Localised quality of service (QoS) routing has recently been proposed as a viable alternative approach to traditional QoS routing algorithms that use global state information. In this approach, problems associated wit...
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Localised quality of service (QoS) routing has recently been proposed as a viable alternative approach to traditional QoS routing algorithms that use global state information. In this approach, problems associated with maintaining global state information are avoided by having the source nodes to infer the network QoS state based on flow blocking statistics collected locally, and perform flow routing using this localised view of the network QoS state. A credit based routing algorithm (CBR) which is a simple yet effective localised QoS routing algorithm is introduced. Its performance is compared against the localised proportional sticky routing (PSR) algorithm using different types of network topologies, QoS requirements and traffic patterns and under a wide range of traffic loads. Extensive simulations show that the algorithm outperforms the PSR scheme while maintaining the same level of adaptivity and stability. Its performance is also compared against the global widest-shortest path algorithm (WSP) and it is shown that CBR gives a comparable performance with better time complexity and very low communication overhead.
As the most important fabric of fixed networks, the optical network plays an important role in expanding network capacity and providing long distance communication. At present, the fixed network has entered a key era,...
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As the most important fabric of fixed networks, the optical network plays an important role in expanding network capacity and providing long distance communication. At present, the fixed network has entered a key era, i.e., the fifth-generation fixed network (F5G). As one of the main features of F5G, the full-fiber connection requires a tenfold to hundredfold increase in the number of connections, which means F5G will have tens of thousands of nodes and millions of connections. Large-scale networks are composed of multiple network domains connected to each other. The whole network can be subdivided according to network functional domain. To meet different service requirements, how to provision fast end-to-end service in a multi-domain scenario has become a key issue. In optical networks, lightpath establishment must precede service transmission. The latency of lightpath establishment includes lightpath establishment signaling latency and optical interleaving device configuration latency. The latter depends on equipment performance. Therefore, how to provision fast lightpath establishment signaling is a key problem. To reduce end-to-end service provisioning latency, we propose an extended-segment-routing-based fast service provisioning scheme for the first time, to our knowledge, which consists of two steps: signaling path acquisition and signaling provisioning. For the signaling path acquisition step, we propose an adaptive segment routing (ASR) algorithm that first performs service path calculation based on service requirements, then performs a label compression algorithm to obtain the signaling path represented by the minimum number of labels according to the service path. For the signaling provisioning step, we propose a fast-signaling provisioning (FSP) process that can realize fast signaling provisioning in both single-domain and multi-domain scenarios. The simulation results show that, (1) compared to the Dijkstra algorithm, the ASR algorithm achieves a lower
Wireless sensor networks (WSNs) are networks with devices that can detect, process, store, and communicate wirelessly. Each network terminal can have multiple sensing devices that can measure physical variations such ...
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Wireless sensor networks (WSNs) are networks with devices that can detect, process, store, and communicate wirelessly. Each network terminal can have multiple sensing devices that can measure physical variations such as temperature, brightness, humidity, and vibration. However, developing and implementing WSNs poses many challenges. This review presents the challenges of WSN using different routing algorithms such as geographic routing, energy-aware routing, delay aware routing, QoS aware routing, secure aware routing, and hierarchical aware routing. Another goal is to find out which WSN component automates interference and behavior. What kind of application is in the WSN depends not only on his work but also on the question of the basis, functionality, and handling of his project. The study was carefully planned, and the systematic review of the literature was set up in a strong framework according to a pre-defined protocol. Finally, we evaluate the performance parameters of previous routing algorithms with diverse routine metrics that are energy consumption, delay, packet delivery ratio, throughput, false ratio, packet loss ratio, and network overhead.
In real time distribution operations, It is generally assumed that demand process parameters can be precisely estimated However, this is rarely the case, particularly for products with a short life cycle Experiments w...
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In real time distribution operations, It is generally assumed that demand process parameters can be precisely estimated However, this is rarely the case, particularly for products with a short life cycle Experiments were done to investigate the performance of various strategies for online distribution operations under disruptions caused by surges in demand patterns at a particular facility Two sets of strategies are considered (a) optimization based strategies, in which an off line optimization problem is formulated and used to update routing and inventory allocation plans, and (b) fixed tour strategies, in which a priori sets of routes to provide retailers with recourse actions depending on different degrees of real time information capabilities for controlling the system are used These are compared against two benchmark policies Simulation results for two scenarios (high and low inventory holding cost products) show that strategies that use real time information to update delivery plans systematically outperform strategies in which routes are not modified after the vehicle leaves the depot The differences tend to be higher in scenarios of products with low Inventory holding costs For replanning strategies, the benefits of en route plan updates are significant, in particular the possibility of diverting the vehicle In the case of fixed tour strategies, the possibility of updating tour Intervals provides potentially great savings Replanning strategies systematically outperform fixed tour strategies
We present two routing algorithms based on deflection and convergence, which are able to provide high bandwidth and an ending guarantee for the end-to-end delay in a core network. We study the performance of these rou...
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We present two routing algorithms based on deflection and convergence, which are able to provide high bandwidth and an ending guarantee for the end-to-end delay in a core network. We study the performance of these routing techniques by using simulations, and we prove the bounds on the delay.
We use the incompressibility method based on Kolmogorov complexity to determine the total number of bits of routing information for almost all network topologies. In most models for routing, for almost all labeled gra...
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We use the incompressibility method based on Kolmogorov complexity to determine the total number of bits of routing information for almost all network topologies. In most models for routing, for almost all labeled graphs, Theta(n(2)) bits are necessary and sufficient for shortest path routing. By "almost all graphs" we mean the Kolmogorov random graphs which constitute a fraction of 1 ? 1/n(c) of all graphs on n nodes, where c > 0 is an arbitrary fixed constant. There is a model for which the average case lower bound rises to Omega(n(2) log n) and another model where the average case upper bound drops to O(n log(2) n). This clearly exposes the sensitivity of such bounds to the model under consideration. If paths have to be short, but need not be shortest (if the stretch factor may be larger than 1), then much less space is needed on average, even in the more demanding models. Full-information routing requires Theta(n(3)) bits on average. For worst-case static networks we prove an Omega(n(2) log n) lower bound for shortest path routing and all stretch factors < 2 in some networks where free relabeling is not allowed.
End-to-end delay, power consumption, and communication cost are some of the most important metrics in a mobile ad hoc network (MANET) when routing from a source to a destination. Recent approaches using the swarm inte...
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End-to-end delay, power consumption, and communication cost are some of the most important metrics in a mobile ad hoc network (MANET) when routing from a source to a destination. Recent approaches using the swarm intelligence (SI) technique proved that the local interaction of several simple agents to meet a global goal has a significant impact on MANET routing. In this work, a hybrid routing intelligent algorithm that has an ant colony optimisation (ACO) algorithm and particle swarm optimisation (PSO) is used to improve the various metrics in MANET routing. The ACO algorithm uses mobile agents as ants to identify the most feasible and best path in a network. Additionally, the ACO algorithm helps to locate paths between two nodes in a network and provides input to the PSO technique, which is a metaheuristic approach in SI. The PSO finds the best solution for a particle's position and velocity and minimises cost, power, and end-to-end delay. This hybrid routing intelligent algorithm has an improved performance when compared with the simple ACO algorithm in terms of delay, power consumption, and communication cost. (C) 2014 Elsevier Ltd. All rights reserved.
With the rapid development of Telematics, Vehicle Self-Organizing Networks (VANETs) play an increasingly critical role in Intelligent Transportation Systems (ITS). Especially in the environment without roadside assist...
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With the rapid development of Telematics, Vehicle Self-Organizing Networks (VANETs) play an increasingly critical role in Intelligent Transportation Systems (ITS). Especially in the environment without roadside assistance units (RSUs), how to effectively manage inter-vehicle communication and improve the stability and communication efficiency of the network has become a hot topic of current research. In this paper, a Deep Reinforcement Learning-based Intelligent QoS-optimized efficient routing algorithm for vehicular networks (DRLIQ) is proposed for VANETs with/without RSU environments, and routing methods are proposed respectively. Among them, in RSU-free environment, the DRLIQ algorithm utilizes the powerful processing capability of deep reinforcement learning to intelligently select the optimal data transmission path by dynamically learning and adapting to the changes in the vehicular network, thus effectively reducing communication interruptions and delays, and improving the accuracy of data transmission. The performance of the DRLIQ algorithm under different vehicle densities is evaluated in simulation experiments and compared with current popular algorithms. The experimental results show that the DRLIQ algorithm outperforms the comparison algorithms in reducing the number of communication interruptions, BER and network delay, especially in vehicle-dense environments. In addition, the DRLIQ algorithm shows higher adaptability and stability in coping with network topology changes and vehicle dynamics.
In the big data environment, the social information of a large number of nodes cannot be reasonably analyzed and utilized, thus leading to the problem of uneven routing performance. Therefore, this paper proposes a So...
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In the big data environment, the social information of a large number of nodes cannot be reasonably analyzed and utilized, thus leading to the problem of uneven routing performance. Therefore, this paper proposes a Social Similarity routing Algorithm (SRRA) based on socially aware networks in the big data environment. In the SRRA algorithm, two main parts in which the process of nodes forwarding messages are in-community and out-of-community. First, we defined three indexes for nodes and communities in which nodes are located by analyzing human social behavior: community connectedness between communities, the activity of nodes, and the social similarity of nodes. Then these three indexes are used to make up two measures: the in-community forwarding measure and the out-of-community forwarding measure. When messages are forwarded within a community, we choose nodes with high in-community forwarding measures as relay nodes so that messages can be delivered quickly in the same community. The relay node with the highest out-of-community forwarding measure is chosen to forward the message to the adjacent communities that are as near as possible to the destination community as much as possible when messages are forwarded outside the community, which ensures that messages can always be sent to the target community fast and accurately. The results of the simulation experiments compared with existing routing algorithms prove that the SRRA routing algorithm significantly improves the message delivery ratio while effectively reducing the network overhead and average latency.
In this study, the author investigates the problem of lifetime enhancement of mobile nodes in mobile ad hoc networks. Here, the author uses two metrics namely, residual battery capacity of the node and non-critical no...
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In this study, the author investigates the problem of lifetime enhancement of mobile nodes in mobile ad hoc networks. Here, the author uses two metrics namely, residual battery capacity of the node and non-critical node to route the data packets from the source to the destination. The proposed model uses the non-critical node if all the nodes contain residual battery capacity above the threshold value. The proposed model has been simulated using Qualnet Simulator-4.5. The proposed model has compared against the existing algorithms such as minimum total transmission power routing, conditional max-min battery capacity routing and lifetime prediction routing. From the results, the author concludes that the proposed model has reached at the top position in terms of the number of survived nodes, energy saving and number of nodes with zero remaining energy.
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