Chemical-Mechanical Polishing (CMP) is one of the key steps during nanometer VLSI manufacturing process where minimum variation of layout pattern densities is desired. This paper proposes a novel Optimal Maze routing ...
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ISBN:
(纸本)9780769528960
Chemical-Mechanical Polishing (CMP) is one of the key steps during nanometer VLSI manufacturing process where minimum variation of layout pattern densities is desired. This paper proposes a novel Optimal Maze routing (OMR) algorithm which optimizes the layout uniformity as well as other routing objectives. The presented routing algorithm is optimal in the sense that it can find routing solutions for nets with minimum wire length, minimum number of vias and minimized layout uniformity-related cost. Experimental results show that compared with a previous routing algorithm, OMR can reduce the total number of vias by up to 24%. Except for the great improvement considering wire length and vias, the proposed routing algorithm also contributes a lot to minimizing the pattern density variation. Since current area fill methods are mostly based on fixed-dissection regime which cannot find the optimal filling solution for all possible floating windows, the proposed routing algorithm makes a good complement.
Enhanced OTIS-cube (E-OTIS-Q(n)), a variation of the OTIS-cube (OTIS-Q(n)) was proposed in [1]. E-OTIS-Q(n) is regular of degree n + 1 and is obtained from the normal OTIS-cube by adding some extra links. In [1], it w...
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ISBN:
(纸本)9780769527703
Enhanced OTIS-cube (E-OTIS-Q(n)), a variation of the OTIS-cube (OTIS-Q(n)) was proposed in [1]. E-OTIS-Q(n) is regular of degree n + 1 and is obtained from the normal OTIS-cube by adding some extra links. In [1], it was shown that the diameter of E-OTIS-Q,, is less than or equal to [4n+5/3] and a heuristic for point-to-point routing has been proposed In this paper an optimal algorithm for one-toone routing in E-OTIS-Qn has been developed. We have shown that the diameter of E-OTIS-Qn is equal to [4n+4/3] which is almost two-third of the diameter of OTIS-Q(n).
Taking the characteristics of multi-constrained QoS (Quality of Service) routing into account, an intelligent QoS multicast routing. algorithm based on PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) is p...
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ISBN:
(纸本)9781424406043
Taking the characteristics of multi-constrained QoS (Quality of Service) routing into account, an intelligent QoS multicast routing. algorithm based on PSO (Particle Swarm Optimization) and GA (Genetic Algorithm) is presented. In this paper, the corresponding model and its mathematical description are introduced Under inaccurate information of QoS parameters, combining fast searching ability of PSO and global optimization ability of GA, the proposed algorithm tries to find the Pareto no-dominated warehouse with the maximum probability of meeting with multiple QoS constraints under the given cost, from which the best multicast routing tree is selected. Simulation research and performance evaluation have shown that the proposed algorithm is both feasible and effective.
The dynamic nature of mobile ad hoc networks makes it difficult to consider a specific model for their topology which might change in a short period of time. Using the knowledge about the location of nodes, several re...
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ISBN:
(纸本)9783642024689
The dynamic nature of mobile ad hoc networks makes it difficult to consider a specific model for their topology which might change in a short period of time. Using the knowledge about the location of nodes, several relatively efficient position based routing algorithms have been proposed but almost all of them are sensitive to the network topology. Ant colony optimization based routing algorithms form another family of routing algorithms that usually converge to optimum routes. In our previous work we proposed POSANT, a position based ant colony routing algorithm for mobile ad-hoc networks. Although POSANT outperforms other routing algorithms in most cases, there are network topologies in which POSANT does not perform well. In this paper we introduce HybNet, a hybrid ant colony optimization based routing algorithm for mobile ad hoc networks which adapts itself to different network topologies. We carry out an empirical analysis of the performance of our algorithm and compare it with other routing algorithms. Our results show that HybNet almost always performs efficiently, even in some complex and variable network topologies.
Most research on energy-aware routings in mobile ad hoc networks (MANETs) only focuses on minimizing the total energy consumption from the source node to the destination node, regardless of the performance degradation...
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ISBN:
(纸本)9781479979813
Most research on energy-aware routings in mobile ad hoc networks (MANETs) only focuses on minimizing the total energy consumption from the source node to the destination node, regardless of the performance degradation caused by the heavy traffic load in the network. In this paper, we propose an energy-aware load-balanced routing (EALB) algorithm. Simulation results demonstrate that the proposed routing algorithm significantly increases the packet delivery ratio, reduces the delay and prolongs the network lifetime in heavy load networks. EALB can also provide better performance when nodes have very low energy levels.
We present a new geographic routing algorithm, Greedy Distributed Spanning Tree routing (GDSTR), that finds shorter routes and generates less maintenance traffic than previous algorithms. While geographic routing pote...
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ISBN:
(纸本)9781931971430
We present a new geographic routing algorithm, Greedy Distributed Spanning Tree routing (GDSTR), that finds shorter routes and generates less maintenance traffic than previous algorithms. While geographic routing potentially scales well, it faces the problem of what to do at local dead ends where greedy forwarding fails. Existing geographic routing algorithms handle dead ends by planarizing the node connectivity graph and then using the right-hand rule to route around the resulting faces. GDSTR handles this situation differently by switching instead to routing on a spanning tree until it reaches a point where greedy forwarding can again make progress. In order to choose a direction on the tree that is most likely to make progress towards the destination, each GDSTR node maintains a summary of the area covered by the subtree below each of its tree neighbors. While GDSTR requires only one tree for correctness, it uses two for robustness and to give it an additional forwarding choice. Our simulations show that GDSTR finds shorter routes than geographic face routing algorithms: GDSTR's stretch is up to 20% less than the best existing algorithm in situations where dead ends are common. In addition, we show that GDSTR requires an order of magnitude less bandwidth to maintain its trees than CLDP, the only distributed planarization algorithm that is known to work with practical radio networks.
This paper addresses a new real-world application of vehicle routing planning in a finite time horizon. A company in the small package shipping industry has a limited fleet of identical vehicles in some depots and mus...
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This paper addresses a new real-world application of vehicle routing planning in a finite time horizon. A company in the small package shipping industry has a limited fleet of identical vehicles in some depots and must serve a set of clients. There is a frequency for each client stating how often this client must be visited. Time intervals between two consecutive visits must be the same but the visiting schedule is flexible. To get some competitive advantage, a company tries to increase the service quality. To this end, each client should be visited by one driver only. The goal is to minimize the total traveling distance for all vehicles over the planning horizon under the frequency constraints and driver shift length constraints. We present an integer linear programming model for this new consistent vehicle routing problem. To find near optimal solutions, we design the Variable Neighborhood Search metaheuristic with nine neighborhood structures. The driver shift length constraints are penalized and included in the objective function. Empirical results for real test instances from Orenburg region in Russia with up to 900 clients and four weeks in the planning horizon are discussed. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
As nodes in wireless sensor networks are usually supplied by a simple non rechargeable battery, the energy available in these nodes is very limited. Moreover, this limited energy is mostly consumed in transmission and...
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ISBN:
(纸本)9781424416851
As nodes in wireless sensor networks are usually supplied by a simple non rechargeable battery, the energy available in these nodes is very limited. Moreover, this limited energy is mostly consumed in transmission and reception of data. As transmission and reception is highly affected by routing algorithms, designing a proper routing algorithm will prolong the network lifetime. In this paper we proposed a novel routing algorithm, called Locality-Aware Diffusion (LAD) that leverages spatial locality of sensed data in sensor networks to reduce energy consumption and prolong the network lifetime. The proposed algorithm is an extension to Shortest Path Tree which is a common approach in routing algorithms. Simulation results show the validity and effectiveness of the proposed algorithm.
We present a routing algorithm that finds n disjoint shortest paths from the source node to n target nodes in the n-dimensional hypercube in O(n(3) log n) = O(log(3) N log log N) time, where N = 2(n), provided that su...
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ISBN:
(纸本)9780769534343
We present a routing algorithm that finds n disjoint shortest paths from the source node to n target nodes in the n-dimensional hypercube in O(n(3) log n) = O(log(3) N log log N) time, where N = 2(n), provided that such disjoint shortest paths exist which can be checked in O(n(5/2)) time, improving the previous O(n(4)) routing algorithm.
This paper describes and evaluates the Confidence-based Dual Reinforcement Q-routing algorithm (CDRQ-routing) for adaptive packet routing in communication networks. CDRQ-routing is based on the Q-learning framework of...
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ISBN:
(纸本)1558606130
This paper describes and evaluates the Confidence-based Dual Reinforcement Q-routing algorithm (CDRQ-routing) for adaptive packet routing in communication networks. CDRQ-routing is based on the Q-learning framework of Q-routing. The main contribution of this work is the increased quantity and improved quality of exploration in CDRQ-routing, which lead to faster adaptation and better routing policies learned as compared to Q-routing, the state-of-the-art adaptive Bellman-Ford routing, and the nonadaptive shortest path routing. Experiments over several network topologies have shown that at different loads, CDRQ-routing learns superior policies significantly faster than Q-routing. Moreover, CDRQ-routing learns policies that sustain higher load levels than Q-routing. Analysis shows that overhead due to exploration is insignificant as compared to the improvements in CDRQ-routing.
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