We present the philosophy, design, and initial evaluation of the Trio Testbed, a new outdoor sensor network deployment that consists of 557 solar-powered motes, seven gateway nodes, and a root server. The testbed covers an area of approximately 50,000 square meters and was in continuous operation during the last four months of 2005. This new testbed in one of the largest solar-powered outdoor sensor networks ever constructed and it offers a unique platform on which both systems and application software can be tested safely at scale. The testbed is based on Trio, a new mote platform that provides sustainable operation, enables efficient in situ interaction, and supports fail-safe programming. The motivation behind this testbed was to evaluate robust multi-target tracking algorithms at scale. However, using the testbed has stressed the system software, networking protocols, and management tools in ways that have exposed subtle but serious weaknesses that were never discovered using indoor testbeds or smaller deployments. We have been iteratively improving our support software, with the eventual aim of creating a stable hardware-software platform for sustainable, scalable, and flexible testbed deployments.

We consider the problem of estimating link quality in an ad-hoc wireless mesh. We argue that estimating links well requires combining information from the network, link, and physical layers. We propose narrow, protocol-independent link estimation interfaces for the layers, which in total provide four bits of information: 1 from the physical layer, 1 from the link layer, and 2 from the network layer. We present a link estimator design with these interfaces that reduces packet delivery costs by up to 44 % over current approaches and maintains a 99 % delivery ratio over large, multihop testbeds. 1

We present Flush, a reliable, high goodput bulk data transport protocol for wireless sensor networks. Flush provides end-to-end reliability, reduces transfer time, and adapts to time-varying network conditions. It achieves these properties using end-to-end acknowledgments, implicit snooping of control information, and a rate-control algorithm that operates at each hop along a flow. Using several real network topologies, we show that Flush closely tracks or exceeds the maximum goodput achievable by a hand-tuned but fixed rate for each hop over a wide range of path lengths and varying network conditions. Flush is scalable; its effective bandwidth over a 48-hop wireless network is approximately one-third of the rate achievable over one hop. The design of Flush is simplified by assuming that different flows do not interfere with each other, a reasonable restriction for many sensornet applications that collect bulk data in a coordinated fashion, like structural health monitoring, volcanic activity monitoring, or protocol evaluation. We collected all of the performance data presented in this paper using Flush itself.

We present a building block approach to hardware platform design based on a decade of collective experience in this area, arriving at an architecture in which general-purpose modules that require expertise to design and incorporate commonlyused functionality are integrated with application-specific carriers that satisfy the unique sensing, power supply, and mechanical constraints of an application. Of course, modules are widespread, but our focus is far less on the performance of any individual module and far more on an overall architecture that supports the prototype, pilot, and production stages of design, and preserves the artifacts and learnings accumulated along the way. We present heuristics for partitioning functionality between modules and carriers, and identify guidelines for their interconnection. Our approach advocates exporting a wide electrical interface, eliminating the system bus, and supporting many physical interconnect options for modules and carriers. We evaluate this approach by constructing a family of general-purpose modules and application-specific carriers that achieve a high degree of reuse despite very different application requirements. We show that this approach shortens platform development time-to-result for novice graduate students, making custom platforms broadly accessible.

While market-based systems have long been proposed as solutions for distributed resource allocation, few have been deployed for production use in real computer systems. Towards this end, we present our initial experience using Mirage, a microeconomic resource allocation system based on a repeated combinatorial auction. Mirage allocates time on a heavilyused 148-node wireless sensor network testbed. In particular, we focus on observed strategic user behavior over a fourmonth period in which 312,148 node hours were allocated across 11 research projects. Based on these results, we present a set of key challenges for market-based resource allocation systems based on repeated combinatorial auctions. Finally, we propose refinements to the system’s current auction scheme to mitigate the strategies observed to date and also comment on some initial steps toward building an approximately strategyproof repeated combinatorial auction. 1

Traditional resource management techniques (resource allocation, admission control and scheduling) have been found to be inadequate for many shared Grid and distributed systems that face unpredictable and bursty workloads. They provide no incentive for users to request resources judiciously and appropriately, and they do not capture the true value and importance (the utility) of user jobs. Consequently, researchers and practitioners have been examining the appropriateness of ‘market-inspired ’ resource management techniques in ensuring that users are treated fairly, without unduly favouring one set of users over another. Such techniques aim to smooth out access patterns and reduce the chance of transient overload, by providing incentives for users to be flexible about their resource requirements and job deadlines. We examine the recent evolution of these systems, looking at the state of the art in price setting and negotiation, grid economy management and utilitydriven scheduling and resource allocation, and identify the advantages and limitations of these systems. We then look to the future of these systems, examining the emerging ‘Catallaxy ’ market paradigm and present Mercato, a decentralised, Catallaxy inspired architecture that encapsulates the future directions that need to be pursued to address the limitations of current generation of market oriented Grids and Utility Computing systems. 1

Understanding the behavior of deployed sensor networks is difficult as they become more sophisticated and larger in scale. Much of the difficulty comes from the lack of tools to provide a global view on the network dynamics. This paper describes LiveNet, a set of tools and techniques for reconstructing complex dynamics of live sensor network deployments. LiveNet is based on the use of passive sniffers co-deployed with the network. We address several challenges: merging multiple sniffer traces, determining coverage of sniffers, inference of missing information for path reconstruction and high-level analyses with application-specific knowledge. To validate LiveNet’s accuracy, we conduct controlled experiments on an indoor testbed. Finally, we present data from a real deployment using LiveNet. The results show that LiveNet is able to to reconstruct network topology, bandwidth usage, routing paths, identify hot-spot nodes, and disambiguate failures observed at application level without instrumenting application code.

Peer-to-peer systems have been proposed for a wide variety of applications, including file-sharing, web caching, distributed computation, cooperative backup, and onion routing. An important motivation for such systems is self-scaling. That is, increased participation increases the capacity of the system. Unfortunately, this property is at risk from selfish participants. The decentralized nature of peer-to-peer systems makes accounting difficult. We show that e-cash can be a practical solution to the desire for accountability in peerto-peer systems while maintaining their ability to self-scale. No less important, e-cash is a natural fit for peer-to-peer systems that attempt to provide (or preserve) privacy for their participants. We show that e-cash can be used to provide accountability without compromising the existing privacy goals of a peer-to-peer system. We show how e-cash can be practically applied to a file sharing application. Our approach includes a set of novel cryptographic protocols that mitigate the computational and communication costs of anonymous e-cash transactions, and system design choices that further reduce overhead and distribute load. We conclude that provably secure, anonymous, and scalable peer-to-peer systems are within reach.

Abstract—We propose a novel payment-based incentive scheme for peer-to-peer (P2P) live media streaming. Using this approach, peers earn points by forwarding data to others. The data streaming is divided into fixed-length periods; during each of these periods, peers compete with each other for good parents (data suppliers) for the next period in a first-price-auction-like procedure using their points. We design a distributed algorithm to regulate peer competitions and consider various individual strategies for parent selection from a game-theoretic perspective. We then discuss possible strategies that can be used to maximize a peer’s expected media quality by planning different bids for its substreams. Finally, in order to encourage off-session users to remain online and continue contributing to the network, we develop an optimal data forwarding strategy that allows peers to accumulate points that can be used in future services. Simulation results show that the proposed methods effectively differentiate the media qualities received by peers making different contributions (which originate from, for example, different forwarding bandwidths or servicing times) and at the same time maintain high overall system performance. Index Terms—Peer-to-peer, media streaming, incentive, service differentiation, payment. 1

Network protocols are typically designed and tested individually. In practice, however, applications use multiple protocols concurrently. This discrepancy can lead to failures from unanticipated interactions between protocols. In this paper, we argue that sensor network communication stacks should have an isolation layer, whose purpose is to make each protocol’s perception of the wireless channel independent of what other protocols are running. We identify two key mechanisms the isolation layer must provide: shared collision avoidance and fair channel allocation. We present an example design of an isolation layer that builds on the existing algorithms of grant-to-send and fair queueing. However, the complexities of wireless make these mechanisms insufficient by themselves. We therefore propose two new mechanisms that address these limitations: channel decay and fair cancellation. Incorporating these new mechanisms reduces the increase in end-to-end delivery cost associated with concurrently operating two protocols by more than 60%. The isolation layer improves median protocol fairness from 0.52 to 0.96 in Jain’s fairness index. Together, these results show that using an isolation layer makes protocols more efficient and robust.