Doug Lundquist

Demand-driven publish/subscribe in mobile environments

We propose a novel routing protocol, Self-Balancing Supply/Demand (SBSD), for Publish/Subscribe in mobile ad hoc environments. SBSD is a controlled flooding that reduces network congestion by constraining how far subscriptions replicate and how many times nodes broadcast them. SBSD ranks subscriptions by a utility function. This function matches the supply of publications with the recent demand for them; more popular subscriptions are replicated farther and their replicas are retained longer. SBSD is therefore demand-driven, as more popular subscriptions are more likely to receive their matching publications and receive them sooner. We show that SBSD is scalable; routing distance is independent of network size. SBSD’s performance is examined under random mobility, under challenging conditions including high node mobility and broadcast failure rates.

An efficient demand-driven and density-controlled publish/subscribe protocol for mobile environments

A protocol for high-density Mobile Ad Hoc Networks (MANETs) is presented. Subscription-Based Permission (<i>SP</i>) routing extends Self-Balancing Supply/Demand (<i>SBSD</i>) protocols, which combine the Publish/Subscribe paradigm and demand-controlled flooding. The goal of <i>SP</i> is to reduce redundant broadcasting without sacrificing coverage, by exploiting high density. <i>SP</i> defines η sets of brokers, each set refusing to accept replicas of a fraction (<i>1/η</i>) of all subscription types. The value of η is determined such that each set is expected to comprise a connected dominating set. Given a theoretical mobile device population <i>N<inf>0</inf></i> sufficient to achieve one connected dominating graph and an actual network population <i>N</i> > <i>N<inf>0</inf></i>, we show that <i>SBSD-SP</i> increases subscription propagation areas by a factor of (<i>N/N<inf>0</inf></i>) without materially sacrificing reachability. This improves network throughput by a factor of (<i>N/N<inf>0</inf></i>), as publications are delivered to (<i>N/N<inf>0</inf></i>) times as many brokers.

A Context-Aware Cross-Layer Broadcast Model for Ad Hoc Networks

Abstract The standard 802.11 medium access control (MAC) performs poorly for heavy broadcast traffic. We present our context-aware cross-layer (CACL) broadcast model as an alternative. CACL uses only contextual data available to the 802.11 MAC and so is usable by any routing protocol that uses the 802.11 MAC. CACL fits the total broadcasts in any two-hop neighborhood to wireless channel capacity. We compare collision rates for CACL and the 802.11 MAC and conclude that, for a wide range of network conditions, CACL offers superior reliability and throughput

A Context-Aware Cross-Layer Broadcast Model for Ad Hoc Networks: Analysis of Multi-Hop Routing

Abstract The standard 802.11 medium access control (MAC) performs poorly for heavy broadcast traffic. We propose an alternative context-aware cross-layer (CACL) broadcast model that relies only on contextual information available to the 802.11 MAC. We compare CACL and the 802.11 MAC in conjunction with a controlled flooding routing protocol, Self-Balancing Supply/Demand (SBSD). We test three different road-based mobility levels, varying the rate of request posting in each. We observe that CACL strongly outperforms the 802.11 MAC at high posting rates.

Distributed Delay: Improving Network Throughput by Reducing Temporal Saturation

We present the Distributed Delay (DD) extension to the Self-Balancing Supply/Demand (SBSD) routing protocols for mobile ad hoc networks. SBSD controls flooding depth to limit network congestion and provides redundant broadcasts at each hop for reliable end-to-end delivery. In DD, the delay between a node-s successive broadcasts increases with that node-s one-hop density, to reduce broadcast redundancy. Simulations consider road-based mobility with varying densities and network traffic levels. Our results show SBSD extended by DD reduces network congestion such that end-to-end delivery for total network traffic is improved without greatly slowing response time.

Dynamic Subscription Permission: Extending the Depth of Demand-Controlled Flooding

We present a method for improving publication delivery range in self-balancing supply/demand (SBSD) routing. This method, dynamic subscription permission (DSP), restricts each subscription type to an estimated connected dominating set and dynamically restricts routing to adapt to local density variations. Given a theoretical mobile device population n0 comprising one connected dominating set and an actual network population n > n0, SBSD using DSP increases subscription propagation areas by up to a factor of (n/n0). Results are presented for road-based mobility models.

A context-aware cross-layer broadcast model for ad hoc networks

The standard 802.11 medium access control (MAC) performs poorly for heavy broadcast traffic. We present our context-aware cross-layer (CACL) broadcast model as an alternative. The basic CACL model uses only contextual data available to the 802.11 MAC and so is usable by any routing protocol that uses the 802.11 MAC. CACL fits the total broadcasts in any two-hop neighborhood to wireless channel capacity. We compare collision rates for CACL and the 802.11 MAC and conclude that, for a wide range of network conditions, CACL offers superior single-hop transmission rates. We also present a geographically constrained extension to CACL, CACL-G and compare it against CACL in vehicular scenarios of varying node density. Our results show that CACL-G offers increasingly superior performance over the basic CACL model as node density increases.

Ontology-Driven Cyber-Security Threat Assessment Based on Sentiment Analysis of Network Activity Data

Sentiment analysis is gaining acceptance as a tool for automated understanding of consumer attitudes and preferences. Based on well-designed rule sets that describe how most people express their sentiments, sentiment analysis models enable automated processes to understand human responses. In this paper, we describe our vision of extending sentiment analysis to the novel domain of cyber-security. Our proposal combines: 1) ontological modeling of attacks, defenses, and attacker goals; 2) sentiment analysis of combinations of elements indicative of probable attacks; and 3) semantic reconciliation of borderline cases to more definitively classify ambiguous network activity as threatening or innocuous. This method has achieved good results (86% correct) in assessing consumer sentiments, and we believe that more detailed models can improve on this accuracy even in the complex domain of cyber-security.

Finding seller quality and quality sellers in online markets: an agent-based analysis

We construct an agent-based model of the online electronics market, consisting of 10,000 buyers and 50 sellers. Buyers repeatedly interact with sellers, searching for high quality and low price, but only some buyers know seller quality prior to purchase. Buyers may learn seller quality directly or from information obtained from other buyers or else estimate quality through market share heuristics. We examine the efficacy of these learning and estimation methods and find that preferential searching, where the probability of searching any seller is its market share, leads to higher consumer surplus and significantly lower levels of price dispersion.

A hybrid ad hoc networking protocol for disaster recovery resource management

Following a major disaster, the infrastructure supporting wired and mobile networking is expected to be inoperable over large areas. Thus, emergency response teams must communicate using their own networking equipment. A large-scale peer-to-peer network offers fast and flexible deployment but requires cooperation among nodes. Usage constraints must be imposed to prevent overloading the shared network capacity. In particular, disparate communication models (for route building and optimisation, resource management, and localised status flooding) must be integrated. We propose a hybrid network protocol which dynamically assigns network capacity to these three communication models by imposing transmission delays in accordance with their attempted usage rates.