Sharif Digital Repository

In this paper, we propose an energy-aware node-eentric load balancing algorithm that constructs a load balanced tree in sensor networks of asymmetric architecture. We show that the proposed energy-aware algorithm creates routing trees with better load balancing across the network and longer network life time compared to the other proposed algorithms. We also introduce a network information gathering (NIG) protocol that can collect the required information (load and neighboring information) from nodes and forward them to the base station. This protocol can be used by all centralized systems that require some additional information about nodes in the network. ©2007 IEEE  

The spread of information cascades over social networks forms the diffusion networks. The latent structure of diffusion networks makes the problem of extracting diffusion links difficult. As observing the sources of information is not usually possible, the only available prior knowledge is the infection times of individuals. We confront these challenges by proposing a new method called DNE to extract the diffusion networks by using the time-series data. We model the diffusion process on information networks as a Markov random walk process and develop an algorithm to discover the most probable diffusion links. We validate our model on both synthetic and real data and show the low dependency... 

Mixture of Experts (ME) is a modular neural network architecture for supervised learning. In this paper, we propose an evidence-based ME to deal with the classification problem. In the basic form of ME the problem space is automatically divided into several subspaces for the experts and the outputs of experts are combined by a gating network. Satisfactory performance of the basic ME depends on the diversity among experts. In conventional ME, different initialization of experts and supervision of the gating network during the learning procedure, provide the diversity. The main idea of our proposed method is to employ the Dempster-Shafer (D-S) theory of evidence to improve determination of... 

Online media play an important role in information societies by providing a convenient infrastructure for different processes. Information diffusion that is a fundamental process taking place on social and information networks has been investigated in many studies. Research on information diffusion in these networks faces two main challenges: (1) In most cases, diffusion takes place on an underlying network, which is latent and its structure is unknown. (2) This latent network is not fixed and changes over time. In this article, we investigate the diffusion network extraction (DNE) problem when the underlying network is dynamic and latent. We model the diffusion behavior (existence... 

A mobile ad hoc network (MANET) is a network without any predefined infrastructure in which every node not only enjoys the services from the network, but serves the network as a relaying router. Because of nodes mobility, these kinds of networks are highly dynamic. Therefore, link failure is so frequent. In this paper we propose a novel mobility management method which is independent of underlying routing protocol. Based on this mechanism, a node tries to keep an alternate node for its next hop and when a link breakage occurs, simply node uses its alternate node as next hop. Simulation results show that this mechanism can reduce average number of hop counts, number of selected routes and... 

Network-on-Chip (NoC) is a precious approach to handle huge number of transistors by virtue of technology scaling to lower than 50nm. Virtual channels have been introduced in order to improve the performance according to a timing multiplexing concept in each physical channel. The incremental effect of virtual channels on power consumption has been shown in literatures. The issue of power saving has always been controversial to many designers. In this paper, we introduce a new technique which tries to adaptively mange the number of virtual channels in order to reduce the power consumption while not degrading the performance of the network without any reconfiguration. Our experimental results... 

Stretched hypercube has recently been introduced as an attractive alternative to the well-known hypercube. Previous research on this network topology has mainly focused on topological properties and VLSI aspects of this network In this paper, we propose some deterministic and adaptive routing algorithms for the stretched hypercubes. The performance of stretched hypercubes using the proposed routing algorithms is then evaluated by means of simulation experiments. Experiments are reahzed under different working loads and for different network actors. © 2008 IEEE  

In a large system, it is neither economical nor efficient to equip each node with a copy of the resource, and it is desirable to distribute the copies of the resource so that certain performance measure is obtained. In this paper we consider the problem of distributing resources in the edge product of networks. The algorithms presented in this paper make use of the known placements for the basic graphs composing the product graph. Therefore, in these placements we avoid the additional costs needed for deploying and rescaling the network. © 2008 IEEE  

People use social networks to share millions of stories every day, but these stories rarely become viral. Can we estimate the probability that a story becomes a viral cascade If so, can we find a set of users that are more likely to trigger viral cascades These estimation and maximization problems are very challenging since both rare-event nature of viral cascades and efficiency requirement should be considered. Unfortunately, this problem still remains largely unexplored to date. In this paper, given temporal dynamics of a network, we first develop an efficient viral cascade probability estimation method, VICE, that leverages an special importance sampling approximation to achieve high... 

User engagement in online social networking depends critically on the level of social activity in the corresponding platform-the number of online actions, such as posts, shares or replies, taken by their users. Can we design data-driven algorithms to increase social activity? At a user level, such algorithms may increase activity by helping users decide when to take an action to be more likely to be noticed by their peers. At a network level, they may increase activity by incentivizing a few influential users to take more actions, which in turn will trigger additional actions by other users. In this paper, we model social activity using the framework of marked temporal point processes,... 

People use social networks to share millions of stories every day, but these stories rarely become viral. Can we estimate the probability that a story becomes a viral cascade? If so, can we find a set of users that are more likely to trigger viral cascades? These estimation and maximization problems are very challenging since both rare-event nature of viral cascades and efficiency requirement should be considered. Unfortunately, this problem still remains largely unexplored to date. In this paper, given temporal dynamics of a network, we first develop an efficient viral cascade probability estimation method, ViCE, that leverages an special importance sampling approximation to achieve high... 

Traditionally, to handle security for stand-alone computers and small networks, user authentication and access control mechanisms would be almost enough. However, considering distributed networks such as the Internet and pervasive environments, these kinds of approaches confront with flexibility challenges and scalability problems. This is mainly because of that open environments lack a central control, and users in them are not predetermined, in such ubiquitous computing environments, issues concerning security and trust become crucial. Adding trust to the existing security infrastructures would enhance the security of these environments. Although many trust models have been proposed to... 

k-Neigh is a basic neighbor-based topology control protocol based on the construction of k-neighbor graph as logical communication graph. Although k-Neigh is based on a connectivity theory, several topological aspects of the constructed topology are not yet analytically investigated. In this paper, several topological properties of the constructed topology after execution of the protocol, including probability density function of the distance between each node to its ith neighbor, probability of unidirectional links after execution of the first phase of the protocol, average logical degree, and average final transmission range, are investigated analytically. Moreover, an extensive simulation... 

Supply chain management integrates planning and controlling of materials, information, and finances in a process which begins from suppliers and ends with customers. Optimal planning decisions made in such a distribution network usually include transportation, facilities location, and inventory. This study presents a new approach for considering customers’ differentiation in an integrated location-allocation and inventory control model using transfer recurrent neural network (RNN). In this study, a location and allocation problem is integrated with inventory control decisions considering two classes of strategic and non-strategic customers. For the first time, a novel transfer RNN is applied...