Progress and Location Based Localized Power Aware Routing for Ad Hoc and Sensor Wireless Networks

Kuruvila, Johnson; Nayak, Amiya; Stojmenović, Ivan

doi:10.1080/15501320500259159

Cited by 61 publications

(57 citation statements)

References 15 publications

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“…In greedy routing [6] for instance, the node currently holding a packet forwards it to the neighbor closest to the destination. This method was then extended to energy efficient variants [11,5], to guaranteed delivery solutions [1] and to a combination of both energy efficient and guaranteed delivery approaches [14,4]. In ORouting [5], the neighbor closest to the line (SD) connecting the source node S to the destination node is considered as the best candidate relay to minimize energy.…”

Section: Related Workmentioning

confidence: 99%

“…In ORouting [5], the neighbor closest to the line (SD) connecting the source node S to the destination node is considered as the best candidate relay to minimize energy. Cost Over Progress (COP) based routing [11] is a localized metric aware greedy routing scheme. A node u forwards a packet to a neighbor v in the forwarding direction of the destination D such that the ratio of the energy consumed for sending a message from u to v (any cost metric can be used) to the progress made (measured as the reduction in distance to D) is minimized.…”

Section: Related Workmentioning

confidence: 99%

“…Moving strategy in [10] may cause useless zig-zag movements. In MobileCOP [12], next hop on the path is selected based on COP [11] metric. Once a path is computed, its nodes are moved and placed equidistantly on the straight line connecting the source to the destination, maintaining the same number of hops as in the computed path.…”

Section: Related Workmentioning

confidence: 99%

“…To compute C ′ s (.) the energy consumed to send a packet, we use parameter values used in the literature [11], i.e. c = 3 8 and α = 4, which lead to an optimal transmission range of r * = 100.…”

Section: Energy Consumptionmentioning

confidence: 99%

See 3 more Smart Citations

Energy Efficient Mobile Routing in Actuator and Sensor Networks with Connectivity Preservation

Hamouda

Mitton

Simplot‐Ryl

2011

Ad-Hoc, Mobile, and Wireless Networks

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Energy Consumptionmentioning

confidence: 99%

See 2 more Smart Citations

Energy Efficient Mobile Routing in Actuator and Sensor Networks with Connectivity Preservation

Hamouda

Mitton

Simplot‐Ryl

2011

Ad-Hoc, Mobile, and Wireless Networks

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“…Cost-over-progress framework with power as the cost has been applied in [19]. It was applied only in greedy phase and had similar performance to previous methods while enjoying simplicity in the design.The Iterative Power Progress algorithm, proposed in [19], is an improvement of the basic Power over Progress algorithm described in [19] as well. It works as follows.…”

Section: Power Consumption Based Routingmentioning

confidence: 99%

Energy-Aware Georouting with Guaranteed Delivery in Wireless Sensor Networks with Obstacles

Hamouda

Mitton

Pavkovic

et al. 2009

Int J Wireless Inf Networks

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We propose, EtE, a novel end-to-end localized routing protocol for wireless sensor networks that is energy-efficient and guarantees delivery. To forward a packet, a node s in graph G computes the cost of the energy weighted shortest path between s and each of its neighbors in the forward direction towards the destination which minimizes the ratio of the cost of the shortest path to the progress (reduction in distance towards the destination). It then sends the message to the first node on the shortest path from s to x: say node x ′ . Node x ′ restarts the same greedy routing process until the destination is reached or an obstacle is encountered and the routing fails. To recover from the latter scenario, local minima trap, our algorithm invokes an energy-aware Face routing that guarantees delivery. Our work is the first to optimize energy consumption of Face routing. It works as follows. First, it builds a connected dominating set from graph G, second it computes its Gabriel graph to obtain the planar graph G ′ . Face routing is invoked and applied to G ′ only to determine which edges to follow in the recovery process. On each edge, greedy routing is applied. This two-phase (greedy-Face) End-to-End routing process (EtE) reiterates until the final destination is reached. Simulation results show that EtE outperforms several existing geographical routing on energy consumption metric and delivery rate. Moreover, we prove that the computed path length and the total energy of the path are constant factors of the optimal for dense networks.

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Energy‐aware geographic routing in wireless sensor networks with anchor nodes

Huang

2011

Int J Communication

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SUMMARY Energy efficiency has become an important design consideration in geographic routing protocols for wireless sensor networks because the sensor nodes are energy constrained and battery recharging is usually not feasible. However, numerous existing energy‐aware geographic routing protocols are energy‐inefficient when the detouring mode is involved in the routing. Furthermore, most of them rarely or at most implicitly take into account the energy efficiency in the advance. In this paper, we present a novel energy‐aware geographic routing (EAGR) protocol that attempts to minimize the energy consumption for end‐to‐end data delivery. EAGR adaptively uses an existing geographic routing protocol to find an anchor list based on the projection distance of nodes for guiding packet forwarding. Each node holding the message utilizes geographic information, the characteristics of energy consumption, and the metric of advanced energy cost to make forwarding decisions, and dynamically adjusts its transmission power to just reach the selected node. Simulation results demonstrate that our scheme exhibits higher energy efficiency, smaller end‐to‐end delay, and better packet delivery ratio compared to other geographic routing protocols. Copyright © 2011 John Wiley & Sons, Ltd.

show abstract

Progress and Location Based Localized Power Aware Routing for Ad Hoc and Sensor Wireless Networks

Cited by 61 publications

References 15 publications

Energy Efficient Mobile Routing in Actuator and Sensor Networks with Connectivity Preservation

Energy Efficient Mobile Routing in Actuator and Sensor Networks with Connectivity Preservation

Energy-Aware Georouting with Guaranteed Delivery in Wireless Sensor Networks with Obstacles

Energy‐aware geographic routing in wireless sensor networks with anchor nodes

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