Energy-centric enabling tecumologies for wireless sensor networks

Min, Rex; Bhardwaj, Manish; Cho, SeongHwan; Ickes, Nathan; Shih, Eugene; Sinha, Abhishek; Wang, Alice; Chandrakasan, Anantha P.

doi:10.1109/mwc.2002.1028875

Cited by 198 publications

(108 citation statements)

References 11 publications

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“…In addition to our mote platform, a number of low-power sensor systems have been proposed and developed [3,4,12,39,55,56,64], though few of these systems have addressed flexible operating systems design. Several projects use more traditional embedded systems (such as PDAs [16]) or customized hardware [64].…”

Section: Related Workmentioning

confidence: 99%

TinyOS: An Operating System for Sensor Networks

Levis

Madden

Polastre

et al.

Ambient Intelligence

1,100

723

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Abstract. We present TinyOS, a flexible, application-specific operating system for sensor networks, which form a core component of ambient intelligence systems. Sensor networks consist of (potentially) thousands of tiny, low-power nodes, each of which execute concurrent, reactive programs that must operate with severe memory and power constraints. The sensor network challenges of limited resources, event-centric concurrent applications, and low-power operation drive the design of TinyOS. Our solution combines flexible, fine-grain components with an execution model that supports complex yet safe concurrent operations. TinyOS meets these challenges well and has become the platform of choice for sensor network research; it is in use by over a hundred groups worldwide, and supports a broad range of applications and research topics. We provide a qualitative and quantitative evaluation of the system, showing that it supports complex, concurrent programs with very low memory requirements (many applications fit within 16KB of memory, and the core OS is 400 bytes) and efficient, low-power operation. We present our experiences with TinyOS as a platform for sensor network innovation and applications.

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Section: Related Workmentioning

confidence: 99%

TinyOS: An Operating System for Sensor Networks

Levis

Madden

Polastre

et al.

Ambient Intelligence

1,100

723

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“…In one school of thought [10]- [11], the traditional Shortest Path First strategy is replaced by Least Energy First routing, i.e., a multi-hop route is preferred to a single-hop one if only multiple short-distance relays cost less energy than a single long-distance transmission. For example, "Minimum Transmission Energy" (MTE)…”

Section: Chapter 3 Related Workmentioning

confidence: 99%

Energy aware routing in high capacity overlays in wireless sensor networks

Shaikot

Sarangan

2008

2008 IEEE/ACS International Conference on Computer Systems and Applications

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“…This is especially true for sensor networks that typically must last for a year or more without battery replacement. Perhaps the most effective way to conserve energy is to periodically put each radio into a sleep mode, since listening to idle channels consumes significant processing and transceiver power [1]. The lifetime of such networks is a function of the duty cycle of the nodes, and networks whose nodes are in a sleep state for a higher percentage of time will last longer.…”

Section: Introductionmentioning

confidence: 99%

“…A complete survey is outside the scope of this paper, but the interested reader is referred to [2] and the references therein. There are two distinct categories of such protocols: (1) Nodes are awaken according to a deterministic rendezvous schedule, and (2) Nodes cycle on-an-off at random. This paper focuses on the second type of protocol, as it lends itself to simple implementation by allowing each node to autonomously set its own sleep schedule and brings to bear the analytical tools of probability theory.…”

Section: Introductionmentioning

confidence: 99%

Geographic random forwarding with hybrid-ARQ for ad hoc networks with rapid sleep cycles

Zhao¹,

Seshadri

Valenti

IEEE Global Telecommunications Conference, 2004. GLOBECOM '04.

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Abstract-This paper proposes and analyzes a new crosslayer protocol for ad hoc and sensor networks that unifies the concepts of Geographic Random Forwarding (GeRaF) and hybrid-ARQ. The protocol is given the descriptive name Hybrid ARq-Based Intra-cluster GEographically-informed Relaying (HARBINGER). Like GeRaF, HARBINGER assumes that each node knows its own position and that messages are addressed by location. As is common for sensor networks, the nodes cycle on-and-off according to a sleep schedule. Unlike GeRaF, which returns to the initial transmission state if no active node is within range, the nodes in HARBINGER combine transmissions thereby achieving an additional timediversity benefit. With HARBINGER, a lower density of active nodes will achieve almost the same delay and energy efficiency as GeRaF, implying that a lower duty cycle sleep schedule could be used to prolong the useful lifetime of the network. The paper gives detailed analysis of a version of the protocol (Fast-HARBINGER) whereby the sleep states of the network are synchronized with the data packet transmission rate of the network.

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Energy-centric enabling tecumologies for wireless sensor networks

Cited by 198 publications

References 11 publications

TinyOS: An Operating System for Sensor Networks

TinyOS: An Operating System for Sensor Networks

Energy aware routing in high capacity overlays in wireless sensor networks

Geographic random forwarding with hybrid-ARQ for ad hoc networks with rapid sleep cycles

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