8,491 research outputs found

    Mobile object location discovery in unpredictable environments

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    Emerging mobile and ubiquitous computing environments present hard challenges to software engineering. The use of mobile code has been suggested as a natural fit for simplifing software development for these environments. However, the task of discovering mobile code location becomes a problem in unpredictable environments when using existing strategies, designed with fixed and relatively stable networks in mind. This paper introduces AMOS, a mobile code platform augmented with a structured overlay network. We demonstrate how the location discovery strategy of AMOS has better reliability and scalability properties than existing approaches, with minimal communication overhead. Finally, we demonstrate how AMOS can provide autonomous distribution of effort fairly throughout a network using probabilistic methods that requires no global knowledge of host capabilities

    Transparent and scalable client-side server selection using netlets

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    Replication of web content in the Internet has been found to improve service response time, performance and reliability offered by web services. When working with such distributed server systems, the location of servers with respect to client nodes is found to affect service response time perceived by clients in addition to server load conditions. This is due to the characteristics of the network path segments through which client requests get routed. Hence, a number of researchers have advocated making server selection decisions at the client-side of the network. In this paper, we present a transparent approach for client-side server selection in the Internet using Netlet services. Netlets are autonomous, nomadic mobile software components which persist and roam in the network independently, providing predefined network services. In this application, Netlet based services embedded with intelligence to support server selection are deployed by servers close to potential client communities to setup dynamic service decision points within the network. An anycast address is used to identify available distributed decision points in the network. Each service decision point transparently directs client requests to the best performing server based on its in-built intelligence supported by real-time measurements from probes sent by the Netlet to each server. It is shown that the resulting system provides a client-side server selection solution which is server-customisable, scalable and fault transparent

    QoS routing in ad-hoc networks using GA and multi-objective optimization

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    Much work has been done on routing in Ad-hoc networks, but the proposed routing solutions only deal with the best effort data traffic. Connections with Quality of Service (QoS) requirements, such as voice channels with delay and bandwidth constraints, are not supported. The QoS routing has been receiving increasingly intensive attention, but searching for the shortest path with many metrics is an NP-complete problem. For this reason, approximated solutions and heuristic algorithms should be developed for multi-path constraints QoS routing. Also, the routing methods should be adaptive, flexible, and intelligent. In this paper, we use Genetic Algorithms (GAs) and multi-objective optimization for QoS routing in Ad-hoc Networks. In order to reduce the search space of GA, we implemented a search space reduction algorithm, which reduces the search space for GAMAN (GA-based routing algorithm for Mobile Ad-hoc Networks) to find a new route. We evaluate the performance of GAMAN by computer simulations and show that GAMAN has better behaviour than GLBR (Genetic Load Balancing Routing).Peer ReviewedPostprint (published version

    Resilient availability and bandwidth-aware multipath provisioning for media transfer over the internet (Best Paper Award)

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    Traditional routing in the Internet is best-effort. Path differentiation including multipath routing is a promising technique to be used for meeting QoS requirements of media intensive applications. Since different paths have different characteristics in terms of latency, availability and bandwidth, they offer flexibility in QoS and congestion control. Additionally protection techniques can be used to enhance the reliability of the network. This paper studies the problem of how to optimally find paths ensuring maximal bandwidth and resiliency of media transfer over the network. In particular, we propose two algorithms to reserve network paths with minimal new resources while increasing the availability of the paths and enabling congestion control. The first algorithm is based on Integer Linear Programming which minimizes the cost of the paths and the used resources. The second one is a heuristic-based algorithm which solves the scalability limitations of the ILP approach. The algorithms ensure resiliency against any single link failure in the network. The experimental results indicate that using the proposed schemes the connections availability improve significantly and a more balanced load is achieved in the network compared to the shortest path-based approaches

    NeuRoute: Predictive Dynamic Routing for Software-Defined Networks

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    This paper introduces NeuRoute, a dynamic routing framework for Software Defined Networks (SDN) entirely based on machine learning, specifically, Neural Networks. Current SDN/OpenFlow controllers use a default routing based on Dijkstra algorithm for shortest paths, and provide APIs to develop custom routing applications. NeuRoute is a controller-agnostic dynamic routing framework that (i) predicts traffic matrix in real time, (ii) uses a neural network to learn traffic characteristics and (iii) generates forwarding rules accordingly to optimize the network throughput. NeuRoute achieves the same results as the most efficient dynamic routing heuristic but in much less execution time.Comment: Accepted for CNSM 201

    Software Defined Networks based Smart Grid Communication: A Comprehensive Survey

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    The current power grid is no longer a feasible solution due to ever-increasing user demand of electricity, old infrastructure, and reliability issues and thus require transformation to a better grid a.k.a., smart grid (SG). The key features that distinguish SG from the conventional electrical power grid are its capability to perform two-way communication, demand side management, and real time pricing. Despite all these advantages that SG will bring, there are certain issues which are specific to SG communication system. For instance, network management of current SG systems is complex, time consuming, and done manually. Moreover, SG communication (SGC) system is built on different vendor specific devices and protocols. Therefore, the current SG systems are not protocol independent, thus leading to interoperability issue. Software defined network (SDN) has been proposed to monitor and manage the communication networks globally. This article serves as a comprehensive survey on SDN-based SGC. In this article, we first discuss taxonomy of advantages of SDNbased SGC.We then discuss SDN-based SGC architectures, along with case studies. Our article provides an in-depth discussion on routing schemes for SDN-based SGC. We also provide detailed survey of security and privacy schemes applied to SDN-based SGC. We furthermore present challenges, open issues, and future research directions related to SDN-based SGC.Comment: Accepte

    A Survey on the Contributions of Software-Defined Networking to Traffic Engineering

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    Since the appearance of OpenFlow back in 2008, software-defined networking (SDN) has gained momentum. Although there are some discrepancies between the standards developing organizations working with SDN about what SDN is and how it is defined, they all outline traffic engineering (TE) as a key application. One of the most common objectives of TE is the congestion minimization, where techniques such as traffic splitting among multiple paths or advanced reservation systems are used. In such a scenario, this manuscript surveys the role of a comprehensive list of SDN protocols in TE solutions, in order to assess how these protocols can benefit TE. The SDN protocols have been categorized using the SDN architecture proposed by the open networking foundation, which differentiates among data-controller plane interfaces, application-controller plane interfaces, and management interfaces, in order to state how the interface type in which they operate influences TE. In addition, the impact of the SDN protocols on TE has been evaluated by comparing them with the path computation element (PCE)-based architecture. The PCE-based architecture has been selected to measure the impact of SDN on TE because it is the most novel TE architecture until the date, and because it already defines a set of metrics to measure the performance of TE solutions. We conclude that using the three types of interfaces simultaneously will result in more powerful and enhanced TE solutions, since they benefit TE in complementary ways.European Commission through the Horizon 2020 Research and Innovation Programme (GN4) under Grant 691567 Spanish Ministry of Economy and Competitiveness under the Secure Deployment of Services Over SDN and NFV-based Networks Project S&NSEC under Grant TEC2013-47960-C4-3-

    Adaptive Dispatching of Tasks in the Cloud

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    The increasingly wide application of Cloud Computing enables the consolidation of tens of thousands of applications in shared infrastructures. Thus, meeting the quality of service requirements of so many diverse applications in such shared resource environments has become a real challenge, especially since the characteristics and workload of applications differ widely and may change over time. This paper presents an experimental system that can exploit a variety of online quality of service aware adaptive task allocation schemes, and three such schemes are designed and compared. These are a measurement driven algorithm that uses reinforcement learning, secondly a "sensible" allocation algorithm that assigns jobs to sub-systems that are observed to provide a lower response time, and then an algorithm that splits the job arrival stream into sub-streams at rates computed from the hosts' processing capabilities. All of these schemes are compared via measurements among themselves and with a simple round-robin scheduler, on two experimental test-beds with homogeneous and heterogeneous hosts having different processing capacities.Comment: 10 pages, 9 figure
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