Research Article
Resource Allocation with Minimum End-to-End Delay Differential Consideration in Multi-hop Cognitive Radio Networks
@INPROCEEDINGS{10.1007/978-3-642-29222-4_11, author={Yean-Fu Wen and Wanjiun Liao}, title={Resource Allocation with Minimum End-to-End Delay Differential Consideration in Multi-hop Cognitive Radio Networks}, proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Networks. 7th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2010, and Dedicated Short Range Communications Workshop, DSRC 2010, Houston, TX, USA, November 17-19, 2010, Revised Selected Papers}, proceedings_a={QSHINE}, year={2012}, month={10}, keywords={Cognitive radio networks delay differential negotiation priority resource allocation spectral bands}, doi={10.1007/978-3-642-29222-4_11} }- Yean-Fu Wen
Wanjiun Liao
Year: 2012
Resource Allocation with Minimum End-to-End Delay Differential Consideration in Multi-hop Cognitive Radio Networks
QSHINE
Springer
DOI: 10.1007/978-3-642-29222-4_11
Abstract
In cognitive radio networks, devices can dynamically sense, negotiate, and switch to available spectral bands so as to enhance spectrum utilization. The available spectral resource may vary with time, location, and spectral bands. This leads to many implementation difficulties, and one especially challenging one is how to fairly allocate these resources for multiple concurrent transmission flows in a multi-hop wireless environment. In this paper, we attempt to minimize the maximum end-to-end delay differential among all multi-hop flows within interference range. Flows within the same interference range may be on different routing paths with different network conditions such as hop count, network load and primary user’s behavior in previous hops. Determining how to fairly allocate resources to flows within the same interference range among a disjoint set of spectral bands in terms of minimal end-to-end delay differential becomes an important issue. We consider the accumulated delays (including sensing and negotiating delay, and queuing delay) up to this hop, and the rates of channel error and primary-user interruption on different bands. We then adopt four approximation schemes to solve this problem. The simulation results show that the average end-to-end delay differential with our proposed algorithms for all flows is minimized.
