"A Survey of Mobility Models for Ad Hoc Network Research," Wireless Comm. & Mobile Computing (WCMC) : Special issue on Mobile Ad Hoc Networking : Research

In the performance evaluation of a protocol for an ad hoc network, the protocol should be tested under realistic conditions including, but not limited to, a sensible transmission range, limited buffer space for the storage of messages, representative data traffic models, and realistic movements of the mobile users (i.e., a mobility model). This paper is a survey of mobility models that are used in the simulations of ad hoc networks. We describe several mobility models that represent mobile nodes whose movements are independent of each other (i.e., entity mobility models) and several mobility models that represent mobile nodes whose movements are dependent on each other (i.e., group mobility models). The goal of this paper is to present a number of mobility models in order to offer researchers more informed choices when they are deciding upon a mobility model to use in their performance evaluations. Lastly, we present simulation results that illustrate the importance of choosing a mobility model in the simulation of an ad hoc network protocol. Specifically, we illustrate how the performance results of an ad hoc network protocol drastically change as a result of changing the mobility model simulated.

/pdf/a-survey-of-mobility-models-for-ad-hoc-network-research-ygkxat400x.pdf

A survey of mobility models for ad hoc network research

The Visual Display of Quantitative Information

Understanding Packet Delivery Performance In Dense Wireless Sensor Networks ∗ Computer Science Department University of Southern California Los Angeles, CA 90089-0781 Jerry Zhao Computer Science Department University of Southern California Los Angeles, CA 90089-0781 Ramesh Govindan zhaoy@usc.edu ABSTRACT Wireless sensor networks promise ﬁne-grain monitoring in a wide variety of environments. Many of these environ- ments (e.g., indoor environments or habitats) can be harsh for wireless communication. From a networking perspec- tive, the most basic aspect of wireless communication is the packet delivery performance: the spatio-temporal charac- teristics of packet loss, and its environmental dependence. These factors will deeply impact the performance of data acquisition from these networks. In this paper, we report on a systematic medium-scale (up to sixty nodes) measurement of packet delivery in three diﬀerent environments: an indoor oﬃce building, a habitat with moderate foliage, and an open parking lot. Our ﬁndings have interesting implications for the design and evaluation of routing and medium-access protocols for sensor networks. ramesh@usc.edu spectrum under use, the particular modulation schemes un- der use, and possibly on the communicating devices them- selves. Communication quality can vary dramatically over time, and has been reputed to change with slight spatial displacements. All of these are true to a greater degree for ad-hoc (or infrastructure-less) communication than for wire- less communication to a base station. Given this, and the paucity of large-scale deployments, it is perhaps not surpris- ing that there have been no medium to large-scale measure- ments of ad-hoc wireless systems; one expects measurement studies to reveal high variability in performance, and one suspects that such studies will be non-representative. Wireless sensor networks [5, 7] are predicted on ad-hoc wireless communications. Perhaps more than other ad-hoc wireless systems, these networks can expect highly variable wireless communication. They will be deployed in harsh, inaccessible, environments which, almost by deﬁnition will exhibit signiﬁcant multi-path communication. Many of the current sensor platforms use low-power radios which do not have enough frequency diversity to reject multi-path prop- agation. Finally, these networks will be fairly densely de- ployed (on the order of tens of nodes within communica- tion range). Given the potential impact of these networks, and despite the anecdotal evidence of variability in wireless communication, we argue that it is imperative that we get a quantitative understanding of wireless communication in sensor networks, however imperfect. Our paper is a ﬁrst attempt at this. Using up to 60 Mica motes, we systematically evaluate the most basic aspect of wireless communication in a sensor network: packet delivery. Particularly for energy-constrained networks, packet de- livery performance is important, since that translates to net- work lifetime. Sensor networks are predicated using low- power RF transceivers in a multi-hop fashion. Multiple short hops can be more energy-eﬃcient than one single hop over a long range link. Poor cumulative packet delivery per- formance across multiple hops may degrade performance of data transport and expend signiﬁcant energy. Depending on the kind of application, it might signiﬁcantly undermine application-level performance. Finally, understanding the dynamic range of packet delivery performance (and the ex- tent, and time-varying nature of this performance) is impor- tant for evaluating almost all sensor network communication protocols. We study packet delivery performance at two layers of the communication stack (Section 3). At the physical-layer and in the absence of interfering transmissions, packet de- Categories and Subject Descriptors C.2.1 [Network Architecture and Design]: Wireless communication; C.4 [Performance of Systems]: Perfor- mance attributes, Measurement techniques General Terms Measurement, Experimentation Keywords Low power radio, Packet loss, Performance measurement 1. INTRODUCTION Wireless communication has the reputation of being no- toriously unpredictable. The quality of wireless communica- tion depends on the environment, the part of the frequency ∗ This work is supported in part by NSF grant CCR-0121778 for the Center for Embedded Systems. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for proﬁt or commercial advantage and that copies bear this notice and the full citation on the ﬁrst page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior speciﬁc permission and/or a fee. SenSys’03, November 5–7, 2003, Los Angeles, California, USA. Copyright 2003 ACM 1-58113-707-9/03/0011 ... $ 5.00.

Understanding Packet Delivery Performance In Dense Wireless Sensor Networks

Wireless sensor networks promise fine-grain monitoring in a wide variety of environments. Many of these environments (e.g., indoor environments or habitats) can be harsh for wireless communication. From a networking perspective, the most basic aspect of wireless communication is the packet delivery performance: the spatio-temporal characteristics of packet loss, and its environmental dependence. These factors will deeply impact the performance of data acquisition from these networks.In this paper, we report on a systematic medium-scale (up to sixty nodes) measurement of packet delivery in three different environments: an indoor office building, a habitat with moderate foliage, and an open parking lot. Our findings have interesting implications for the design and evaluation of routing and medium-access protocols for sensor networks.

/pdf/understanding-packet-delivery-performance-in-dense-wireless-4qg4yfw795.pdf

Understanding packet delivery performance in dense wireless sensor networks

To understand better how users take advantage of wireless networks, we examine a twelve-week trace of a building-wide local-area wireless network. We analyze the network for overall user behavior (when and how intensively people use the network and how much they move around), overall network traffic and load characteristics (observed throughput and symmetry of incoming and outgoing traffic), and traffic characteristics from a user point of view (observed mix of applications and number of hosts connected to by users).Amongst other results, we find that users are divided into distinct location-based sub-communities, each with its own movement, activity, and usage characteristics. Most users exploit the network for web-surfing, session-oriented activities and chat-oriented activities. The high number of chat-oriented activities shows that many users take advantage of the mobile network for synchronous communication with others. In addition to these user-specific results, we find that peak throughput is usually caused by a single user and application. Also, while incoming traffic dominates outgoing traffic overall, the opposite tends to be true during periods of peak throughput, implying that significant asymmetry in network capacity could be undesirable for our users.While these results are only valid for this local-area wireless network and user community, we believe that similar environments may exhibit similar behavior and trends. We hope that our observations will contribute to a growing understanding of mobile user behavior.

Analysis of a local-area wireless network

At Google, experimentation is practically a mantra; we evaluate almost every change that potentially affects what our users experience. Such changes include not only obvious user-visible changes such as modifications to a user interface, but also more subtle changes such as different machine learning algorithms that might affect ranking or content selection. Our insatiable appetite for experimentation has led us to tackle the problems of how to run more experiments, how to run experiments that produce better decisions, and how to run them faster. In this paper, we describe Google's overlapping experiment infrastructure that is a key component to solving these problems. In addition, because an experiment infrastructure alone is insufficient, we also discuss the associated tools and educational processes required to use it effectively. We conclude by describing trends that show the success of this overall experimental environment. While the paper specifically describes the experiment system and experimental processes we have in place at Google, we believe they can be generalized and applied by any entity interested in using experimentation to improve search engines and other web applications.

/pdf/overlapping-experiment-infrastructure-more-better-faster-5cqmfta4d9.pdf

Overlapping experiment infrastructure: more, better, faster experimentation

We analyze a seven-week trace of the Metricom metropolitan-area packet radio wireless network to find how users take advantage of a mobile environment. Such understanding is critical for planning future large-scale mobile network infrastructures. Amongst other results, we find that users typically use the radios during the day and evening. Of the users who move around during the trace (over half), we find that the more locations a user visits on a daily basis, the closer together, on average, those locations are. While these results are only known to be valid for this particular network, we hope future analysis of other networks will add to a growing understanding of mobile network behavior.

Analysis of a metropolitan-area wireless network

Most analysts start with an overview of the data before gradually refining their view to be more focused and detailed. Multiscale pan-and-zoom systems are effective because they directly support this approach. However, generating abstract overviews of large data sets is difficult and most systems take advantage of only one type of abstraction: visual abstraction. Furthermore, these existing systems limit the analyst to a single zooming path on their data and thus to a single set of abstract views. This paper presents: 1) a formalism for describing multiscale visualizations of data cubes with both data and visual abstraction and 2) a method for independently zooming along one or more dimensions by traversing a zoom graph with nodes at different levels of detail. As an example of how to design multiscale visualizations using our system, we describe four design patterns using our formalism. These design patterns show the effectiveness of multiscale visualization of general relational databases.

/pdf/multiscale-visualization-using-data-cubes-2rwy8z3lin.pdf

Multiscale visualization using data cubes

In the last several years, large OLAP databases have become common in a variety of applications such as corporate data warehouses and scientific computing. To support interactive analysis, many of these databases are augmented with hierarchical structures that provide meaningful levels of abstraction that can be leveraged by both the computer and analyst. This hierarchical structure generates many challenges and opportunities in the design of systems for the query, analysis, and visualization of these databases.In this paper, we present an interactive visual exploration tool that facilitates exploratory analysis of data warehouses with rich hierarchical structure, such as might be stored in data cubes. We base this tool on Polaris, a system for rapidly constructing table-based graphical displays of multidimensional databases. Polaris builds visualizations using an algebraic formalism derived from the interface and interpreted as a set of queries to a database. We extend the user interface, algebraic formalism, and generation of data queries in Polaris to expose and take advantage of hierarchical structure. In the resulting system, analysts can navigate through the hierarchical projections of a database, rapidly and incrementally generating visualizations for each projection.

https://graphics.stanford.edu/papers/polaris_olap/paper.pdf

Diane Tang

Papers

Analysis of a local-area wireless network

Overlapping experiment infrastructure: more, better, faster experimentation

Analysis of a metropolitan-area wireless network

Multiscale visualization using data cubes

Query, analysis, and visualization of hierarchically structured data using Polaris