A Probabilistic Energy-Aware Model for Mobile Ad-Hoc Networks

Abstract

Abstract. We propose a probabilistic, energy-aware, broadcast calculus for the analysis of mobile ad-hoc networks. The semantics of our model is expressed in terms of Segala's probabilistic automata driven by schedulers to resolve the nondeterministic choice among the probability distributions over target states. We develop a probabilistic observational congruence and a energy-aware preorder semantics. The observational congruence allows us to verify whether two networks exhibit the same observable probabilistic behaviour (connectivity), while the preorder is used to compare the energy consumption of different, but behaviourally equivalent, networks. As an application, we analyse and compare the energy consumption of two well-known automatic repeat request (ARQ)-based error control protocols: stop-and-wait (SW) and go-back-N (GBN).

Connectivity and energy-aware preorders for mobile ad-hoc networks

“…Drawing on earlier work on the subject [11,14,25,29], in the present paper we introduce a calculus to provide a formal basis for the analysis of connectivity and the evaluation of energy consumption in MANETs.…”

“…This paper is an extended and improved version of [11]. The main novelties concern the extension of the calculus through the channel restriction operator (νc) over networks.…”

“…Recently, in [42] the same authors propose a new version of their calculus built upon a stochastic mobility function to model the stochastic changes of connectivity. As in our works [12,11,14] broadcast actions are associated with the loca-tions of the intended recipients of the message. However, differently from our calculus, in [42] any notion of transmission radius is introduced and any performance analysis is considered.…”

Interference-Sensitive Preorders for MANETs

“…Drawing on earlier work on the subject (by the authors [3], [4], and by others [5], [6]), in the present paper we introduce a calculus to provide a formal basis for the analysis of connectivity and the evaluation of interference in MANETs. Like its predecessors [3], [6], our calculus is built around nodes, representing the devices of the systems, and locations, identifying the position cells across which each device may move inside the network.…”

“…Like its predecessors [3], [6], our calculus is built around nodes, representing the devices of the systems, and locations, identifying the position cells across which each device may move inside the network. Node mobility is governed by probability distributions as in [3].…”