A distributed approach for graph mining in massive networks

We propose a novel distributed algorithm for mining frequent subgraphs from a single, very large, labeled network. Our approach is the first distributed method to mine a massive input graph that is too large to fit in the memory of any individual compute node. The input graph thus has to be partitioned among the nodes, which can lead to potential false negatives. Furthermore, for scalable performance it is crucial to minimize the communication among the compute nodes. Our algorithm, DistGraph, ensures that there are no false negatives, and uses a set of optimizations and efficient collective communication operations to minimize information exchange. To our knowledge DistGraph is the first approach demonstrated to scale to graphs with over a billion vertices and edges. Scalability results on up to 2048 IBM Blue Gene/Q compute nodes, with 16 cores each, show very good speedup.     

An informatics-based approach to object tracking for distributed live video computing

Omnipresent camera networks have been a popular research topic in recent years. They are applicable to a range of monitoring tasks, from bridges to gas stations to the inside of industrial chemical tanks. Though a large body of existing work focuses on image and video processing techniques, very few address the usability of such systems or the implications of real-time video dissemination. In this article, we present our work on extending the LVDBMS prototype with a multifaceted object model to characterize objects in live video streams. This forms the basis for a cross-camera tracking framework which permits objects to be tracked from one video stream to another. With this infrastructure, real-time queries may be posed to monitor complex events that occur in multiple video streams simultaneously. This live video database environment provides a general-purpose platform for distributed live video computing with the goal of enabling rapid application development for camera networks.     

An optimal control approach to dynamic routing in networks

This paper explores the application of optimal control theory to the problem of dynamic routing in networks. The approach derives from a continuous state space model for dynamic routing and an associated linear optimal control problem with linear state and control variable inequality constraints. The conceptual form of an algorithm is presented for finding a feedback solution to the optimal control problem when the inputs are assumed to be constant in time. The algorithm employs a combination of necessary conditions, dynamic programming, and linear programming to construct a set of convex polyhedral cones which cover the admissible state space with optimal controls. An implementable form of the algorithm, along with a simple example, is presented for a special class of single destination networks.     

Change-aware community detection approach for dynamic social networks

Community mining is one of the most popular issues in social network analysis. Although various changes may occur in a dynamic social network, they can be classified into two categories, gradual changes and abrupt changes. Many researchers have attempted to propose a method to discover communities in dynamic social networks with various changes more accurately. Most of them have assumed that changes in dynamic social networks occur gradually. This presumption for the dynamic social network in which abrupt changes may occur misleads the problem. Few methods have tried to detect abrupt changes, but they used the statistical approach which has such disadvantages as the need for a lot of snapshots. In this paper, we propose a novel method to detect the type of changes using the least information of social networks and then, apply it to a new community detection framework named change-aware model. The experimental results on different benchmark and real-life datasets confirmed that the new method and framework have improved the performance of community detection algorithms.     

MultiGrain/MAPPER: A distributed multiscale computing approach to modeling and simulating gene regulation networks

Modeling and simulation of gene-regulatory networks (GRNs) has become an important aspect of modern systems biology investigations into mechanisms underlying gene regulation. A key task in this area is the automated inference or reverse-engineering of dynamic mechanistic GRN models from gene expression time-course data. Besides a lack of suitable data (in particular multi-condition data from the same system), one of the key challenges of this task is the computational complexity involved. The more genes in the GRN system and the more parameters a GRN model has, the higher the computational load. The computational challenge is likely to increase substantially in the near future when we tackle larger GRN systems. The goal of this study was to develop a distributed computing framework and system for reverse-engineering of GRN models. We present the resulting software called MultiGrain/MAPPER. This software is based on a new architecture and tools supporting multiscale computing in a distributed computing environment. A key feature of MultiGrain/MAPPER is the realization of GRN reverse-engineering based on the underlying distributed computing framework and multi-swarm particle swarm optimization. We demonstrate some of the features of MultiGrain/MAPPER and evaluate its performance using both real and artificial gene expression data.     

Access control method in distributed grid computing networks

The problem of data unauthorized access in distributed computing networks is considered. Existing implementations of access control mechanisms used in grid systems are analyzed and their disadvantages are listed. The access control method that makes it possible to verify the status of distributed computing networks is proposed. Security parameters that form the initial state of the system are determined.     

Efficient migration for mobile computing in distributed networks

The speed and convenience of the Internet makes it advantageous to online applications. Basing on the elliptic curve cryptosystem, this study proposes a hierarchical mobile agent framework for handling key management and access control problems between mobile agent and host. It raises the security of key management, and also controls access to distributed environment in non-specific network. The proposed method successfully secures the accessing relationship between the mobile agent and the host while economizing the exhaust of storage space. Such an achievement lets the mobile agent operate efficiently, and puts in order a secure execution environment for mobile computing.     

An efficient approach for distributed dynamic channel allocation with queues for real-time and non-real-time traffic in cellular networks

We are witnessing these days a rapid growth of mobile users. Therefore, frequency spectrum must be efficiently utilized, as available frequency spectrum is limited. This paper proposes a channel allocation scheme with efficient bandwidth reservation, which initially reserves some channels for handoff calls, and later reserves the channels dynamically, based on the user mobility. The direction of user mobility may not be straight always, but the user may also go left, right or backwards. Thus, QoS can be improved, if the channel reservation is made based upon the user mobility and the location of the user. We devise here a new algorithm that deals with multiple traffic systems by modifying the existing DDCA algorithm [Krishna, P.V., Iyengar, N.Ch.S.N., 2008. Optimal channel allocation algorithm with efficient channel reservation for cellular networks. International Journal of Communication Networks and Distributed Systems 1 (1), 33-51]. This algorithm reserves more channels for hot cells, less number of channels for cold cells and an average number of channels for the medium cells. Furthermore, we maintain queues for all types of calls. We model the system by a three-dimensional Markov Chain and compute the QoS parameters in terms of the blocking probability of originating calls and the dropping probability of handoff calls. The results indicate that the proposed channel allocation scheme exhibits better performance by considering the above mentioned user mobility, type of cells, and maintaining of the queues for various traffic sources. In addition, it can be observed that our approach reduces the dropping probability by using reservation factor.     

Access control system for distributed computing networks

The architecture of access control system for user jobs access to computational resources of grid distributed computing networks, which provides protection of data being processed against threats of exceeding user privileges, is presented. The developed system is compared to the available analogues, and the results of efficiency assessment of performance of the developed system are discussed.     

Improved migration for mobile computing in distributed networks

A mobile ad hoc network (MANET) is a special type of wireless network in which a collection of mobile nodes with wireless network interfaces may form a temporary network, without the aids of any fixed infrastructure. Security has become a hot research topic in mobile ad hoc networks. In 1998, Volker and Mehrdad proposed a tree-based key management and access control scheme for the mobile agents to manage rights to access its own resources for the visited mobile nodes. Latter, Huang et al. showed that Volker and Mehrdad's scheme needs a large amount of storage and costs for managing and storing secret keys. Huang et al. further proposed a new and efficient scheme based on the elliptic curve cryptosystems to reduce costs and gain better efficiency. However, there is a security leak inherent in Huang et al.'s scheme that the malicious node can overstep his authority to access unauthorized information. This paper will propose a secure, robust, and efficient hierarchical key management scheme for MANETs. Some practical issues and solutions about dynamic key management are also considered and proposed. As compared with Huang et al.'s scheme, our proposed scheme can provide better security assurance, while requiring smaller key-size, lower computational complexities, and constant key management costs which is independent on the number of the confidential files and the visited nodes.     

An efficient algorithm for community mining with overlap in social networks

Detecting communities in social networks represents a significant task in understanding the structures and functions of networks. Several methods are developed to detect disjoint partitions. However, in real graphs vertices are often shared between communities, hence the notion of overlap. The study of this case has attracted, recently, an increasing attention and many algorithms have been designed to solve it. In this paper, we propose an overlapping communities detecting algorithm called DOCNet (Detecting overlapping communities in Networks). The main strategy of this algorithm is to find an initial core and add suitable nodes to expand it until a stopping criterion is met. Experimental results on real-world social networks and computer-generated artificial graphs demonstrate that DOCNet is efficient and highly reliable for detecting overlapping groups, compared with four newly known proposals.     

Periodic subgraph mining in dynamic networks

In systems of interacting entities such as social networks, interactions that occur regularly typically correspond to significant, yet often infrequent and hard to detect, interaction patterns. To identify such regular behavior in streams of dynamic interaction data, we propose a new mining problem of finding a minimal set of periodically recurring subgraphs to capture all periodic behavior in a dynamic network. We analyze the computational complexity of the problem and show that it is polynomial, unlike many related subgraph or itemset mining problems. We propose an efficient and scalable algorithm to mine all periodic subgraphs in a dynamic network. The algorithm makes a single pass over the data and is also capable of accommodating imperfect periodicity. We demonstrate the applicability of our approach on several real-world networks and extract interesting and insightful periodic interaction patterns. We also show that periodic subgraphs can be an effective way to uncover and characterize the natural periodicities in a system.     

Tasks of providing information security in distributed computing networks

The issue of providing information security for data and computing resources in grid networks is reviewed. Specific features of architecture of distributed computing networks based on grid platforms are analyzed. Security threats specific for grid systems are typified. The available measures ensuring security for grid systems are considered, and their drawbacks are indicated. The set of applied issues associated with ensuring grid protection from unauthorized access is defined.     

An artificial neural network approach for routing in distributed computer networks

This paper presents a new approach based on the Hopfield model of artificial neural networks to solve the routing problem in a context of computer network design. The computer networks considered are packet switching networks, modeled as non-oriented graphs where nodes represent servers, hosts or switches, while bi-directional and symmetric arcs represent full duplex communication links. The proposed method is based on a network representation enabling to match each network configuration with a Hopfield neural network in order to find the best path between any node pair by minimizing an energy function. The results show that the time delay derived from flow assignment carried out by this approach is, in most cases, better than those determined using conventional routing heuristics. Therefore, this neural-network approach is suitable to be integrated into an overall topological design process of moderate-speed and high-speed networks subject to quality of service constraints as well as to changes in configuration and link costs.     

A soft computing approach to localization in wireless sensor networks

In this paper, we propose two intelligent localization schemes for wireless sensor networks (WSNs). The two schemes introduced in this paper exhibit range-free localization, which utilize the received signal strength (RSS) from the anchor nodes. Soft computing plays a crucial role in both schemes. In the first scheme, we consider the edge weight of each anchor node separately and combine them to compute the location of sensor nodes. The edge weights are modeled by the fuzzy logic system (FLS) and optimized by the genetic algorithm (GA). In the second scheme, we consider the localization as a single problem and approximate the entire sensor location mapping from the anchor node signals by a neural network (NN). The simulation and experimental results demonstrate the effectiveness of the proposed schemes by comparing them with the previous methods.     

Reconfigurable distributed storage for dynamic networks

This paper presents a new algorithm for implementing a reconfigurable distributed shared memory in an asynchronous dynamic network. The algorithm guarantees atomic consistency (linearizability) in all executions in the presence of arbitrary crash failures of the processing nodes, message delays, and message loss. The algorithm incorporates a classic quorum-based algorithm for read/write operations, and an optimized consensus protocol, based on Fast Paxos for reconfiguration, and achieves the design goals of: (i) allowing read and write operations to complete rapidly and (ii) providing long-term fault-tolerance through reconfiguration, a process that evolves the quorum configurations used by the read and write operations. The resulting algorithm tolerates dynamism. We formally prove our algorithm to be correct, we present its performance and compare it to existing reconfigurable memories, and we evaluate experimentally the cost of its reconfiguration mechanism.     

Dragonmail: An exercise in distributed computing

A conversation-based message system groups related messages into conversations and orders messages within conversations according to the context in which they were submitted. This paper describes the implementation of a comprehensive conversation-based message system, called Dragonmail, that extends an earlier prototype in two ways. First, it integrates conversations with conventional memo-based mail in a way that preserves the semantics of the conversation abstraction. Secondly, it provides for the distribution of software components across multiple hosts to support remote interfaces.     

An approach to efficient distributed transactions

Most distributed systems proposed on the basis of the concept of atomic action or transaction strongly limit parallelism, thus reducing their level of efficiency. In this paper, features of efficiency in a distributed transaction system are investigated. Two mechanisms are proposed in order to enhance potential concurrency both among different transactions and within a single transaction during the commit phase:

- a synchronization mechanism has been designed which suggests an approach to concurrency control by allowing the release of acquired locks before transaction completion. The possibility of exploiting this mechanism to implement nested transactions is also discussed.

- a distributed commit protocol is developed which enhances concurrency among the participants in an atomic action, thus achieving quick execution with high modularity.