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Energy conservation in wireless sensor networks: A survey
"... In the last years, wireless sensor networks (WSNs) have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery-powered devices, the critical aspects to face concern how to reduce the energy consumption of nodes, so that the network lifeti ..."
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Cited by 227 (11 self)
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In the last years, wireless sensor networks (WSNs) have gained increasing attention from both the research community and actual users. As sensor nodes are generally battery-powered devices, the critical aspects to face concern how to reduce the energy consumption of nodes, so that the network lifetime can be extended to reasonable times. In this paper we first break down the energy consumption for the components of a typical sensor node, and discuss the main directions to energy conservation in WSNs. Then, we present a systematic and comprehensive taxonomy of the energy conservation schemes, which are subsequently discussed in depth. Special attention has been devoted to promising solutions which have not yet obtained a wide attention in the literature, such as techniques for energy efficient data acquisition. Finally we conclude the paper with insights for research directions about energy conservation in WSNs.
Protothreads: simplifying event-driven programming of memory-constrained embedded systems.
- In SenSys ’06: Proceedings of the 4th international conference on Embedded networked sensor systems
, 2006
"... Abstract Event-driven programming is a popular model for writing programs for tiny embedded systems and sensor network nodes. While event-driven programming can keep the memory overhead down, it enforces a state machine programming style which makes many programs difficult to write, maintain, and d ..."
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Cited by 119 (12 self)
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Abstract Event-driven programming is a popular model for writing programs for tiny embedded systems and sensor network nodes. While event-driven programming can keep the memory overhead down, it enforces a state machine programming style which makes many programs difficult to write, maintain, and debug. We present a novel programming abstraction called protothreads that makes it possible to write eventdriven programs in a thread-like style, with a memory overhead of only two bytes per protothread. We show that protothreads significantly reduce the complexity of a number of widely used programs previously written with event-driven state machines. For the examined programs the majority of the state machines could be entirely removed. In the other cases the number of states and transitions was drastically decreased. With protothreads the number of lines of code was reduced by one third. The execution time overhead of protothreads is on the order of a few processor cycles.
Dozer: ultra-low power data gathering in sensor networks
- In IPSN ’07
, 2007
"... Environmental monitoring is one of the driving applications in the domain of sensor networks. The lifetime of such systems is envisioned to exceed several years. To achieve this longevity in unattended operation it is crucial to minimize energy consumption of the battery-powered sensor nodes. This p ..."
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Cited by 118 (5 self)
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Environmental monitoring is one of the driving applications in the domain of sensor networks. The lifetime of such systems is envisioned to exceed several years. To achieve this longevity in unattended operation it is crucial to minimize energy consumption of the battery-powered sensor nodes. This paper proposes Dozer, a data gathering protocol meeting the requirements of periodic data collection and ultra-low power consumption. The protocol comprises MAC-layer, topology control, and routing all coordinated to reduce energy wastage of the communication subsystem. Using a tree-based network structure, packets are reliably routed towards the data sink. Parents thereby schedule precise rendezvous times for all communication with their children. In a deployed network consisting of 40 TinyOSenabled sensor nodes, Dozer achieves radio duty cycles in the magnitude of 0.2%.
Active Sensor Networks
- in Proc. 2nd USENIX/ACM Symposium on Network Systems Design and Implementation (NSDI
, 2005
"... We propose using application specific virtual machines (ASVMs) to reprogram deployed wireless sensor networks. ASVMs provide a way for a user to define an applicationspecific boundary between virtual code and the VM engine. This allows programs to be very concise (tens to hundreds of bytes), making ..."
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Cited by 117 (12 self)
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We propose using application specific virtual machines (ASVMs) to reprogram deployed wireless sensor networks. ASVMs provide a way for a user to define an applicationspecific boundary between virtual code and the VM engine. This allows programs to be very concise (tens to hundreds of bytes), making program installation fast and inexpensive. Additionally, concise programs interpret few instructions, imposing very little interpretation overhead. We evaluate ASVMs against current proposals for network programming runtimes and show that ASVMs are more energy efficient by as much as 20%. We also evaluate ASVMs against hand built TinyOS applications and show that while interpretation imposes a significant execution overhead, the low duty cycles of realistic applications make the actual cost effectively unmeasurable. 1.
The design and implementation of a declarative sensor network system
- In ACM SenSys
, 2006
"... Sensor networks are notoriously difficult to program, given that they encompass the complexities of both distributed and embedded systems. To address this problem, we present the design and implementation of a declarative sensor network platform, DSN: a declarative language, compiler and runtime sui ..."
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Cited by 95 (11 self)
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Sensor networks are notoriously difficult to program, given that they encompass the complexities of both distributed and embedded systems. To address this problem, we present the design and implementation of a declarative sensor network platform, DSN: a declarative language, compiler and runtime suitable for programming a broad range of sensornet applications. We demonstrate that our approach is a natural fit for sensor networks by specifying several very different classes of traditional sensor network protocols, services and applications entirely declaratively – these include tree and geographic routing, link estimation, data collection, event tracking, version coherency, and localization. To our knowledge, this is the first time these disparate sensornet tasks have been addressed by a single high-level programming environment. Moreover, the declarative approach accommodates the desire for architectural flexibility and simple management of limited resources. Our results suggest that the declarative approach is well-suited to sensor networks, and that it can produce concise and flexible code by focusing on what the code is doing, and not on how it is doing it.
Programming Wireless Sensor Networks: Fundamental Concepts and State-of-the-Art
"... Wireless sensor networks (WSNs) are attracting great interest in a number of application domains concerned with monitoring and control of physical phenomena, as they enable dense and untethered deployments at low cost and with unprecedented flexibility. However, application development is still one ..."
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Cited by 81 (12 self)
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Wireless sensor networks (WSNs) are attracting great interest in a number of application domains concerned with monitoring and control of physical phenomena, as they enable dense and untethered deployments at low cost and with unprecedented flexibility. However, application development is still one of the main hurdles to a wide adoption of WSN technology. In current real-world WSN deployments, programming is typically carried out very close to the operating system, therefore requiring the programmer to focus on low-level system issues. This not only shifts the focus of the programmer away from the application logic, but also requires a technical background that is rarely found among application domain experts. The need for appropriate high-level programming abstractions, capable to simplify the programming chore without sacrificing efficiency, has been long recognized and several solutions have been hitherto proposed, which differ along many dimensions. In this paper, we survey the state-of-the-art in programming approaches for WSNs. We begin by presenting a taxonomy of WSN applications, to identify the fundamental requirements programming platforms must deal with. Then, we introduce a taxonomy of WSN programming approaches that captures the fundamental differences among existing solutions, and constitutes the core contribution of this paper. Our presentation style relies on concrete examples and code snippets taken from programming platforms representative of the taxonomy dimensions being discussed. We use the taxonomy to provide an exhaustive classification of existing approaches. Moreover, we also map existing approaches back to the application requirements, therefore providing not only a complete view of the state-of-the-art, but also useful insights for selecting the programming abstraction most appropriate to the application at hand.
Toward a theory of in-network computation in wireless sensor networks
- IEEE Communications Magazine
, 2006
"... Abstract — Sensor networks are not just data networks with sensors being the sources of data. Rather, they are often developed and deployed for a specific application, and the entire network operation is accordingly geared towards satisfying this application. For overall system efficiency, it may be ..."
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Cited by 77 (1 self)
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Abstract — Sensor networks are not just data networks with sensors being the sources of data. Rather, they are often developed and deployed for a specific application, and the entire network operation is accordingly geared towards satisfying this application. For overall system efficiency, it may be necessary for nodes to perform computations on data, as opposed to simply originating or forwarding data. Thus, the entire network can be viewed as performing an application specific distributed computation. The topic of this paper is to survey some lines of research which may be useful in developing a theory of in-network computation, that aims to elucidate how a wireless sensor network should efficiently perform such distributed computation. We review several existing approaches to computation problems in network settings, with a particular emphasis on the communication aspect of computation. We begin by studying the basic two-party communication complexity model and how to optimally compute functions of distributed inputs in this setting. We proceed to larger multi-hop networks, and study how blockcomputation and function structure can be exploited to provide greater computational throughput. We then consider distributed computation problems in networks subject to noise. Finally, we review some randomized gossip based approaches to computing aggregate functions in networks. These are diverse approaches spanning many different research communities, but together may find a role in the development of a more substantial theoretical foundation for sensor networks. I.
EnviroSuite: An Environmentally Immersive Programming Framework for Sensor Networks
- ACM Transactions on Embedded Computing Systems
, 2006
"... Sensor networks open a new frontier for embedded distributed computing. Paradigms for sensor network programming in the large have been identified as a significant challenge towards developing large-scale applications. Classical programming languages are too low-level. This paper presents the design ..."
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Cited by 64 (12 self)
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Sensor networks open a new frontier for embedded distributed computing. Paradigms for sensor network programming in the large have been identified as a significant challenge towards developing large-scale applications. Classical programming languages are too low-level. This paper presents the design, implementation, and evaluation of EnviroSuite, a programming framework that introduces a new paradigm, called environmentally immersive programming, to abstract distributed interactions with the environment. Environmentally immersive programming refers to an object-based programming model in which individual objects represent physical elements in the external environment. It allows the programmer to think directly in terms of environmental abstractions. EnviroSuite provides language primitives for environmentally immersive programming that map transparently into a support library of distributed algorithms for tracking and environmental monitoring. We show how nesC code of realistic applications is significantly simplified using EnviroSuite, and demonstrate the resulting system performance on Mica2 and XSM platforms.
Logical Neighborhoods: A programming abstraction for wireless sensor networks
- In Proc. of the the 2 st Int. Conf. on Distributed Computing on Sensor Systems (DCOSS
, 2006
"... Abstract. Wireless sensor networks (WSNs) typically exploit a single base station for collecting data and coordinating activities. However, decentralized architectures are rapidly emerging, as witnessed by wireless sensor and actuator networks (WSANs), and in general by solutions involving multiple ..."
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Cited by 63 (19 self)
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Abstract. Wireless sensor networks (WSNs) typically exploit a single base station for collecting data and coordinating activities. However, decentralized architectures are rapidly emerging, as witnessed by wireless sensor and actuator networks (WSANs), and in general by solutions involving multiple data sinks, heterogeneous nodes, and in-network coordination. These settings demand new programming abstractions to tame complexity without sacrificing efficiency. In this work we introduce the notion of logical neighborhood, which replaces the physical neighborhood provided by wireless broadcast with a higher-level, applicationdefined notion of proximity. The span of a logical neighborhood is specified declaratively based on the characteristics of nodes, along with requirements about communication costs. This paper presents the SPIDEY programming language for defining logical neighborhoods, and a routing strategy that efficiently supports the communication enabled by its programming constructs. 1
Algorithms for Distributed Functional Monitoring
, 2008
"... We study what we call functional monitoring problems. We have k players each tracking their inputs, say player i tracking a multiset Ai(t) up until time t, and communicating with a central coordinator. The coordinator’s task is to monitor a given function f computed over the union of the inputs ∪iAi ..."
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Cited by 60 (12 self)
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We study what we call functional monitoring problems. We have k players each tracking their inputs, say player i tracking a multiset Ai(t) up until time t, and communicating with a central coordinator. The coordinator’s task is to monitor a given function f computed over the union of the inputs ∪iAi(t), continuously at all times t. The goal is to minimize the number of bits communicated between the players and the coordinator. A simple example is when f is the sum, and the coordinator is required to alert when the sum of a distributed set of values exceeds a given threshold τ. Of interest is the approximate version where the coordinator outputs 1 if f ≥ τ and 0 if f ≤ (1 − ɛ)τ. This defines the (k, f, τ, ɛ) distributed, functional monitoring problem. Functional monitoring problems are fundamental in distributed systems, in particular sensor networks, where we must minimize communication; they also connect to problems in communication complexity, communication theory, and signal processing. Yet few formal bounds are known for functional monitoring. We give upper and lower bounds for the (k, f, τ, ɛ) problem for some of the basic f’s. In particular, we study frequency moments (F0, F1, F2). For F0 and F1, we obtain continuously monitoring algorithms with costs almost the same as their one-shot computation algorithms. However, for F2 the monitoring problem seems much harder. We give a carefully constructed multi-round algorithm that uses “sketch summaries ” at multiple levels of detail and solves the (k, F2, τ, ɛ) problem with communication Õ(k2 /ɛ+ ( √ k/ɛ) 3). Since frequency moment estimation is central to other problems, our results have immediate applications to histograms, wavelet computations, and others. Our algorithmic techniques are likely to be useful for other functional monitoring problems as well.
