first (LR) grooming policy, which is an improvement over the existing grooming policies in the literature, by integrating the wavelength and transceiver metrics together. Simulation results show that the LBAG model achieves a comparable blocking performance with the layered-AG approach while using a significantly less amount of running time. We also present the worst case time complexity analysis of the CIGA grooming algorithm and evaluate the performance of the LR grooming policy by simulation.

The static provisioning problem in wavelength-routed optical networks has been studied for many years. However, service providers are still facing the challenges arising from the special requirements for provisioning services at the optical layer. In this paper, we incorporate some realistic constraints into the static provisioning problem, and formulate it under different network resource availability conditions. We consider three classes of shared risk link group (SRLG)-diverse path protection schemes: dedicated, shared, and unprotected. We associate with each connection request a lightpath length constraint and a revenue value. When the network resources are not sufficient to accommodate all the connection requests, the static provisioning problem is formulated as a revenue maximization problem, whose objective is maximizing the total revenue value. When the network has sufficient resources, the problem becomes a capacity minimization problem with the objective of minimizing the number of used wavelength-links. We provide integer linear programming (ILP) formulations for these problems. Because solving these ILP problems is extremely time consuming, we propose a tabu search heuristic to solve these problems within a reasonable amount of time. We also develop a rerouting optimization heuristic, which is based on previous work. Experimental results are presented to compare the solutions obtained by the tabu search heuristic and the rerouting optimization heuristic. For both problems, the tabu search heuristic outperforms the rerouting optimization heuristic.

Wireless LANs are growing rapidly and security has always been a concern. We have implemented a hybrid system, which does not only detect active attacks such as identity theft causing denial of service attacks, but also detects the usage of accesspoint discovery tools. The system responds in real time by sending out an alert to the network administrator.

The next-generation SONET metro network is evolving into a service-rich infrastructure. At the edge of such a network, multi-service provisioning platforms (MSPPs) provide efficient data mapping enabled by generic framing procedure (GFP) and virtual concatenation (VC). The core of the network tends to be a meshed architecture equipped with multi-service switches (MSSs), In the context of these emerging technologies, we propose a load-balancing spare capacity reallocation approach to improve network utilization in the next-generation SONET metro networks. Using our approach, carriers can postpone network upgrades, resulting in increased revenue with reduced capital expenditures (CAPEX). For the first time, we consider the spare capacity reallocation problem from a capacity upgrade and network planning perspective. Our approach can operate in the context of shared-path protection (with backup multiplexing) because it reallocates spare capacity without disrupting working services. Unlike previous spare capacity reallocation approaches which aim at minimizing total spare capacity, our load-balancing approach minimizes the network load vector (NLV), which is a novel metric that reflects the network load distribution. Because NLV takes into consideration both uniform and non-uniform link capacity distribution, our approach can benefit both uniform and non-uniform networks. We develop a greedy load-balancing spare capacity reallocation (GLB-SCR) heuristic algorithm to implement this approach. Our experimental results show that GLB-SCR outperforms a previously proposed algorithm (SSR) in terms of established connection capacity and total network capacity in both uniform and non-uniform networks.

Network survivability is one of the most important issues in the design of optical WDM networks. In this work we study the problem of survivable routing of a virtual topology on a physical topology with shared risk link groups (SRLG). The survivable virtual topology routing problem against single-link failures in the physical topology is proved to be NP-complete in E. Modiano and A. Narula-Tam, May 2002. We prove that survivable virtual topology routing problem against SRLG/node failures is also NP-complete. We present an improved integer linear programming (ILP) formulation (in comparison to E. Modiano and A. Narula-Tam, May 2002) for computing the survivable routing under SRLG/node failures. Using an ILP solver, we computed the survivable virtual topology routing against link and SRLG failures for small and medium sized networks efficiently. As even our improved ILP formulation becomes intractable for large networks, we present a congestion-based heuristic and a tabu search heuristic (which uses the congestion-based heuristic solution as the initial solution) for computing survivable routing of a virtual topology. Our experimental results show that tabu search heuristic coupled with the congestion based heuristic (used as initial solution) provides fast and near-optimal solutions.

Survivable traffic grooming (STG) is a promising approach to provide reliable and resource-efficient multigranularity connection services in wavelength division multiplexing (WDM) optical networks. In this paper, we study the STG problem in WDM mesh optical networks employing path protection at the connection level. Both dedicated protection and shared protection schemes are considered. Given the network resources, the objective of the STG problem is to maximize network throughput. To enable survivability under various kinds of single failures such as fiber cut and duct cut, we consider the general shared risk link group (SRLG) diverse routing constraints. We first resort to the integer linear programming (ILP) approach to obtain optimal solutions. To address its high computational complexity, we then propose three efficient heuristics, namely separated survivable grooming algorithm (SSGA), integrated survivable grooming algorithm (ISGA) and tabu search survivable grooming algorithm (TSGA). While SSGA and ISGA correspond to an overlay network model and a peer network model respectively, TSGA further improves the grooming results from SSGA and ISGA by incorporating the effective tabu search method. Numerical results show that the heuristics achieve comparable solutions to the ILP approach, which uses significantly longer running times than the heuristics.

Traffic grooming in optical WDM mesh networks is a two-layer routing problem to pack low-rate connections effectively onto high-rate lightpaths, which, in turn, are established on wavelength links. We employ the rerouting approach to improve the network throughput under the dynamic traffic model. We propose two rerouting schemes, rerouting at lightpath level (RRAL) and rerouting at connection level (RRAC). A qualitative comparison is made between RRAL and RRAC. We also propose the critical-wavelength-avoiding one-lightpath-limited (CWA-1L) and critical-lightpath-avoiding one-connection-limited (CLA-1C) rerouting heuristics, which are based on the respective rerouting schemes. Simulation results show that rerouting reduces the connection blocking probability significantly.

The problem of waveband switching (WBS) in a wavelength-division multiplexing (WDM) mesh network with dynamic traffic requests is investigated. To solve the WBS problem in a homogeneous dynamic WBS network, where every node is a multigranular optical crossconnect (MG-OXC), we construct an auxiliary graph. Based on the auxiliary graph, we develop two heuristic on-line WBS algorithms with different grouping policies, namely the wavelength-first WBS algorithm based on the auxiliary graph (WFAUG) and the waveband-first WBS algorithm based on the auxiliary graph (BFAUG). Our results show that the WFAUG algorithm outperforms the BFAUG algorithm.

Survivable routing of a connection involves computation of a pair of diverse routes such that at most one route fails when failures occur in the network topology. A subset of links in the network that share the risk of failure at the same time are said to belong to a shared risk link group (SRLG) [J. Strand et al., Feb 2001]. A network with shared risk link groups defined over its links is an SRLG network. A failure of an SRLG is equivalent to the failure of all the links in the SRLG. For a connection to be survivable in an SRLG network, its working and protection paths must be routed on SRLG diverse paths. SRLG diverse routing problem has been proved to be NP-complete in J.Q. Hu (2003). According to the quality of service requirement of a survivable connection request, dedicated protection or shared protection can be used to establish the connection request. With dedicated protection, the connection is established on both the SRLG diverse working and protection paths. The simplest heuristic for computing SRLG diverse path pair is the two-step approach, but it suffers from the trap topology problem. In the previous study by Pin-Han Ho, an iterative heuristic (ITSH) using the two-step approach was proposed to compute the least cost SRLG diverse path pair. Suurballe's algorithm computes a pair of least cost link-disjoint paths between a node pair. In this work, we present a modified Suurballe's heuristic for computing the SRLG diverse routes between a node pair. We then propose an iterative heuristic (IMSH) which uses the modified Suurballe's heuristic for computing the least cost SRLG diverse routes. We also present an 1/2-cost-improvement optimality check criterion for dedicated protection

Traffic grooming is critical in WDM optical metropolitan area networks (MANs), where low-rate connections are packed onto high-rate wavelength paths (lightpaths). Various applications in the MAN demand different levels of reliability. Therefore, it is necessary to provision connections with differentiated reliability guarantees in the MAN. In this paper, we first present an analytical model to calculate the availability of connections using different protection schemes in WDM optical MANs with general mesh topologies. Then we propose and simulate two grooming algorithms which can provision availability guaranteed connections based on per-connection requirements.

Next-generation optical transport networks will automatically and dynamically provision end-to-end connections. In this paper, we study the problem of inter-domain dynamic routing under a multi-layer multi-domain network model, which allows the end-to-end connections to be set up not only across multiple routing domains but also through two transport layers: the optical layer and the digital layer. In this model, a connection can traverse the domain boundary either through optical bypass or through optical-electrical-optical (O/E/O) processing. We propose an inter-domain dynamic routing scheme with modest time complexity to address the problem from an algorithmic perspective.

Wireless LAN technology, despite the numerous advantages it has over competing technologies, has not seen widespread deployment. A primary reason for markets not adopting this technology is its failure to provide adequate security. Data that is sent over wireless links can be compromised with utmost ease. In this project, we propose a distributed agent based intrusion detection and response system for wireless LANs that can detect unauthorized wireless elements like access points, wireless clients that are in promiscuous mode etc. The system reacts to intrusions by either notifying the concerned personnel, in case of rogue access points and promiscuous nodes, or by blocking unauthorized users from accessing the network resources.

Optical networks provide a new dimension to meet the demands of exponentially growing traffic. Optical packet switching requires a good switch architecture, which eliminates the O/E/O conversion as much as possible. Wavelength division multiplexing (WDM) provides a breakthrough to exploit the huge bandwidth of the optical fiber. Different applications have different requirements, which necessitate employing differentiated services. This paper presents the idea of a priority-based /spl lambda/-scheduler, where the packets are differentiated into different classes and services are provided accordingly. For example, class 0 can correspond to non-real-time applications like email and ftp, while class 1 can correspond to real-time audio and video communications. The architecture is based on that of the /spl lambda/-scheduler and hence it has the added advantage of reduced component cost by using WDM internally.

The emergence of wavelength-division multiplexing (WDM) technology provides the capability for increasing the bandwidth of synchronous optical network (SONET) rings by grooming low-speed traffic streams onto different high-speed wavelength channels. Since the cost of SONET add-drop multiplexers (SADM) at each node dominates the total cost of these networks, how to assign the wavelength, groom the traffic, and bypass the traffic through the intermediate nodes has received a lot of attention from researchers recently. Moreover, the traffic pattern of the optical network changes from time to time. How to develop dynamic reconfiguration algorithms for traffic grooming is an important issue. In this paper, two cases (best fit and full fit) for handling reconfigurable SONET over WDM networks are proposed. For each approach, an integer linear programming model and heuristic algorithms (TS-1 and TS-2, based on the tabu search method) are given. The results demonstrate that the TS-1 algorithm can yield better solutions but has a greater running time than the greedy algorithm for the best fit case. For the full fit case, the tabu search heuristic yields competitive results compared with an earlier simulated annealing based method and it is more stable for the dynamic case.

The emergence of wavelength division multiplexing (WDM) technology provides the capability for increasing the bandwidth of synchronous optical network (SONET) rings by grooming low-speed traffic streams onto different high-speed wavelength channels. Since the cost of SONET add-drop multiplexers (SADM) at each node dominates the total cost of these networks, how to assign the wavelength, groom the traffic and bypass the traffic through the intermediate nodes has received a lot of attention from researchers recently. Moreover, the traffic pattern of the optical network changes from time to time. How to develop dynamic reconfiguration algorithms for traffic grooming is an important issue. We propose two cases (best-fit and full-fit) for handling reconfigurable SONET over WDM networks. For each approach, an integer linear programming model and heuristic algorithms (based on the tabu search method) are given. The results demonstrate that the tabu search heuristic can yield better solutions but has a greater running time than the greedy algorithm for the best-fit case. For the full-fit case, the tabu search heuristic yields competitive results compared with an earlier simulated annealing based method and it is more stable for the dynamic case.

Centralized and distributed methods are two connection management schemes in wavelength convertible optical networks. In the earlier work, the centralized scheme is said to have lower network blocking probability than the distributed one. Hence, much of the previous work in connection management has focused on the comparison of different algorithms in only distributed scheme or in only centralized scheme. However, we believe that the network blocking probability of these two connection management schemes depends, to a great extent, on the network traffic patterns and reservation times. Our simulation results reveal that the performance improvement (in terms of blocking probability) of the centralized method over the distributed method is inversely proportional to the ratio of average connection inter-arrival time to reservation time. After that the ratio increases beyond a threshold, those two connection management schemes yield almost the same blocking probability under the same network load. In this paper, we review the working procedure of distributed and centralized schemes, discuss the tradeoff between them, compare these two methods under different network traffic patterns via simulation and give our conclusion based on the simulation data.

Translucent WDM optical networks use sparse placement of regenerators to overcome the impairments and wavelength contention introduced by fully transparent networks, and achieve a performance close to fully opaque networks with much less cost. Our previous study proved the feasibility of translucent networks using the sparse regeneration technique. We addressed the placement of regenerators based on static schemes allowing only fixed number of regenerators at fixed locations. This paper furthers the study by proposing a suite of dynamical routing schemes. Dynamic allocation, advertisement and discovery of regeneration resources are proposed to support sharing transmitters and receivers between regeneration and access functions. This study follows the current trend in the optical networking industry by utilizing the extension of IP control protocols. Dynamic routing algorithms, aware of current regeneration resources and link states, are designed to smartly route the connection requests under quality constraints. A hierarchical network model, supported by the MPLS-based control plane, is also proposed to provide scalability. Experiments show that network performance is improved without placement of extra regenerators.

An analytical model for virtual topology reconfiguration (VTR) in optical networks is developed. It aims at the optical networks with a circuit-based data plane and an IP-like control plane. By identifying and analyzing the important factors impacting the network performance due to VTR operations on both planes, we can compare the benefits and penalties of different VTR algorithms and policies. The best VTR scenario can be adaptively chosen from a set of such algorithms and policies according to the real-time network situations. For this purpose, a cost model integrating all these factors is created to provide a comparison criterion independent of any specific VTR algorithm and policy. A case study based on simulation experiments is conducted to illustrate the application of our models.

This paper proposes an alternate approach to fully transparent and fully opaque optical networks for operating a wavelength routed optical network. The architecture of the regeneration node that performs sparse regeneration (or translucency) is discussed. The regeneration demands generated from call blocking and signal quality requirements are addressed. Two implementation strategies for incorporating sparse regeneration are introduced and their relative merits are studied.

Access control is a fundamental concern in any system that manages resources, e.g., operating systems, file systems, databases and communications systems. The problem we address is how to specify, enforce, and implement access control in distributed environments. This problem occurs in many applications such as management of distributed project resources, e-newspaper and pay TV subscription services. Starting from an access relation between users and resources, we derive a user hierarchy, a resource hierarchy, and a unified hierarchy. The unified hierarchy is then used to specify the access relation in a way that is compact and that allows efficient queries. It is also used in cryptographic schemes that enforce the access relation. We introduce three specific cryptography based hierarchical schemes, which can effectively enforce and implement access control and are designed for distributed environments because they do not need the presence of a central authority (except perhaps for setup).

Web content hosting, in which a Web server stores and provides Web access to documents for different customers, is becoming increasingly common. For example, a Web server can host Web pages for several different companies and individuals. Traditionally, Web service providers (WSPs) provide all customers with the same level of performance (best-effort service). Most service differentiation has been in the pricing structure (individual vs. business rates) or the connectivity type (dial-up access vs. leased line, etc.). This report presents DiffServer, a program that implements two simple, server-side, application-level mechanisms (server-centric and client-centric) to provide different levels of Web service. The results of the experiments show that there is not much overhead due to the addition of this additional layer of abstraction between the client and the Apache Web server under light load conditions. Also, the average waiting time for high priority requests decreases significantly after they are assigned priorities as compared to a FIFO approach.

Wavelength division multiplexing (WDM) offers a solution to the problem of exploiting the large bandwidth on optical links; it is the current favorite multiplexing technology for optical communication networks. Due to the high cost of an optical amplifier, it is desirable to strategically place the amplifiers throughout the network in a way that guarantees that all the signals are adequately amplified while minimizing the total number amplifiers being used. Previous studies all consider a star-based network. This paper demonstrates an original approach for solving the problem in switch-based WDM optical network assuming the traffic matrix is always the permutation of the nodes. First we formulate the problem by choosing typical permutations which can maximize the traffic load on individual links; then a GA (genetic algorithm) is used to search for feasible amplifier placements. Finally, by setting up all the lightpaths without violating the power constraints we confirm the feasibility of the solution.

The bandwidth requirements of the Internet are increasing every day and there are newer and more bandwidth-thirsty applications emerging on the horizon. Wavelength division multiplexing (WDM) is the next step towards leveraging the capabilities of the optical fiber, especially for wide-area backbone networks. The ability to switch a signal at intermediate nodes in a WDM network based on their wavelengths is known as wavelength-routing. One of the greatest advantages of using wavelength-routing WDM is the ability to create a virtual topology different from the physical topology of the underlying network. This virtual topology can be reconfigured when necessary, to improve performance. We discuss the previous work done on virtual topology design and also discuss and propose different reconfiguration algorithms applicable under different scenarios.

Server responsiveness and scalability are more important than ever in today's client/server dominated network environments. Researchers have begun to consider cluster-based computers using commodity hardware as an alternative to expensive specialized hardware for building scalable Web servers. In this paper, we present performance results comparing two cluster-based Web servers based on different server infrastructures: MAC-based dispatching (LSMAC) and IP-based dispatching (LSNAT). Both cluster-based server systems were implemented as application-space programs running on commodity hardware. We point out the advantages and disadvantages of both systems. We also identify when servers should be clustered and when clustering will not improve performance.

In this paper, we investigate the problem of routing connections in ail-optical networks while allowing for degradation of routed signals by different optical components. To overcome the complexity of the problem, we divide it into two parts. First, we solve the pure RWA problem using fixed routes for every connection. Second, power assignment is accomplished by either using the smallest-gain first (SGF) heuristic or using a genetic algorithm. Numerical examples on a wide variety of networks show that: (a) the number of connections established without considering the signal attenuation was most of the time greater than that achievable considering attenuation; and (b) the genetic solution quality was much better than that of SGF, especially when the conflict graph of the connections generated by the linear solver is denser.

Wavelength conversion has been proposed for use in wavelength-division multiplexed networks to improve efficiency. This study highlights systems challenges and performance issues which need to be addressed in order to incorporate wavelength conversion effectively. A review/survey of the enabling technologies, design methods, and analytical models used in wavelength-convertible networks is provided.

Optical networks based on passive-star couplers and employing WDM have been proposed for deployment in local and metropolitan areas. These networks suffer from splitting, coupling, and attenuation losses. Since there is an upper bound on transmitter power and a lower bound on receiver sensitivity, optical amplifiers are usually required to compensate for the power losses mentioned above. Due to the high cost of amplifiers, it is desirable to minimize their total number in the network. However, an optical amplifier has constraints on the maximum gain and the maximum output power it can supply; thus, optical amplifier placement becomes a challenging problem. In fact, the general problem of minimizing the total amplifier count is a mixed-integer nonlinear problem. Previous studies have attacked the amplifier-placement problem by adding the "artificial" constraint that all wavelengths, which are present at a particular point in a fiber, be at the same power level. This constraint simplifies the problem into a solvable mixed-integer linear program. Unfortunately, this artificial constraint can miss feasible solutions that have a lower amplifier count but do not have the equally powered wavelengths constraint. In this paper, we present a method to solve the minimum-amplifier-placement problem, while avoiding the equally powered wavelength constraint. We demonstrate that, by allowing signals to operate at different power levels, our method can reduce the number of amplifiers required.

Optical networks based on passive star couplers and employing wavelength-division multiplexing (WDM) have been proposed for deployment in local and metropolitan areas. Amplifiers are required in such networks to compensate for the power losses due to splitting and attenuation. However, an optical amplifier has constraints on the maximum gain and the maximum output power it can supply; thus optical amplifier placement becomes a challenging problem. The general problem of minimizing the total amplifier count, subject to the device constraints, is a mixed-integer nonlinear problem. Previous studies have attacked the amplifier-placement problem by adding the "artificial" constraint that all wavelengths, which are present at a particular point in a fiber, be at the same power level. In this paper, we present a method to solve the minimum-amplifier-placement problem while avoiding the equally-powered-wavelength constraint. We demonstrate-that, by allowing signals to operate at different power levels, our method can reduce the number of amplifiers required in several small to medium-sized networks.