62235343
A simulation-based study of wireless sensor network middleware
Future wireless sensor networks (WSNs) will transport high-bandwidth, low-latency streaming data, and will host sophisticated processing, such as image fusion and object tracking, in-network on sensor network nodes. Recent middleware proposals provide capabilities for in-network processing, reducing energy drain based on communication costs alone. However, hosting complex processing on WSN nodes incurs additional processing energy and latency costs that impact network lifetime and application performance. There is a need for a WSN planning framework to explore energy saving and application performance trade-offs for models of future sensor networks that account for processing costs in addition to communication costs. In this work, we present a simulation framework to analyze the interplay between resource requirements for compute-and communication-intensive in-network processing for streaming applications. We simulate a surveillance application workload with middleware capabilities for data fusion, adaptive policy-driven migration of data fusion computation across network nodes, and prefetching of streaming data inputs for fusion processing. Our study sheds light on application figures of merit such as latency, throughput, and lifetime with respect to migration policy and node CPU and radio characteristics.
10511055
RF2ID: A Reliable Middleware Framework for RFID Deployment
The reliability of RFID systems depends on a number of factors including: RF interference, deployment environment, configuration of the readers, and placement of readers and tags. While RFID technology is improving rapidly, a reliable deployment of this technology is still a significant challenge impeding widespread adoption. This paper investigates system software solutions for achieving a highly reliable deployment that mitigates inherent unreliability in RFID technology. We have developed (1) a virtual reader abstraction to improve the potentially error-prone nature of reader generated data (2) a novel path abstraction to capture the logical flow of information among virtual readers. We have designed and implemented an RFID middleware: RF2ID (reliable framework for radio frequency identification) to organize and support queries over data streams in an efficient manner. Prototype implementation using both RFID readers and simulated readers using an empirical model of RFID readers show that RF2ID is able to provide high reliability and support path-based object detection.
5316084
On Improving Wireless Broadcast Reliability of Sensor Networks Using Erasure Codes
Efficient and reliable dissemination of information over a large area is a critical ability of a sensor network for various reasons such as software updates and transferring large data objects (e.g., surveillance images). Thus efficiency of wireless broadcast is an important aspect of sensor network deployment. In this paper, we study FBcast, a new broadcast protocol based on the principles of modern erasure codes. We show that our approach provides high reliability, often considered critical for disseminating codes. In addition FBcast offers limited data confidentiality. For a large network, where every node may not be reachable by the source, we extend FBcast with the idea of repeaters to improve reliable coverage. Simulation results on TOSSIM show that FBcast offers higher reliability with lower number of retransmissions than traditional broadcasts.
6817196
Design of Adaptive Overlays for Multi-scale Communication in Sensor Networks
In wireless sensor networks, energy and communication bandwidth are precious resources. Traditionally, layering has been used as a design principle for network stacks; hence routing protocols assume no knowledge of the application behavior in the sensor node. In resource-constrained sensor-nodes, there is simultaneously a need and an opportunity to optimize the protocol to match the application. In this paper, we design a network architecture that efficiently supports multi-scale communication and collaboration among sensors. The architecture complements the previously proposed Abstract Regions architecture for local communication and collaboration. We design a self-organizing hierarchical overlay that scales to a large number of sensors and enables multi-resolution collaboration. We design effective Network Programming Interfaces to simplify the development of applications on top of the architecture; these interfaces are efficiently implemented in the network layer. The overlay hierarchy can adapt to match the collaboration requirements of the application and data both temporally and spatially. We present an initial evaluation of our design under simulation to show that it leads to reduced communication overhead, thereby saving energy. We are currently building our architecture in the TinyOS environment to demonstrate its effectiveness.
7841699
Dynamic data fusion for future sensor networks
DFuse is an architectural framework for dynamic application-specified data fusion in sensor networks. It bridges an important abstraction gap for developing advanced fusion applications that takes into account the dynamic nature of applications and sensor networks. Elements of the DFuse architecture include a fusion API, a distributed role assignment algorithm that dynamically adapts the placement of the application task graph on the network, and an abstraction migration facility that aids such dynamic role assignment. Experimental evaluations show that the API has low overhead, and simulation results show that the role assignment algorithm significantly increases the network lifetime over static placement.
1898402
DFuse: a framework for distributed data fusion
Simple in-network data aggregation (or fusion) techniques for sensor networks have been the focus of several recent research efforts, but they are insufficient to support advanced fusion applications. We extend these techniques to future sensor networks and ask two related questions: (a) what is the appropriate set of data fusion techniques, and (b) how do we dynamically assign aggregation roles to the nodes of a sensor network. We have developed an architectural framework, DFuse, for answering these two questions. It consists of a data fusion API and a distributed algorithm for energy-aware role assignment. The fusion API enables an application to be specified as a coarse-grained dataflow graph, and eases application development and deployment. The role assignment algorithm maps the graph onto the network, and optimally adapts the mapping at run-time using role migration. Experiments on an iPAQ farm show that, the fusion API has low-overhead, and the role assignment algorithm with role migration significantly increases the network lifetime compared to any static assignment.
14984794
A Local Search Heuristic for Biobjective Intersecting Geometric Graphs
In this work, we consider the problem of constructing spanning trees from two geometric graphs corresponding to two nets, each with multiple terminals, with a goal to minimize the total edge cost and the number of intersections among the edges of the two trees. Such an optimization problem is computationally hard for which no efficient algorithm or good heuristic is known to exist. Additionally, in a biobjective setting, the major challenge to solve a problem is to obtain many representative diverse solutions across the (near-) optimal Pareto-front. We present a local search based heuristic to find near-optimal Pareto-front in the feasible solution space. Each element of this solution set is a tuple of two spanning trees corresponding to the given geometric graphs. The heuristic is shown to give superior results over the existing stochastic technique
22550674
Timing-sync protocol for sensor networks
Wireless ad-hoc sensor networks have emerged as an interesting and important research area in the last few years. The applications envisioned for such networks require collaborative execution of a distributed task amongst a large set of sensor nodes. This is realized by exchanging messages that are time-stamped using the local clocks on the nodes. Therefore, time synchronization becomes an indispensable piece of infrastructure in such systems. For years, protocols such as NTP have kept the clocks of networked systems in perfect synchrony. However, this new class of networks has a large density of nodes and very limited energy resource at every node; this leads to scalability requirements while limiting the resources that can be used to achieve them. A new approach to time synchronization is needed for sensor networks.In this paper, we present Timing-sync Protocol for Sensor Networks (TPSN) that aims at providing network-wide time synchronization in a sensor network. The algorithm works in two steps. In the first step, a hierarchical structure is established in the network and then a pair wise synchronization is performed along the edges of this structure to establish a global timescale throughout the network. Eventually all nodes in the network synchronize their clocks to a reference node. We implement our algorithm on Berkeley motes and show that it can synchronize a pair of neighboring motes to an average accuracy of less than 20ms. We argue that TPSN roughly gives a 2x better performance as compared to Reference Broadcast Synchronization (RBS) and verify this by implementing RBS on motes. We also show the performance of TPSN over small multihop networks of motes and use simulations to verify its accuracy over large-scale networks. We show that the synchronization accuracy does not degrade significantly with the increase in number of nodes being deployed, making TPSN completely scalable.
9294393
Decentralized control of discrete event systems with specializations to local control and concurrent systems
The decentralized supervisory control problem of discrete event systems under partial observation is studied in this paper. The main result of the paper is a necessary and sufficient condition for the existence of decentralized supervisors for ensuring. That the controlled behavior of the system lies in a given range. The contribution of the paper is (1) our setting of decentralized control generalizes the prior ones; (2) we present an alternative approach for solving the decentralized control problem, which leads to computational saving for concurrent systems and certain other systems; and (3) our generalized formulation and its solution lets us extend several of the existing results reported previously. The results of our paper are illustrated by an example of a simple manufacturing system.
14410544
Fluid modeling of pollution proliferation in P2P networks
P2P systems are highly vulnerable to pollution attacks in which attackers inject multiple versions of corrupted content into the system, which is then further proliferated by unsuspecting users. However, to our knowledge, there are no closed-form solutions that describe this phenomenon, nor are there models that describe how the injection of multiple versions of corrupted content impacts a clients' ability to receive a valid copy. In this paper we develop a suite of fluid models that model pollution proliferation in P2P systems. These fluid models lead to systems of non-linear differential equations. We obtain closed-form solutions for the differential equations; for the remaining models, we efficiently solve the differential equations numerically. The models capture a variety of user behaviors, including propensity for popular versions, abandonment after repeated failure to obtain a good version, freeloading, and local version blacklisting. Our analysis reveals intelligent strategies for attackers as well as strategies for clients seeking to recover non-polluted content within large-scale P2P networks.
47199334
Computation Hierarchy for In-Network Processing
In this paper we explore the network level architecture of distributed sensor systems that perform in-network processing. We propose a system with heterogeneous nodes that organizes into a hierarchical structure dictated by the computational capabilities. The presence of high-performance nodes amongst a sea of resource-constrained nodes exposes new tradeoffs for the efficient implementation of network-wide applications. Our experiments show that even for a low relative density of resource-constrained nodes to high-performance nodes there are certain gains in performance for a heterogeneous and hierarchical network over a homogeneous one. The introduction of hierarchy enables partitioning of the application into sub-tasks that can be mapped onto the heterogeneous nodes in the network in multiple ways. We analyze the tradeoffs between the execution time of the application, accuracy of the output produced and the overall energy consumption of the network for the different mapping of the sub-tasks onto the heterogeneous nodes. We evaluate the performance and energy consumption of a typical sensor network application of target tracking via beamforming and line of bearing (LOB) calculations on the different nodes. Our experiments also include the study of the overall performance and energy consumption of the LOB calculation using two different types of resource constrained sensor nodes (MICA and MICA2 nodes) and show how these metrics are affected by changes in the node architecture and operation. Our results indicate that when using MICA motes as resource-constrained nodes, 85% of the time on average the hierarchical network outperforms a homogeneous network for approximately the same energy budget. When using MICA2 motes as resource-constrained nodes, 54% of the time the hierarchical network performs better than a homogeneous network with approximately the same energy budget.