A gradient tracking method for resource allocation base on distributed convex optimization

Fu, Ermeng; Gao, Hui; Fasehullah, Muhammad; Tan, Lian

doi:10.1109/isass.2019.8757716

Cited by 2 publications

(1 citation statement)

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“…The energy savings can be done with the help of an event and a self-triggered system in which the amount of transmission to be done is informed before transmission actually occurs and resources are provided by the system. Distributed resource allocation [59] has an inefficiency when agents compete to reduce the cost constraint by total resource and capacity. Ermeng Fu and the team describe a cost function that can get good objective function with limited conditions.…”

Section: G Resource Allocationmentioning

confidence: 99%

Reckoning Network Lifetime Ratio for Wireless Sensor Network

Saqhib¹,

S²

2019

IJITEE

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Advanced Technologies such as Internet of Things, Machine Networking give rise to the deployment of autonomous Wireless Sensor Nodes. They are used for various domains namely battlefield monitoring, enemy detection and monitoring the environment change. These Wireless Sensor Nodes have the properties of low cost and high battery life. NL (Network Lifetime) is an important phase of Wireless Sensor Network (WSNs), in which the nodes can maintain sensing for a more amount of time. NL can be improved by use of multiple techniques namely Opportunistic Transmission, Scheduling of Timed Data Packets, Clustering of Nodes, Energy Harvesting and Connectivity. This paper provides the energy consumption computation, life time ratio definition and the overview of NL improvement techniques. The paper also presents brief review of the Destination based and Source based routing algorithm

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Section: G Resource Allocationmentioning

confidence: 99%