The focus of this paper is to extend the lifetime of a battery powered node in wireless context. The lifetime of a battery depends on both the manner of discharge and the transmission power requirements. We present a framework for computing the optimal discharge strategy which maximizes the lifetime of a node by exploiting the battery characteristics and adapting to the varying power requirements for wireless operations. The complexity of the optimal computation is linear in the number of system states. However, since the number of states can be large, the optimal strategy can only be computed offline and executed via a table lookup. We present a simple discharge strategy which can be executed online without any This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. Abstract-The focus of this paper is to extend the lifetime of a battery powered node in wireless context. The lifetime of a battery depends on both the manner of discharge and the transmission power requirements. We present a framework for computing the optimal discharge strategy which maximizes the lifetime of a node by exploiting the battery characteristics and adapting to the varying power requirements for wireless operations. The complexity of the optimal computation is linear in the number of system states. However, since the number of states can be large, the optimal strategy can only be computed offline and executed via a table lookup. We present a simple discharge strategy which can be executed online without any table lookup and attains near maximum lifetime.
The focus of this paper is to extend the lifetime of a battery powered node in wireless context. The lifetime of a battery depends on both the manner of discharge and the transmission power requirements. We present a framework for computing the optimal discharge strategy which maximizes the lifetime of a node by exploiting the battery characteristics and adapting to the varying power requirements for wireless operations. The complexity of the optimal computation is linear in the number of system states. However, since the number of states can be large, the optimal strategy can only be computed offline and executed via a table lookup. We present a simple discharge strategy which can be executed online without any This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. Abstract-The focus of this paper is to extend the lifetime of a battery powered node in wireless context. The lifetime of a battery depends on both the manner of discharge and the transmission power requirements. We present a framework for computing the optimal discharge strategy which maximizes the lifetime of a node by exploiting the battery characteristics and adapting to the varying power requirements for wireless operations. The complexity of the optimal computation is linear in the number of system states. However, since the number of states can be large, the optimal strategy can only be computed offline and executed via a table lookup. We present a simple discharge strategy which can be executed online without any table lookup and attains near maximum lifetime.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.