Mukundan Sridharan

ExScal: elements of an extreme scale wireless sensor network

Project ExScal (for extreme scale) fielded a 1000+ node wireless sensor network and a 200+ node peer-to-peer ad hoc network of 802.11 devices in a 13km by 300m remote area in Florida, USA during December 2004. In comparison with previous deployments, the ExScal application is relatively complex and its networks are the largest ones of either type fielded to date. In this paper, we overview the key requirements of ExScal, the corresponding design of the hardware/software platform and application, and some results of our experiments.

Kansei: a testbed for sensing at scale

The Kansei testbed at the Ohio State University is designed to facilitate research on networked sensing applications at scale. Kansei embodies a unique combination of characteristics as a result of its design focus on sensing and scaling: (i) Heterogeneous hardware infrastructure with dedicated node resources for local computation, storage, data exfiltration and back-channel communication, to support complex experimentation, (ii) Time accurate hybrid simulation engine for simulating substantially larger arrays using testbed hardware resources, (iii) High fidelity sensor data generation and real-time data and event injection, (iv) Software components and associated job control language to support complex multi-tier experiments utilizing real hardware resources and data generation and simulation engines. In this paper, we present the elements of Kansei testbed architecture, including its hardware and software platforms as well as its hybrid simulation and sensor data generation engines

Performance Measurement and Analysis of H.323 Traffic

The popularity of H.323 applications has been demonstrated by the billions of minutes of audio and video traffic seen on the Internet every month. Our objective in this paper is to obtain Good, Acceptable and Poor performance bounds for network metrics such as delay, jitter and loss for H.323 applications based on objective and subjective quality assessment of various audio and video streams. To obtain the necessary data for our analysis we utilize the H.323 Beacon tool we have developed and a set of Videoconferencing tasks performed in a LAN and also with end-points located across multiple continents, connected via disparate network paths on the Internet.

Differential games in large-scale sensor-actuator networks

Surveillance systems based on sensor network technology have been shown to successfully detect, classify and track targets of interest over a large area. State information collected via the sensor network also enables these systems to actuate mobile agents so as to achieve surveillance goals such as target capture and asset protection. But satisfying these goals is complicated by the fact that track information in a sensor network is routed to mobile agents through multi-hop communication links and is thus subject to delays and losses. In addition, as the sensor network is scaled in size, high throughput rates for all pursuers cannot be sustained at all times, which necessitates a network communication strategy that adapts to pursuer information requirements. In this paper, we concentrate on the formulation of optimal pursuit control strategies in the presence of network effects, assuming that target track information has been established locally in the sensor network. We adapt ideas from the theory of differential games to networked games-including ones involving non-periodic track updates, message losses and message delays-to derive optimal strategies, bounds on the information requirements, and scaling properties of these bounds. Moreover, we present a specific network communication protocol which has the required scalable information characteristics and conclude with the results of experimental studies

Trail: A distance-sensitive sensor network service for distributed object tracking

Distributed observation and control of mobile objects via static wireless sensors demands timely information in a distance-sensitive manner: Information about closer objects is required more often and more quickly than that of farther objects. In this article, we present a wireless sensor network protocol, Trail, that supports distance-sensitive tracking of mobile objects for in-network subscribers upon demand. Trail achieves a find time that is linear in the distance from a subscriber to an object, via a distributed data structure that is updated only locally when the object moves. Notably, Trail does not partition the network into a hierarchy of clusters and clusterheads, and as a result Trail has lower maintenance costs, is more locally fault tolerant, and it better utilizes the network in terms of load balancing and minimizing the size of the data structure needed for tracking. Moreover, Trail is reliable and energy efficient, despite the network dynamics that are typical of wireless sensor networks. Trail can be refined by tuning certain parameters, thereby yielding a family of protocols that are suited for different application settings such as rate of queries, rate of updates, and network size. We evaluate the performance of Trail by analysis, simulations in a 90 × 90 sensor network, and experiments on 105 Mica2 nodes in the context of a pursuer-evader control application.

Trail: a distance sensitive WSN service for distributed object tracking

Distributed observation and control of mobile objects via static wireless sensors demands timely information in a distance sensitive manner: information about closer objects is required more often and more quickly than that of farther objects. In this paper, we present a wireless sensor network protocol, Trail, that supports distance sensitive tracking of mobile object by in-network subscribers upon demand. Trail achieves a find time that is linear in the distance from the subscriber to the object, via a distributed data structure that is updated only locally when objects move. Trail seeks to minimize the size of the data structure. Moreover, Trail is reliable, fault-tolerant and energy-efficient, despite the network dynamics that are typical of wireless sensor networks. We evaluate the performance of Trail by simulations in a 90-by-90 sensor network and report on 105 node experiments in the context of a pursuer-evader control application.

Congestion control using multilevel explicit congestion notification in satellite networks

Exponential growth of Internet traffic and the proliferation of new user applications warrant the development of a new Internet infrastructure. Due to the fundamental satellite system characteristics such as global coverage, broadcast nature and bandwidth on demand, satellite systems are excellent candidates for providing high data rate Internet access and global connectivity accommodating multimedia applications. However, to meet this goal, provisioning of quality-of-service (QoS) within the advanced satellite network systems is the critical requirement. Congestion remains the main obstacle to QoS on the Internet. In todays TCP networks, explicit congestion notification (ECN) is the only explicit mechanism which delivers congestion signals to the source. We present a new traffic management scheme based on an enhanced ECN mechanism. In particular, we used multilevel ECN, which conveys more accurate feedback information about the network congestion status than the current ECN scheme. We have designed a TCP source reaction that takes advantage of the extra feedback information and tunes better its response to the congestion than the current schemes. Our analysis and simulations results show that our scheme performed better than the current ECN, having fewer losses, better network utilization, fewer delays, and the solution is scalable.

TBI: end-to-end network performance measurement testbed for empirical bottleneck detection

Recent advances in networking include new bandwidth-intensive applications, sophisticated protocols that enable real-time data and multimedia delivery and aspects of network security that were not conceived in the beginnings of the Internet. Given these advances and the rapid increase in the number of users accessing the Internet, todays networks need to deliver high levels of end-to-end performance in a reliable fashion. In this paper, we present our novel network measurement methodology which employs an application-specific measurement toolkit including a scaleable test scheduler and analysis module to empirically identify end-to-end bottleneck paths in monitored network routes. To show the utility of our proposed methodology, we present case-studies from a network measurement testbed between 3 University campus labs traversing regional and national academic network backbones. Our case-studies address identifying network measurement anomalies in routine ISP operations due to route changes, device misconfigurations and erroneous data from measurement tools. We also present a performance comparison of campus, regional, national-academic and national-commercial network paths based on the measurement data obtained from our testbed. Finally, we illustrate the requirements and potential of federated measurement testbeds to better characterize end-to-end network performance bottlenecks across multiple ISP domains.

Next-Generation Internet Architectures and Protocols: KanseiGenie: software infrastructure for resource management and programmability of wireless sensor network fabrics

This chapter describes an architecture for slicing, virtualizing, and federating wireless sensor network (WSN) resources. The architecture, which we call KanseiGenie, allows users—be they sensing/networking researchers or application developers—to specify and acquire node and network resources as well as sensor data resources within one or more facilities for launching their programs. It also includes server side measurement and management support for user programs, as well as client side support for experiment composition and control. We illustrate KanseiGenie architectural concepts in terms of a current realization of KanseiGenie that serves WSN testbeds and application-centric fabrics at The Ohio State University and at Wayne State University.

Association management for data dissemination over wireless mesh networks

To enable multimedia broadcasting services in mesh networks, it is critical to optimize the broadcast traffic load. Traditionally, users associate with access points (APs) with the strongest signal strength. We explore the concept of dual-association, where the AP for unicast traffic and the AP for broadcast traffic are independently chosen by exploiting overlapping coverages that are typical in mesh networks. The goal of our proposed solution is to optimize the overall network load by exploiting the flexibility provided by independent selection of unicast and broadcast APs. We propose a novel cost metric based on ETT (Expected Transmission Time) and the number of nodes in range of the APs, that are advertised in the beacons from the APs. Users periodically scan and associate with the AP which has the lowest cost metric. The proposed approach reduces the number of APs that handle the broadcast traffic resulting in a heavy reduction in control and data packet overhead. This leads to higher packet delivery rate and enhanced video quality measured in terms of PSNR. Our approach allows the freed up resources at APs to increase the unicast throughput. We compare the performance of our approach with traditional signal strength based association using extensive simulations and real experiments on an indoor testbed of 180 IEEE 802.11b based devices.