Destination-based Routing Research Articles

Enhanced Message Replication Technique for DTN Routing Protocols

Delay-tolerant networks (DTNs) are networks where there is no immediate connection between the source and the destination. Instead, nodes in these networks use a store-carry-forward method to route traffic. However, approaches that rely on flooding the network with unlimited copies of messages may not be effective if network resources are limited. On the other hand, quota-based approaches are more resource-efficient but can have low delivery rates and high delivery delays. This paper introduces the Enhanced Message Replication Technique (EMRT), which dynamically adjusts the number of message replicas based on a node's ability to quickly disseminate the message. This decision is based on factors such as current connections, encounter history, buffer size history, time-to-live values, and energy. The EMRT is applied to three different quota-based protocols: Spray and Wait, Encounter-Based Routing (EBR), and the Destination-Based Routing Protocol (DBRP). The simulation results show that applying the EMRT to these protocols improves the delivery ratio, overhead ratio, and latency average. For example, when combined with Spray and Wait, EBR, and DBRP, the delivery probability is improved by 13%, 8%, and 10%, respectively, while the latency average is reduced by 51%, 14%, and 13%, respectively.

Mitigating Routing Update Overhead for Traffic Engineering by Combining Destination-Based Routing With Reinforcement Learning

Traffic Engineering (TE) is a widely-adopted network operation to optimize network performance and resource utilization. Destination-based routing is supported by legacy routers and more readily deployed than flow-based routing, where the forwarding entries could be frequently updated by TE to accommodate traffic dynamics. However, as the network size grows, destination-based TE could render high time complexity when generating and updating many forwarding entries, which may limit the responsiveness of TE and degrade network performance. In this paper, we propose a novel destination-based TE solution called FlexEntry, which leverages emerging Reinforcement Learning (RL) to reduce the time complexity and routing update overhead while achieving good network performance simultaneously. For each traffic matrix, FlexEntry only updates a few forwarding entries called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">critical entries</i> for redistributing a small portion of the total traffic to improve network performance. These critical entries are intelligently selected by RL with traffic split ratios optimized by Linear Programming (LP). We find out that the combination of RL and LP is very effective. Our simulation results on six real-world network topologies show that FlexEntry reduces up to 99.3% entry updates on average and generalizes well to unseen traffic matrices with near-optimal load balancing performance.

Network Mobility Management Challenges, Directions, and Solutions: An Architectural Perspective

Efficient mobility management solutions are essential to provide users with seamless connectivity and session continuity during movement. However, user mobility was not envisaged as one of the early Internet’s use cases due to the early adoption of destination based routing and the assumption that end-nodes are static. This has become a critical hinder for providing efficient mobility support. This paper presents the challenges, drivers, and solutions that aim to overcome the drawbacks of current mobility management approaches. Furthermore, it introduces a promising solution that builds on emerging path-based forwarding architectures that identify network links rather than end nodes. Delivery path information is stored inside the packet while forwarding is achieved by performing a simple set membership test rather than the current destination-based routing approach. Mobility management in these architectures simply requires partial recomputation of the delivery path allowing for efficient mobility support over an optimal path. Evaluation results show significant cost savings in terms of delivery paths and end-to-end packet delay when using a path forwarding architecture.

Mitigating Broadcasting Storm Using Multihead Nomination Clustering in Vehicular Content Centric Networks

Vehicles are highly mobile nodes; therefore, they frequently change their topology. To maintain a stable connection with the server in high-speed vehicular networks, the handover process is restarted again to satisfy the content requests. To satisfy the requested content, a vehicular-content-centric network (VCCN) is proposed. The proposed scheme adopts in-network caching instead of destination-based routing to satisfy the requests. In this regard, various routing protocols have been proposed to increase the communication efficiency of VCCN. Despite disruptive communication links due to head vehicle mobility, the vehicles create a broadcasting storm that increases communication delay and packet drop fraction. To address the issues mentioned above in the VCCN, we proposed a multihead nomination clustering scheme. It extends the hello packet header to get the vehicle information from the cluster vehicles. The novel cluster information table (CIT) has been proposed to maintain several nominated head vehicles of a cluster on roadside units (RSUs). In disruptive communication links due to the head vehicle’s mobility, the RSU nominates the new head vehicle using CIT entries, resulting in the elimination of the broadcasting storm effect on disruptive communication links. Finally, the proposed scheme increases the successful communication rate, decreases the communication delay, and ensures a high cache success ratio on an increasing number of vehicles.

Load-Optimal Local Fast Rerouting for Dense Networks

Reliable and highly available computer networks must implement resilient fast rerouting mechanisms: upon a link or node failure, an alternative route is determined quickly, without involving the network control plane. Designing such fast failover mechanisms capable of dealing with multiple concurrent failures, however, is challenging, as failover rules need to be installed proactively , i.e., ahead of time, without knowledge of the actual failures happening at runtime. Indeed, only little is known today about the design of resilient routing algorithms. This paper introduces a general framework to reason about and design local failover algorithms that minimize the resulting load after failover on dense networks, beyond destination-based routing. We show that due to the inherent locality of the failover decisions at runtime, the problem is fundamentally related to the field of distributed algorithms without coordination . We derive an intriguing lower bound on the inherent network load overhead any local fast failover scheme that will introduce in the worst case, even though globally seen, much more balanced traffic allocations exist. We then present different randomized and deterministic failover algorithms and analyze their overhead load. In particular, we build upon the theory of combinatorial designs and develop a novel deterministic failover mechanism based on symmetric block design theory , which tolerates a maximal number of link failures while ensuring low loads.

Tomographic Node Placement Strategies and the Impact of the Routing Model

Fault-tolerant computer networks rely on mechanisms supporting the fast detection of link failures. Tomographic techniques can be used to implement such mechanisms at low cost: it is often sufficient to deploy a small number of tomography nodes exchanging probe messages along paths between them and detect link failures based on these messages. Our paper studies a practically relevant aspect of network tomography: the impact of the routing model. While the relevance of the routing model on path diversity and hence tomography cost is obvious and well-known on an anecdotal level, we lack an analytical framework to quantify the influence of different routing models (such as destination-based routing) exists. This paper fills this gap and introduces a formal model for asymmetric network tomography and a taxonomy of path routing models. This facilitates algorithmic reasoning about tomographic placement problems and quantifying the difference between routing models. In particular, we provide optimal and near-optimal algorithms to deploy a minimal number of asymmetric and symmetric tomography nodes for basic network topologies (modelled as graphs) under different routing model classes. Interestingly, we find that in many cases routing according to a more restrictive routing model gives better results: compared to a more general routing model, computing a good placement is algorithmically more tractable and does not entail high monitoring costs, a desirable trade-off in practice.

Load Balancing in IP Networks Using Generalized Destination-Based Multipath Routing

Intradomain traffic engineering (TE) has become an indispensable tool for Internet service providers (ISPs) to optimize network performance and utilize network resources efficiently. Various explicit routing TE methods were recently proposed and have been able to achieve high network performance. However, explicit routing has high complexity and requires large ternary content addressable memories (TCAMs) in the routers. Moreover, it is costly to deploy explicit routing in IP networks. In this paper, we present an approach, called generalized destination-based multipath routing (GDMR), to achieve the same high performance as explicit routing. The main contribution of this paper is that we prove that an arbitrary explicit routing can be converted to a loop-free destination-based routing without any performance penalty for a given traffic matrix. We present a systematic approach including a heuristic algorithm to realize GDMR. Extensive evaluation demonstrates the effectiveness and robustness of GDMR.

멀티미디어 인터넷망의 최적화 전송을 위한 라벨링망 응용 정책설정 고찰

ABSTRACT Traditional IP routing, see only the Destination Address When Forwarding Layer 3 routing and exchange information and Destination-Based Routing Lookup is required for all Hop. Thus, all routers Full Internet routing information, the route information of more than about 120,000 may require. Therefore, the router configuration, which can be dispersed in the environment, the traffic load is required in accordance with this congestion. In this study, a unique characteristic of the Internet in the environment of an existing network Best Effect for QoS guarantee and hardware high speed switching of large multimedia data transmitted using a Labeling for forwarding a packet environment configuration is required. Video Stream Broadcast Transport Labeling rather than in much of the higher performance of the multi-step policy to most of the Video Stream Packet deulim was fixed to Labeling Header Format proposes a method of applying an effective QoS policy to a more simplified policy. 키워드 :

Polynomial-time algorithms for special cases of the maximum confluent flow problem

A flow on a directed network is said to be confluent if the flow uses at most one outgoing arc at each node. Confluent flows arise naturally in destination-based routing. We study the maximum confluent flow problem (MaxConf) with a single commodity but multiple sources and sinks and heterogeneous arc capacities. It was recently shown that MaxConf is NP-hard even on trees. We improve the classification of easy and hard confluent flow problems by providing polynomial-time algorithms for outerplanar graphs with a single sink, as well as trees with a constant number of either sources or sinks. Furthermore, we present an FPTAS for graphs with bounded treewidth.

A scalable publish/subscribe system for large mobile ad hoc networks

Since nodes that compose mobile ad hoc networks (MANETs) does not have any prior knowledge about other nodes in many cases, the publish/subscribe communication paradigm that has the decoupling and asynchrony properties can be useful to share information between nodes. Existing publish/subscribe services for MANETs can be categorized into document flooding (DF), destination-based routing (DBR), and content-based routing (CBR). Although those approaches may work well when the size of network is small, all of them suffer from the performance decline as the size of the network increases. In this paper, we compare those approaches, and then propose a scalable publish/subscribe communication scheme in large MANETs by combining DF and CBR hierarchically. Our approach is to cluster all nodes in networks and to exploit CBR and DF for the intra- and inter-cluster communication, respectively. By using this approach, we can effectively utilize benefits of both approaches. Then, we present performance evaluation results which validate our idea with respect to system performance and scalability.

Benefits of traffic engineering using QoS routing schemes and network controls

We demonstrate the benefits of traffic engineering by studying three realistic network models derived from an actual service provider network. We evaluate traffic engineering in the presence of QoS-based routing schemes compared with Destination-Based Routing, the default routing behavior for the Internet. We also simulate prioritization of important traffic flows by implementing priority in one or more of the path caching, path ordering, and actual route selection phases of the constraint-based routing framework. We observe that traffic engineering can provide 20–50% network capacity savings. We also observe that prioritization in more than one phase of constraint-based routing can provide even more significant benefits.

Path selection and bandwidth allocation in MPLS networks

Multi-protocol label switching extends the IP destination-based routing protocols to provide new and scalable routing capabilities in connectionless networks using relatively simple packet forwarding mechanisms. MPLS networks carry traffic on virtual connections called label switched paths. This paper considers path selection and bandwidth allocation in MPLS networks in order to optimize the network quality of service. The optimization is based upon the minimization of a non-linear objective function which under light load simplifies to OSPF routing with link metrics equal to the link propagation delays. The behavior under heavy load depends on the choice of certain parameters. It can essentially be made to minimize maximal expected utilization, or to maximize minimal expected weighted slacks (both over all links). Under certain circumstances it can be made to minimize the probability that a link has an instantaneous offered load larger than its transmission capacity. We present a model of an MPLS network and an algorithm which optimally distributes the traffic among a set of active paths and reserves a set of back-up paths for carrying the traffic of failed or congested paths. The algorithm is an improvement of the well-known flow deviation non-linear programming method. The algorithm is applied to compute optimal LSPs for a 100-node network carrying a single traffic class. A link carrying some 1400 routes fails. The back-up paths are activated and we compare the performance of the path sets before and after the back-up paths are deployed.