Optimal Routing Strategy Research Articles

Extended Mobile IPv6 Route Optimization for Mobile Networks in Local and Global Mobility Domain

Network mobility (NEMO) route optimization support is strongly demanded in next generation networks; without route optimization the mobile network (e.g., a vehicle) tunnels all traffic to its Home Agent (HA). The mobility may cause the HA to be geographically distant from the mobile network, and the tunneling causes increased delay and overhead in the network. It becomes peculiar in the event of nesting of mobile networks due to pinball routing, for example, a Personal Area Network (PAN) inside a vehicle. The authors propose an Extended Mobile IPv6 route optimization (EMIP) scheme to enhance the performance of nested mobile networks in local and global mobility domain. The EMIP scheme is based on MIPv6 route optimization and the root Mobile Router (MR) performs all the route optimization tasks on behalf of all active Mobile Network Nodes (MNNs). Thus, the network movement remains transparent to sub MRs and MNNs and modifies only MRs and MNNs leaving other entities untouched and is more efficient than the Network Mobility Basic Support protocol (NEMO BS). The authors carried out an extensive simulation study to evaluate the performance of EMIP.

Distributed Algorithms for Minimum Cost Multicast With Network Coding

Network coding techniques are used to find the minimum-cost transmission scheme for multicast sessions with or without elastic rate demand. It is shown that in wireline networks, solving for the optimal coding subgraphs in network coding is equivalent to finding the optimal routing scheme in a multicommodity flow problem. A set of node-based distributed gradient projection algorithms are designed to jointly implement congestion control/routing at the source node and virtual routing at intermediate nodes. The analytical framework and distributed algorithms are further extended to interference-limited wireless networks where link capacities are functions of the signal-to-interference-plus-noise ratio (SINR). To achieve minimum-cost multicast in this setting, the transmission powers of links must be jointly optimized with coding subgraphs and multicast input rates. Node-based power allocation and power control algorithms are developed for the power optimization. The power algorithms, when iterated in conjunction with the congestion control and routing algorithms, converge to the jointly optimal multicast configuration. The scaling matrices required in the gradient projection algorithms are explicitly derived and are shown to guarantee fast convergence to the optimum from any initial condition.

Authenticated route optimization scheme for network mobility (NEMO) support in heterogeneous networks

AbstractFor the efficient communications between mobile or fixed hosts in mobile networks, the route optimization and its security are indispensable. So, the Internet Engineering Task Force introduced a NEMO basic support protocol in 2005. However, this protocol does not provide a strong security between hosts and especially in nested‐mobile network it can incur a pinball routing problem. And the previous Proxy Binding Update (PUB) protocol has an advantage that can prove the ownership of address of a host using Multi‐key Cryptographically Generated Address (MCGA) which can alleviate a neighbor bombing attack. However, a Mobile Network Node (MNN) belonging to the mobile network which can have low power or limited computing capability may be require burdened costs such as signification and verification of messages. Also, the PUB protocol does not provide the secure message communication architecture between the MNN and its Mobile Router (MR). In this paper we propose a CGA‐based Authentication Route Optimization scheme (CARO) in mobile hotspots with heterogeneous networks. The proposed CARO protocol satisfies two problems using IPsec Encapsulating Security Payload (ESP) tunnel, a secret mobile group key, and the CGA. And we also do not require the considerable computing costs to the MNN or a Correspondent Node. In performance analysis, we prove more secure and efficient protocols than the previous protocols using the defense of various attacks and the result of computational cost, etc. Copyright © 2010 John Wiley & Sons, Ltd.

A Security Routing Optimization Scheme for Multi-hop Wireless Networks

A Security Routing Optimization Scheme for Multi-hop Wireless Networks

ROAD+: Route Optimization with Additional Destination-Information and Its Mobility Management in Mobile Networks

In the NEtwork MObility (NEMO) environment, mobile networks can form a nested structure. In nested mobile networks that use the NEMO Basic Support (NBS) protocol, pinball routing problems occur because packets are routed to all the home agents of the mobile routers using nested tunneling. In addition, the nodes in the same mobile networks can communicate with each other regardless of Internet connectivity. However, the nodes in some mobile networks that are based on NBS cannot communicate when the network is disconnected from the Internet. In this paper, we propose a route optimization scheme to solve these problems. We introduce a new IPv6 routing header named “destination-information header” (DH), which uses DH instead of routing header type 2 to optimize the route in the nested mobile network. The proposed scheme shows at least 30% better performance than ROTIO and similar performance improvement as DBU in inter-route optimization. With respect to intra-route optimization, the proposed scheme always uses the optimal routing path. In addition, the handover mechanism in ROAD+ outperforms existing schemes and is less sensitive to network size than other existing schemes.

On routing strategy with finite-capacity effect on scale-free networks

We propose a class of systems with finite-capacity effect to investigate routing-strategy optimization. The local topology and the variable capacity, two crucial elements for routing, are naturally coupled by considering the interactions among packets. We show how the combination of these two elements controls the normal and efficient functioning of routing in the frame of condensation and coverage, respectively. Specifically, it is shown that the dynamic behaviors of diffusing packets exhibit condensation, for which exact results of the stationary state and phase transition are given. Further, we explore the diffusion coverage of routed packets through simulation. Various alternatives for the strategy parameters are illustrated to apply standard techniques to alleviate condensation and accelerate coverage. Our results provide a practical way for the design of optimal routing strategies in complex networks by the manipulation of a few parameters.

Route optimization in network mobility: Solutions, classification, comparison, and future research directions

Network mobility (NEMO) handles mobility of a set of mobile nodes in an aggregate way using one or more mobile routers. NEMO introduces several advantages, such as reduced signaling, increased manageability, reduced power consumption and conservation of bandwidth when compared to individual host mobility. NEMO Basic Support Protocol (BSP), the IETF standard for NEMO, suffers from a number of limitations, like inefficient route and increased handoff latency. Most of the recent research efforts on NEMO have concentrated on solving the problem of inefficient route resulting in several route optimization schemes to solve the problem. To choose a route optimization scheme, it is very important to have a quantitative comparison of the available route optimization schemes. The objective of this article is to survey, classify and compare the route optimization schemes proposed in the literature over the last five years. We classify the schemes based on the basic approach for route optimization, and compare the schemes based on protocol overhead, such as header overhead, amount of signalling, and memory requirements. We conclude that performance of the classes of schemes has to be evaluated under criteria such as available bandwidth, topology of the mobile network and mobility type.

Genetical Swarm Optimization of Multihop Routes in Wireless Sensor Networks

In recent years, wireless sensor networks have been attracting considerable research attention for a wide range of applications, but they still present significant network communication challenges, involving essentially the use of large numbers of resource-constrained nodes operating unattended and exposed to potential local failures. In order to maximize the network lifespan, in this paper, genetical swarm optimization (GSO) is applied, a class of hybrid evolutionary techniques developed in order to exploit in the most effective way the uniqueness and peculiarities of two classical optimization approaches; particle swarm optimization (PSO) and genetic algorithms (GA). This procedure is here implemented to optimize the communication energy consumption in a wireless network by selecting the optimal multihop routing schemes, with a suitable hybridization of different routing criteria, confirming itself as a flexible and useful tool for engineering applications.

Enhanced PMIPv6 Route Optimization Handover Using PFMIPv6

In PMIPv6, all packets sent by mobile nodes or correspondent nodes are transferred through the local mobility anchor. This unnecessary detour results in high delivery latency and significant processing cost. Several PMIPv6 route optimization schemes have been proposed to solve this issue. However, they also suffer from the high signaling costs when determining the optimized path. The proposed scheme which adopts the prediction algorithm in PFMIPv6 can reduce the signaling costs of the previous schemes. Analytical performance evaluation is performed to show the effectiveness of the proposed scheme.

Robust Routing and Scheduling in Wireless Mesh Networks under Dynamic Traffic Conditions

Joint routing-and-scheduling has been considered in wireless mesh networks for its significant performance improvement. While existing work assumes it, accurate traffic information is usually not available due to traffic dynamics, as well as inaccuracy and delay in its measurement and dissemination. In addition, the joint routing and scheduling usually requires a centralized controller to calculate the optimal routing and scheduling and distribute such policies to all the nodes. Thus, even if the accurate traffic information is always available, the central controller has to compute the routing and scheduling repeatedly because the traffic demands change continuously. This leads to prohibitive computation and distribution overhead. Therefore, in this paper, we propose a joint routing-scheduling scheme that achieves robust performance under traffic information uncertainty. In particular, it achieves worst-case optimal performance under a range of traffic conditions. This unique feature validates the use of centralized routing and scheduling in wireless mesh networks. As long as the traffic variation is within the estimation range, the routing and scheduling do not need to be recomputed and redistributed. Through extensive simulations, we show that our proposed scheme meets the objective (i.e., optimizes the worst-case performance). Moreover, although it only guarantees the worst-case performance in theory, its average performance is also good. For example, our proposed scheme can perform better than a fixed optimal routing and scheduling scheme in more than 80 percent of 500 random traffic instances. Our scheme provides insights on the desired properties of multipath routing, namely, spatial reuse and load balancing.

Route Learning in Vehicle Routing with Pickup and Delivery

We consider a multi-cluster vehicle routing problem with pickups and deliveries. A cluster consists of a set of nodes with requests for shipment. A single depot serves all requests in each cluster by means of capacitated trucks which pick up a consignment and deliver the same at nodes with delivery requests. A truck returns to its base depot after its consignment is exhausted or when the requirement of all nodes in a cluster is fully satisfied. Because of truck capacity constraints, multiple trips are required to serve all nodes. A truck can choose from among several alternate routing strategies. Trucks are evaluated for efficiency depending upon deliveries made and length of route covered. The computed efficiency depends on the routing strategy adopted by the truck. We provide details of a Genetic Algorithm for route selection and explain how we can examine whether any routing strategy does significantly better than others. The model and the experiments outlined are representative of a large number of combinational variations possible. The VRPPD1 transportation requirement is common to many companies and the results of these experiments can be used to determine optimal routing strategies for their eet of vehicles. Given the vast expenditure most company's incur in transshipment logistics, this has the potential to significantly reduce costs and increase a company's profitability.

A wireless access network based on WDM-PON for HMIPv6 mobility support

In this paper, an IP-based wireless access network is proposed, which is designed to support the hierarchical MIPv6 standard on the wavelength division multiplexed passive optical network access network in order to provide a fast and seamless handoff support. Two schemes for enhancing the mobility management are included in the proposed network's infrastructure support. Firstly, the local-link channels between sub-networks are provided to improve the mobility management efficiency for the mobile nodes roaming between neighboring sub-networks. Secondly, the early route optimization scheme has been applied, which optimizes the mobility management process between the corresponding node and the home agent (HA), resulting in reduced bandwidth waste and long end-to-end packet delays, as well as lowering the heavy burden on the HA. The performance of the proposed mobility management scheme has been evaluated in terms of handoff delays, packet losses and transmission costs. The superior performance of the proposed scheme has been verified and compared to other schemes.

Capacity Scaling in Ad Hoc Networks With Heterogeneous Mobile Nodes: The Super-Critical Regime

We analyze the capacity scaling laws of mobile ad hoc networks comprising heterogeneous nodes and spatial inhomogeneities. Most of previous work relies on the assumption that nodes are identical and uniformly visit the entire network space. Experimental data, however, show that the mobility pattern of individual nodes is usually restricted over the area, while the overall node density is often largely inhomogeneous due to the presence of node concentration points. In this paper we introduce a general class of mobile networks which incorporates both restricted mobility and inhomogeneous node density, and describe a methodology to compute the asymptotic throughput achievable in these networks by the store-carry-forward communication paradigm. We show how the analysis can be mapped, under mild assumptions, into a Maximum Concurrent Flow (MCF) problem over an associated Generalized Random Geometric Graph (GRGG). Moreover, we propose an asymptotically optimal scheduling and routing scheme that achieves the maximum network capacity.

Q Value-Based Dynamic Programming with Boltzmann Distribution for Global Optimal Traffic Routing Strategy

In this paper, we propose a heuristic method -- Boltzmann Optimal Route Method trying to find a good approximation to the global optimum route for Origin-Destination pairs through iterations until the total traveling time converges. The overall idea of our method is to update the traveling time of each route section iteratively according to its corresponding traffic volume, and continuously generate a new global route by Q value-based Dynamic Programming combined with Boltzmann distribution. Finally, we can get the global optimum route considering the traffic volumes of the road sections. The new proposed method is compared with the conventional shortest-path method- Greedy strategy both in the static traffic system where the volumes of all the given Origin-Destination pairs of road networks are constant and in the dynamic traffic system in which changing traffic volumes are constantly provided. The results demonstrate that the proposed method performs better than the conventional method in global perspective.

Leapfrog: Optimal Opportunistic Routing in Probabilistically Contacted Delay Tolerant Networks

Delay tolerant networks (DTNs) experience frequent and long lasting network disconnection due to various reasons such as mobility, power management, and scheduling. One primary concern in DTNs is to route messages to keep the end-to-end delivery delay as low as possible. In this paper, we study the single-copy message routing problem and propose an optimal opportunistic routing strategy - Leapfrog Routing - for probabilistically contacted DTNs where nodes encounter or contact in some fixed probabilities. We deduce the iterative computation formulate of minimum expected opportunistic delivery delay from each node to the destination, and discover that under the optimal opportunistic routing strategy, messages would be delivered from high-delay node to low-delay node in the leapfrog manner. Rigorous theoretical analysis shows that such a routing strategy is exactly the optimal among all possible ones. Moreover, we apply the idea of Reverse Dijkstra algorithm to design an algorithm. When a destination is given, this algorithm can determine for each node the routing selection function under the Leapfrog Routing strategy. The computation overhead of this algorithm is only O(n2) where n is the number of nodes in the network. In addition, through extensive simulations based on real DTN traces, we demonstrate that our algorithm can significantly outperform the previous ones.

Gossiping and routing in undirected triple-loop networks

Given integers n ≥ 7 and a, b, c with 1 ≤ a, b, c ≤ n − 1 such that a, n − a, b, n − b, c, n − c are pairwise distinct, the (undirected) triple-loop network TLn(a, b, c) is the degree-six graph with vertices 0, 1, 2,…,n − 1 such that each vertex x is adjacent to x ± a, x ± b, and x ± c, where the operation is modulo n. It is known that the maximum order of a connected triple-loop network of the form TLn(a, b, n − (a + b)) with given diameter d ≥ 2 is nd = 3d2 + 3d + 1, which is achieved by TL = TL(1, 3d+ 1, 3d2 − 1). In this article, we study the routing and gossiping problems for such optimal triple-loop networks under the store-and-forward, all-port, and full-duplex model, and prove that they admit “perfect” gossiping and routing schemes which exhibit many interesting features. Using a group-theoretic approach we develop for TL a method for systematically producing such optimal gossiping and routing schemes. Moreover, we determine the minimum gossip time, the edge- and arc-forwarding indices, and the minimal edge- and arc-forwarding indices of TL, and prove that our routing schemes are optimal with respect to these four indices simultaneously. As a key step towards these results, we prove that TL is a Frobenius graph on a Frobenius group with Frobenius kernel ℤ, and that TL is arc-transitive with respect to this Frobenius group. In addition, we show that TL admits complete rotations. © 2009 Wiley Periodicals, Inc. NETWORKS, 2010

Utility max–min fair resource allocation for communication networks with multipath routing

This paper considers the flow control and resource allocation problem as applied to the generic multipath communication networks with heterogeneous applications. We propose a novel distributed algorithm, show and prove that among all the sources with positive increasing and bounded utilities (no need to be concave) in steady state, the utility max–min fairness is achieved, which is essential for balancing Quality of Service (QoS) for different applications. By combining the first order Lagrangian method and filtering mechanism, the adopted approach eliminates typical oscillation behavior in multipath networks and possesses a rapid convergence property. In addition, the algorithm is capable of deciding the optimal routing strategy and distributing the total traffic evenly out of the available paths. The performance of our utility max–min fair flow control algorithm is evaluated through simulations under two representative case studies, as well as the real implementation issues are addressed deliberately for the practical purpose.

Special issue on “Intelligent systems and services for ubiquitous computing”

Ubiquitous computing is emerging rapidly as an exciting new paradigm to provide computing and communication services anytime and anywhere. To offer smart services at the right time, right place and using the right means, ubiquitous systems must possess appropriate levels of intelligence. Our special issue provides an opportunity for academic and industry professionals to present recent progress in the area of intelligent ubiquitous computing systems including models, infrastructures, new directions and novel applications associated with the utilization and acceptance of intelligent ubiquitous devices and systems. This special issue aims to foster the dissemination of high quality, original research on new intelligent systems and services. Submissions to this special issue come from an open call for papers as well as from selected papers presented at the 3rd International Symposium on Ubiquitous Application and Security Service (UASS-08) held at Ginowan, Okinawa, Japan, from 25 March to 28 March 2008. Accordingly, a number of papers included in this special issue concentrate on intelligent systems and its building blocks, including routing schemes, broadcasting protocols, collision avoidance mechanism, information processing and middleware architectures for ubiquitous computing environments. Others focus on specific intelligent services and applications based on ubiquitous computing environments. More specifically, H. Kim presents an intra-domain route optimization scheme for ubiquitous networks. Her scheme shows cost-effectiveness in every hierarchical domain that spans mesh network topology and it performs much better than the Network Mobility protocol, when the number of mobile nodes or mobile routers or correspondent nodes increases in hierarchically nested in ubiquitous networks. Vaidya also presents a routing scheme guaranteeing robustness and security, and this scheme is especially designed for wireless multi-hop networks. His routing protocol achieves better performance in terms of various metrics than other protocols. Zhang introduces concepts bringing quality of service (QoS) to peer-to-peer (P2P)-based semantic service discovery for the universal network. Generally, service discovery in the universal network is quite distinct from that of present networks. Zhang puts QoS measurements into service discovery so as to adapt to the universal network, especially P2P networks, as an infrastructure to fulfill the service discovery due to the large amount of services in the network. Peng presents adaptive broadcasting protocols, which can be used in ubiquitous intelligent VOD applications. Peng’s schemes can intelligently adjust the solution J. H. Park (&) Department of Computer Science and Engineering, Kyungnam University, Kyungnam, Korea e-mail: parkjonghyuk1@hotmail.com

Routing strategies in multihop cooperative networks

The fading characteristics and broadcast nature of wireless channels are usually not fully considered in the design of routing protocols for wireless networks. In this paper, we combine routing and cooperative diversity, with the consideration of a realistic channel model. We focus on a multihop network with multiple relays at each hop, and three routing strategies are designed to achieve the full diversity gain provided by cooperation among the relays. In particular, an optimal routing strategy is proposed to minimize the end-to-end outage, which requires the channel information of all the links and serves as a performance bound. An ad-hoc routing strategy is then proposed based on a hop-by-hop relay selection, which can be easily implemented in a distributed way. As expected, ad-hoc routing performs worse than optimal routing, especially with a large number of hops. To achieve a good complexity-performance tradeoff, an N-hop routing strategy is further proposed, where a joint optimization is performed every N hops. Simulation results are provided which verify the outage analyses of the proposed routing strategies.

Optimal traffic routing strategy on scale-free complex networks

In this paper, we propose a new routing strategy to improve the transportation performance on scale-free networks, named optimal routing strategy. It can proportionally distribute the traffic load between central nodes and the noncentral nodes. Analytical results indicate that by using the optimal routing strategy, the network capability in processing traffic is proportional to the square of the network size and is independent of each node degree. Simulations show that compared with the classic shortest path routing strategy, the new strategy can enhance the network capability several times with the small-world character and its performance is gradually improved with the increasing of the average degree. Moreover, the comparison with the efficient routing strategy also reveals the prominent performance of the new strategy.