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Routing algorithms can improve network performance by maximizing routing adaptiveness but can be problematic in the presence of endpoint congestion. Tree-saturation is a well-known behavior caused by endpoint congestion. Adaptive routing can, however, spread the congestion and result in thick branches of the congestion tree — creating Head-of-Line (HoL) blocking and degrading performance. In this...
In this paper, we consider the privacy preserving problem in an agreement network under interception attacks. First, we introduce a consensus protocol with privacy preserving, where each node hides their initial states into a set of random sequences, and then injects the sequences into the process of consensus. Second, we assume that an attacker with limited power can intercept the data transmitted...
A rapid growth in the internet network technologies claims for a better routing protocol in transmitting data. The network performance is evaluated to compare the two Link State (LS) routing protocols which are the Open Shortest Path First version3 (OSPFv3) and Intermediate System to Intermediate System (IS-IS). The evaluation is done in terms of the performance in the network convergence through...
In this paper, we present a new adaptive multiflow routing algorithm to select end-to-end paths in packetswitched networks. This algorithm provides provable optimality guarantees in the following game theoretic sense: The network configuration converges to a configuration arbitrarily close to a pure Nash equilibrium. In this context, a Nash equilibrium is a configuration in which no flow can improve...
The distributed optimal power flow problem is addressed. No assumptions on the problem cost function, and network topology are needed to solve the optimization problem. A distributed particle swarm optimization algorithm is proposed, based on Deb's rule to handle hard constraints. Moreover, the approach enables to treat a class of distributed optimization problems in which the agents share a common...
This paper proposes a method to design the coupling strengths in a multi-agent system in order to achieve consensus in arbitrary directed networks in the presence of input time-varying delays. A model transformation is carried out to convert the consensus problem into a stability one. Then, based on an appropriate Lyapunov-Krasovskii functional, sufficient conditions for consensus in multi-agent systems...
Motivated by broad applications in various fields of engineering, we study network resource allocation problems where the goal is to optimally allocate a fixed portion of resources over a network of nodes. In these problems, due to the large scale of the network and complicated interconnections between nodes, any solution must be implemented in parallel and based only on local data resulting in a...
This paper focuses on the resource allocation problem with equality and inequality constraints in a fixed weight-balanced directed or undirected network. Moreover, we propose a fully decentralized subgradient algorithm with event-triggered for solving above resource allocation problem based on first-order discrete-time multi-agent systems. Where each agent only communicates with its neighbors and...
The study of the synchronization problems in wireless sensor networks (WSNs) is increasingly significant. Some researchers found that the network topology has an important impact on the convergence performance of the synchronization in WSNs. According to the feature of WSNs, we use random geometric graph (RGG) to describe the model of WSNs. And the degree distribution in RGG is similar to binomial...
This paper presents a hierarchical structure to solve the discrete time consensus problem for a group of agents. All the agents are divided into a couple of groups, and a new notation, called group information is proposed, which indicates all the agents' states inside one group. For each agent, it receives the information not only from the agent neighbors in the same group, but also the group information...
In this paper, we consider the privacy preserving problem of consensus protocol. First, we introduce a privacy preserving scheme, where each node produces and transmits a sequence of random values with their mean equaling to the node's initial state. We show that the network can reach average consensus with privacy preserving scheme, and provide a sufficient condition under which the initial state...
This paper presents a preemptive job scheduler based on a 3-layer Backpropagation Neural Network (BPNN) and a greedy task alignment procedure. The BPNN estimates priority values of jobs based on the attributes of their subtasks and the given job selection criteria of the scheduler. The scheduler is formulated in such a way that, at each time interval, the most priority job will be selected from the...
This paper studies the consensus based Kalman filtering problem for discrete-time linear systems in sensor networks. Considering the fact that just part of sensors in the network can measure the target, the filtering algorithms of the sensors are assigned differently according to the availability to get the direct measurements. For the sensors that can directly get the measurement outputs, we call...
The consensus algorithm is proposed to solve the bounded consensus tracking problems of leader-following multi-agent systems under directed networks, where the control input of an agent can only use the information measured at the sampling instants from its neighbors or the virtual leader. Based on the delay decomposition approach, the augmented matrix method and the frequency domain analysis, the...
The dynamics of two-word naming game incorporating the influence of biased assimilation is investigated in this paper. Firstly an extended naming game with biased assimilation (NGBA) is proposed. The hearer in NGBA accepts the received information in a biased manner, where he will refuse to accept the conveyed word with a predefined probability, if it is different from his own current memory. Secondly,...
Conventional routing protocols such as RIP, OSPF, EIGRP and BGP have a very rigid and intricate system thus narrowing the adaptability of networks to the ever changing Internet. The emergence of Software Defined Networking (SDN) provides a solution for this problem. Due to the handiness of a centralized controller, SDN has provided an effective method in terms of routing computation and fine control...
Convergence speed of the multi-agent system is usually determined by the algebraic connectivity of the communication network. By changing the network topology or getting more state information, the algebraic connectivity can increase, but it is usually fixed and may be very small, which means that it cannot be adjusted flexibly according to the requirements of the convergence speed. In order to overcome...
This paper investigates the asymptotic behavior of opinion dynamics in relative-opinion-dependent networks, which is motivated by the observation that a social agent tends to accept opinions close to itself. That is, the interpersonal influence between social agents decreases gradually in their relative opinion. It is interesting that this model can also provide a unified framework to study both the...
This paper develops a distributed stochastic subgrandient-based support vector machine algorithm when training data to train support vector machines are distributed in the network. In this situation, all the data are decentralized stored and unavailable to all agents and each agent has to make its own update based on its computation and communication with neighbors. With mild connectivity conditions,...
This paper proposes a diffusion proportionate affine projection sign algorithm for distributed estimation of sparse vector over network. The algorithm is derived by minimizing l1-norm intermediate error vector subject to a weighted constraint on the filter coefficients, where the positive definite weighting matrix is designed to accelerate the convergence of the nonzero coefficients for sparse vector...
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