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

ABSTRACT

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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    • "Therefore, achieving fast data delivery and response for the massive data generated in WSNs poses new research challenges. Data delivery delay has been extensively studied in forwarding quality measurement [7] [8] [9], sensor network routing, and scheduling [10] [11] [12] [13]. Most of the works focus on investigating the metrics to characterize the forwarding quality or minimizing average path delay. "
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    ABSTRACT: Many time-sensitive applications impose high requirement on real-time response. There exist many algorithms and routing protocols for efficient data packet delivery. However, previous works set the same retransmission threshold for all the relay nodes along a delivery path. The method decreases the probability of a packet being transmitted through the delivery path within given deadline. In this paper, we focus on finding the optimal retransmission thresholds for the relay nodes, such that the summation of the probability of a packet being transmitted to the next relay node or destination node within the specified deadline is maximized. A distributed greedy algorithm that can be run on sensor node is proposed, which enables the sensor node to adaptively set the optimal retransmission threshold. To avoid dropping the packet forwarded to the destination within given deadline with high probability, we develop a packet dropped protocol based on probabilistic delay bound. Experimental results show that the proposed protocols have better performance.
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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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