Heuristic Design Algorithm for Computer Communication Networks with Different Classes of Packets

To provide the differential quality of service (QoS) for different classes of packets and reduce the packet loss probability (PLP), a novel priority-based composite assembly scheme for optical burst switching (OBS) networks is proposed. The low and high packet classes are aggregated into a single burst simultaneously, and the highest-priority packets are placed in the middle, while the low-priority packets are at the tail and head of the burst. The priority is lowered gradually from the middle to the ends. Simulation results demonstrate that the proposed assembly strategy not only guarantees the integrity of the high-priority bursts, but also significantly reduces the average end-to-end delay of the bursts and the PLP of network. So it can adapt to the flexible network with QoS requirement.

In this paper, a new packet loss control mechanism in congested networks known as dynamic partial buffer sharing (DPBS) is proposed. In contrast to the static partial buffer sharing (SPBS) scheme, the thresholds are dynamically varied in run-time based on packet loss behaviors. A problem with the SPBS scheme is that there is no simple mathematical expression relating the thresholds to the desired packet loss ratios among the different classes of packets, especially in the case of nested thresholds. Also, the variation of packet loss probabilities can be very large. These problems are overcome in the DPBS scheme. The desired packet loss ratios can be achieved by setting the control parameters according to a simple formula. Simulation results show that the mean packet loss probability of DPBS is smaller than that of SPBS by 3% to 47% while the loss variation is improved by 100 times to 1000 times under the same input traffic. It is a benefit, especially for congestion control.

A heuristic search algorithm is given that determines and resolves the Hamiltonian circuit problem in directed graphs. The heuristic information of each vertex is a set composed of its possible path length values from the starting vertex, which is obtained by the path length extension algorithm. A detailed analysis of algorithm examples shows that the heuristic algorithm can greatly reduce the number of processing nodes compared to the backtracking algorithm without information; meanwhile, the algorithm’s time complexity is related to the number of loops in the directed graph. If a directed graph G(V, E) only contains loops that contain the starting point, then the Hamiltonian problem of G can be determined in polynomial time. The algorithm is implemented using C++ and Python programming, and all of the test graphs are generated by the random graph algorithm. The experiments show that the heuristic algorithm can reduce the number of extended nodes by at least 10% in directed random graphs with no or only a few loops. This heuristic algorithm can save time in applications that perform tasks while extending nodes because it reduce the number of extended nodes.

On etudie ici une version continue du probleme de dimensionnement et routage dans un reseau de communications, dans lequel les couts de conception sont combines aux mesures de delai moyen d'acheminement, engendrant un probleme de multiflots avec une fonction objectif non convexe. On propose un encadrement de la valeur optimale par convexification separable sur les arcs, d'une part, et par calcul d'optima locaux issus d'un modele DC (difference de fonctions convexes) des fonctions de cout. Cette derniere technique permet de reduire la distance a la valeur optimale et on illustre son efficacite sur des problemes d'expansion de capacites.

An algorithm for the optimization of nonbifurcated flows in computer communication networks

We propose a quasi-dynamic network design algorithm considering traffic growth in multi-layered photonic networks that consist of electrical paths and optical paths. The quasi-dynamic network design proposed herein leaves existing paths unchanged in order to minimize service disruption due to path rerouting as well as human error. Simulations verify that the network cost strongly depends on the network design algorithms adopted and the holding terms of service traffic. We, then, introduce a new parameter that represents expected service holding terms. The parameter is shown to represent effectively the network cost trend versus the number of the incremental designs. Furthermore, lower network cost is obtained by taking advantage of the network design algorithms that consider service holding times. This study is the first to address the criteria in designing future multi-layered photonic networks that offer cost-effective expansion while accommodating different services.

ObjectivesGrey matter network disruptions in Alzheimer's disease (AD) are associated with worse cognitive impairment cross‐sectionally. Our aim was to investigate whether indications of a more random network organization are associated with longitudinal decline in specific cognitive functions in individuals with subjective cognitive decline (SCD). Experimental design: We included 231 individuals with SCD who had annually repeated neuropsychological assessment (3 ± 1 years; n = 646 neuropsychological investigations) available from the Amsterdam Dementia Cohort (54% male, age: 63 ± 9, MMSE: 28 ± 2). Single‐subject grey matter networks were extracted from baseline 3D‐T1 MRI scans and we computed basic network (size, degree, connectivity density) and higher‐order (path length, clustering, betweenness centrality, normalized path length [lambda] and normalized clustering [gamma]) parameters at whole brain and/or regional levels. We tested associations of network parameters with baseline and annual cognition (memory, attention, executive functioning, language composite scores, and global cognition [all domains with MMSE]) using linear mixed models, adjusted for age, sex, education, scanner and total gray matter volume. Principal observations: Lower network size was associated with steeper decline in language (β ± SE = 0.12 ± 0.05, p < 0.05FDR). Higher‐order network parameters showed no cross‐sectional associations. Lower gamma and lambda values were associated with steeper decline in global cognition (gamma: β ± SE = 0.06 ± 0.02); lambda: β ± SE = 0.06 ± 0.02), language (gamma: β ± SE = 0.11 ± 0.04; lambda: β ± SE = 0.12 ± 0.05; all p < 0.05FDR). Lower path length values in precuneus and fronto‐temporo‐occipital cortices were associated with a steeper decline in global cognition.ConclusionsA more randomly organized grey matter network was associated with a steeper decline of cognitive functioning, possibly indicating the start of cognitive impairment.

Survivable ATM mesh networks: Techniques and performance evaluation

The ever-increasing concerns of the growth in the volume of waste tires, reduction in natural resources and new strict government legislations to reduce the environmental impact of the end-of-life (EOL) tires have increased interest among companies to design a sustainable and efficient closed-loop supply-chain (CLSC) network. A CLSC is a network with a holistic view of the entire forward and reverse logistic system with the aim of transferring the EOL products up the stream from the end users for value recovery such as reuse, repair, remanufacturing, or recycling.There are many factors that are considered when designing a closed-loop supply-chain network, such as uncertainty in the parameters, costs, environmental impacts, social dimensions, governmental regulations, domestic and international competition, disruption and operational risks, reliability of the network, technological advancements, etc. In the real world, the CLSC network design is subject to a variety of uncertainties which can be random and fuzzy. Designing a reliable and environmentally conscious CLSC which considers the risks and uncertainties of the parameters in the network is necessary for a successful supply-chain network. The government regulations could have a significant impact on the supply chain network design, its management and the long/short-term investment decisions. Ever-changing restrictions, mandates and tax policies can affect corporation's competitive advantage, market share, and operational costs. Tariffs and caps imposed on imported goods, intended to limit the volume of imports, protect domestic employment and reduce competition among domestic industries. One of the challenges facing the recovery of EOL products is the uncertainty associated with the conditions of the EOL products after being returned. Designing intelligent products that can collect valuable information during their life cycles is something that has been studied in the past decade. This information can be used to extend the life span of the products and improve the value recovery of EOL products. In this dissertation, we take a closer look at the challenges facing the tire industry and obtain a solution that creates a win-win situation for companies in the tire network as well as the environment. We evaluate the available recovery options for EOL tires, identify the uncertain parameters in the logistics network and find the solution for dealing with these uncertainties using robust modeling for the logistics network. In the first model, we introduce a robust multi-objective, multi-product, multi-echelon, multi-cycle, multi-capacity, green closed-loop supply-chain network under hybrid uncertainty with the objective of reducing costs, reducing environmental impacts, and increasing the social responsibilities and the reliability of the network. Second, we study the impact of tariffs and government regulations on the profitability of the network. Third, we evaluate the impact of using sensor embedded tires on the design of CLSC network. The analysis is done using a novel Robust Fuzzy/ Possibilistic Stochastics Programming (RFSP) model that controls scenario-based uncertainty (disruption risks) and fuzzy-based uncertainty (operational risks) in the network simultaneously and provides more reliable results for the managers and the decision makers. We evaluate the possibility and feasibility of expanding the existing forward logistic network at different capacity levels to cope with the market demand under various scenarios as well as the feasibility of establishing a new reverse logistic network at different capacity levels to cope with the return rate of EOL tires. A case example is considered to illustrate the implementations and validation of the proposed models. --Author's abstract

Priority assignment in the multi-robot path planning becomes a key challenge in the present situation. The motivation for the priority assignment is to utilize the search space for all the robots and minimize the overall path length. When the number of robots increases, the complexity also increases for the same search space. This paper gives the idea about how to assign the priority and choose the best minimum path length. The simulation results show the output performed and success rate of the robots.

In this paper, two distinct optical network design approaches, namely mesh and multi-ring, for survivable WDM networks are investigated. The main objective is to compare these two design approaches in terms of network costs so that their merits in practical environments can be identified. In the mesh network design, a new mathematical model based on integer liner programming (ILP) and a heuristic algorithm are presented for achieving a minimal cost network design. In the multi-ring network design, a heuristic algorithm that can be applied to large network problems is proposed. The influence of wavelength conversion and the number of wavelengths multiplexed in a fiber on system designs are also discussed. Based on the simulation results, the redundancy quantities required for full protection in multi-ring approach are significantly larger in comparison to the minimal cost mesh counterpart.

Metaheuristics for optimization problems in computer communications

We propose a network segmentation and design algorithm based on traffic distribution information. Numerical experiments demonstrated that the proposed algorithm can greatly reduce network cost.

Dynamic Modeling in Design and Operation Safety Checking of Large Scale Pipeline Networks

We focus on the design of the logical layer on an optical infrastructure for three different architectures: fixed grid WDM with fixed-rate multilevel modulation (WDM-FRMF), fixed grid WDM with time-domain hybrid modulation formats (WDM-TDHFM) and flexible grid (FG). A fairly detailed physical layer modeling is considered in the network design algorithms. Simulations are performed on a 20 nodes network with varying traffic loads. Besides comparing the two paradigms of flexible and fixed grid networks, including both pure and hybrid modulation formats, in terms of their spectral efficiency and number of blocked requests, we show the importance of integrating a detailed physical layer modeling in the network design phase. We mostly focus on the investigation of the impact of changing physical layer design parameters such as fiber type and span length on network level performance.