QoS and energy trade off in distributed energy-limited mesh/relay networks: A queuing analysis

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dc.contributor.authorFallahi, A
dc.contributor.authorHossain, E
dc.contributor.authorAlfa, AS
dc.date.accessioned2007-10-04T17:44:54Z
dc.date.available2007-10-04T17:44:54Z
dc.date.issued2006-06-30
dc.description.abstractIn a distributed multihop mesh/relay network (e.g., wireless ad hoc/sensor network, cellular multihop network), each node acts as a relay node to forward data packets from other nodes. These nodes are often energy-limited and also have limited buffer space. Therefore, efficient power saving mechanisms (e.g., sleeping mechanisms) are required so that the lifetime of these nodes can be extended while at the same time the quality of service (QoS) requirements (e.g., packet delay and packet loss rate) for the relayed packets can be satisfied. In this paper, we present a novel queueing analytical framework to study the tradeoff between the energy saving and the QoS at a relay node. Specifically, by modeling the bursty traffic arrival process as a MAP (Markovian Arrival Process) and the packet service process as having a phase-type (PH) distribution, we model each node as a MAP/PH/1 nonpreemptive priority queue. Here, the relayed packets and the node's own packets form two priority classes and the medium access control (MAC)/physical (PHY) layer protocol in the transmission protocol stack acts as the server process. Moreover, we use a phase-type vacation model for the energy-saving mechanism in a node when the MAC/PHY protocol refrains from transmitting in order to save battery power. Two different power saving mechanisms due to the standard exhaustive and the number-limited exhaustive vacation models (both in multiple vacation cases) are analyzed to study the tradeoff between the QoS performance of the relayed packets and the energy saving at a relay node. Also, an optimization formulation is presented to design an optimal wakeup strategy for the server process under QoS constraints. We use matrix-geometric method to obtain the stationary probability distribution for the system states from which the performance metrics are derived. Using phase-type distribution for both the service and the vacation processes and combining the priority queueing model with the vacation queueing model make the analysis very general and comprehensive.en
dc.format.extent2638698 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.citation1045-9219; IEEE TRANS PARALL DISTRIB SYS, JUN 2006, vol. 17, no. 6, p.576 to 592.en
dc.identifier.doihttp://dx.doi.org/10.1109/TPDS.2006.76
dc.identifier.urihttp://hdl.handle.net/1993/2878
dc.language.isoengen_US
dc.rights©2006 IEEE. 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 Manitoba'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.en
dc.rightsrestricted accessen_US
dc.statusPeer revieweden
dc.subjectwireless ad hoc/sensor networksen
dc.subjectquality of serviceen
dc.subjectenergy efficiencyen
dc.subjectqueuing analysisen
dc.subjectmatrix-geometric methoden
dc.subjectMarkovian arrival processen
dc.subjectphase-type distributionen
dc.subjectpriority queuesen
dc.subjectvacation queuing modelen
dc.subjectWIRELESS SENSOR NETWORKSen
dc.subjectDISCRETE-TIMEen
dc.subjectACCESSen
dc.titleQoS and energy trade off in distributed energy-limited mesh/relay networks: A queuing analysisen
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