Showing papers on "Network management published in 2007"

Bayesian Neural Networks for Internet Traffic Classification

Abstract: Internet traffic identification is an important tool for network management. It allows operators to better predict future traffic matrices and demands, security personnel to detect anomalous behavior, and researchers to develop more realistic traffic models. We present here a traffic classifier that can achieve a high accuracy across a range of application types without any source or destination host-address or port information. We use supervised machine learning based on a Bayesian trained neural network. Though our technique uses training data with categories derived from packet content, training and testing were done using features derived from packet streams consisting of one or more packet headers. By providing classification without access to the contents of packets, our technique offers wider application than methods that require full packet/payloads for classification. This is a powerful advantage, using samples of classified traffic to permit the categorization of traffic based only upon commonly available information

Methods and apparatus for centralized content and data delivery

Abstract: Methods and apparatus for centralized content, media and data delivery and access within a premises such as, e.g., a residence. In one embodiment, the apparatus comprises a remotely manageable premises device that acts as a centralized client networking platform, providing gateway services such as network management as well as traditional content and high-speed data delivery functions. The device also acts as the shared internet connection for all devices in the premises via a cable modem, sharing personal and DVR content such as video, music and photos (and any associated metadata) throughout the premises, and providing both a wired and wireless network in the home. Telephony services utilizing e.g., embedded multimedia terminal adapter (eMTA) and/or Wi-Fi architectures may also be provided via the device. The device can also provide a trusted domain for content or data, as well as allowing a subscriber total mobility in the home.

Control of Large-Scale Irrigation Networks

Abstract: Irrigation networks of open-water channels are used throughout the world to support agricultural activity. By and large, these networks are managed in open loop. To achieve closed-loop water distribution management, it is necessary to augment these civil engineering systems with an appropriate information infrastructure-sensors, actuators, information processing, and communication resources. Recent pilot projects in Australia demonstrate the significant potential of closed-loop management, which can yield a significant improvement in the quality of service, while achieving improved water distribution efficiency. This paper focuses on the modelling and closed-loop control of open-water channels from the perspective of large-scale irrigation network management. Several feedback information structures are discussed and the key design tradeoffs identified

Network Management Reconsidered: An Inquiry into Management of Network Structures in Public Sector Service Provision

Abstract: Although policy and collaborative networks have been studied since the 1970s and 1980s, only recently has the management of these entities come under greater scrutiny. Studies of “network management” are designed to better understand the unique challenges of operating in a context where bureaucracy no longer provides the primary tool for “social steering.” These studies typically make three assumptions about networks, public managers, and the tasks of network management that empirical evidence from our casework in “Newstatia” suggests are suspect at best. If so, then network management theory needs to be reconsidered. The second half of this article begins this process. We have organized this article into six sections. The first defines policy and collaborative networks and discusses why analyzing them and their management independently is probably flawed. The second presents our data and justifications for believing the assumptions outlined above are oversimplifications. The third section reviews three perspectives and two partial models of network management and points out how the perspectives and models need integration. The fourth section develops a resource dependence framework for network management that can encompass the existing models and our new data on the environment in which network management occurs. The final section outlines a series of propositions that flow from our reconsideration of network management.

Towards autonomic management of communications networks

Abstract: As communications networks become increasingly dynamic, heterogeneous, less reliable, and larger in scale, it becomes difficult, if not impossible, to effectively manage these networks using traditional approaches that rely on human monitoring and intervention to ensure they operate within desired bounds. Researchers and practitioners are pursuing the vision of autonomic network management, which we view as the capability of network entities to self-govern their behavior within the constraints of business goals that the network as a whole seeks to achieve. However, applying autonomic principles to network management is challenging for a number of reasons, including: (1) A means is required to enable business rules to determine the set of resources and/or services to be provided. (2) Contextual changes in the network must be sensed and interpreted, because new management policies may be required when context changes. (3) As context changes, it may be necessary to adapt the management control loops that are used to ensure that system functionality adapts to meet changing user requirements, business goals, and environmental conditions. (4) A means is required to verify modeled data and to add new data dynamically so that the system can learn and reason about itself and its environment. This article provides an introduction to the FOCALE autonomic network management architecture, which is designed to address these challenges.

Experiences in using WiFi for rural internet in India

Abstract: Access to communication can play a pivotal role in the socio-economic development of rural regions in the third world. For affordability, the choice of technology to achieve this is a significant aspect. We have chosen IEEE 802.11 as a cost-effective technology to provide rural connectivity in the context of two projects in India: digital Gangetic plains (DGP) and Ashwini. This article presents our experiences with these two projects and discusses five important aspects in the use of WiFi for rural connectivity: network planning and deployment, network protocols, network management and operations, power savings, and applications and services

Bargaining Strategies for Networked Multimedia Resource Management

Abstract: Multiuser multimedia applications such as enterprise streaming, surveillance, and gaming are recently emerging, and they are often deployed over bandwidth-constrained network infrastructures. To ensure the quality of service (QoS) required by the delay-sensitive and bandwidth intensive multimedia data for these applications, efficient resource (bandwidth) management becomes paramount. We propose to deploy the well-known game theoretic concept of bargaining to allocate the bandwidth fairly and optimally among multiple collaborative users. Specifically, we consider two bargaining solutions for our resource management problem: the Nash bargaining solution (NBS) and the Kalai-Smorodinsky bargaining solution (KSBS). We provide interpretations for the two investigated bargaining solutions for multiuser resource allocation: the NBS can be used to maximize the system utility, while the KSBS ensures that all users incur the same utility penalty relative to the maximum achievable utility. The bargaining strategies and solutions are implemented in the network using a resource manager, which explicitly considers the application-specific distortion for the bandwidth allocation. We show that the bargaining solutions exhibit important properties (axioms) that can be used for effective multimedia resource allocation. Moreover, we propose several criteria for determining bargaining powers for these solutions, which enable us to provide additional flexibility in choosing solution by taking into consideration the visual quality impact, the deployed spatiotemporal resolutions, etc. We also determine the complexity of these solutions for our application and quantify the performance of the proposed bargaining-based resource strategies for different scenarios.

Non-Adaptive Fault Diagnosis for All-Optical Networks via Combinatorial Group Testing on Graphs

Abstract: We consider the problem of detecting failures for all-optical networks, with the objective of keeping the diagnosis cost low. Compared to the passive paradigm based on parity check in SONET, optical probing signals are sent proactively along lightpaths to probe their state of health and failure pattern is identified through the set of test results (i.e., probe syndromes). As an alternative to our previous adaptive approach where all the probes are sent sequentially, we consider in this work a non-adaptive approach where all the probes are sent in parallel. The design objective is to minimize the number of parallel probes, so as to keep network cost low. The non-adaptive fault diagnosis approach motivates a new technical framework that we introduce: combinatorial group testing with graph-based constraints. Using this framework, we develop several new probing schemes to detect network faults for all-optical networks with different topologies. The efficiency of our schemes often depends on the network topology; in many cases we can show that our schemes are optimal in minimizing the number of probes.

Systems and methods for load balancing based on user selected metrics

Abstract: The present invention provides improvements to load balancing by providing a load balancing solution that allows a user to select metrics, weights and thresholds from metrics collected or determined by a load balancing appliance as well as metrics obtained from another device, such as a server running the service. The systems and methods described providing a load balancing technique in which load balancing decisions can be made based on metrics known by another device monitoring such metrics. The load balancing appliance uses a network management protocol and communication model, such as a Simple Network Management Protocol (SNMP), to identify and collect metrics from a server, service or other device. These metrics are available on the load balancing appliance with appliance determined metrics. Via a configuration interface of the appliance, a user can select one or more appliance determined metrics and/or the metrics obtained via the network management protocol to determine the load of a service.

Quality assured network service provision system compatible with a multi-domain network and service provision method and service broker device

Abstract: The invention provides quality assured network services in a multi-domain network and comprises a network service management device for managing device clusters incorporated within the operations management network of each provider network and receiving service orders, and a multi-domain service broker for providing a broker function for achieving agreement between a plurality of providers, and the multi-domain service broker further comprises a device for collecting domain information and information relating to the services each provider is able to provide from the network service management devices, and a device which on receipt of a network service request from a customer, extracts the network service management device of the domain which is able to satisfy the required quality level, and then issues instructions for the setting of the required information within the extracted network service management device.

Optimization Based Rate Control for Multicast with Network Coding

Abstract: Recent advances in network coding have shown great potential for efficient information multicasting in communication networks, in terms of both network throughput and network management. In this paper, we address the problem of rate control at end-systems for network coding based multicast flows. We develop two adaptive rate control algorithms for the networks with given coding subgraphs and without given coding subgraphs, respectively. With random network coding, both algorithms can be implemented in a distributed manner, and work at transport layer to adjust source rates and at network layer to carry out network coding. We prove that the proposed algorithms converge to the globally optimal solutions for intra-session network coding. Some related issues are discussed, and numerical examples are provided to complement our theoretical analysis.

Key research challenges in network management

Abstract: Although network management has always played a key role for industry, it only recently received a similar level of attention from many research communities, accelerated by funding opportunities from new initiatives, including the FP7 Program in Europe and GENI/FIND in the United States. Work is ongoing to assess the state of the art and identify the challenges for future research in the field, and this article contributes to this discussion. It presents major findings from a two-day workshop organized jointly by the IRTF/NMRG and the EMANICS Network of Excellence, at which researchers, operators, vendors, and technology developers discussed the research directions to be pursued over the next five years. The workshop identified several topic areas, including management architectures, distributed real-time monitoring, data analysis and visualization, ontologies, economic aspects of management, uncertainty and probabilistic approaches, as well as understanding the behavior of managed systems.

CONMan: a step towards network manageability

Abstract: Networks are hard to manage and in spite of all the so called holistic management packages, things are getting worse. We argue that the difficulty of network management can partly be attributed to a fundamental flaw in the existing architecture: protocols expose all their internal details and hence, the complexity of the ever-evolving data plane encumbers the management plane. Guided by this observation, in this paper we explore an alternative approach and propose Complexity Oblivious Network Management (CONMan), a network architecture in which the management interface of data-plane protocols includes minimal protocol-specific information. This restricts the operational complexity of protocols to their implementation and allows the management plane to achieve high level policies in a structured fashion. We built the CONMan interface of a few protocols and a management tool that can achieve high-level configuration goals based on this interface. Our preliminary experience with applying this tool to real world VPN configuration indicates the architecture's potential to alleviate the difficulty of configuration management.

Diagnosing network disruptions with network-wide analysis

Abstract: To maintain high availability in the face of changing network conditions, network operators must quickly detect, identify, and react to events that cause network disruptions. One way to accomplish this goal is to monitor routing dynamics, by analyzing routing update streams collected from routers. Existing monitoring approaches typically treat streams of routing updates from different routers as independent signals, and report only the "loud" events (i.e., events that involve large volume of routing messages). In this paper, we examine BGP routing data from all routers in the Abilene backbone for six months and correlate them with a catalog of all known disruptions to its nodes and links. We find that many important events are not loud enough to be detected from a single stream. Instead, they become detectable only when multiple BGP update streams are simultaneously examined. This is because routing updates exhibit network-wide dependencies.This paper proposes using network-wide analysis of routing information to diagnose (i.e., detect and identify) network disruptions. To detect network disruptions, we apply a multivariate analysis technique on dynamic routing information, (i.e., update traffic from all the Abilene routers) and find that this technique can detect every reported disruption to nodes and links within the network with a low rate of false alarms. To identify the type of disruption, we jointly analyze both the network-wide static configuration and details in the dynamic routing updates; we find that our method can correctly explain the scenario that caused the disruption. Although much work remains to make network-wide analysis of routing data operationally practical, our results illustrate the importance and potential of such an approach.

Group decision-making for leakage management strategy of water network

Abstract: The problem of leakage is complex and requires actions drawn from different aspects of water network management. Inadequate maintenance has serious consequences, both financial and environmental. This paper proposes a group decision-making model based on PROMETHEE V method to aim a leakage management strategy, which takes into account the points of view of four stakeholders, selecting feasible options, and considering the available budget as constraint. Thus, this strategy is the combination of options that will efficiently meet technical, socio-economic and environmental criteria to achieve sustainable development.

Large-Scale Optimal Sensor Array Management for Multitarget Tracking

Abstract: In this paper, we are concerned with the problem of utilizing a large network of sensors in order to track multiple targets. Large-scale sensor array management has applications in a number of target tracking domains. For example, in ground target tracking, hundreds or even thousands of unattended ground sensors may be dropped over a large surveillance area. At any one time, it may then only be possible to utilize a very small number of the available sensors at the fusion center because of physical limitations, such as available communications bandwidth. A similar situation may arise in tracking sea-surface or underwater targets using a large network of sonobuoys. The general problem is then to select a small subset of the available sensors in order to optimize tracking performance. In a practical scenario with hundreds of sensors, the number of possible sensor combinations would make it infeasible to use enumeration in order to find the optimal solution. Motivated by this consideration, in this paper we use an efficient search technique in order to determine near-optimal sensor utilization strategies in real-time. This search technique consists of convex optimization followed by greedy local search. We consider several problem formulations and the posterior Cramer-Rao lower bound is used as the basis for network management. Simulation results illustrate the performance of the algorithms, both in terms of their real-time capability and the resulting estimation accuracy. Furthermore, in comparisons it can also be seen that the proposed solutions are near-optimal.

Network management method

Abstract: The present invention provides a method in which the physical connection information and the logical network configuration information are kinked to the status of spanning tree, and the status of spanning tree is displayed with the physical connection and the logical network configurations. The method can provide the better recognition about not only intended the physical and logical configurations but the status of spanning tree to a network administrator. Therefore, the network administrator can integrally recognize the status of the network and the failure in the network will be analyzed easily to recover the network to normal state in shorter time.

Approximation via cost sharing: Simpler and better approximation algorithms for network design

Abstract: We present constant-factor approximation algorithms for several widely-studied NP-hard optimization problems in network design, including the multicommodity rent-or-buy, virtual private network design, and single-sink buy-at-bulk problems. Our algorithms are simple and their approximation ratios improve over those previously known, in some cases by orders of magnitude.We develop a general analysis framework to bound the approximation ratios of our algorithms. This framework is based on a novel connection between random sampling and game-theoretic cost sharing.

Apparatus and method for measuring and using response to SNMP requests to provide real-time network parameter estimates in a network management zone

Abstract: Method creates Real-Time Estimates (RTE) of network parameters for responsive resources of a network management zone (NMZ) by sending requests in a management protocol and uses those real-time estimates to present a resource map of the NMZ, possibly altering a responsive resource, possibly posting a service schedule request. The invention includes implementation mechanisms and installation packages. The RTE of network parameter is a product of the process. Constructing a quality of service measure from RTE of at least two network parameters. Quality of service measure as a product of the process. The quality of service measure may include or be the Mean Opinion Score.

Building constructive innovation networks: role of relationship management

Abstract: In response to the growing demands for innovation, networked arrangements that draw together and synthesize the knowledge resources of multiple organizations and sectors have come to the fore-front within the construction arena. Because they are based on a relational governance principal, these new arrangements require management strategies and techniques that may not be synonymous with conventional approaches. Drawing on the Cooperative Research Centre for Construction Innovation as an example of an interorganizational innovation network, this case study examines its formation and operation to determine the role that relational governance plays in these new arrangements and to provide insights into the relationship-based management strategies employed. The case study indicates that although a mix of governance modes supplements the relational approach, network management remains a critical, if often overlooked, function. Based on the findings, a preliminary relationship management framework is presented as well as some key lessons for those responsible for the architecture, operation, and administration of these innovation networks.

ProgME: towards programmable network measurement

Abstract: Traffic measurements provide critical input for a wide range of network management applications, including traffic engineering, accounting, and security analysis. Existing measurement tools collect traffic statistics based on some pre-determined, inflexible concept of "flows". They do not have sufficient built-in intelligence to understand the application requirements or adapt to the traffic conditions. Consequently, they have limited scalability with respect to the number of flows and the heterogeneity of monitoring applications.We present ProgME, a Programmable MEasurement architecture based on a novel concept of flowset - arbitrary set of flows defined according to application requirements and/or traffic conditions. Through a simple flowset composition language, ProgME can incorporate application requirements, adapt itself to circumvent the challenges on scalability posed by the large number of flows, and achieve a better application-perceived accuracy. ProgME can analyze and adapt to traffic statistics in real-time. Using sequential hypothesis test, ProgME can achieve fast and scalable heavy hitter identification.

Hierarchical storage manager (HSM) for intelligent storage of large volumes of data

Abstract: The present invention is a video surveillance, storage, and alerting system having the following components. One or more surveillance cameras capture video data having attribute data, the attribute data representing importance of the surveillance cameras. One or more video analytics devices process the video data from one or more of the surveillance cameras and detect primitive video events in the video data. A network management module monitors network status of the surveillance cameras, and the video analytics devices, and generates network events reflective of the network status of all subsystems. A correlation engine correlates two or more primitive video events from the video analytics devices weighted by the attribute data of the surveillance cameras used to capture the video data, and network events from the network management module weighted by attribute data of device corresponding to the network event. An alerting engine generates one or more alerts and performs one or more actions based on the correlation performed by the correlation engine.

Mining behavioral groups in large wireless LANs

Abstract: Recent years have witnessed significant growth in the adoption of portable wireless communication and computing devices (e.g., laptops, PDAs, smart phones) and large-scale deployment of wireless networks (e.g., cellular, WLANs). We envision that future usage of mobile devices and services will be highly personalized. Users will incorporate these new technologies into their daily lives, and the way they use new devices and services will reflect their personality and lifestyle. Therefore it is imperative to study and characterize the fundamental structure of wireless user behavior in order to model, manage, leverage and design efficient mobile networks and services. In this study, using our systematic TRACE approach, we analyze wireless users' behavioral patterns by extensively mining wireless network logs from two major university campuses. We represent the data using location-preference vectors, and utilize unsupervised learning (clustering) to classify trends in user behavior using novel similarity metrics. Matrix decomposition techniques are used to identify (and differentiate between) major patterns. We discover multi-modal user behavior and hundreds of distinct groups with unique behavioral patterns in both campuses, and their sizes follow a power-law distribution. Our methods and findings might provide new directions in network management and behavior-aware network protocols and applications, to name a few.

Policy-Based Network Management for NeXt Generation Spectrum Access Control

Abstract: This paper describes the design and implementation of a policy-based spectrum access control framework as part of the DARPA next generation communications program. The main emphasis of the framework is to overcome two types of concerns: harmful interference caused by a malfunctioning device and harmful interference caused by a malicious user. In tandem with signal-detection-based interference-avoidance algorithms employed by software-defined radios, we design a set of policy- based components, tightly integrated with the accredited kernel on the radio, for avoiding potentially harmful interference caused by a malfunctioning device. The policy conformance and enforcement components ensure that a radio does not violate policies, which define regulatory and other stakeholders' goals and requirements, and which are encoded in an abstract, declarative language. We further secure the policy management and distribution mechanisms in order to prevent malicious users from altering loaded policies as well as from inserting additional policies and thus causing a harmful interference. Additionally, we report on a prototype implementation and demonstration of our framework, which qualitatively illustrates the capability offered to radio for enforcing policies and the capability for managing radios and securing access control to interfaces changing the radio's configuration.

Lightweight application classification for network management

Abstract: Traffic application classification is an essential step in the network management process to provide high availability of network services. However, network management has seen limited use of traffic classification because of the significant overheads of existing techniques. In this context we explore the feasibility and performance of lightweight traffic classification based on NetFlow records. In our experiments, the NetFlow records are created from packet-trace data and pre-tagged based upon packet content. This provides us with NetFlow records that are tagged with a high accuracy for ground-truth. Our experiments show that NetFlow records can be usefully employed for application classification. We demonstrate that our machine learning technique is able to provide an identification accuracy (a 91%) that, while a little lower than that based upon previous packet-based machine learning work (> 95%), is significantly higher than the commonly used port-based approach (50--70%). Trade-offs such as the complexity of feature selection and packet sampling are also studied. We conclude that a lightweight mechanism of classification can provide application information with a considerably high accuracy, and can be a useful practice towards more effective network management.