Network has been a general tool for studying the complex interactions between different genes, proteins and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases a single network is…
Tags: Veins OMNet++
Joint Traffic Splitting, Rate Control, Routing and Scheduling Algorithm for Maximizing Network Utility in Wireless Mesh Networks
The existence of multiple gateways, as is a common case in Wireless Mesh Networks (WMNs), brings the possibility to improve network performance. However, previous studies, including both heuristic-based works and theory-driven crosslayer design works, cannot guarantee an optimal exploitation of multiple gateways. In this paper, we focus on exploiting multiple gateways optimally to achieve maximum…
An Order Optimal Policy for Exploiting Idle Spectrum in Cognitive Radio Networks
In this paper, a spectrum sensing policy employing recency-based exploration is proposed for cognitive radio networks. We formulate the problem of finding a spectrum sensing policy for multiband dynamic spectrum access as a stochastic restless multiarmed bandit problem with stationary unknown reward distributions. In cognitive radio networks, the multiarmed bandit problem arises when deciding where…
Ultimate boundedness of non-autonomous dynamical complex networks under impulsive control
This paper is concerned with the ultimate boundedness problem of non-autonomous complex networks with different dynamical nodes by using the impulsive control method. Some ultimate boundedness and asymptotical stability criteria for the non-autonomous complex networks with different dynamical nodes under impulsive control are obtained by using Lyapunov functions. The results show that not only unstable…
OpenFlow-assisted online defragmentation in single-/multi-domain software-defined elastic optical networks [invited]
Spectrum fragmentation limits the efficiency of spectrum utilization in elastic optical networks (EONs). This paper studies how to take advantage of the centralized network control and management provided by software-defined EONs (SD-EONs) for realizing OpenFlow-assisted implementation of online defragmentation (DF). We first discuss the overall system design and OpenFlow protocol extensions to support efficient online…
Lag Synchronization of Switched Neural Networks via Neural Activation Function and Applications in Image Encryption
This paper investigates the problem of global exponential lag synchronization of a class of switched neural networks with time-varying delays via neural activation function and applications in image encryption. The controller is dependent on the output of the system in the case of packed circuits, since it is hard to measure the inner state of…
Second-Order Global Consensus in Multiagent Networks With Random Directional Link Failure
In this paper, we consider the second-order globally nonlinear consensus in a multiagent network with general directed topology and random interconnection failure by characterizing the behavior of stochastic dynamical system with the corresponding time-averaged system. A criterion for the second-order consensus is derived by constructing a Lyapunov function for the time-averaged network. By associating the…
TDMA-based MAC Protocols for Vehicular Ad Hoc Networks: A Survey, Qualitative Analysis and Open Research Issues
Vehicular Ad-hoc NETworks (VANETs) have attracted a lot of attention in the research community in recent years due to their promising applications. VANETs help improve traffic safety and efficiency. Each vehicle can exchange information to inform other vehicles about the current status of the traffic flow or a dangerous situation such as an accident. Road…
From Feedforward to Recurrent LSTM Neural Networks for Language Modeling
Language models have traditionally been estimated based on relative frequencies, using count statistics that can be extracted from huge amounts of text data. More recently, it has been found that neural networks are particularly powerful at estimating probability distributions over word sequences, giving substantial improvements over state-of-the-art count models. However, the performance of neural network…
Multiple-Loop Self-Triggered Model Predictive Control for Network Scheduling and Control
We present an algorithm for controlling and scheduling multiple linear time-invariant processes on a shared bandwidth-limited communication network using adaptive sampling intervals. The controller is centralized and not only computes at every sampling instant the new control command for a process but also decides the time interval to wait until taking the next sample.The approach…