TY - GEN
T1 - LEARN
T2 - 2006 3rd Annual IEEE Communications Society on Sensor and Ad hoc Communications and Networks, Secon 2006
AU - Wang, Yu
AU - Song, Wen Zhan
AU - Wang, Weizhao
AU - Li, Xiang Yang
AU - Dahlberg, Teresa A.
PY - 2006
Y1 - 2006
N2 - In this paper, we address the problem of energy efficient localized routing in wireless ad hoc networks. Numerous energy aware routing protocols were proposed to seek the power efficiency of routes. Among them, several geographical localized routing protocols were proposed to help making smarter routing decision using only local information and reduce the routing overhead. However, most of the proposed localized routing methods cannot theoretically guarantee the power efficiency of their routes. In this paper, we give the first localized routing algorithm, called Localized Energy Aware Restricted Neighborhood routing (LEARN), which can guarantee the power efficiency of its route asymptotically almost sure. Given destination node t, an intermediate node u will only select a certain neighbor v such that ∠ vut ≤ a for a parameter α < π/3 in our LEARN method. We theoretically prove that for a network, formed by nodes that are produced by a Poisson distribution with rate n over a compact and convex region Ω with unit area, when the transmission range rn = √ LEARN routing protocol will find the route for any pair of nodes asymptotically almost sure. When the transmission range rn = √βln n/πn for some β < π/α, the LEARN routing protocol will not be able to find the route for any pair of nodes asymptotically almost sure. We also conducted simulations to study the performance of LEARN and compare it with a typical localized routing protocol (GPSR) and a global ad hoc routing protocol (DSR).
AB - In this paper, we address the problem of energy efficient localized routing in wireless ad hoc networks. Numerous energy aware routing protocols were proposed to seek the power efficiency of routes. Among them, several geographical localized routing protocols were proposed to help making smarter routing decision using only local information and reduce the routing overhead. However, most of the proposed localized routing methods cannot theoretically guarantee the power efficiency of their routes. In this paper, we give the first localized routing algorithm, called Localized Energy Aware Restricted Neighborhood routing (LEARN), which can guarantee the power efficiency of its route asymptotically almost sure. Given destination node t, an intermediate node u will only select a certain neighbor v such that ∠ vut ≤ a for a parameter α < π/3 in our LEARN method. We theoretically prove that for a network, formed by nodes that are produced by a Poisson distribution with rate n over a compact and convex region Ω with unit area, when the transmission range rn = √ LEARN routing protocol will find the route for any pair of nodes asymptotically almost sure. When the transmission range rn = √βln n/πn for some β < π/α, the LEARN routing protocol will not be able to find the route for any pair of nodes asymptotically almost sure. We also conducted simulations to study the performance of LEARN and compare it with a typical localized routing protocol (GPSR) and a global ad hoc routing protocol (DSR).
UR - http://www.scopus.com/inward/record.url?scp=44049096342&partnerID=8YFLogxK
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U2 - 10.1109/SAHCN.2006.288507
DO - 10.1109/SAHCN.2006.288507
M3 - Conference contribution
AN - SCOPUS:44049096342
SN - 1424406269
SN - 9781424406265
T3 - 2006 3rd Annual IEEE Communications Society on Sensor and Adhoc Communications and Networks, Secon 2006
SP - 508
EP - 517
BT - 2006 3rd Annual IEEE Communications Society on Sensor and Adhoc Communications and Networks, Secon 2006
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 25 September 2006 through 28 September 2006
ER -