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

We propose a novel routing protocol, SelfBalancing 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.

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 n 0 comprising one connected dominating set and an actual network population n > n 0 , SBSD using DSP increases subscription propagation areas by up to a factor of (n/n 0 ). Results are presented for road-based mobility models.

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.