Apoorva Jindal

Modeling spatially correlated data in sensor networks

The physical phenomena monitored by sensor networks, for example, forest temperature or water contamination, usually yield sensed data that are strongly correlated in space. With this in mind, researchers have designed a large number of sensor network protocols and algorithms that attempt to exploit such correlations.There is an increasing need to synthetically generate large traces of spatially correlated data representing a wide range of conditions to carefully study the performance of these algorithms. Further, a mathematical model for generating synthetic traces would provide guidelines for designing more efficient algorithms. These reasons motivate us to obtain a simple and accurate model of spatially correlated sensor network data.The proposed model is Markovian in nature and can capture correlation in data irrespective of the node density, the number of source nodes, or the topology. We describe a rigorous mathematical procedure and a simple practical method to extract the model parameters from real traces. We also show how to efficiently generate synthetic traces on a given topology using these parameters. The correctness of the model is verified by statistically comparing synthetic and real data. Further, the model is validated by comparing the performance of algorithms whose behavior depends on the degree of spatial correlation in data, under real and synthetic traces. The real traces are obtained from remote sensing data, publicly available sensor data, and sensor networks that we deploy. We show that the proposed model is more general and accurate than the commonly used jointly Gaussian model. Finally, we create tools that can be easily used by researchers to synthetically generate traces of any size and degree of correlation.

Understanding congestion control in multi-hop wireless mesh networks

Complex interference in static multi-hop wireless mesh networks can adversely affect transport protocol performance. Since TCP does not explicitly account for this, starvation and unfairness can result from the use of TCP over such networks. In this paper, we explore mechanisms for achieving fair and efficient congestion control for multi-hop wireless mesh networks. First, we design an AIMD-based rate-control protocol called Wireless Control Protocol (WCP) which recognizes that wireless congestion is a neighborhood phenomenon, not a node-local one, and appropriately reacts to such congestion. Second, we design a distributed rate controller that estimates the available capacity within each neighborhood, and divides this capacity to contending flows, a scheme we call Wireless Control Protocol with Capacity estimation (WCPCap). Using analysis, simulations, and real deployments, we find that our designs yield rates that are both fair and efficient, and achieve near optimal goodputs for all the topologies that we study. WCP achieves this level of performance while being extremely easy to implement. Moreover, WCPCap achieves the max-min rates for our topologies, while still being distributed and amenable to real implementation.

Performance analysis of epidemic routing under contention

Epidemic routing has been proposed as a robust transmission scheme for sparse mobile ad hoc networks. Under the assumption of no contention, epidemic routing has the minimum end-to-end delay amongst all the routing schemes proposed for such networks. The assumption of no contention was justified by arguing that since the network is sparse, there will be very few simultaneous transmissions. Some recent papers have shown through simulations that this argument is not correct and that contention cannot be ignored while analyzing the performance of routing schemes, even in sparse networks.Incorporating contention in the analysis has always been a hard problem and hence its effect has been studied mostly through simulations only. In this paper, we find analytical expressions for the delay performance of epidemic routing with contention. We include all the three main manifestations of contention, namely (i) the finite bandwidth of the link which limits the number of packets two nodes can exchange, (ii) the scheduling of transmissions between nearby nodes which is needed to avoid excessive interference, and (iii) the interference from transmissions outside the scheduling area. The accuracy of the analysis is verified via simulations.

Modeling spatially-correlated sensor network data

The physical phenomena monitored by sensor networks, e.g. forest temperature, water contamination, usually yield sensed data that are strongly correlated in space. With this in mind, researchers have designed a large number of sensor network protocols and algorithms that attempt to exploit such correlations. To carefully study the performance of these algorithms, there is an increasing need to synthetically generate large traces of spatially correlated data representing a wide range of conditions. Further, a mathematical model for generating synthetic traces would provide guidelines for designing more efficient algorithms. These reasons motivate us to obtain a simple and accurate model of spatially correlated sensor network data. The model can capture correlation in data irrespective of the node density, the number of source nodes or the topology. We describe a mathematical procedure to extract the model parameters from real traces and generate synthetic traces using these parameters. Then, we validate our model by statistically comparing synthetic data and experimental data, as well as by comparing the performance of various algorithms whose performance depends on the degree of spatial correlation. Finally, we create a tool that can be easily used by researchers to synthetically generate traces of any size and degree of correlation.

Contention-Aware Performance Analysis of Mobility-Assisted Routing

A large body of work has theoretically analyzed the performance of mobility-assisted routing schemes for intermittently connected mobile networks. But the vast majority of these prior studies have ignored wireless contention. Recent papers have shown through simulations that ignoring contention leads to inaccurate and misleading results, even for sparse networks. In this paper, we analyze the performance of routing schemes under contention. First, we introduce a mathematical framework to model contention. This framework can be used to analyze any routing scheme with any mobility and channel model. Then, we use this framework to compute the expected delays for different representative mobility-assisted routing schemes under random direction, random waypoint and community-based mobility models. Finally, we use these delay expressions to optimize the design of routing schemes while demonstrating that designing and optimizing routing schemes using analytical expressions which ignore contention can lead to suboptimal or even erroneous behavior.

An analytical study of fundamental mobility properties for encounter-based protocols

Traditionally, mobility in ad hoc networks was considered as a necessary evil that hinders node communication. However, it has recently been recognised that mobility can be turned into a useful ally, by making nodes carry data between disconnected parts. Yet, this model of routing requires new theoretical tools to analyse its performance. A mobility-assisted or encounter-based protocol forwards data only when appropriate relays encounter each other. To be able to evaluate the performance of mobility-assisted routing schemes, it is necessary to know the statistics of various quantities related to node encounters. In this article, we present an analytical methodology to calculate a number of useful encounter-related statistics for a general class of mobility models. We apply our methodology to derive accurate closed form expressions for popular mobility models like Random Direction, as well as for a more sophisticated mobility model that better captures behaviours observed in real traces. Finally, we show how these results can be used to analyse the performance of mobility-assisted routing schemes or other processes based on node encounters. We demonstrate that derivative results concerning the delay of various routing schemes are very accurate under all mobility models examined.

The achievable rate region of 802.11-scheduled multihop networks

In this paper, we characterize the achievable rate region for any IEEE 802.11-scheduled static multihop network. To do so, we first characterize the achievable edge-rate region, that is, the set of edge rates that are achievable on the given topology. This requires a careful consideration of the interdependence among edges since neighboring edges collide with and affect the idle time perceived by the edge under study. We approach this problem in two steps. First, we consider two-edge topologies and study the fundamental ways they interact. Then, we consider arbitrary multihop topologies, compute the effect that each neighboring edge has on the edge under study in isolation, and combine to get the aggregate effect. We then use the characterization of the achievable edge-rate region to characterize the achievable rate region. We verify the accuracy of our analysis by comparing the achievable rate region derived from simulations with the one derived analytically. We make a couple of interesting and somewhat surprising observations while deriving the rate regions. First, the achievable rate region with 802.11 scheduling is not necessarily convex. Second, the performance of 802.11 is surprisingly good. For example, in all the topologies used for model verification, the max-min allocation under 802.11 is at least 64% of the max-min allocation under a perfect scheduler.

Neighborhood-centric congestion control for multihop wireless mesh networks

Complex interference in static multihop wireless mesh networks can adversely affect transport protocol performance. Since TCP does not explicitly account for this, starvation and unfairness can result from the use of TCP over such networks. In this paper, we explore mechanisms for achieving fair and efficient congestion control for multihop wireless mesh networks. First, we design an AIMD-based rate-control protocol called Wireless Control Protocol (WCP), which recognizes that wireless congestion is a neighborhood phenomenon, not a node-local one, and appropriately reacts to such congestion. Second, we design a distributed rate controller that estimates the available capacity within each neighborhood and divides this capacity to contending flows, a scheme we call Wireless Control Protocol with Capacity estimation (WCPCap). Using analysis, simulations, and real deployments, we find that our designs yield rates that are both fair and efficient. WCP assigns rates inversely proportional to the number of bottlenecks a flow passes through while remaining extremely easy to implement. An idealized version of WCPCap is max-min fair, whereas a practical implementation of the scheme achieves rates within 15% of the max-min optimal rates while still being distributed and amenable to real implementation.

Fundamental Mobility Properties for Realistic Performance Analysis of Intermittently Connected Mobile Networks

Traditional mobile ad hoc routing protocols fail to deliver any data in intermittently connected mobile ad hoc networks (ICMNs) because of the absence of complete end-to-end paths in these networks. To overcome this issue, researchers have proposed to use node mobility to carry data around the network. These schemes are referred to as mobility-assisted routing schemes. A mobility-assisted routing scheme forwards data only when appropriate relays meet each other. The time it takes for them to first meet each other is referred to as the meeting time. The time duration they remain in contact with each other is called the contact time. If they fail to exchange the packet during the contact time (due to contention in the network), then they have to wait till they meet each other again. This time duration is referred to as the inter meeting time. A realistic performance analysis of any mobility-assisted routing scheme requires a knowledge of the statistics of these three quantities. These quantities vary largely depending on the mobility model at hand. This paper studies these three quantities for the three most popularly used mobility models: random direction, random waypoint and random walk models. Hence, this work allows for a realistic performance analysis of any routing scheme under any of these three mobility models

Optimizing Multi-Copy Routing Schemes for Resource Constrained Intermittently Connected Mobile Networks

Intermittently connected mobile networks are wireless networks where most of the time there does not exist a complete path from a source to a destination. Researchers have proposed flooding based schemes for routing in such networks. While flooding based schemes are robust and have a high probability of delivery, they suffer from a huge overhead in terms of bandwidth, buffer space and energy dissipation due to large number of transmissions per packet. So flooding based schemes are impractical for resource constrained networks. Controlled replication or spraying methods can reduce this overhead by distributing a small, fixed number of copies to only a few relays, which then independently route each copy towards the destination. These schemes demonstrate a good delay performance without using a lot of resources. There are three important questions in the context of the design of these spraying based schemes: (i) How many copies per packet should be distributed? (ii) How to distribute these copies amongst the potential relays? (iii) How are each of these copies routed towards the destination? The first and the third questions have been studied in detail by different researchers. But, there has been no study which looks at the second question. This paper fills this void. Specifically, we propose a methodology to derive the optimal spraying policy. As a case study, we find the optimal spraying policy for two different spraying based schemes. Finally, we study the optimal policies to infer simple heuristics which achieve expected delays very close to the optimal.