Heterogeneous Wireless Sensor Networks
2.8 OPEN PROBLEMS
Research in heterogeneous WSNs is in its infancy and is therefore rich in open prob-lems. Some of them include:
Inadequate Theory of Heterogeneous WSNs. Most of the models assume that a heterogeneous WSN provides data that are clock-driven (or periodic).
OPEN PROBLEMS 43
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Figure 2.15.(a) A “do not disturb” application deployed in an office area and (b) its corres-ponding topology.
Theory for query-driven and event-driven heterogeneous WSNs needs to be explored. While Mhatre et al. [15] consider hardware cost, models that also consider energy consumed in data processing (compression, fusion, etc.) are of interest.
TABLE 2.1. Heterogeneous WSN Projects.
Project Brief Description and Website
CENS, Center for Embedded Networked Sensing University of
California, Los Angeles
A mission of CENS is to develop and demonstrate architectural principles and methodologies for deeply embedded, massively distributed, sensor-rich systems. Research areas that relate to heterogeneous WSNs include the Multiscaled Sensing and Actuation (MAS) project, the Tenet project, the EmStar family of generalized deployment software tools, and individual protocols such as the centralized (CentRoute) and distributed (Hyper) routing protocols.
http://research.cens.ucla.edu/
CoSense, Collaborative Sensemaking Palo Alto Research
Center
Collaborative sensemaking of distributed sensor data for target recognition and condition monitoring.
http://www2.parc.com/spl/projects/cosense/
DSN-CC, Distributed Sensor Networks with Collective Computation Los Alamos National
Laboratory
The goal of DSN-CC is to demonstrate in situ collective computation abilities of heterogeneous sensor networks in simulation and using inexpensive, readily available off-the-shelf platforms. One application is a staged heterogeneous wireless sensor network for the detection of radioactive sources.
http://www.lanl.gov/source/orgs/isr/dsn/background.shtml GNOMES, Generalized Network of Miniature Environmental Sensors Rice University GNOMES is a low-cost hardware and software testbed. It is
designed to explore the properties of heterogeneous wireless sensor networks, to test theory in sensor networks architecture, and to be deployed in practical application environments.
http://cmclab.rice.edu/projects/sensors/
HSN, Heterogeneous Sensor Networks
University of
California, Berkeley
Heterogeneous sensor networks for automated target recognition and tracking in urban terrain is the focus. Issues addressed include: a new theory for distributed signal processing with random spatiotemporal sampling of complex scenes, robust design principles for sensor networks with both low- and high-bandwidth sensors, and metrics for the design and deployment of sensor networks and incorporating mobility into sensor networks.
http://trust.eecs.berkeley.edu/hsn/
OPEN PROBLEMS 45
TABLE 2.1. (Continued)
Project Brief Description and Website Intel Research Heterogeneous Sensor Networks
To address the scalability problem in WSNs, high-end nodes (such as Intel XScale-based nodes) are overlaid on a sensor network.
Goals include identifying and utilizing heterogeneous capabilities, such as links and services, for embedding local processing, imposing a database model, and enhancing routing protocols. Applications include preventive maintenance for equipment in Intel’s fabs and sensor networks for theme parks.
http://www.intel.com/research/exploratory/heterogeneous.htm Microsoft Research Networked Embedded Computing Group
Microsoft is developing new service architectures, interoperation protocols, and programming models that are resource-aware and resource-efficient across heterogeneous devices that can range from extremely limited sensor nodes to more powerful servers.
http://research.microsoft.com/nec/
SensEye, A Multitier Multimodal Camera Sensor Network University of
Massachusetts, Amherst
Trends in technology have resulted in a spectrum of camera sensors, wireless radios, and embedded sensor platforms.
SensEye is designed on the principle that multitier networks are not only scalable, but also offer a number of advantages over simpler, single-tier unimodal networks: lower cost, better coverage, higher functionality, and better reliability.
http://sensors.cs.umass.edu/projects/senseye/
SensorNets, Pervasive Infrastructure Sensor Networks Carnegie Mellon
University
SensorNets creates a framework for applications of networks of sensors in long-lived infrastructure systems such as buildings, bridges, and highways—a heterogeneous collection of sensors that must continue to operate even as parts of the infrastructure are changed, upgraded, or remodeled. The project has four main areas of thrust: devices, applications, systems, and data.
http://www.ices.cmu.edu/sensornets/
TABLE 2.2. Systems Infrastructure for Heterogeneous WSNs Systems Brief Project Description and Website
Aspen, Abstraction-based Sensor Programming at Penn University of
Pennsylvania
The Aspen project focuses on the challenges in developing a programming environment and runtime system for complex applications that may have heterogeneous types of sensor, confidentiality requirements, different levels of connectivity, and timing constraints. A programming model that handles heterogeneous data stream types and sensor capabilities is under development.
Avrora is an instruction-level sensor network simulator. Avrora simulates a network of AVR/Mica2 motes. The goal is to enhance Avrora with new capabilities for executing and monitoring simulations of heterogeneous sensor networks.
Specifically, this includes supporting sensor code that is dynamically updated, other sensor platforms, and source-level monitoring of simulations.
http://research.cens.ucla.edu/projects/ 2006/Systems/Avrora
DSS, Distributed Sensors Simulator
Los Alamos National Laboratory
DSS is a simulation framework that assists in implementing and debugging wireless distributed sensor networks. The user provides data on node locations and characteristics, defines event phenomena, and plugs in the applications each node runs.
DSS provides simulation of the wireless and environmental channels and was specifically designed for investigations of topological, phenomenological, networking, robustness,
EmStar is a family of tools, libraries, and services that provide an environment to help enable the design, development,
and deployment of WSN applications. EmStar supports heterogeneous deployments consisting of both mote-class and microserver-class component systems.
http://research.cens.ucla.edu/
BIBLIOGRAPHY 47
Tradeoffs Between Local and Remote Processing.The tradeoffs regarding where processing of the sensed data should be performed are not well understood.
What are the benefits of staged versus hierarchical architectures, and centralized processing at a sink node versus distributed processing by the cluster heads?
Querying, In-Network Processing, Caching.A related question to the processing tradeoff is how to support querying in a heterogeneous WSN, what to cache and where to cache, and what kind of in-networking processing can be performed.
Event Detection.A large application of heterogeneous WSNs is in event detection.
How do we reliably detect events with a low false alarm rate?
Quality-of-Service Support.Heterogeneous WSNs bring the potential of of high-bandwidth sources such as audio and video. Such data streams require quality-of-service support in order to meet delay, jitter, and related constraints.
Nonuniform Energy Drainage.While hierarchical architectures have alleviated the problem of non-uniform energy drainage, the problem remains unsolved.
Mobility in Sensor Nodes.Eventually, mobile nodes will be integrated into het-erogeneous WSNs. This will add another dimension of complexity to all of the problems.
ACKNOWLEDGMENTS
The work of V. R. Syrotiuk and B. Li is supported, in part, by LANL contract 13638-001-05 and NSF grant ANI-0240524. Any opinions, findings, conclusions, or recom-mendations expressed are those of the authors and do not necessarily reflect the views of LANL or NSF.
The work of A. M. Mielke is supported by the U.S. Department of Energy/NNSA and Los Alamos National Laboratory funds under Contract Number DE-AC52-06NA25396 and is approved for public release under LA-UR-06-5787.
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CHAPTER 3