860 research outputs found

    Distributed Software Router Management

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    With the stunning success of the Internet, information and communication technologies diffused increasingly attracting more uses to join the the Internet arsenal which in turn accelerates the traffic growth. This growth rate does not seem to slow down in near future. Networking devices support these traffic growth by offering an ever increasing transmission and switching speed, mostly due to the technological advancement of microelectronics granted by Moore’s Law. However, the comparable growth rate of the Internet and electronic devices suggest that capacity of systems will become a crucial factor in the years ahead. Besides the growth rate challenge that electronic devices face with respect to traffic growth, networking devices have always been characterized by the development of proprietary architectures. This means that incompatible equipment and architectures, especially in terms of configuration and management procedures. The major drawback of such industrial practice, however, is that the devices lack flexibility and programmability which is one of the source of ossification for today’s Internet. Thus scaling or modifying networking devices, particularly routers, for a desired function requires a flexible and programmable devices. Software routers (SRs) based on personal computers (PCs) are among these devices that satisfy the flexibility and programmability criteria. Furthermore, the availability of large number of open-source software for networking applications both for data as well as control plane and the low cost PCs driven by PC-market economy scale make software routers appealing alternative to expensive proprietary networking devices. That is, while software routers have the advantage of being flexible, programmable and low cost, proprietary networking equipments are usually expensive, difficult to extend, program, or otherwise experiment with because they rely on specialized and closed hardware and software. Despite their advantages, however, software routers are not without limitation. The objections to software routers include limited performance, scalability problems and lack of advanced functionality. These limitations arose from the fact that a single server limited by PCI bus width and CPU is given a responsibility to process large amount of packets. Offloading some packet processing tasks performed by the CPU to other processors, such as GPUs of the same PC or external CPUs, is a viable approach to overcome some of these limitations. In line with this, a distributed Multi-Stage Software Router (MSSR) architecture has been proposed in order to overcome both the performance and scalability issues of single PC based software routers. The architecture has three stages: i) a front-end layer-2 load balancers (LBs), open-software or open-hardware based, that act as interfaces to the external networks and distribute IP packets to ii) back-end personal computers (BEPCs), also named back-end routers in this thesis, that provide IP routing functionality, and iii) an interconnection network, based on Ethernet switches, that connects the two stages. Performance scaling of the architecture is achieved by increasing the redundancy of the routing functionality stage where multiple servers are given a coordinated task of routing packets. The scalability problem related to number of interfaces per PC is also tackled in MSSR by bundling two or more PCs’ interfaces through a switch at the front-end stage. The overall architecture is controlled and managed by a control entity named Virtual Control Processor (virtualCP), which runs on a selected back-end router, through a DIST protocol. This entity is also responsible to hide the internal details of the multistage software router architecture such that the whole architecture appear to external network devices as a single device. However, building a flexible and scalable high-performance MSSR architecture requires large number of independently, but coordinately, running internal components. As the number of internal devices increase so does the architecture control and management complexity. In addition, redundant components to scale performance means power wastage at low loads. These challenges have to be addressed in making the multistage software router a functional and competent network device. Consequently, the contribution of this thesis is to develop an MSSR centralized management system that deals with these challenges. The management system has two broadly classified sub-systems: I) power management: a module responsible to address the energy inefficiency in multistage software router architecture II) unified information management: a module responsible to create a unified management information base such that the distributed multistage router architecture appears as a single device to external network from management information perspective. The distributed multistage router power management module tries to minimize the energy consumption of the architecture by resizing the architecture to the traffic demand. During low load periods only few components, especially that of routing functionality stage, are required to readily give a service. Thus it is wise to device a mechanism that puts idle components to low power mode to save energy during low load periods. In this thesis an optimal and two heuristic algorithms, namely on-line and off-line, are proposed to adapt the architecture to an input load demand. We demonstrate that the optimal algorithm, besides having scalability issue, is an off-line approach that introduce service disruption and delay during the architecture reconfiguration period. In solving these issues, heuristic solutions are proposed and their performance is measured against the optimal solution. Results show that the algorithms fairly approximate the optimal solution and use of these algorithms save up to 57.44% of the total architecture energy consumption during low load periods. The on-line algorithms are superior among the heuristic solutions as it has the advantage of being less disruptive and has minimal service delay. Furthermore, the thesis shows that the proposed algorithms will be more efficient if the architecture is designed keeping in mind energy as one of the design parameter. In achieving this goal three different approaches to design an MSSR architecture are proposed and their energy saving efficient is evaluated both with respect to the optimal solution and other similar cluster design approaches. The multistage software router is unique from a single device as it is composed of independently running components. This means that the MSSR management information is distributed in the architecture since individual components register their own management information. It is said, however, that the MSSR internal devices work cooperatively to appear as a single network device to the external network. The MSSR architecture, as a single device, therefore requires its own management information base which is built from the management information bases dispersed among internal components. This thesis proposes a mechanism to collect and organize this distributed management information and create a single management information base representing the whole architecture. Accordingly existing SNMP management communication model has been modified to fit to distributed multi-stage router architecture and a possible management architecture is proposed. In compiling the management information, different schemes has been adopted to deal with different SNMP management information variables. Scalability analysis shows that proposed management system scales well and does not pose a threat to the overall architecture scalability

    Mesh-Mon: a Monitoring and Management System for Wireless Mesh Networks

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    A mesh network is a network of wireless routers that employ multi-hop routing and can be used to provide network access for mobile clients. Mobile mesh networks can be deployed rapidly to provide an alternate communication infrastructure for emergency response operations in areas with limited or damaged infrastructure. In this dissertation, we present Dart-Mesh: a Linux-based layer-3 dual-radio two-tiered mesh network that provides complete 802.11b coverage in the Sudikoff Lab for Computer Science at Dartmouth College. We faced several challenges in building, testing, monitoring and managing this network. These challenges motivated us to design and implement Mesh-Mon, a network monitoring system to aid system administrators in the management of a mobile mesh network. Mesh-Mon is a scalable, distributed and decentralized management system in which mesh nodes cooperate in a proactive manner to help detect, diagnose and resolve network problems automatically. Mesh-Mon is independent of the routing protocol used by the mesh routing layer and can function even if the routing protocol fails. We demonstrate this feature by running Mesh-Mon on two versions of Dart-Mesh, one running on AODV (a reactive mesh routing protocol) and the second running on OLSR (a proactive mesh routing protocol) in separate experiments. Mobility can cause links to break, leading to disconnected partitions. We identify critical nodes in the network, whose failure may cause a partition. We introduce two new metrics based on social-network analysis: the Localized Bridging Centrality (LBC) metric and the Localized Load-aware Bridging Centrality (LLBC) metric, that can identify critical nodes efficiently and in a fully distributed manner. We run a monitoring component on client nodes, called Mesh-Mon-Ami, which also assists Mesh-Mon nodes in the dissemination of management information between physically disconnected partitions, by acting as carriers for management data. We conclude, from our experimental evaluation on our 16-node Dart-Mesh testbed, that our system solves several management challenges in a scalable manner, and is a useful and effective tool for monitoring and managing real-world mesh networks

    Demand Response on domestic thermostatically controlled loads

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    Dimensionerings- en werkverdelingsalgoritmen voor lambda grids

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    Grids bestaan uit een verzameling reken- en opslagelementen die geografisch verspreid kunnen zijn, maar waarvan men de gezamenlijke capaciteit wenst te benutten. Daartoe dienen deze elementen verbonden te worden met een netwerk. Vermits veel wetenschappelijke applicaties gebruik maken van een Grid, en deze applicaties doorgaans grote hoeveelheden data verwerken, is het noodzakelijk om een netwerk te voorzien dat dergelijke grote datastromen op betrouwbare wijze kan transporteren. Optische transportnetwerken lenen zich hier uitstekend toe. Grids die gebruik maken van dergelijk netwerk noemt men lambda Grids. Deze thesis beschrijft een kader waarin het ontwerp en dimensionering van optische netwerken voor lambda Grids kunnen beschreven worden. Ook wordt besproken hoe werklast kan verdeeld worden op een Grid eens die gedimensioneerd is. Een groot deel van de resultaten werd bekomen door simulatie, waarbij gebruik gemaakt wordt van een eigen Grid simulatiepakket dat precies focust op netwerk- en Gridelementen. Het ontwerp van deze simulator, en de daarbijhorende implementatiekeuzes worden dan ook uitvoerig toegelicht in dit werk

    ADAPTIVE POWER MANAGEMENT FOR COMPUTERS AND MOBILE DEVICES

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    Power consumption has become a major concern in the design of computing systems today. High power consumption increases cooling cost, degrades the system reliability and also reduces the battery life in portable devices. Modern computing/communication devices support multiple power modes which enable power and performance tradeoff. Dynamic power management (DPM), dynamic voltage and frequency scaling (DVFS), and dynamic task migration for workload consolidation are system level power reduction techniques widely used during runtime. In the first part of the dissertation, we concentrate on the dynamic power management of the personal computer and server platform where the DPM, DVFS and task migrations techniques are proved to be highly effective. A hierarchical energy management framework is assumed, where task migration is applied at the upper level to improve server utilization and energy efficiency, and DPM/DVFS is applied at the lower level to manage the power mode of individual processor. This work focuses on estimating the performance impact of workload consolidation and searching for optimal DPM/DVFS that adapts to the changing workload. Machine learning based modeling and reinforcement learning based policy optimization techniques are investigated. Mobile computing has been weaved into everyday lives to a great extend in recent years. Compared to traditional personal computer and server environment, the mobile computing environment is obviously more context-rich and the usage of mobile computing device is clearly imprinted with user\u27s personal signature. The ability to learn such signature enables immense potential in workload prediction and energy or battery life management. In the second part of the dissertation, we present two mobile device power management techniques which take advantage of the context-rich characteristics of mobile platform and make adaptive energy management decisions based on different user behavior. We firstly investigate the user battery usage behavior modeling and apply the model directly for battery energy management. The first technique aims at maximizing the quality of service (QoS) while keeping the risk of battery depletion below a given threshold. The second technique is an user-aware streaming strategies for energy efficient smartphone video playback applications (e.g. YouTube) that minimizes the sleep and wake penalty of cellular module and at the same time avoid the energy waste from excessive downloading. Runtime power and thermal management has attracted substantial interests in multi-core distributed embedded systems. Fast performance evaluation is an essential step in the research of distributed power and thermal management. In last part of the dissertation, we present an FPGA based emulator of multi-core distributed embedded system designed to support the research in runtime power/thermal management. Hardware and software supports are provided to carry out basic power/thermal management actions including inter-core or inter-FPGA communications, runtime temperature monitoring and dynamic frequency scaling

    Development of mobile agent framework in wireless sensor networks for multi-sensor collaborative processing

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    Recent advances in processor, memory and radio technology have enabled production of tiny, low-power, low-cost sensor nodes capable of sensing, communication and computation. Although a single node is resource constrained with limited power, limited computation and limited communication bandwidth, these nodes deployed in large number form a new type of network called the wireless sensor network (WSN). One of the challenges brought by WSNs is an efficient computing paradigm to support the distributed nature of the applications built on these networks considering the resource limitations of the sensor nodes. Collaborative processing between multiple sensor nodes is essential to generate fault-tolerant, reliable information from the densely-spatial sensing phenomenon. The typical model used in distributed computing is the client/server model. However, this computing model is not appropriate in the context of sensor networks. This thesis develops an energy-efficient, scalable and real-time computing model for collaborative processing in sensor networks called the mobile agent computing paradigm. In this paradigm, instead of each sensor node sending data or result to a central server which is typical in the client/server model, the information processing code is moved to the nodes using mobile agents. These agents carry the execution code and migrate from one node to another integrating result at each node. This thesis develops the mobile agent framework on top of an energy-efficient routing protocol called directed diffusion. The mobile agent framework described has been mapped to collaborative target classification application. This application has been tested in three field demos conducted at Twentynine palms, CA; BAE Austin, TX; and BBN Waltham, MA

    Artificial intelligence (AI) methods in optical networks: A comprehensive survey

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    Producción CientíficaArtificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.Ministerio de Economía, Industria y Competitividad (Project EC2014-53071-C3-2-P, TEC2015-71932-REDT
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