A complementary pivoting algorithm for linear network problems

1986 ◽  
Vol 5 (1-4) ◽  
pp. 439-462 ◽  
Author(s):  
M. H. Schneider
Keyword(s):  
Linear Network ◽  
Network Problems ◽  
Pivoting Algorithm ◽  
Complementary Pivoting

scholarly journals Non-linear network problems

1956 ◽  
Vol 13 (4) ◽  
pp. 431-443 ◽  
Author(s):  
Garrett Birkhoff ◽  
J. B. Diaz
Keyword(s):  
Linear Network ◽  
Network Problems ◽  
Non Linear

INTEGRAL ASSESSMENT OF ANTHROPOGENIC PRESSURE ON WATER BODIES IN THE LAKE BAIKAL BASIN

2020 ◽  
Author(s):  
Irina Ulzetueva ◽  
Bair Gomboev ◽  
Daba Zhamyanov ◽  
Valentin Batomunkuev ◽  
Zorikto Banzaraktsaev
Keyword(s):  
Lake Baikal ◽  
River Basins ◽  
Anthropogenic Load ◽  
Anthropogenic Pressure ◽  
Linear Network ◽  
Baikal Basin ◽  
Discharge Water ◽  
Lake Baikal Basin ◽  
Integral Assessment ◽  
The Impact

The integrated assessment of the ecological state of the main rivers of the lake Baikal basin - Verkhnyaya Angara, Tyya, Barguzin, Selenga, Snezhnaya, Bolshaya Rechka, Khilok, Chikoy is based on the assessment of the variability of the basin system under the influence of two groups of indicators: 1) Direct (immediate) impact - the volume of water intake and wastewater discharge, water use and sequential water supply. Assessment of the impact on the state of the above-listed rivers basins from wastewater was performed using the algorithm proposed by A. Korolev et al. (2007). 2) Indirect (mediate) impact - indicators of areal and linear-network impacts on the catchment area. Based on the calculation of the integral anthropogenic pressure on the territory of the above-listed river basins, only the Selenga river experiences an “average” anthropogenic load. On the territory of most river basins, the anthropogenic load is “lowered” and “low”.

On random walks in direction-aware network problems

2010 ◽  
Vol 38 (2) ◽  
pp. 9-11 ◽  
Author(s):  
Ali Tizghadam ◽  
Alberto Leon-Garcia
Keyword(s):  
Random Walks ◽  
Network Problems

scholarly journals A Secure Protocol against Selfish and Pollution Attacker Misbehavior in Clustered WSNs

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1244
Author(s):  
Hana Rhim ◽  
Damien Sauveron ◽  
Ryma Abassi ◽  
Karim Tamine ◽  
Sihem Guemara
Keyword(s):  
Denial Of Service ◽  
Base Station ◽  
Hierarchical Organization ◽  
Secure Routing ◽  
Sensor Nodes ◽  
Dos Attacks ◽  
Linear Network ◽  
Secure Protocol ◽  
Misbehaving Nodes ◽  
Pollution Attacks

Wireless sensor networks (WSNs) have been widely used for applications in numerous fields. One of the main challenges is the limited energy resources when designing secure routing in such networks. Hierarchical organization of nodes in the network can make efficient use of their resources. In this case, a subset of nodes, the cluster heads (CHs), is entrusted with transmitting messages from cluster nodes to the base station (BS). However, the existence of selfish or pollution attacker nodes in the network causes data transmission failure and damages the network availability and integrity. Mainly, when critical nodes like CH nodes misbehave by refusing to forward data to the BS, by modifying data in transit or by injecting polluted data, the whole network becomes defective. This paper presents a secure protocol against selfish and pollution attacker misbehavior in clustered WSNs, known as (SSP). It aims to thwart both selfish and pollution attacker misbehaviors, the former being a form of a Denial of Service (DoS) attack. In addition, it maintains a level of confidentiality against eavesdroppers. Based on a random linear network coding (NC) technique, the protocol uses pre-loaded matrices within sensor nodes to conceive a larger number of new packets from a set of initial data packets, thus creating data redundancy. Then, it transmits them through separate paths to the BS. Furthermore, it detects misbehaving nodes among CHs and executes a punishment mechanism using a control counter. The security analysis and simulation results demonstrate that the proposed solution is not only capable of preventing and detecting DoS attacks as well as pollution attacks, but can also maintain scalable and stable routing for large networks. The protocol means 100% of messages are successfully recovered and received at the BS when the percentage of lost packets is around 20%. Moreover, when the number of misbehaving nodes executing pollution attacks reaches a certain threshold, SSP scores a reception rate of correctly reconstructed messages equal to 100%. If the SSP protocol is not applied, the rate of reception of correctly reconstructed messages is reduced by 90% at the same case.

An extreme‐point tabu‐search algorithm for fixed‐charge network problems

Networks ◽  
2021 ◽  
Vol 77 (2) ◽  
pp. 322-340 ◽  
Author(s):  
Richard S. Barr ◽  
Fred Glover ◽  
Toby Huskinson ◽  
Gary Kochenberger
Keyword(s):  
Tabu Search ◽  
Extreme Point ◽  
Search Algorithm ◽  
Fixed Charge ◽  
Tabu Search Algorithm ◽  
Network Problems

Queues in transportation systems, II: An independently-dispatched system

1974 ◽  
Vol 11 (01) ◽  
pp. 145-158 ◽  
Author(s):  
Michael A. Crane
Keyword(s):  
Limit Theorems ◽  
Transportation Systems ◽  
Linear Network ◽  
Random Functions ◽  
Arrival Processes ◽  
Vehicle Fleet ◽  
Vehicle Capacity ◽  
Service Groups ◽  
Functional Central Limit Theorems ◽  
Functional Central Limit

We consider a transportation system consisting of a linear network of N + 1 terminals served by S vehicles of fixed capacity. Customers arrive stochastically at terminal i, 1 ≦ i ≦ N, seeking transportation to some terminal j, 0 ≦ j ≦ i − 1, and are served as empty units of vehicle capacity become available at i. The vehicle fleet is partitioned into N service groups, with vehicles in the ith group stopping at terminals i, i − 1,···,0. Travel times between terminals and idle times at terminals are stochastic and are independent of the customer arrival processes. Functional central limit theorems are proved for random functions induced by processes of interest, including customer queue size processes. The results are of most interest in cases where the system is unstable. This occurs whenever, at some terminal, the rate of customer arrivals is at least as great as the rate at which vehicle capacity is made available.

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