Research Article
DETOUR: Delay- and Energy-Aware Multi-Path Routing in Wireless Ad Hoc Networks
@INPROCEEDINGS{10.1109/MOBIQ.2007.4451005, author={Nadine Shillingford and David C. Salyers and Christian Poellabauer and Aaron Striegel}, title={DETOUR: Delay- and Energy-Aware Multi-Path Routing in Wireless Ad Hoc Networks}, proceedings={4th International ICST Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services}, publisher={IEEE}, proceedings_a={MOBIQUITOUS}, year={2008}, month={2}, keywords={Delay Energy consumption Energy efficiency Mobile ad hoc networks Mobile communication Routing protocols Sensor phenomena and characterization Spread spectrum communication Telecommunication traffic Wireless networks}, doi={10.1109/MOBIQ.2007.4451005} }
- Nadine Shillingford
David C. Salyers
Christian Poellabauer
Aaron Striegel
Year: 2008
DETOUR: Delay- and Energy-Aware Multi-Path Routing in Wireless Ad Hoc Networks
MOBIQUITOUS
IEEE
DOI: 10.1109/MOBIQ.2007.4451005
Abstract
Streaming real-time applications require the timely distribution of information in mobile ad-hoc and sensor networks. At the same time, such networks must operate energy-efficiently to maximize the lifetime of mobile devices and applications. In multi-hop networks, multiple communication paths between a single sender and receiver can be established, with varying real-time and energy characteristics of each path. This paper introduces the DETOUR (Delay- and Energy- aware mulTicOUrse Routing) protocol that applies feedback-driven path diversification, where traffic load is balanced across two or more paths to ensure both timeliness and energy-efficiency. We apply the (m,k) model for firm real-time communication to wireless networks, i.e., the protocol aims to meet at least m end-toend deadlines out of k packet transmissions, thereby sacrificing additional improvement in latency in order to maximize the lifetime of the network by minimizing energy consumption. The experimental results of this paper show the protocols ability to reduce energy consumptions (up to 35%) while meeting the data streams firm real-time constraints.