Dynamic Heterogeneous Networks Research Articles

Numerical modeling of drug delivery in a dynamic solid tumor microvasculature

The complicated capillary network induced by angiogenesis is one of the main reasons of unsuccessful cancer therapy. A multi-scale mathematical method which simulates drug transport to a solid tumor is used in this study to investigate how capillary network structure affects drug delivery. The mathematical method involves processes such as blood flow through vessels, solute and fluid diffusion, convective transport in extracellular matrix, and extravasation from blood vessels. The effect of heterogeneous dynamic network on interstitial fluid flow and drug delivery is investigated by this multi-scale method. The sprouting angiogenesis model is used for generating capillary network and then fluid flow governing equations are implemented to calculate blood flow through the tumor-induced capillary network and fluid flow in normal and tumor tissues. Finally, convection–diffusion equation is used to simulate drug delivery. Three approaches are used to simulate drug transport based on the developed mathematical method: without a vascular network, using a static vascular network, and a dynamic vascular network. The avascular approach predicts more uniform and higher drug concentration than vascular approaches since the simplified assumptions are implemented in this method. The dynamic network which uses more realistic assumptions predicts more irregular blood vessels, high interstitial pressure, and more heterogeneity in drug distribution than other two approaches.

A Survey on Opportunistic Routing in Wireless Communication Networks

The great advances made in the wireless technology have enabled the deployment of wireless communication networks in some of the harshest environments such as volcanoes, hurricane-affected regions, and underground mines. In such challenging environments suffering from the lack of infrastructure, traditional routing is not efficient and sometimes not even feasible. Moreover, the exponential growth of the number of wireless connected devices has created the need for a new routing paradigm that could benefit from the potentials offered by these heterogeneous wireless devices. Hence, in order to overcome the traditional routing limitations, and to increase the capacity of current dynamic heterogeneous wireless networks, the opportunistic routing paradigm has been proposed and developed in recent research works. Motivated by the great interest that has been attributed to this new paradigm within the last decade, we provide a comprehensive survey of the existing literature related to opportunistic routing. We first study the main design building blocks of opportunistic routing. Then, we provide a taxonomy for opportunistic routing proposals, based on their routing objectives as well as the optimization tools and approaches used in the routing design. Hence, five opportunistic routing classes are defined and studied in this paper, namely, geographic opportunistic routing, link-state-aware opportunistic routing, probabilistic opportunistic routing, optimization-based opportunistic routing, and cross-layer opportunistic routing. We also review the main protocols proposed in the literature for each class. Finally, we identify and discuss the main future research directions related to the opportunistic routing design, optimization, and deployment.

A Bio-Inspired QoS-Oriented Handover Model in Heterogeneous Wireless Networks

We propose a bio-inspired model for making handover decision in heterogeneous wireless networks. It is based on an extended attractor selection model, which is biologically inspired by the self-adaptability and robustness of cellular response to the changes in dynamic environments. The goal of the proposed model is to guarantee multiple terminals’ satisfaction by meeting the QoS requirements of those terminals’ applications, and this model also attempts to ensure the fairness of network resources allocation, in the meanwhile, to enable the QoS-oriented handover decision adaptive to dynamic wireless environments. Some numerical simulations are preformed to validate our proposed bio-inspired model in terms of adaptive attractor selection in different noisy environments. And the results of some other simulations prove that the proposed handover scheme can adapt terminals’ network selection to the varying wireless environment and benefits the QoS of multiple terminal applications simultaneously and automatically. Furthermore, the comparative analysis also shows that the bio-inspired model outperforms the utility function based handover decision scheme in terms of ensuring a better QoS satisfaction and a better fairness of network resources allocation in dynamic heterogeneous wireless networks.

Gossip-based density estimation in dynamic heterogeneous wireless sensor networks

The density estimation of diverse sensor types in a heterogeneous sensor network is an important service that can be used in clustering schemes, node redeployment and sleep scheduling strategies. Similar to any wireless sensor network service, energy efficiency is one of the main requirements. The service has to provide an updated estimation at each node. Network dynamics, especially node mobility, introduce new challenges. Moreover, churn makes the problem even more complicated. In this paper we introduce a new approach called Gossip based Density Estimation GDE for heterogeneous dynamic networks. The devised method is able to cope with node mobility and churn, as well as redeployment of new nodes. It is fully distributed and adaptive to network dynamics. We analyse the effect of mobility as well as increased scale in the number of clusters and the quantity of nodes. The simulation results support the idea that our algorithm has a fast convergence speed and provides more accurate estimation compared to similar approaches.

Optimal forwarding ratio on dynamical networks with heterogeneous mobility

As the discovery of non-Poissonian statistics of human mobility trajectories, more attention has been paid to understanding the role of these patterns in different dynamics. In this study, we first introduce the heterogeneous mobility of mobile agents into dynamical networks, and then investigate the forwarding strategy on the heterogeneous dynamical networks. We find that the faster speed and the higher proportion of high-speed agents can enhance the network throughput and reduce the mean traveling time in the case of random forwarding. A hierarchical structure in the dependence of high-speed is observed: the network throughput remains unchanged in small and large high-speed value. It is interesting to find that the slightly preferential forwarding to high-speed agents can maximize the network capacity. Through theoretical analysis and numerical simulations, we show that the optimal forwarding ratio stems from local structural heterogeneity of low-speed agents.

Prescient Precoding in Heterogeneous DSA Networks with Both Underlay and Interweave MIMO Cognitive Radios

This work examines a novel heterogeneous dynamic spectrum access network where the primary users (PUs) coexist with both underlay and interweave cognitive transmitters (UCTs and ICTs); all terminals being potentially equipped with multiple antennas. UCTs are allowed to transmit concurrently with PUs subject to interference constraints, while the ICTs employ spectrum sensing and are permitted to access the shared spectrum only when both PUs and UCTs are absent. We investigate the design of MIMO precoding algorithms for the UCT that increase the detection probability at the ICTs, while simultaneously meeting a desired Quality-of-Service target to the underlay cognitive receivers (UCRs) and constraining interference leaked to PUs. The objective of such a proactive approach, referred to as prescient precoding, is to minimize the probability of interference from ICTs to the UCRs and primary receivers due to imperfect spectrum sensing. We begin with downlink prescient precoding algorithms for multiple single-antenna UCRs and multi-antenna PUs/ICTs. We then present prescient block-diagonalization algorithms for the MIMO underlay downlink where spatial multiplexing is performed for a plurality of multi-antenna UCRs. Numerical experiments demonstrate that prescient precoding by UCTs provides a pronounced performance gain compared to conventional underlay precoding strategies.

Synchronization analysis of heterogeneous dynamical networks

This paper investigates the synchronization problem over heterogeneous dynamical networks, in which nonidentical dynamical systems coexist. By introducing a virtual target, synchronization with an error level, called quasi-synchronization, is analyzed in asymmetric and symmetric networks, respectively. Some sufficient quasi-synchronization conditions are presented and explicit expressions of error levels are derived to estimate the synchronization error. Finally, two networks with six different Chua's circuits are provided to verify the theoretical results.

Consensus for Agents with Double Integrator Dynamics in Heterogeneous Networks

AbstractThis paper studies the convergence properties of consensus algorithms for agents with double integrator dynamics communicating over networks modelled by undirected graphs. The positions and velocities of the agents are shared along heterogeneous, i.e. different, undirected communication networks. The main result is that consensus can be achieved, even though the networks along which position and velocity information are shared are different, and not even connected. Insights on the consensus rate are given based only on the topological properties of the network.

A bio-inspired approach for cognitive radio networks

The recent increasing interest in cognitive radio networks has motivated the study and development of new approaches capable of coping with the intrinsic challenges of this kind of network, such as dynamic spectrum availability, distributed and heterogeneous network architectures, and soaring complexity. The bio-inspired approaches, with appealing characteristics such as autonomy, adaptation and collective intelligence of collaborative individuals, have been extensively studied. This paper presents a comprehensive survey of bio-inspired approaches for cognitive radio networks, emphasizing their domains of application. Specifically, ant colony optimization and particle warm optimization are further investigated with examples and numerical simulation.

FAST: Fuzzy Decision-Based Resource Admission Control Mechanism for MANETs

Mobile Ad Hoc Networks (MANETs) have inherently dynamic topologies and heterogeneous network environments. Due to the distributed, multi-hop nature of these networks, as well as limited network resource, wireless capacity and random mobility of nodes, Quality of Service (QoS) provisioning faces severe challenges, especially in multicast scenarios. Resource admission control is one of the most effective methods for resource utilization and QoS guaranteed. In this paper, we combine resource admission control technologies and intelligent methods, propose a fuzzy decision-based resource admission control mechanism for MANETs (FAST), which can fast respond to dynamic topology changes and unstable link status. FAST also supports multicast and destination heterogeneity. Users can choose multiple evaluation parameters with different weights of services in fuzzy decision. Simulation results have proved the efficiency of the mechanism.

Opinion Dynamics in Heterogeneous Networks: Convergence Conjectures and Theorems

Recently, significant attention has been dedicated to the models of opinion dynamics in which opinions are described by real numbers and agents update their opinions synchronously by averaging their neighbors' opinions. The neighbors of each agent can be defined as either (1) those agents whose opinions are in its “confidence range” or (2) those agents whose “influence range” contain the agent's opinion. The former definition is employed in Hegselmann and Krause's bounded confidence model, and the latter is novel here. As the confidence and influence ranges are distinct for each agent, the heterogeneous state-dependent interconnection topology leads to a poorly-understood complex dynamic behavior. In both models, we classify the agents via their interconnection topology and, accordingly, compute the equilibria of the system. Then, we define a positive invariant set centered at each equilibrium opinion vector. We show that if a trajectory enters one such set, then it converges to a steady state with constant interconnection topology. This result gives us a novel sufficient condition for both models to establish convergence and is consistent with our conjecture that all trajectories of the bounded confidence and influence models eventually converge to a steady state under fixed topology. Furthermore, we study the trajectories of systems with fixed interconnection topology and prove the existence of a leader group for each group of agents that determines the follower's rate and direction of convergence.

SYLPH

The significance that Ambient Intelligence (AmI) has acquired in recent years requires the development of innovative solutions. In this sense, the development of AmI-based systems requires the creation of increasingly complex and flexible applications. The use of context-aware technologies is an essential aspect in these developments in order to perceive stimuli from the context and react upon it autonomously. This paper presents SYLPH, a novel platform that defines a method for integrating dynamic and self-adaptable heterogeneous Wireless Sensor Networks (WSN). This approach facilitates the inclusion of context-aware capabilities when developing intelligent ubiquitous systems, where functionalities can communicate in a distributed way. A WSN infrastructure has been deployed for testing and evaluating this platform. Preliminary results and conclusions are presented in this paper.

Effort/gains dynamics in heterogeneous networks

AbstractWe investigate the behaviour of TCP(α, β) protocols in the presence of wireless networks. We seek an answer to strategic issues of maximizing energy and bandwidth exploitation, without damaging the dynamics of multiple‐flow equilibrium. We take a fresh perspective on protocol design: What is the return of the effort that a protocol expends? Can we achieve more gains with less effort? We study first the design assumptions of TCP(α, β) protocols and discuss the impact of equation‐based modulation of α and β on protocol efficiency. We introduce two new measures to capture protocol behaviour: the ‘Extra Energy Expenditure’ and the ‘Unexploited Available Resource Index’. We confirm experimentally that, in general, smoothness and responsiveness constitute a tradeoff; however, we show that this tradeoff does not graft its dynamics into a conservative/aggressive behaviour, as it is traditionally believed. We uncover patterns of unjustified tactics; our results suggest that an adaptive congestion control algorithm is needed to integrate the dynamics of heterogeneous networks into protocol behaviour. Copyright © 2007 John Wiley & Sons, Ltd.

Fast Bitstream Switching Algorithms for Real-Time Adaptive Video Multicasting

Bitstream switching among multiple bitstreams encoded at different bit rates is an effective way to address the bandwidth variation issue in transmitting multimedia over the Internet or wireless networks. This paper proposes two new fast real-time bitstream switching algorithms that aim to minimize the drifting error, while avoiding the problems of long delay, high complexity and bit-rate overhead for storage and transmission that often occur in prior solutions. The basic idea is to choose a switching point in a neighborhood with the highest encoding quality, within a switching window determined by the switching delay constraint. We show that they can significantly outperform a simple switching algorithm, and achieve performance that is closer to an offline mean-square-error-optimized bitstream switching solution, when compared to our previous work based on the similarity of the reference frames. The proposed schemes are especially useful in the scenario of real-time multicasting over dynamic heterogeneous networks, where multiple bitstreams with different bit rates are generated on the fly and dynamic bitstream switching is required for individual clients

Dielectric behaviour and relaxation in poly(propylene glycol)–water mixtures studied by time domain reflectometry

AbstractDielectric behaviour of poly(propylene glycol) (PPG) of number‐average molecular weight 2000 g mol−1 and binary mixtures of PPG with water (PPG–W) of various concentrations were carried out in the frequency range 10 MHz to 4 GHz at 25 °C. The dielectric dispersion and absorption curves related to the orientational motion of these molecules in the binary mixtures are described by a single relaxation time using Debye's model. The values of static dielectric constant εo, high frequency limiting dielectric constant ε∞, and dielectric relaxation time τo were determined for PPG and PPG–W mixtures. The values of the dielectric parameters were used to explore the nature of homogeneous and heterogeneous dynamic networks formed through hydrogen bonding in the binary mixtures of PPG and water molecules with concentration variation. The dielectric studies of PPG molecules were also carried out in the same frequency range at four temperatures, namely 25, 35, 45 and 55 °C. The temperature‐dependent relaxation times were used to evaluate the thermodynamical parameters for the dielectric relaxation processes. The dielectric relaxation free energy of activation ΔFτ for PPG molecules was found in the range ∼4.5 to 4.7 kcal mol−1, which corresponds to the activation energy needed for the breakage of hydrogen bonds. Furthermore, the large negative value of the entropy ΔSτ of PPG molecules confirms that the configuration involved in dipolar orientation has an activated state, which is more ordered than in the normal state. Copyright © 2004 Society of Chemical Industry

Literate Activity and Disciplinarity: The Heterogeneous (Re)production of American Studies Around a Graduate Seminar

Taking up a sociohistoric approach to writing as literate activity in functional systems and to disciplines as dynamic heterogeneous networks, I examine writing in graduate education as a key arena of disciplinary enculturation. Through an ethnographic analysis centered on the literate activity of students and a professor in an American Studies seminar, I work to integrate participants' situated activity around a field research and writing task with the historically sedimented affordances of key mediational means. The analysis particularly foregrounds heterogeneity, as multiple trajectories are woven together in the deeply laminated functional systems that (re)produce American Studies and its interdisciplinarity.