Conference Paper

Minimizing End-to-End Delay: A Novel Routing Metric for Multi-Radio Wireless Mesh Networks

Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL
DOI: 10.1109/INFCOM.2009.5061905 Conference: INFOCOM 2009. 28th IEEE International Conference on Computer Communications, Joint Conference of the IEEE Computer and Communications Societies, 19-25 April 2009, Rio de Janeiro, Brazil
Source: DBLP


This paper studies how to select a path with the minimum cost in terms of expected end-to-end delay (EED) in a multi-radio wireless mesh network. Different from the previous efforts, the new EED metric takes the queuing delay into account, since the end-to-end delay consists of not only the transmission delay over the wireless links but also the queuing delay in the buffer. In addition to minimizing the end-to-end delay, the EED metric implies the concept of load balancing. We develop EED- based routing protocols for both single-channel and multi-channel wireless mesh networks. In particular for the multi-radio multichannel case, we develop a generic iterative approach to calculate a multi-radio achievable bandwidth (MRAB) for a path, taking the impacts of inter/intra-flow interference and space/channel diversity into account. The MRAB is then integrated with EED to form the metric of weighted end-to-end delay (WEED). As a byproduct of MRAB, a channel diversity coefficient can be defined to quantitatively represent the channel diversity along a given path. Both numerical analysis and simulation studies are presented to validate the performance of the routing protocol based on the EED/WEED metric, with comparison to some well- known routing metrics.

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Available from: Weihua Zhuang, Sep 02, 2014
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    • "Despite much work in throughput-or energy-efficiency-oriented wireless routing [6] [13] [20] [47], real-time routing is much less studied . Moreover, the existing work that do consider data delivery delay in wireless routing either only try to minimize average path delay without ensuring probabilistic delay bounds [44] [19] [22] [31] [45], or they do not address the challenges that delay uncertainties pose to the task of quantifying probabilistic path delays and the task of addressing instability of delay-adaptive routing [25] [37]. Therefore , how to enable real-time routing in the presence of dynamic, uncertain link/path delays remains an important open problem for real-time wireless networked sensing and control. "

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    • "This implies that it is not difficult to find Q p for path p. Following [4] [11] [31], the available bandwidth of path p, BðpÞ, is estimated as: "
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    • "Where, T B l corresponds to the total available bandwidth of link l and T x l corresponds to the amount of data occupying the link l during the time window ω. Then, considering a path p =< l 1 , l 2 , ..., l h >, the available bandwidth of the path p is no longer the minimum of RLCs of links composing the path but it is estimated as follows [10]: "
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