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[en] The design of routing strategies for traffic-driven epidemic spreading has received increasing attention in recent years. In this paper, we propose an adaptive routing strategy that incorporates topological distance with local epidemic information through a tunable parameter h. In the case where the traffic is free of congestion, there exists an optimal value of routing parameter h, leading to the maximal epidemic threshold. This means that epidemic spreading can be more effectively controlled by adaptive routing, compared to that of the static shortest path routing scheme. Besides, we find that the optimal value of h can greatly relieve the traffic congestion in the case of finite node-delivering capacity. We expect our work to provide new insights into the effects of dynamic routings on traffic-driven epidemic spreading.
[en] This paper presents and evaluates a cross-layered communication architecture which allows for robust, reliable and efficient data collection in an embedded wireless multi-hop network. The proposed solution, based on a novel embodiment of gradient routing, proposes to piggyback control data along with data packets. We show how this simple scheme is robust against topological changes which are quickly absorbed by the network, and that it is largely unaffected by the density or size of the network. Experimental results confirm these observations and show how the nodes and sinks can be added/removed without disturbing network operation while staying energy efficient. The simple solution proposed in this paper offers a true deploy-and-forget user experience
[en] In complex networks characterized by broad degree distribution, node significance is often associated with its degree or with centrality metrics which relate to its reachability and shortest paths passing through it. Such measures do not consider availability of efficient backup of the node and thus often fail to capture its contribution to the functionality and resilience of the network operation. In this paper, we suggest the quality of backup (QoB) and alternative path centrality (APC) measures as complementary methods which enable analysis of node significance in a manner which considers backup. We examine the theoretical significance of these measures and use them to classify nodes in social interaction networks and in the Internet AS (autonomous system) graph while applying the valley-free routing restrictions which reflect the economic relationships between the AS nodes in the Internet. We show that both node degree and node centrality are not necessarily evidence of its significance. In particular, we show that social structures do not necessarily depend on highly central nodes and that medium degree nodes with medium centrality measure prove to be crucial for efficient routing in the Internet AS graph
[en] There is plenty of oil in Central Asia, and plenty of companies have signed agreements to extract that oil. Now the focus is on finding secure and financially viable export routes. And it looks increasingly as if a route through the Caucasus to a Turkish terminal on the Mediterranean will be favoured for Azerbaijani crude, and perhaps also for exports from Chevron's giant venture at Tengiz in Kazakhstan. (author)
[en] We present a family of networks, expanded deterministic Apollonian networks, which are a generalization of the Apollonian networks and are simultaneously scale free, small world and highly clustered. We introduce a labeling of their nodes that allows one to determine the shortest path routing between any two nodes of the network based only on the labels
[en] Highlights: ► An idea of a high-performance computer using RSFQ circuits is shown. ► An outline of processor with reconfigurable data-paths (RDPs) is shown. ► Architectural details of an SFQ-RDP are described. -- Abstract: We show recent progress in our research on an energy-efficient high-performance processor with reconfigurable data-paths (RDPs) using rapid single-flux-quantum (RSFQ) circuits. We mainly describe the architectural details of an RDP implemented using RSFQ circuits. An RDP consists of a lot of floating-point units (FPUs) and operand routing networks (ORNs) which connect the FPUs. We reconfigure the RDP to fit a computation, i.e., a group of floating-point operations, appearing in a ‘for’ loop of programs for numerical computations by setting the route in ORNs before the execution of the loop. In the RDP, a lot of FPUs work in parallel with pipelined fashion, and hence, very high-performance computation is achieved
[en] In this paper we are going to discuss a variation on the problem of finding the shortest path between two points in optimal ship routing problems consisting of obstacles that are not allowed to be crossed by the path. Our main goal are going to be the construction of an appropriate algorithm, based in an earlier work by computing the shortest path between two points in the plane that avoids a set of polygonal obstacles.
[en] We consider a real case study of a vehicle routing problem with a heterogeneous fleet and time windows (HFVRPTW) for a franchise company bottling Coca-Cola products in Colombia. This study aims to determine the routes to be performed to fulfill the demand of the customers by using a heterogeneous fleet and considering soft time windows. The objective is to minimize the distance traveled by the performed routes. Design/methodology/approach: We propose a two-phase heuristic algorithm. In the proposed approach, after an initial phase (first phase), a granular tabu search is applied during the improvement phase (second phase). Two additional procedures are considered to help that the algorithm could escape from local optimum, given that during a given number of iterations there has been no improvement. Findings: Computational experiments on real instances show that the proposed algorithm is able to obtain high-quality solutions within a short computing time compared to the results found by the software that the company currently uses to plan the daily routes. Originality/value: We propose a novel metaheuristic algorithm for solving a real routing problem by considering heterogeneous fleet and time windows. The efficiency of the proposed approach has been tested on real instances, and the computational experiments shown its applicability and performance for solving NP-Hard Problems related with routing problems with similar characteristics. The proposed algorithm was able to improve some of the current solutions applied by the company by reducing the route length and the number of vehicles.
[en] Nowadays, communication networks are represented one of the main important application areas all over the world. Wireless Networks are consisting of nodes having limited radio range and bandwidth without having any fixed infrastructure. However, to successfully deliver the message from source to destination, the network must use the optimum route. On the other hand, recently, genetic algorithms (GAs) have proved their effectiveness as learning and optimization technique to optimize the route performance. Thus, the proposed system introduces the use of the genetic algorithms to optimize the derived router that not only considered as the shortest path but also ensure its minimum delay and reliability. The proposed system has proved its success and performance for the practical applications when applied for a communication network