Limitations of Front-To-End Bidirectional Heuristic Search
... consistent heuristic, which results in f costs that are monotonically non-decreasing with increased depth. As such, neither direction of search can intersect the other before most nodes with lower depth have been expanded, and a pathological case like that of figure 3 would be very unlikely. ...
... consistent heuristic, which results in f costs that are monotonically non-decreasing with increased depth. As such, neither direction of search can intersect the other before most nodes with lower depth have been expanded, and a pathological case like that of figure 3 would be very unlikely. ...
Limitations of Front-to-End Bidirectional Heuristic Search
... its heuristic weak and show that a bidirectional heuristic search expands no fewer nodes than a bidirectional bruteforce search. If the majority are expanded at shallower depth than the solution midpoint, then we call it a strong heuristic and show that a bidirectional heuristic search would expand ...
... its heuristic weak and show that a bidirectional heuristic search expands no fewer nodes than a bidirectional bruteforce search. If the majority are expanded at shallower depth than the solution midpoint, then we call it a strong heuristic and show that a bidirectional heuristic search would expand ...
Graph Partitioning with AMPL - Antonio Mucherino Home Page
... How can we solve a graph partitioning problem? We need to find a partition in clusters of a weighted undirected graph G = (V , E, c), where V is the set of vertices of G, E is the set of edges of G, c is the set of weights eventually assigned to the edges. This problem can be formulated as a global ...
... How can we solve a graph partitioning problem? We need to find a partition in clusters of a weighted undirected graph G = (V , E, c), where V is the set of vertices of G, E is the set of edges of G, c is the set of weights eventually assigned to the edges. This problem can be formulated as a global ...
Assessing the Vulnerability of the Fiber Infrastructure
... Internet is influenced by geographical concepts [2], [15], [29]. These observations motivated the modeling of the Internet as a scale free geographical graph [26], [30]. Although these models may prove useful in generating logical network topologies, we decided to present numerical results based on ...
... Internet is influenced by geographical concepts [2], [15], [29]. These observations motivated the modeling of the Internet as a scale free geographical graph [26], [30]. Although these models may prove useful in generating logical network topologies, we decided to present numerical results based on ...
Outfitting an Inter-AS Topology to a Network of DDoS Countermeasures
... provides AS Rank based on ASRD and IP allocation data. As shown in Algorithm 1, TRF simply picks N ASes from Rank 1 AS. When we tried this simple filtering method, some problem occurred, which we call “Isolated Island Problem”. Isolated Island Problem is that a subgraph of an inter-AS Topology, whic ...
... provides AS Rank based on ASRD and IP allocation data. As shown in Algorithm 1, TRF simply picks N ASes from Rank 1 AS. When we tried this simple filtering method, some problem occurred, which we call “Isolated Island Problem”. Isolated Island Problem is that a subgraph of an inter-AS Topology, whic ...
Cross-Layer Optimization in TCP/IP networks - Netlab
... Here are our main results. In the case of pure dynamic routing, i.e., when link costs are the congestion prices generated by TCP–AQM, it turns out that we can interpret TCP/IP as a distributed primal-dual algorithm to maximize aggregate utility over both source rates (by TCP–AQM) and routes (by IP), ...
... Here are our main results. In the case of pure dynamic routing, i.e., when link costs are the congestion prices generated by TCP–AQM, it turns out that we can interpret TCP/IP as a distributed primal-dual algorithm to maximize aggregate utility over both source rates (by TCP–AQM) and routes (by IP), ...
Optimizing Network Resource Sharing in Grids
... Finally we let Z = 2n, i.e., we ask whether it is possible to accept 2n requests. We now have a uniform network, and we can reproduce the main ideas of the proof of Theorem 1. The main trick is that egress ek cannot accept both requests rk and rn+k , because 2a0k > 2(1 + S) > B. Hence only one of th ...
... Finally we let Z = 2n, i.e., we ask whether it is possible to accept 2n requests. We now have a uniform network, and we can reproduce the main ideas of the proof of Theorem 1. The main trick is that egress ek cannot accept both requests rk and rn+k , because 2a0k > 2(1 + S) > B. Hence only one of th ...
MoCA Installation and Troubleshooting Reference Guide
... In the diagram below, MoCA Device 1 is connected off the initial split to the cable modem, while the other MoCA devices are connected after a home amplifier. Consequently, MoCA network transmissions between MoCA Device 1 and the other MoCA devices must traverse the reverse isolation of the home ampl ...
... In the diagram below, MoCA Device 1 is connected off the initial split to the cable modem, while the other MoCA devices are connected after a home amplifier. Consequently, MoCA network transmissions between MoCA Device 1 and the other MoCA devices must traverse the reverse isolation of the home ampl ...
TIE Breaking: Tunable Interdomain Egress Selection
... the trade-off between sensitivity to IGP changes and adaptability to network events, (ii) computationally easy for the routers to execute in real time, and (iii) easy for a higher-level management system to optimize based on diverse network objectives. • Optimization of network-wide objectives: We p ...
... the trade-off between sensitivity to IGP changes and adaptability to network events, (ii) computationally easy for the routers to execute in real time, and (iii) easy for a higher-level management system to optimize based on diverse network objectives. • Optimization of network-wide objectives: We p ...
SameField(+f,c,c
... MCMC: Gibbs Sampling state ← random truth assignment for i ← 1 to num-samples do for each variable x sample x according to P(x|neighbors(x)) state ← state with new value of x P(F) ← fraction of states in which F is true ...
... MCMC: Gibbs Sampling state ← random truth assignment for i ← 1 to num-samples do for each variable x sample x according to P(x|neighbors(x)) state ← state with new value of x P(F) ← fraction of states in which F is true ...
Hybrid (MPP+OpenMP) version of LS-DYNA
... LS-DYNA/MPP There is a consistent option (ncpu=-N) in LS-DYNA SMP version. Many customers used to run their jjobs with the option p in SMP era,, even though g there is about 10-15% p performance penalty with the option. LSTC added the option into LS-DYNA Hybrid version. So customers can use the opti ...
... LS-DYNA/MPP There is a consistent option (ncpu=-N) in LS-DYNA SMP version. Many customers used to run their jjobs with the option p in SMP era,, even though g there is about 10-15% p performance penalty with the option. LSTC added the option into LS-DYNA Hybrid version. So customers can use the opti ...
TIE Breaking: Tunable Interdomain Egress Selection
... to have a clean separation between the intradomain and interdomain routing protocols. For example, the interdomain routing protocol allows the border routers to learn how to reach external destinations, whereas the intradomain protocol determines how to direct traffic from one router in the Autonomo ...
... to have a clean separation between the intradomain and interdomain routing protocols. For example, the interdomain routing protocol allows the border routers to learn how to reach external destinations, whereas the intradomain protocol determines how to direct traffic from one router in the Autonomo ...
Notes
... You can have an insert before the head node, an insert after the tail node, an insert before the current node and an insert after the current node. You can think up many more, but should do at least insert before and after the current node. You should do a remove current node. ...
... You can have an insert before the head node, an insert after the tail node, an insert before the current node and an insert after the current node. You can think up many more, but should do at least insert before and after the current node. You should do a remove current node. ...
Teletraffic tools for performance analysis
... Call arrivals follow a Poisson process. Packet arrivals do not Some challenges • Applications will have different rate characteristics • Correlation and long-range dependence issues • Taking advantage of the statistical multiplexing gain ...
... Call arrivals follow a Poisson process. Packet arrivals do not Some challenges • Applications will have different rate characteristics • Correlation and long-range dependence issues • Taking advantage of the statistical multiplexing gain ...
Dynamic Anchor Points Selection for Mobility Management in
... and the mobility anchor point. However, the selection of the mobility anchor stays rigid and fixed while the MN moves continually. This results in non-optimal routing, known as “triangle routing” problem, as packets always have to pass through the mobility anchor irrespective of the optimal route. T ...
... and the mobility anchor point. However, the selection of the mobility anchor stays rigid and fixed while the MN moves continually. This results in non-optimal routing, known as “triangle routing” problem, as packets always have to pass through the mobility anchor irrespective of the optimal route. T ...
How To Make Databases on Linux on System z Highly Available SUSE
... Maximum or Continuous Availability provides the most options and features with the most complexity and cost ...
... Maximum or Continuous Availability provides the most options and features with the most complexity and cost ...
IJESRT
... to wavelength continuity constraint, the already established calls or lightpaths are wavelength reassigned, so as to create a wavelength-continuous route in order to accommodate the new call. The author proposed two heuristic reassignment algorithms namely, MOLC (Minimum Overlap wavelength to Least ...
... to wavelength continuity constraint, the already established calls or lightpaths are wavelength reassigned, so as to create a wavelength-continuous route in order to accommodate the new call. The author proposed two heuristic reassignment algorithms namely, MOLC (Minimum Overlap wavelength to Least ...
Shortest Paths in Directed Planar Graphs with Negative Lengths: a
... They further show that the following problem can in turn be reduced to feasible circulation: Feasible flow: Given a directed planar graph with arc-capacities and node-demands, find an assignment of flow that respects the arc-capacities and such that, for each node, the flow into the node minus the f ...
... They further show that the following problem can in turn be reduced to feasible circulation: Feasible flow: Given a directed planar graph with arc-capacities and node-demands, find an assignment of flow that respects the arc-capacities and such that, for each node, the flow into the node minus the f ...
This critique of LISP concerns LISP+ALT
... Testing reachability of the ETRs is complex and costly - and insufficient. ITRs cannot test network reachability via each ETR, since the ITRs have no address of a device in that network. So ETRs must test network reachability and convey this to ITRs. LISP involves complex communication between ITRs ...
... Testing reachability of the ETRs is complex and costly - and insufficient. ITRs cannot test network reachability via each ETR, since the ITRs have no address of a device in that network. So ETRs must test network reachability and convey this to ITRs. LISP involves complex communication between ITRs ...
worksummary_netshiel.. - Northwestern University
... and similar speed comparing with Regular Expression based approaches – Feasibility: Snort ruleset (6,735 signatures) 86.7% can be improved by vulnerability signatures. – High speed Parsing: 2.7~12 Gbps – High speed Matching: ...
... and similar speed comparing with Regular Expression based approaches – Feasibility: Snort ruleset (6,735 signatures) 86.7% can be improved by vulnerability signatures. – High speed Parsing: 2.7~12 Gbps – High speed Matching: ...
On the Maximum Benefit Chinese Postman Problem
... The problem may be brie?y de"ned as follows. Given an undirected network G(V; E), with V representing the set of nodes, and E representing the set of edges. For each edge (i; j) ∈ E, we are given a non-negative service cost cijs for the edge traversal with service, and a non-negative deadhead cost c ...
... The problem may be brie?y de"ned as follows. Given an undirected network G(V; E), with V representing the set of nodes, and E representing the set of edges. For each edge (i; j) ∈ E, we are given a non-negative service cost cijs for the edge traversal with service, and a non-negative deadhead cost c ...
CROSS-LAYER MODELING AND OPTIMIZATION OF NEXT-GENERATION INTERNET NETWORKS a dissertation
... to massive core bandwidth growth. In this scenario, the following question arises: How can that amount of information be transported? In addressing such a fundamental question, the research community is concerned about three main facts: • In 2020, the bandwidth required will be two orders of magnitu ...
... to massive core bandwidth growth. In this scenario, the following question arises: How can that amount of information be transported? In addressing such a fundamental question, the research community is concerned about three main facts: • In 2020, the bandwidth required will be two orders of magnitu ...
Complex and Adaptive Dynamcial Systems A Lecture
... focus of these notes is the notion of complexity arising within evolving and dynamical network structures, such as the gene expression networks at the basis of all living, adaptive ecological networks or neural networks for cognitive information processing. Complex system theory ultimately forms the ...
... focus of these notes is the notion of complexity arising within evolving and dynamical network structures, such as the gene expression networks at the basis of all living, adaptive ecological networks or neural networks for cognitive information processing. Complex system theory ultimately forms the ...
Network science
Network science is an academic field which studies complex networks such as telecommunication networks, computer networks, biological networks, cognitive and semantic networks, and social networks, considering distinct elements or actors represented by nodes (or vertices) and the connections between the elements or actors as links (or edges). The field draws on theories and methods including graph theory from mathematics, statistical mechanics from physics, data mining and information visualization from computer science, inferential modeling from statistics, and social structure from sociology. The United States National Research Council defines network science as ""the study of network representations of physical, biological, and social phenomena leading to predictive models of these phenomena.""