Speeding Up the Estimation of Expected Maximum Flows Through Reliable Networks

In this paper we present a strategy for speeding up the estimation of expected maximum flows through reliable networks. Our strategy tries to minimize the repetition of computational effort while evaluating network states sampled using the crude Monte Carlo method. Computational experiments with this strategy on three types of randomly generated networks show that it reduces the number of flow augmentations required for evaluating the states in the sample by as much as 52% on average with a standard deviation of 7% compared to the conventional strategy. This leads to an average time saving of about 71% with a standard deviation of about 8%.

Exact Computation of Influence Spread by Binary Decision Diagrams

Evaluating influence spread in social networks is a fundamental procedure to estimate the word-of-mouth effect in viral marketing. There are enormous studies about this topic; however, under the standard stochastic cascade models, the exact computation of influence spread is known to be #P-hard. Thus, the existing studies have used Monte-Carlo simulation-based approximations to avoid exact computation. We propose the first algorithm to compute influence spread exactly under the independent cascade model. The algorithm first constructs binary decision diagrams (BDDs) for all possible realizations of influence spread, then computes influence spread by dynamic programming on the constructed BDDs. To construct the BDDs efficiently, we designed a new frontier-based search-type procedure. The constructed BDDs can also be used to solve other influence-spread related problems, such as random sampling without rejection, conditional influence spread evaluation, dynamic probability update, and gradient computation for probability optimization problems. We conducted computational experiments to evaluate the proposed algorithm. The algorithm successfully computed influence spread on real-world networks with a hundred edges in a reasonable time, which is quite impossible by the naive algorithm. We also conducted an experiment to evaluate the accuracy of the Monte-Carlo simulation-based approximation by comparing exact influence spread obtained by the proposed algorithm.Comment: WWW'1

Full duplex switched ethernet for next generation "1553B" -based applications

Over the last thirty years, the MIL-STD 1553B data bus has been used in many embedded systems, like aircrafts, ships, missiles and satellites. However, the increasing number and complexity of interconnected subsystems lead to emerging needs for more communication bandwidth. Therefore, a new interconnection system is needed to overcome the limitations of the MIL-STD 1553B data bus. Among several high speed networks, Full Duplex Switched Ethernet is put forward here as an attractive candidate to replace the MIL-STD 1553B data bus. However, the key argument against Switched Ethernet lies in its non-deterministic behavior that makes it inadequate to deliver hard timeconstrained communications. Hence, our primary objective in this paper is to achieve an accepted QoS level offered by Switched Ethernet, to support diverse "1553B"-based applications requirements. We evaluate the performance of traffic shaping techniques on Full Duplex Switched Ethernet with an adequate choice of service strategy in the switch, to guarantee the real-time constraints required by these specific 1553B-based applications. An analytic study is conducted, using the Network Calculus formalism, to evaluate the deterministic guarantees offered by our approach. Theoretical analysis are then investigated in the case of a realistic "1553B"-based application extracted from a real military aircraft network. The results herein show the ability of profiled Full Duplex Switched Ethernet to satisfy 1553B-like real-time constraints

WiLiTV: A Low-Cost Wireless Framework for Live TV Services

With the evolution of HDTV and Ultra HDTV, the bandwidth requirement for IP-based TV content is rapidly increasing. Consumers demand uninterrupted service with a high Quality of Experience (QoE). Service providers are constantly trying to differentiate themselves by innovating new ways of distributing content more efficiently with lower cost and higher penetration. In this work, we propose a cost-efficient wireless framework (WiLiTV) for delivering live TV services, consisting of a mix of wireless access technologies (e.g. Satellite, WiFi and LTE overlay links). In the proposed architecture, live TV content is injected into the network at a few residential locations using satellite dishes. The content is then further distributed to other homes using a house-to-house WiFi network or via an overlay LTE network. Our problem is to construct an optimal TV distribution network with the minimum number of satellite injection points, while preserving the highest QoE, for different neighborhood densities. We evaluate the framework using realistic time-varying demand patterns and a diverse set of home location data. Our study demonstrates that the architecture requires 75 - 90% fewer satellite injection points, compared to traditional architectures. Furthermore, we show that most cost savings can be obtained using simple and practical relay routing solutions