3,622 research outputs found

    Possible Collision Avoidance with Off-line Route Selection

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    The paper describes the traffic flow problems in telecommunication networks based on the Internet protocol. The main aim of telecommunication network operator today is to offer an SLA (Service Level Agreement) contract to end users, with provided QoS (Quality of Service) for different classes of services. In order to achieve this, it is necessary to establish the routes between marginal network nodes meeting the network traffic requirements and optimizing the network performances free of simultaneous flows conflicts. In DiffServ/MPLS (Multi-Protocol Label Switching) networks traffic flows traverse the network simultaneously and there may come to collision of concurrent flows. They are distributed among LSPs (Labeled Switching Paths) related to service classes. In LSP creation the IGP (Interior Gateway Protocol) uses simple on-line routing algorithms based on the shortest path methodology. In highly loaded networks this becomes an insufficient technique. In this suggested approach LSP need not necessarily be the shortest path solution. It can be pre-computed much earlier, possibly during the SLA negotiation process. In that sense an effective algorithm for collision control is developed. It may find a longer but lightly loaded path, taking care of the collision possibility. It could be a very good solution for collision avoidance and for better load-balancing purpose where links are running close to capacity. The algorithm can be significantly improved through heuristic approach. Heuristic options are compared in test-examples and their application for collision control is explained. KEYWORDS: Telecommunication networks, collision avoidance, multi-constraint route selection, self-organizing systems, MPLS, Qo

    On Content-centric Wireless Delivery Networks

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    The flux of social media and the convenience of mobile connectivity has created a mobile data phenomenon that is expected to overwhelm the mobile cellular networks in the foreseeable future. Despite the advent of 4G/LTE, the growth rate of wireless data has far exceeded the capacity increase of the mobile networks. A fundamentally new design paradigm is required to tackle the ever-growing wireless data challenge. In this article, we investigate the problem of massive content delivery over wireless networks and present a systematic view on content-centric network design and its underlying challenges. Towards this end, we first review some of the recent advancements in Information Centric Networking (ICN) which provides the basis on how media contents can be labeled, distributed, and placed across the networks. We then formulate the content delivery task into a content rate maximization problem over a share wireless channel, which, contrasting the conventional wisdom that attempts to increase the bit-rate of a unicast system, maximizes the content delivery capability with a fixed amount of wireless resources. This conceptually simple change enables us to exploit the "content diversity" and the "network diversity" by leveraging the abundant computation sources (through application-layer encoding, pushing and caching, etc.) within the existing wireless networks. A network architecture that enables wireless network crowdsourcing for content delivery is then described, followed by an exemplary campus wireless network that encompasses the above concepts.Comment: 20 pages, 7 figures,accepted by IEEE Wireless Communications,Sept.201

    An Efficient Algorithm for Congestion Control in Highly Loaded DiffServ/MPLS Networks

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    Optimal QoS path provisioning of coexisted and aggregated traffic in networks is still demanding problem. All traffic flows in a domain are distributed among LSPs (Label Switching Path) related to N service classes, but the congestion problem of concurrent flows can appear. As we know the IGP (Interior Getaway Protocol) uses simple on-line routing algorithms (e.g. OSPFS, IS-IS) based on shortest path methodology. In QoS end-to-end provisioning where some links may be reserved for certain traffic classes (for particular set of users) it becomes insufficient technique. On other hand, constraint-based explicit routing (CR) based on IGP metric ensures traffic engineering (TE) capabilities. But in overloaded and poorly connected MPLS/DiffServ networks the CR becomes insufficient technique. As we need firm correlation with bandwidth management and traffic engineering (TE) the initial (pro-active) routing can be pre-computed in the context of all priority traffic flows (former contracted SLAs) traversing the network simultaneously. It mean that LSP can be pre-computed much earlier, possibly during SLA (Service Level Agreement) negotiation process. In the paper a new load simulation technique for load balancing control purpose is proposed. The algorithm proposed in the paper may find a longer but lightly loaded path, better than the heavily loaded shortest path. It could be a very good solution for congestion avoidance and for better load-balancing purpose where links are running close to capacity. Also, such technique could be useful in inter-domain end-to-end provisioning, where bandwidth reservation has to be negotiated with neighbor ASes (Autonomous System). To be acceptable for real applications such complicated routing algorithm can be significantly improved. Algorithm was tested on the network of M core routers on the path (between edge routers) and results are given for N=3 service classes. Further improvements through heuristic approach are made and results are discussed

    Minimization Problems in Signalized Road Networks

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    In this study, we present a bilevel programming model in which upper level is defined as a biobjective problem and the lower level is considered as a stochastic user equilibrium assignment problem. It is clear that the biobjective problem has two objectives: the first maximizes the reserve capacity whereas the second minimizes performance index of a road network. We use a weighted-sum method to determine the Pareto optimal solutions of the biobjective problem by applying normalization approach for making the objective functions dimensionless. Following, a differential evolution based heuristic solution algorithm is introduced to overcome the problem presented by use of biobjective bilevel programming model. The first numerical test is conducted on two-junction network in order to represent the effect of the weighting on the solution of combined reserve capacity maximization and delay minimization problem. Allsop & Charlesworth's network, which is a widely preferred road network in the literature, is selected for the second numerical application in order to present the applicability of the proposed model on a medium-sized signalized road network. Results support authorities who should usually make a choice between two conflicting issues, namely, reserve capacity maximization and delay minimization. C1 [Baskan, Ozgur; Ceylan, Huseyin] Pamukkale Univ, Dept Civil Engn, Fac Engn, TR-20160 Denizli, Turkey. [Ozan, Cenk] Adnan Menderes Univ, Dept Civil Engn, Fac Engn, TR-09100 Aydin, Turkey. Document type: Articl

    Solving Signal Control Problems with Second-Order Sensitivity Information of Equilibrium Network Flows

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    The equilibrium network signal control problem is represented as a Stackelberg game. Due to the characteristics of a Stackelberg game, solving the upper-level problem and lower-level problem iteratively cannot be expected to converge to the solution. The reaction function of the lower-level problem is the key information to solve a Stackelberg game. Usually, the reaction function is approximated by the network sensitivity information. This paper firstly presents the general form of the second-order sensitivity formula for equilibrium network flows. The second-order sensitivity information can be applied to the second-order reaction function to solve the network signal control problem efficiently. Finally, this paper also demonstrates two numerical examples that show the computation of second-order sensitivity and the speed of convergence of the nonlinear approximation algorithm
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