Network partition

About: Network partition is a research topic. Over the lifetime, 654 publications have been published within this topic receiving 11713 citations. The topic is also known as: Partition tolerance.

Maximum lifetime routing in wireless sensor networks

Abstract: A routing problem in static wireless ad hoc networks is considered as it arises in a rapidly deployed, sensor based, monitoring system known as the wireless sensor network. Information obtained by the monitoring nodes needs to be routed to a set of designated gateway nodes. In these networks, every node is capable of sensing, data processing, and communication, and operates on its limited amount of battery energy consumed mostly in transmission and reception at its radio transceiver. If we assume that the transmitter power level can be adjusted to use the minimum energy required to reach the intended next hop receiver then the energy consumption rate per unit information transmission depends on the choice of the next hop node, i.e., the routing decision. We formulate the routing problem as a linear programming problem, where the objective is to maximize the network lifetime, which is equivalent to the time until the network partition due to battery outage. Two different models are considered for the information-generation processes. One assumes constant rates and the other assumes an arbitrary process. A shortest cost path routing algorithm is proposed which uses link costs that reflect both the communication energy consumption rates and the residual energy levels at the two end nodes. The algorithm is amenable to distributed implementation. Simulation results with both information-generation process models show that the proposed algorithm can achieve network lifetime that is very close to the optimal network lifetime obtained by solving the linear programming problem.

An energy-efficient unequal clustering mechanism for wireless sensor networks

Abstract: Clustering provides an effective way for prolonging the lifetime of a wireless sensor network. Current clustering algorithms usually utilize two techniques, selecting cluster heads with more residual energy and rotating cluster heads periodically, to distribute the energy consumption among nodes in each cluster and extend the network lifetime. However, they rarely consider the hot spots problem in multihop wireless sensor networks. When cluster heads cooperate with each other to forward their data to the base station, the cluster heads closer to the base station are burdened with heavy relay traffic and tend to die early, leaving areas of the network uncovered and causing network partition. To address the problem, we propose an energy-efficient unequal clustering (EEUC) mechanism for periodical data gathering in wireless sensor networks. It partitions the nodes into clusters of unequal size, and clusters closer to the base station have smaller sizes than those farther away from the base station. Thus cluster heads closer to the base station can preserve some energy for the inter-cluster data forwarding. We also propose an energy-aware multihop routing protocol for the inter-cluster communication. Simulation results show that our unequal clustering mechanism balances the energy consumption well among all sensor nodes and achieves an obvious improvement on the network lifetime

A gossip-style failure detection service

Abstract: Failure Detection is valuable for system management, replication, load balancing, and other distributed services. To date, Failure Detection Services scale badly in the number of members that are being monitored. This paper describes a new protocol based on gossiping that does scale well and provides timely detection. We analyze the protocol, and then extend it to discover and leverage the underlying network topology for much improved resource utilization. We then combine it with another protocol, based on broadcast, that is used to handle partition failures.

Learning latent block structure in weighted networks

Abstract: Community detection is an important task in network analysis, in which we aim to learn a network partition that groups together vertices with similar community-level connectivity patterns. By finding such groups of vertices with similar structural roles, we extract a compact representation of the network's large-scale structure, which can facilitate its scientific interpretation and the prediction of unknown or future interactions. Popular approaches, including the stochastic block model (SBM), assume edges are unweighted, which limits their utility by discarding potentially useful information. We introduce the weighted stochastic block model (WSBM), which generalizes the SBM to networks with edge weights drawn from any exponential family distribution. This model learns from both the presence and weight of edges, allowing it to discover structure that would otherwise be hidden when weights are discarded or thresholded. We describe a Bayesian variational algorithm for efficiently approximating this model's posterior distribution over latent block structures. We then evaluate the WSBM's performance on both edge-existence and edge-weight prediction tasks for a set of real-world weighted networks. In all cases, the WSBM performs as well or better than the best alternatives on these tasks.

Method and apparatus for balancing distributed applications

Abstract: An improved method and apparatus for balancing distributed applications within a client/server network, such as a cable television network, is disclosed. In one aspect of the invention, a method of balancing the load of distributed application client portions (DACPs) across various server portions (DASPs) and server machines is disclosed. Statistics are maintained by one or more software processes with respect to the available resources of the servers and their loading; new process threads and/or distributed application server portions are allocated across the servers to maintain optimal system performance as client device loading increases or changes. In another aspect of the invention, a novel object-oriented distributed application software architecture employing both vertical and horizontal partitions and “mutable” (i.e., transportable) objects is disclosed. The mutable objects may reside on either the server or client portions of the distributed application while maintaining at least one network partition. A runtime environment adapted for the operation of the foregoing object-oriented distributed application, including an efficient message protocol useful for interprocess communication, is also disclosed. Methods for downloading the DACP from the servers, and scaling the DACP at download based on client device configuration, are further disclosed.