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31
Multicast Routing in Datagram Internetworks and Extended LANs
 ACM Transactions on Computer Systems
, 1990
"... Multicasting, the transmission of a packet to a group of hosts, is an important service for improving the efficiency and robustness of distributed systems and applications. Although multicast capability is available and widely used in local area networks, when those LANs are interconnected by store ..."
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Cited by 993 (6 self)
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Multicasting, the transmission of a packet to a group of hosts, is an important service for improving the efficiency and robustness of distributed systems and applications. Although multicast capability is available and widely used in local area networks, when those LANs are interconnected by storeandforward routers, the multicast service is usually not offered across the resulting internetwork. To address this limitation, we specify extensions to two common internetwork routing algorithmsdistancevector routing and linkstate routingto support lowdelay datagram multicasting beyond a single LAN. We also describe modifications to the singlespanningtree routing algorithm commonly used by linklayer bridges, to reduce the costs of multicasting in large extended LANs. Finally, we discuss how the use of multicast scope control and hierarchical multicast routing allows the multicast service to scale up to large internetworks.
Inverse optimization
 OPERATIONS RESEARCH
, 2001
"... In this paper, we study inverse optimization problems defined as follows. Let S denote the set of feasible solutions of an optimization problem P, let c be a specified cost vector, and x 0 be a given feasible solution. The solution x 0 may or may not be an optimal solution of P with respect to the c ..."
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Cited by 27 (2 self)
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In this paper, we study inverse optimization problems defined as follows. Let S denote the set of feasible solutions of an optimization problem P, let c be a specified cost vector, and x 0 be a given feasible solution. The solution x 0 may or may not be an optimal solution of P with respect to the cost vector c. The inverse optimization problem is to perturb the cost vector c to d so that x 0 is an optimal solution of P with respect to d and �d − c � p is minimum, where �d − c � p is some selected L p norm. In this paper, we consider the inverse linear programming problem under L 1 norm (where �d − c � p = ∑ i∈J w j�d j − c j�, with J denoting the index set of variables x j and w j denoting the weight of the variable j) and under L � norm (where �d −c � p = max j∈J �w j�d j −c j���. We prove the following results: (i) If the problem P is a linear programming problem, then its inverse problem under the L 1 as well as L � norm is also a linear programming problem. (ii) If the problem P is a shortest path, assignment or minimum cut problem, then its inverse problem under the L 1 norm and unit weights can be solved by solving a problem of the same kind. For the nonunit weight case, the inverse problem reduces to solving a minimum cost flow problem. (iii) If the problem P is a minimum cost flowproblem, then its inverse problem under the L 1 norm and unit weights reduces to solving a unitcapacity minimum cost flowproblem. For the nonunit weight case, the inverse problem reduces to solving a minimum cost flowproblem. (iv) If the problem P is a minimum cost flowproblem, then its inverse problem under the L � norm and unit weights reduces to solving a minimum mean cycle problem. For the nonunit weight case, the inverse problem reduces to solving a minimum costtotime ratio cycle problem. (v) If the problem P is polynomially solvable for linear cost functions, then inverse versions of P under the L 1 and L � norms are also polynomially solvable.
Maximizable routing metrics
 In Proc. IEEE ICNP
, 1998
"... Abstract—We present a simple theory for maximizable routing metrics. First, we give a formal definition of routing metrics and identify two important properties: boundedness and monotonicity. We show that these two properties are both necessary and sufficient for a routing metric to be maximizable i ..."
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Cited by 21 (2 self)
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Abstract—We present a simple theory for maximizable routing metrics. First, we give a formal definition of routing metrics and identify two important properties: boundedness and monotonicity. We show that these two properties are both necessary and sufficient for a routing metric to be maximizable in any network. We show how to combine two (or more) routing metrics into a single composite metric such that if the original metrics are both bounded and monotonic (and, hence, maximizable), then the composite metric is also bounded and monotonic (and, hence, maximizable). We present several applications of our theory. We show that the composite routing metric used in the InterGateway Routing Protocol (IGRP) is not maximizable and we show that Enhanced IGRP (EIGRP) does not behave as expected for nonmonotonic metrics. We also show that a technique for scalable linkstate routing does not work correctly when applied to composite metrics. A common theme throughout our paper is that the intuitions generated by using distance metrics to produce shortest paths do not carry over to other routing metrics. Index Terms—Communication system routing, communication system signaling, computer networks, distance vector, distributed
VehicletoVehicletoInfrastructure (V2V2I) Intelligent Transportation System Architecture
 IEEE 4 th Intelligent Vehicles Symposium
, 2008
"... Abstract – In this paper, I describe the vehicletovehicletoinfrastructure (V2V2I) architecture, which is a hybrid of the vehicletovehicle (V2V) and vehicletoinfrastructure (V2I) architectures. The V2V2I architecture leverages the benefits of fast queries and responses from the V2I architecture ..."
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Cited by 8 (5 self)
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Abstract – In this paper, I describe the vehicletovehicletoinfrastructure (V2V2I) architecture, which is a hybrid of the vehicletovehicle (V2V) and vehicletoinfrastructure (V2I) architectures. The V2V2I architecture leverages the benefits of fast queries and responses from the V2I architecture, but with the advantage of a distributed architecture not having a single pointoffailure from the V2V architecture. In the V2V2I architecture, the transportation network is broken into zones in which a single vehicle is known as the Super Vehicle. Only Super Vehicles are able to communicate with the central infrastructure or with other Super Vehicles, and all other vehicles can only communicate with the Super Vehicle responsible for the zone in which they are currently traversing. I describe the Super Vehicle Detection (SVD) algorithm for how a vehicle can find or become a Super Vehicle of a zone and how Super Vehicles can aggregate the speed and location data from all of the vehicles within their zone to still ensure an accurate representation of the network. I perform an analysis using FreeSim to determine the tradeoffs experienced based on the size and number of zones within a transportation network and describe the benefits of the V2V2I architecture over the pure V2I or V2V architectures. I.
FreeSim – A V2V and V2R Freeway Traffic Simulator
 IEEE 3 rd International Workshop on VehicletoVehicle Communication in conjunction with IEEE 3 rd Intelligent Vehicle Symposium
, 2007
"... Abstract – In this paper we describe FreeSim, which is a fullycustomizable macroscopic and microscopic freeflow traffic simulator. FreeSim allows for multiple freeway systems to be easily represented and loaded into the simulator as a graph data structure with edge weights determined by the current ..."
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Cited by 5 (5 self)
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Abstract – In this paper we describe FreeSim, which is a fullycustomizable macroscopic and microscopic freeflow traffic simulator. FreeSim allows for multiple freeway systems to be easily represented and loaded into the simulator as a graph data structure with edge weights determined by the current speeds. Traffic and graph algorithms can be created and executed for the entire freeway system or for individual vehicles, and the traffic data used by the simulator can be usergenerated or be converted from realtime data gathered by a transportation organization. The vehicles in FreeSim can communicate with the system monitoring the traffic on the freeways (V2R) or with other vehicles (V2V), which makes FreeSim ideal for ITS simulation and testing of protocol designs. A centralized and a distributed peertopeer architecture are both described and supported by FreeSim. FreeSim is licensed under the GNU General Public License, and the source code is available for download from
OPERATIONS RESEARCH GAMES: A SURVEY
, 2001
"... This paper surveys the research area of cooperative games associated with several types of operations research problems in which various decision makers (players) are involved. Cooperating players not only face a joint optimisation problem in trying, e.g., to minimise total joint costs, but also fac ..."
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Cited by 5 (0 self)
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This paper surveys the research area of cooperative games associated with several types of operations research problems in which various decision makers (players) are involved. Cooperating players not only face a joint optimisation problem in trying, e.g., to minimise total joint costs, but also face an additional allocation problem in how to distribute these joint costs back to the individual players. This interplay between optimisation and allocation is the main subject of the area of operations research games. It is surveyed on the basis of a distinction between the nature of the underlying optimisation problem: connection, routing, scheduling, production and inventory.
BR: Evaluation of computerassisted instruction in principles of economics
 Ed Tech Soc
"... Despite increasing use, little is known about the effectiveness of webbased instructional material. This study assesses the effectiveness of supplementary webbased materials and activities in introductory economics courses. We have collected data on 66 students from three principles sections that ..."
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Cited by 3 (0 self)
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Despite increasing use, little is known about the effectiveness of webbased instructional material. This study assesses the effectiveness of supplementary webbased materials and activities in introductory economics courses. We have collected data on 66 students from three principles sections that describe demographic characteristics, use of webbased instructional resources, and performance on graded quizzes and examinations. We use this data to statistically assess the effectiveness of the webbased material. Student utilization of webbased material was extensive. Students frequently used online practice quizzes and accessed the webbased material often. A sizable fraction of the students actively posted and read threaded discussions on the course bulletin board. The statistical analysis shows that both online computer graded practice quizzes and posting to the class bulletin board are positively correlated with student performance on the quizzes and exams, but use of webbased content and passive reading of bulletin board posts ("lurking") is not. These results suggest that faculty should focus more on developing selftest quizzes and effective bulletin board discussion projects and less on generating online content.
An OnLine Handwriting Recognizer with Fisher Matching, Hypotheses Propagation Network and Context Constraint Models
, 2001
"... ..."
Learning State Machines in the Robot Moving Context
, 2001
"... In this paper we introduce a method for use state machines as topological maps for remembering the landmarks used to navigate the robot in the static environment. Also we explain how to generalize the state machine model to simplify the search and localization. This generalization process also allow ..."
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Cited by 1 (1 self)
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In this paper we introduce a method for use state machines as topological maps for remembering the landmarks used to navigate the robot in the static environment. Also we explain how to generalize the state machine model to simplify the search and localization. This generalization process also allows us to remove redundancy from our topological map. We find the shortest path between landmarks, represented as states in a state machine, using breadthfirst method for the search. For localizing the robot, we use a simple statistical method. For learning and generalizing the topological map, we use the RPNI (Regular Positive and Negative Inference) algorithm, which learns regular finite automata. We present the experimental results and explain how the environment was modelled.