Flow-Aware Multi-Topology Adaptive Routing (FAMTAR) is a new approach to multipath and adaptive routing in IP networks which enables automatic use of alternative paths when the primary one becomes congested. It provides more efficient network resource utilization and higher quality of transmission compared to standard IP routing. However, thus far it has only been evaluated through simulations. In this paper we share our experiences from building a real-time FAMTAR router and present results of its tests in a physical network. The results are in line with those obtained previously through simulations and they open the way to implementation of a production grade FAMTAR router.
FAMTAR was developed to answer the aforementioned problems. This was possible thanks to the development of flow-aware traffic handling, such as Flow-Aware Networking (FAN) @cite_8 . There were attempts to increase the efficiency of routing with the use of FAN, as presented, for example, in @cite_7 . The technique of trunk reservation borrowed from the telephone network is proposed in this paper for route selection. It is assumed that a path for a flow is chosen based on the bandwidth it requires. Also, a simple intelligent routing for FAN is presented in @cite_2 , where it is assumed that only non-congested links are considered when forwarding packets. However, it is not specified how to inform all routers about the congested links. FAMTAR provides a solution to that problem. Moreover, FAMTAR is a general idea, not specific to FAN networks.
@cite_2 @cite_7 @cite_8
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A new algorithm for intelligent routing in Approximate Flow-Aware Networks (AFAN) is presented and analyzed in the paper. In contrast to basic AFAN, where cross-protect routers block excessive traffic under congestion, it assumes a possibility of using other routes to destination nodes based on the idea similar to load balancing. The analysis is provided for the AFAN concept, which is the newest version of Flow-Aware Networks (FAN). The simulation experiments, discussed in the paper, were provided for basic AFAN and for the network with one of two congestion control mechanisms, the Remove and Accept Most Active Flows (RAMAF) and Simple Congestion Control Mechanism (SCCM). These solutions allow for fast acceptance of streaming flows independently of the volume of traffic load in a network. The results are presented for four different simulation topologies and prove the advantages of the proposed intelligent routing approach. Moreover, it is shown that the SCCM ensures better transmission properties than the RAMAF. This paper deals with an energy saving routing solution, called Energy Saving IP Routing (ESIR), to be applied in an IP network. ESIR operation is integrated with Open Shorthest Path First (OSPF) protocol and allows the selection of the links to be switched off so that the negative effects of the IP topology reconfiguration procedures are avoided. The basic mechanisms which ESIR is based on are the concepts of SPT exportation and move. These mechanisms allow to share a Shortest Path Tree (SPT) between neighbor routers, so that the overall set of active network links can be reduced. Properties of moves are defined and the energy saving problem in an IP network is formulated as the problem of finding the Maximum Set of Compatible Moves (MSCM). The MSCM problem is investigated in two steps: firstly, a relaxed version of the problem, named basic MSCM problem, is considered in which QoS requirements are neglected; in the second step, the solution of the full problem, named QoS-aware MSCM problem, is faced. We prove that the basic MSCM problem can be formulated as the well-known Maximum Clique Problem in a graph; instead the QoS-aware MSCM introduces a condition equivalent to the Knapsack problem. ILP formulations to solve both the problems are given and heuristics to solve them in practical cases are proposed. The performance evaluation shows that in a real ISP network scenario ESIR is able to switch off up to 30 of network links by exploiting over-provisioning adopted by operators in the network resource planning phase and typical daily traffic trend. This paper compares two approaches to realizing adaptive routing in the Internet: flow-oblivious multi-path routing using optimal end-to-end congestion control and flow-aware routing using fair queueing to share bandwidth on one or several paths. Multi-path congestion control provides ideal performance, assuming protocols can be designed to approximate the optimal fluid model. Flow-aware networking is more robust and less dependent on user cooperation and provides satisfactory performance provided use of long paths is limited in heavy traffic by applying "trunk reservation". Since ad hoc and sensor networks can be composed of a very large number of devices, the scalability of network protocols is a major design concern. Furthermore, network protocols must be designed to prolong the battery lifetime of the devices. However, most existing routing techniques for ad hoc networks are known not to scale well. On the other hand, the so-called geographical routing algorithms are known to be scalable but their energy efficiency has never been extensively and comparatively studied. In a geographical routing algorithm, data packets are forwarded by a node to its neighbor based on their respective positions. The neighborhood of each node is constituted by the nodes that lie within a certain radio range. Thus, from the perspective of a node forwarding a packet, the next hop depends on the width of the neighborhood it perceives. The analytical framework proposed in this paper allows to analyze the relationship between the energy efficiency of the routing tasks and the extension of the range of the topology knowledge for each node. A wider topology knowledge may improve the energy efficiency of the routing tasks but increases the cost of topology information due to signaling packets needed to acquire this information. The problem of determining the optimal topology knowledge range for each node to make energy efficient geographical routing decisions is tackled by integer linear programming. It is shown that the problem is intrinsically localized, i.e., a limited topology knowledge is sufficient to make energy efficient forwarding decisions. The leading forwarding rules for geographical routing are compared in this framework, and the energy efficiency of each of them is studied. Moreover, a new forwarding scheme, partial topology knowledge forwarding (PTKF), is introduced, and shown to outperform other existing schemes in typical application scenarios. A probe-based distributed protocol for knowledge range adjustment (PRADA) is finally introduced that allows each node to efficiently select online its topology knowledge range. PRADA is shown to rapidly converge to a near-optimal solution.