Reaction-Diffusion Based Transmission Patterns for Ad Hoc Networks

We present a new scheme that mimics pattern formation in biological systems to create transmission patterns in multi-hop ad hoc networks. Our scheme is decentralized and relies exclusively on local interactions between the network nodes to create global transmission patterns. A transmission inhibits other transmissions in its immediate surrounding and encourages nodes located further away to transmit. The transmission patterns created by our medium access control scheme combine the efficiency of allocation-based schemes at high traffic loads and the flexibility of random access schemes. Moreover, we show that with appropriately chosen parameters our scheme converges to collision free transmission patterns that guarantee some degree of spatial reuse

Spatial Fluid Limits for Stochastic Mobile Networks

We consider Markov models of large-scale networks where nodes are characterized by their local behavior and by a mobility model over a two-dimensional lattice. By assuming random walk, we prove convergence to a system of partial differential equations (PDEs) whose size depends neither on the lattice size nor on the population of nodes. This provides a macroscopic view of the model which approximates discrete stochastic movements with continuous deterministic diffusions. We illustrate the practical applicability of this result by modeling a network of mobile nodes with on/off behavior performing file transfers with connectivity to 802.11 access points. By means of an empirical validation against discrete-event simulation we show high quality of the PDE approximation even for low populations and coarse lattices. In addition, we confirm the computational advantage in using the PDE limit over a traditional ordinary differential equation limit where the lattice is modeled discretely, yielding speed-ups of up to two orders of magnitude

A Reaction-Diffusion-Based Coding Rate Control Mechanism for Camera Sensor Networks

A wireless camera sensor network is useful for surveillance and monitoring for its visibility and easy deployment. However, it suffers from the limited capacity of wireless communication and a network is easily overflown with a considerable amount of video traffic. In this paper, we propose an autonomous video coding rate control mechanism where each camera sensor node can autonomously determine its coding rate in accordance with the location and velocity of target objects. For this purpose, we adopted a biological model, i.e., reaction-diffusion model, inspired by the similarity of biological spatial patterns and the spatial distribution of video coding rate. Through simulation and practical experiments, we verify the effectiveness of our proposal

Self-Limiting Epidemic Forwarding

We define a self-limiting epidemic service as a dissemination service for ad-hoc environments that is broadcast in nature, but is limited to a local scope around each source. Example applications are chatting or bulletin boards in a traffic jam, in an instant crowd in a campus or, in contrast, along a desert highway. Our goal is to support such a service across a wide range of conditions (dense or sparse). The main problems are to adaptively control scoping and traffic rates to avoid congestion. We propose a system design with the following elements: (1) manipulation of TTL by adaptive aging mechanisms; (2) control of forwarding factor by self-inhibition and inter-inhibition and (3) control of rate of injection by sources. We validate the design by an implementation in Java and analyze it using both simulation and ordinary differential equations. We show how it can be tuned to achieve an appropriate balance between limitation of scope and rate of information. Our design is entirely self-organized, and is free of any form of clustering or leader election

Fluid aggregations for Markovian process algebra

Quantitative analysis by means of discrete-state stochastic processes is hindered by the well-known phenomenon of state-space explosion, whereby the size of the state space may have an exponential growth with the number of objects in the model. When the stochastic process underlies a Markovian process algebra model, this problem may be alleviated by suitable notions of behavioural equivalence that induce lumping at the underlying continuous-time Markov chain, establishing an exact relation between a potentially much smaller aggregated chain and the original one. However, in the modelling of massively distributed computer systems, even aggregated chains may be still too large for efficient numerical analysis. Recently this problem has been addressed by fluid techniques, where the Markov chain is approximated by a system of ordinary differential equations (ODEs) whose size does not depend on the number of the objects in the model. The technique has been primarily applied in the case of massively replicated sequential processes with small local state space sizes. This thesis devises two different approaches that broaden the scope of applicability of efficient fluid approximations. Fluid lumpability applies in the case where objects are composites of simple objects, and aggregates the potentially massive, naively constructed ODE system into one whose size is independent from the number of composites in the model. Similarly to quasi and near lumpability, we introduce approximate fluid lumpability that covers ODE systems which can be aggregated after a small perturbation in the parameters. The technique of spatial aggregation, instead, applies to models whose objects perform a random walk on a two-dimensional lattice. Specifically, it is shown that the underlying ODE system, whose size is proportional to the number of the regions, converges to a system of partial differential equations of constant size as the number of regions goes to infinity. This allows for an efficient analysis of large-scale mobile models in continuous space like ad hoc networks and multi-agent systems

Modelling the IEEE 802.11 protocol in wireless multi-hop networks

IEEE 802.11 is probably the most widely used, medium access control protocol in current wireless networks. In the Wireless LAN (i.e., single-hop) setting, its performance is by now quite well understood. However, in the multi-hop setting where relay nodes are used to achieve end-to-end communication, there is, to date, no widely accepted model. Consequently, when confronted with experimental results, people often find it hard to interpret them. The goals of this thesis are (i) to model protocols "à la 802.11" in the context of multi-hop ad hoc networks, (ii) to derive theoretical limits for their performance, (iii) to contrast the performance of the current IEEE 802.11 protocol with these limits and (iv) to identify all the factors that prevent IEEE 802.11 from reaching these limits. Most of this thesis is dedicated to achieving the two first goals. We begin by proposing an idealized version of IEEE 802.11. We model this idealized protocol using a continuous Markov chain. We then use the properties and the stationary distribution of this Markov chain to derive the performance of the idealized 802.11 protocol. We first look at its spatial reuse or, in other words, at its ability to schedule a large number of concurrent successful transmissions. We show that the idealized 802.11 protocol organizes the transmissions in space in such a way that it leads to an optimal spatial reuse when its access intensity is large. This is encouraging, as it shows that a protocol using only local interactions can find a global optimum in a completely decentralize way. We then consider the short and long-term fairness properties of the idealized 802.11 protocol. We observe a clear trade-off between its spatial reuse and its fairness. At low access intensities, its fairness is high but its spatial reuse is low; whereas at high access intensities, the reverse is true. As a result, the access intensity of the protocol can be used to adapt its performance to fit the requirements of the applications running on top of it. The fairness performance of 802.11 also highly depends on the underlying network topology – 802.11 only amplifies the existing topological inequalities. In regular lattice topologies these inequalities arise only at the border where the nodes have fewer neighbors than the nodes inside the network. We demonstrate that, in large line networks and for all finite access-intensities, this border effect does not propagate inside the network, as a result 802.11 is fair. In contrast, we demonstrate that in large grid topologies a phase transition occurs. Under a certain access intensity, the border effect fades away; whereas above a certain access intensity, it propagates throughout the network, and the protocol is severely unfair. Finally, after extending our model to consider different node sensing and capture capabilities, we compare the performance of the ns-2 implementation of IEEE 802.11 and of the idealized protocol. We observe a large gap between the theoretical and practical performance. We identify the three problems that are responsible for this gap. We then propose a remedy to address each of these problems, and show that a 'cured' IEEE 802.11 can achieve the level of performance of the idealized 802.11 protocol