Green Diffusion: Data dissemination in sensor networks using solar power

Abu-Baker, Amjad; Huang, Hong; Johnson, Eric; Misra, Satyajayant

doi:10.1109/ccnc.2011.5766603

Cited by 3 publications

(5 citation statements)

References 16 publications

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“…For such networks, attention has been focused on the design of energy harvesting aware algorithms to create perpetualoperation [6], [8], [14]. Research has also been focused on energy harvesting aware routing [1]. We consider the problem of energy harvesting aware RNP, namely EH-CRNP, which to our best knowledge has not been studied in the literature.…”

Section: Related Workmentioning

confidence: 99%

“…where c(z) ∈ [1,2]. This weight function ensures that the locations that have more energy harvesting potential have lower weights, hence will be favored by our algorithms for placement.…”

Section: Basic Definitions and Notationsmentioning

confidence: 99%

“…Instead of using just the fraction, we added a one to the weight function to ensure that a relay node placement comes at an additional cost (weight). Having c(z) ∈ [1,2] ensures that placing an RN incurs an additional cost of one per position, hence an RN will only be placed if absolutely necessary for connectivity/survivability. Our aim is to place the minimum number of RNs, the decision of whether a position is good for harvesting energy or not is the next decision.…”

Section: Basic Definitions and Notationsmentioning

confidence: 99%

“…Our aim is to place the minimum number of RNs, the decision of whether a position is good for harvesting energy or not is the next decision. Also, having c(z) ∈ [1,2] helps prove the approximation bounds efficiently (refer Sections 4 and 5). Based on the above conditions, the SNs, RNs, and BSs, with their communication ranges and their energy harvesting potentials, induce the hybrid communication graph (HCG) formally defined below.…”

Section: Basic Definitions and Notationsmentioning

confidence: 99%

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Approximation Algorithms for Constrained Relay Node Placement in Energy Harvesting Wireless Sensor Networks

Misra

Majd

Huang

2014

IEEE Trans. Comput.

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The constrained relay node placement problem in a wireless sensor network seeks the deployment of a minimum number of relay nodes (RNs) in a set of candidate locations in the network to satisfy specific requirements, such as connectivity or survivability. In this paper, we study the constrained relay node placement problem in an energy-harvesting network in which the energy harvesting potential of the candidate locations are known a priori. Our aim is to place a minimum number of relay nodes, to achieve connectivity or survivability, while ensuring that the relay nodes harvest large amounts of ambient energy. We present the connectivity and survivability problems, discuss their NP-hardness, and propose polynomial time O(1)-approximation algorithms with low approximation ratios to solve them. We validate the effectiveness of our algorithms through numerical results to show that the RNs placed by our algorithms harvest 50% more energy on average than those placed by the algorithms unaware of energy harvesting. We also develop a unified-mixed integer linear program (MILP)-based formulation to compute a lower bound of the optimal solution for minimum relay node placement and demonstrate that the results of our proposed algorithms were on average within 1.5 times of the optimal.

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Section: Related Workmentioning

confidence: 99%

“…where c(z) ∈ [1,2]. This weight function ensures that the locations that have more energy harvesting potential have lower weights, hence will be favored by our algorithms for placement.…”

Section: Basic Definitions and Notationsmentioning

confidence: 99%

Section: Basic Definitions and Notationsmentioning

confidence: 99%

Section: Basic Definitions and Notationsmentioning

confidence: 99%

See 2 more Smart Citations

Approximation Algorithms for Constrained Relay Node Placement in Energy Harvesting Wireless Sensor Networks

Misra

Majd

Huang

2014

IEEE Trans. Comput.

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“…Otherwise, this node will always be selected as the best route and will use up all its energy. Recently, there have been some studies that have demonstrated that the nodes must be energetically self-sustainable, i.e., equipped with battery recharge, as shown in Abu-Baker et al (2010). Another proposal takes into account the energy required for the route selection, such as is shown in PEMuR Kandris et al (2011).…”

Section: Energy Considerationsmentioning

confidence: 99%