Geography-informed energy conservation for Ad Hoc routing

Xu, Ya; Heidemann, John; Estrin, Deborah

doi:10.1145/381677.381685

Cited by 2,200 publications

(1,445 citation statements)

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“…Similarly, Chiasserini [3] allows a station to go to sleep, but a special hardware is required to receive wakeup signals. Also, in [31] the geographical area is partitioned into smaller grids in each of which only one host needs to remain active to relay packets.…”

Section: Related Workmentioning

confidence: 99%

A unified interference/collision model for optimal MAC transmission power in ad hoc networks

Gobriel

Melhem

Mossé

2006

IJWMC

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Abstract:In this paper we address the issue of controlling transmission power in power-aware adhoc networks. We argue that minimum transmission power is not always optimal. Previous work that minimizes the transmission power does not consider both the energy consumed in collision resolution and the energy disbursed to overcome the interference resulting from neighboring nodes. We investigate the basic transmission power control for the 802.11 MAC protocol, in which the control frames and the data frames can be transmitted at different power levels. A unified collision and interference model of a uniformly distributed network is constructed. Based on this model, the end-to-end network throughput and the total energy consumption of the network are examined for different network parameters. For a net-work with a given node density, our results show the optimal transmission power for control messages and for data messages that will yield maximum throughput and minimum energy consumption per message.

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Section: Related Workmentioning

confidence: 99%

A unified interference/collision model for optimal MAC transmission power in ad hoc networks

Gobriel

Melhem

Mossé

2006

IJWMC

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“…Only cell heads need to transmit data to the chain leader. The other sensor nodes just fall into sleep mode based on GAF protocol [7].…”

Section: Introductionmentioning

confidence: 99%

“…Only cell heads need to transmit data to the chain leader. The other sensor nodes just fall into sleep mode based on GAF protocol [7].The rest of this paper is organized as follows. Section II briefly reviews some related works.…”

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confidence: 99%

Grid-Based Data Aggregation for Wireless Sensor Networks

Wang¹,

Chiang²,

Hsieh³

et al. 2014

JACN

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Abstract-In a wireless sensor network (WSN), a huge number of sensor nodes with limited battery power are generally deployed over a severe field to gather data. It is impractical to recharge or replace the batteries of the sensor nodes in such a severe environment. Therefore, an energy efficient protocol is essential to maximize the lifetimes of nodes. In this paper, we propose a grid-based data aggregation scheme (GBDAS) for WSNs. We partition the whole sensor field into a 2-D logical grid of cells. In each cell, the node with the most residual energy takes turn to be the cell head, responsible for aggregating its own data with the data sensed by the other sensor nodes of the cell, and then transmitting it out. In order to reduce the data transmissions to the base station (BS), we further link each cell head to form a chain. In the chain, the cell head with the most residual energy is designated in turn as the chain leader. Aggregated data moves from head to head along the chain, and finally the chain leader transmits to the BS. In GBDAS, only the cell heads need to transmit data toward the BS. Therefore, the data transmissions to the BS substantially decrease. Besides, the cell heads and chain leader are designated in turn according to the energy level so that the energy depletion of nodes is evenly distributed. Simulation shows that GBDAS outperforms Direct and PEGASIS.Index Terms-Base station, cell head, data aggregation, grid-based, wireless sensor networks. I. INTRODUCTIONWireless sensor networks (WSNs) with a variety of potential applications have been drawing a lot of attention in recent years [1], [2]. Such networks usually comprise of a great number of low-cost and low-power tiny sensor nodes with the capability of gathering, processing, and transmitting data [3]- [5]. Sensor nodes are typically powered by batteries so their energy is strictly constrained. After being deployed, these sensor nodes are left unattended. Therefore, it is critical to manage sensor nodes in an energy efficiency manner.Since the energy consumption of sensor nodes is significantly spent in data transmission, especially for a long distance. An energy efficient transmission protocol is essential to maximize the lifetimes of sensor nodes. This paper mainly addresses the problem of data transmission from sensor nodes to a remote base station (BS), where the end-user can access the data. Since the location of the BS is distant, the energy consumed by nodes to directly transmit Manuscript received July 10, 2013; revised September 10, 2013 their data to the BS is so considerable that they will die very soon. Therefore, it is important for an approach to use as few transmissions as possible to the BS and reduce the amount of data that needs to be transmitted to the BS [6].In our proposed scheme, only a small portion of nodes are responsible for disseminating the data to the BS instead to decrease the data transmissions. To reduce the amount of data transmitted to the BS, the dissemination nodes aggregate their own data with the data s...

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“…Among existing approaches, TTDD [8] and GAF [9] use geographic location to partition the network into a 2-D mesh. (2) Each sen point (cluster) has at least one sensor.…”

Section: Introductionmentioning

confidence: 99%