Impairment aware optimal diverse routing for survivable optical networks

In wavelength-routed optical networks, a lightpath connection can be provisioned only if a path, or a pair of paths in case of path protection is required, can be found which satisfies multiple constraints while simultaneously achieving optimal primary cost. The primary cost can be any metric set by network administrators, and the constraints concerned in optical networks include wavelength continuity constraint, accumulation effect of some transmission impairments in the optical domain, and SRLG-disjoint requirement in survivable networks. In this paper, the impact of these constraints on the optimal path calculation algorithms is studied. Three novel algorithms for solving this problem, which we call “Impairment Aware Optimal Path Pair” problem, are proposed, and their performance is evaluated through extensive simulations. This research has been supported by a National Natural Science Foundation of China (NSFC) grant (90604002, 60472008), and Program for New Century Excellent Talents in University grant (NCET-05-0807).     

WDM光网络中固定路由的优化算法

通过研究WDM光网络中固定路由策略的选取对网络性能的影响，提出了一种新的用于优化固定路由的算法-综合代价法。该算法综合考虑了链路负载和路由跳数这两个因素，以综合代价为策略进行路由优化。计算机仿真结果表明，针对不同的网络负载情况，综合代价法能够有效地降低网络的阻塞率，提高网络的性能。     

Context information prediction for social-based routing in opportunistic networks

Context information can be used to streamline routing decisions in opportunistic networks. We propose a novel social context-based routing scheme that considers both the spatial and the temporal dimensions of the activity of mobile nodes to predict the mobility patterns of nodes based on the BackPropagation Neural Networks model.     

CPTR: conditional probability tree based routing in opportunistic networks

In opportunistic networks due to the inconsistency of the nodes link, routing is carried out dynamically and we cannot use proactive routes. In these networks, nodes use opportunities gained based on store-carry-forward patterns to forward messages. Every node that receives a message when it encounters another node makes decision regarding the forwarding or not forwarding the node encountered. In some previous methods, the recognition of whether encounter with current node is considered as an appropriate opportunity or not has been carried out based on the comparison of the probability of carrier node and the node encountered. In these methods, if the message is delivered to the encountered node, a better opportunity would be lost. To fight with this challenge we have posed CPTR method by using conditional probability tree method through which in addition to the probability of the delivery of carrier and encountered nodes’ message delivery, the opportunities for after encounter will be involved in messages’ forwarding. Results of simulation showed that the proposed method can improve the ratio of delivery and delay of message delivery compared to other similar methods in networks with limited buffer.     

The use of artificial neural networks for optimal message routing

Artificial neural networks are being designed to exploit the unique computational power of the human brain. A brief review of neural networks and their applications in communications is presented. Following that, the neural network solutions to the routing problems are given. Simulation results and performance comparisons are discussed. A comparison between the neural approach and other popular routing algorithms such as Bellman-Ford's and Dijkstra's algorithms is then presented. The practical significance of this new routing algorithm is discussed and further research work is suggested     

Complexity of gradient projection method for optimal routing indata networks

In this paper, we derive a time-complexity bound for the gradient projection method for optimal routing in data networks. This result shows that the gradient projection algorithm of Goldstein-Levitin-Poljak type formulated by Bertsekas (1982), Bertsekas and Gallager (1987) and Bertsekas et al. (1984) converges to within ε in relative accuracy in O(ε^-2h_minN_max) number of iterations, where N_max is the number of paths sharing the maximally shared link, and h_min is the diameter of the network. Based on this complexity result, we also show that the one-source-at-a-time update policy has a complexity bound which is O(n) times smaller than that of the all-at-a-time update policy, where n is the number of nodes in the network. The result of this paper argues for constructing networks with low diameter for the purpose of reducing complexity of the network control algorithms. The result also implies that parallelizing the optimal routing algorithm over the network nodes is beneficial     

Energy-efficient information routing in sensor networks for robotic target tracking

Target tracking problems have been studied for both robots and sensor networks. However, existing robotic target tracking algorithms require the tracker to have access to information-rich sensors, and may have difficulty recovering when the target is out of the tracker??s sensing range. In this paper, we present a target tracking algorithm that combines an extremely simple mobile robot with a networked collection of wireless sensor nodes, each of which is equipped with an unreliable, limited-range, boolean sensor for detecting the target. The tracker maintains close proximity to the target using only information sensed by the network, and can effectively recover from temporarily losing track of the target. We present two algorithms that manage message delivery on this network. The first, which is appropriate for memoryless sensor nodes, is based on dynamic adjustments to the time-to-live (TTL) of transmitted messages. The second, for more capable sensor nodes, makes message delivery decisions on-the-fly based on geometric considerations driven by the messages?? content. We present an implementation along with simulation results. The results show that our system achieves both good tracking precision and low energy consumption.     

Near‐optimal online routing in opportunistic networks

In opportunistic networks, nodes communicate intermittently based on store‐carry‐forward paradigm while exploiting node mobility. The challenge is to determine the ideal nodes to deliver the messages since there is no end‐to‐end connectivity. The nodes might make this decision based on the data sensed from the network. This technique is not ideal in scenarios where the speed of changes in the network topology is greater than the speed at which the nodes can collect info on the network, which might, in turn, be restricted due to usage constraints and uncertainty of knowledge about future contacts. To tackle the problems raised by the non‐deterministic environments, in this paper, a stochastic optimization model and corresponding algorithm are developed to find the optimal routes by considering the short and long‐term impact of choices, ie, the next hop. Herein, we first propose a stochastic model to resolve the routing problem by identifying the shortest path. In the second step, we show that the optimal solution of the proposed model can be determined in polynomial time. An online algorithm is then proposed and analyzed. The algorithm is O( lognρ ) competitive considering the number of nodes and their associated energy. This model can take advantage of the unexpected meets to make the routing more elastic in a short time of contact and with less of a burden on the buffer. The simulation results, against the prominent algorithms, demonstrate significant improvement of the proposed approach in delivery and average delay ratio.     

Jointly optimal routing and scheduling in packet ratio networks

A multihop packet radio network is considered with a single traffic class and given end-to-end transmission requirements. A transmission schedule specifies at each time instant the set of links which are allowed to transmit. The purpose of a schedule is to prevent interference among transmissions from neighboring links. Given amounts of information are residing initially at a subset of the network nodes and must be delivered to a prespecified set of destination nodes. The transmission schedule that evacuates the network in minimum time is specified. The decomposition of the problem into a pure routing and a pure scheduling problem is crucial for the characterization of the optimal transmission schedule     

Surviving double-link failures for near optimal heuristic routing in protected optical networks

The survivability for double-link failures in WDM optical network has been studied in recent years. In previous algorithm, to survive the double-link failures each connection request will be assigned to one primary path and two link-disjoint backup paths. However, the previous algorithm is the so-called simple algorithm which may lead to low resources utilization and high blocking probability. In this paper, we propose a new heuristic algorithm called routing with optimal solution (ROS) to protect the double-link failures. Differing from the previous algorithm, ROS can obtain near optimal solution by recomputing the primary path and two backup paths based on the rerouting policy for each connection request. Simulation results show that ROS can significantly outperform the previous algorithm.     

Combining trust with location information for routing in wireless sensor networks

As the applications of wireless sensor networks proliferate, the efficiency in supporting large sensor networks and offering security guarantees becomes an important requirement in the design of the relevant networking protocols. Geographical routing has been proven to efficiently cope with large network dimensions while trust management schemes have been shown to assist in defending against routing attacks. Once trust information is available for all network nodes, the routing decisions can take it into account, i.e. routing can be based on both location and trust attributes. In this paper, we investigate different ways to incorporate trust in location‐based routing schemes and we propose a novel way of balancing trust and location information. Computer simulations show that the proposed routing rule exhibits excellent performance in terms of delivery ratio, latency time and path optimality. Copyright © 2010 John Wiley & Sons, Ltd.     

Near optimal routing and capacity management for PWCE-based survivable WDM networks

Protected Working Capacity Envelope (PWCE) has been proposed to simplify resource management and traffic control for survivable WDM networks. In a PWCE-based network, part of the link capacity is reserved for accommodating working routes, and the remaining capacity is reserved for backup routes. The shortest path routing is applied in PWCE-based networks. An arrival call is accepted only when each link along the shortest path has a free working channel. Such a working path routing scheme greatly simplifies the call admission control process for dynamic traffic, and it is especially suitable for implementation in a distributed manner among network nodes. In this article, we investigate two protection strategies: Bundle Protection (BP) and Individual Protection (IDP). In BP, only one backup path can be used to protect a failure component, whereas multiple backup paths can be used in IDP. We formulate four mixed integer non-linear programming (MINLP) problems using BP and IDP strategies for single link and single node failure protection. Each model is designed to determine link metrics for shortest working path routing, working and backup channel assignments, and backup path planning. Our objective is to minimize call-blocking probability on the bottleneck link. Since these models are highly non-linear and non-convex, it is difficult to obtain exact global optimal solutions. We propose a Simulated Annealing-based Heuristic (SAH) algorithm to obtain near optimal solutions. This SAH adopts the concepts of simulated annealing as well as the bi-section technique to minimize call-blocking probabilities. To evaluate the performance, we made simulation comparisons between SAH and the unity link weight assignment scheme. The results indicate that SAH can greatly reduce call-blocking probabilities on benchmark and the randomly generated networks.     

Dissemination of routing information in broadcast networks: OSPFversus IS-IS

OSPF and IS-IS are two main standard link state routing protocols designed to operate in various complex network topologies. One aspect that both protocols handle is the reliable dissemination of routing information over broadcast networks such as Ethernet and FDDI. Both protocols suggest different schemes for this purpose and in this article we compare the two. The performance criteria being checked are: the longest arrival time of a routing update packet at all the routers; the average arrival time of routing update packets at all the routers; the total required bandwidth; and the number of memory accesses a router performs, which is evidence of the amount of internal work it performs. We find that in our model of broadcast networks the scheme suggested in IS-IS is more efficient than that of OSPF in terms of the arrival times of routing update packets. In particular, the average arrival time of routing update packets in OSPF is 2-10 times longer than in IS-IS. In terms of the bandwidth each scheme consumes, there are scenarios where OSPF outperforms IS-IS and vice versa. In terms of the number of memory accesses routers perform in each scheme, IS-IS outperforms OSPF     

QoS routing in networks with inaccurate information: theory andalgorithms

This paper investigates the problem of routing flows with quality-of-service (QoS) requirements through one or more networks, when the information available for making such routing decisions is inaccurate. Inaccuracy in the information used in computing QoS routes, e.g., network state such as link and node metrics, arises naturally in a number of different environments that are reviewed in the paper. The goal is to determine the impact of such inaccuracy on the ability of the path-selection process to successfully identify paths with adequate available resources. In particular, we focus on devising algorithms capable of selecting path(s) that are most likely to successfully accommodate the desired QoS, in the presence of uncertain network state information for the purpose of the analysis, we assume that this uncertainty is expressed through probabilistic models, and we briefly discuss sample cases that can give rise to such models. We establish that the impact of uncertainty is minimal for flows with only bandwidth requirements, but that it makes path selection intractable when end-to-end delay requirements are considered. For this latter case, we provide efficient solutions for special cases of interest and develop useful heuristics     

Hop-distance based addressing and routing for dense sensor networks without location information

One of the most challenging problems in wireless sensor networks is the design of scalable and efficient routing algorithms without location information. The use of specialized hardware and/or infrastructure support for localization is costly and in many deployment scenarios infeasible. In this study, the wave mapping coordinate (WMC) system to address the localization problem is introduced for dense sensor networks and a highly efficient routing algorithm applicable to WMC systems is proposed. The performance of the WMC system is evaluated through simulations and compared with the performance of geographic routing without location information (GWL). The WMC system is found to be highly scalable and efficient with a simple system set-up procedure. Simulation studies confirm the high routing performance of WMC systems which is comparable to the performance of greedy geographic routing with the availability of location information.     

双环网络并行最优寻径策略及宽直径的研究

将双环网络拓扑结构映射到平面直角坐标系,基于直角坐标系研究双环网络的并行最优寻径方法。首先研究坐标轴上节点及其等价节点的分布规律,建立等价节点分布模型,得出基于等价节点的并行最优寻径策略及双环网络宽直径求解方法。在双环网络最小路径图（MDD）的基础上拓展,提出并行路径图（PDD）的设计思路并予以仿真实现,基于PDD图,设计两点间2条内点不交的并行最短路径的快速求解方法。仿真实验表明,宽直径分布随步长的变化呈现一定波动性,相对于传统的寻径方式,并行最优寻径明显提高了网络传输效率。     

Link energy minimization for wireless networks

In this paper, we formalize the problem of minimizing the energy dissipated to successfully transmit a single information bit over a link, considering circuit power consumption, packetization and retransmission overhead, bit/packet error probability, and the duty cycle of the transceiver. We optimize the packet length and transmit power as a function of distance between the transmitter and the receiver for different modulation schemes. We propose a general unconstrained energy consumption model that provides a lower bound on the energy dissipated per information bit. A practical unconstrained physical layer optimization scheme is also provided to illustrate the utilization of the model. Furthermore, minimized energy consumptions of different modulation schemes are compared over an additive white Gaussian noise (AWGN) channel. We extend this general energy consumption model by considering two particular constraints: fixed average power and fixed average rate. We explore the impact of the average power and the information rate constraints on energy consumption and determine the optimum constellation size, packet length, and duty cycle.     

Hardness of crosstalk minimization in two-layer channel routing

Crosstalk minimization is one of the most important aspects of high-performance VLSI circuit design. With the advancement of fabrication technology, devices and interconnecting wires are being placed in close vicinity, and circuits are operating at higher frequencies. This results in crosstalk between adjacent wire segments. In this paper, it has been shown that the crosstalk minimization problem in the reserved two-layer Manhattan routing model is NP-complete, even if channels are free from all vertical constraints. It has also been demonstrated that it is hard to approximate the crosstalk minimization problem. Besides, the issue of minimizing bottleneck crosstalk has been introduced that is a new problem for crosstalk minimization. It has been proven that this problem is also NP-complete. It has been further shown that all these results hold even if doglegging is allowed.     

A decision model and support system for the optimal design ofhealth information networks

Health information networks (HINs) have become increasingly important in the structure of the health care industry. In this paper, we develop decision models and decision-support systems for designing and performing cost-benefit analyses of HINs. Our models prioritize the connection of various types of health providers to the network based on the costs and benefits of all participants: the network owners, information providers and information users of the HIN. The business strategy underlying this analysis is to design the system with the maximum value for the network owner(s), while ensuring that the network provides positive added value to each of its nodes. Our framework could be used to examine the design of and to perform a cost-benefit analysis for an existing network, for the expansion of an existing network, or for the development of a new network. One can also use the models for break-even point and scenario analyses. We have used our approach to examine an existing HIN [the Wisconsin Health Information Network (WHIN)] and to perform a scenario analysis for a possible restructuring of the network. Our empirical results in this case show that HINs could be highly profitable for all network participants