Michele Garetto

Modeling per-flow throughput and capturing starvation in CSMA multi-hop wireless networks

Multi-hop wireless networks employing random access protocols have been shown to incur large discrepancies in the throughputs achieved by the flows sharing the network. Indeed, flow throughputs can span orders of magnitude from near starvation to many times greater than the mean. In this paper, we address the foundations of this disparity. We show that the fundamental cause is not merely differences in the number of contending neighbors, but a generic coordination problem of CSMA-based random access in a multi-hop environment. We develop a new analytical model that incorporates this lack of coordination, identifies dominating and starving flows and accurately predicts per-flow throughput in a large-scale network.We then propose metrics that quantify throughput imbalances due to the MAC protocol operation. Our model and metrics provide a deeper understanding of the behavior of CSMA protocols in arbitrary topologies and can aid the design of effective protocol solutions to the starvation problem.

Modeling the performance of wireless sensor networks

A critical issue in wireless sensor networks is represented by the limited availability of energy within network nodes; therefore making good use of energy is a must. A widely employed energy-saving technique is to place nodes in sleep mode, corresponding to a low-power consumption as well as to reduced operational capabilities. In this work, we develop a Markov model of a sensor network whose nodes may enter a sleep mode, and we use this model to investigate the system performance in terms of energy consumption, network capacity, and data deliver delay. Furthermore, the proposed model enables us to investigate the trade-offs existing between these performance metrics and the sensor dynamics in sleep/active mode. Analytical results present an excellent matching with simulation results for a large variety of system scenarios showing the accuracy of our approach.

Modeling Per-Flow Throughput and Capturing Starvation in CSMA Multi-Hop Wireless Networks

Multi-hop wireless networks employing random access protocols have been shown to incur large discrepancies in the throughputs achieved by the flows sharing the network. Indeed, flow throughputs can span orders of magnitude from near starvation to many times greater than the mean. In this paper, we address the foundations of this disparity. We show that the fundamental cause is not merely differences in the number of contending neighbors, but a generic coordination problem of CSMA-based random access in a multi-hop environment. We develop a new analytical model that incorporates this lack of coordination, identifies dominating and starving flows and accurately predicts per-flow throughput in a large-scale network. We then propose metrics that quantify throughput imbalances due to the MAC protocol operation. Our model and metrics provide a deeper understanding of the behavior of CSMA protocols in arbitrary topologies and can aid the design of effective protocol solutions to the starvation problem.

Modeling media access in embedded two-flow topologies of multi-hop wireless networks

In this paper, we decompose a large- or small-scale multi-hop wireless network into embedded subgraphs, each consisting of four nodes and two flow pairs. We systematically study all twelve possible topologies that arise according to whether the different nodes are in radio range of each other. We show that under both a random spatial distribution of nodes and random waypoint mobility with shortest-path routing, a critical and highly probable scenario is a class in which the channel state shared by the two flows is not only incomplete (i.e., the graph is not fully connected), but there is also asymmetry in the state between the two flows. We develop an accurate analytical model validated by simulations to characterize the long-term unfairness that naturally arises when CSMA with two- or four-way handshake is employed as a random access protocol. Moreover, we show that another key class of topologies consists of incomplete but symmetric shared state. We show via modeling and simulations that in this case, the system achieves long-term fairness, yet endures significant durations in which one flow dominates channel access with many repeated transmissions before relinquishing the channel. The model predicts the time-scales of this unfairness as a function of system parameters such as the maximum retransmission limit.

An Analytical Model for Wireless Sensor Networks with Sleeping Nodes

We consider a wireless sensor network whose nodes may enter the so-called sleep mode, corresponding to low power consumption and reduced operational capabilities. We develop a Markov model of the network representing: 1) the behavior of a single sensor as well as the dynamics of the entire network, 2) the channel contention among sensors, and 3) the data routing through the network. We use this model to evaluate the system performance in terms of energy consumption; network capacity, and data delivery delay. Analytical results present a very good matching with simulation results for a large variety of system scenarios, showing the accuracy of our approach

Temporal locality in today's content caching: why it matters and how to model it

The dimensioning of caching systems represents a difficult task in the design of infrastructures for content distribution in the current Internet. This paper addresses the problem of defining a realistic arrival process for the content requests generated by users, due its critical importance for both analytical and simulative evaluations of the performance of caching systems. First, with the aid of \youtube traces collected inside operational residential networks, we identify the characteristics of real traffic that need to be considered or can be safely neglected in order to accurately predict the performance of a cache. Second, we propose a new parsimonious traffic model, named the Shot Noise Model (SNM), that enables users to natively capture the dynamics of content popularity, whilst still being sufficiently simple to be employed effectively for both analytical and scalable simulative studies of caching systems. Finally, our results show that the SNM presents a much better solution to account for the temporal locality observed in real traffic compared to existing approaches.

Impact of correlated mobility on delay-throughput performance in mobile ad hoc networks

We extend the analysis of the scaling laws of wireless ad hoc networks to the case of correlated nodes movements, which are commonly found in real mobility processes. We consider a simple version of the Reference Point Group Mobility model, in which nodes belonging to the same group are constrained to lie in a disc area, whose center moves uniformly across the network according to the i.i.d. model. We assume fast mobility conditions and take as a primary goal the maximization of per-node throughput. We discover that correlated node movements have a huge impact on asymptotic throughput and delay and can sometimes lead to better performance than the one achievable under independent nodes movements.

Capacity scaling in delay tolerant networks with heterogeneous mobile nodes

We provide a general framework for the analysis of the capacity scaling properties in mobile ad-hoc networks with heterogeneous nodes and spatial inhomogeneities. Existing analytical studies strongly rely on the assumption that nodes are identical and uniformly visit the entire network space. Experimental data, however, have shown that the mobility pattern of individual nodes is typically restricted over the area, while the overall node density is often largely inhomogeneous, due to prevailing clustering behavior resulting from hot-spots. Such ubiquitous features of realistic mobility processes demand to reconsider the scaling laws for the per-user throughput achievable by the store-carry-forward communication paradigm which provides the foundation of many promising applications of delay tolerant networking. We show how the analysis of the asymptotic capacity of dense mobile ad-hoc networks can be transformed, under mild assumptions, into a Maximum Concurrent Flow (MCF) problem over anassociated Generalized Random Geometric Graph (GRGG). Our methodology allows to identify the scaling laws for a general class of mobile wireless networks, and to precisely determine under which conditions the mobility of nodes can indeed be exploited to increase the per-node throughput. At last we propose a simple, asymptotically optimal, scheduling and routing scheme that achieves the maximum transport capacity of the network.

Modeling, simulation and measurements of queuing delay under long-tail internet traffic

In this paper we describe an analytical approach for estimating the queuing delay distribution on an Internet link carrying realistic TCP traffic, such as that produced by a large number of finite-size connections transferring files whose sizes are taken from a long-tail distribution. The analytical predictions are validated against detailed simulation experiments and real network measurements. Despite its simplicity, our model proves to be accurate and robust under a variety of operating conditions, and offers novel insights into the impact on the network of long-tail flow length distributions. Our contribution is a performance evaluation methodology that could be usefully employed in network dimensioning and engineering.

A Distributed Sensor Relocatlon Scheme for Environmental Control

We consider the problem of self-deployment and relocation in mobile wireless networks, where nodes are both sensors and actuators. We propose a unified, distributed algorithm that has the following features. During deployment, our algorithm yields a regular tessellation of the geographical area with a given node density, called monitoring configuration. Upon the occurrence of a physical phenomenon, network nodes relocate themselves so as to properly sample and control the event, while maintaining the network connectivity. Then, as soon as the event ends, all nodes return to the monitoring configuration. To achieve these goals, we use a virtual force-based strategy, which proves to be very effective even when compared to an optimal centralized solution.