JouleTrack: a web based tool for software energy profiling
Proceedings of the 38th annual Design Automation Conference
Distributed Algorithms
A framework for energy-scalable communication in high-density wireless networks
Proceedings of the 2002 international symposium on Low power electronics and design
Energy-balanced task allocation for collaborative processing in networked embedded systems
Proceedings of the 2003 ACM SIGPLAN conference on Language, compiler, and tool for embedded systems
VLSID '00 Proceedings of the 13th International Conference on VLSI Design
Power-Aware Resource Allocation for Independent Tasks in Heterogeneous Real-Time Systems
ICPADS '02 Proceedings of the 9th International Conference on Parallel and Distributed Systems
Network Distributed Computing: Fitscapes and Fallacies
Network Distributed Computing: Fitscapes and Fallacies
Distributed Network Systems: From Concepts to Implementations (Network Theory and Applications)
Distributed Network Systems: From Concepts to Implementations (Network Theory and Applications)
Energy-balanced task allocation for collaborative processing in wireless sensor networks
Mobile Networks and Applications
Aware, Adaptive and Cognitive Radio: The Engineering Foundations of Radio XML
Aware, Adaptive and Cognitive Radio: The Engineering Foundations of Radio XML
Cognitive engine implementation for wireless multicarrier transceivers
Wireless Communications & Mobile Computing - Cognitive Radio, Software Defined Radio And Adaptive Wireless Systems
A Task Allocation Model for Distributed Computing Systems
IEEE Transactions on Computers
IEEE Transactions on Computers
Application of artificial intelligence to wireless communications
Application of artificial intelligence to wireless communications
Development of a case-based reasoning cognitive engine for IEEE 802.22 WRAN applications
ACM SIGMOBILE Mobile Computing and Communications Review
On balancing exploration vs. exploitation in a cognitive engine for multi-antenna systems
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Cognitive engine design for link adaptation: an application to multi-antenna systems
IEEE Transactions on Wireless Communications
Energy-Aware Distributed QR Decomposition on Wireless Sensor Nodes
The Computer Journal
A survey of spectrum sensing algorithms for cognitive radio applications
IEEE Communications Surveys & Tutorials
Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks
IEEE Journal on Selected Areas in Communications
Cyclostationary Signatures in Practical Cognitive Radio Applications
IEEE Journal on Selected Areas in Communications
Task allocation and scheduling in wireless distributed computing networks
Analog Integrated Circuits and Signal Processing
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Individual cognitive radio nodes in an ad-hoc cognitive radio network (CRN) have to perform complex data processing operations for several purposes, such as situational awareness and cognitive engine (CE) decision making. In an implementation point of view, each cognitive radio (CR) may not have the computational and power resources to perform these tasks by itself. In this paper, wireless distributed computing (WDC) is presented as a technology that enables multiple resource-constrained nodes to collaborate in computing complex tasks in a distributed manner. This approach has several benefits over the traditional approach of local computing, such as reduced energy and power consumption, reduced burden on the resources of individual nodes, and improved robustness. However, the benefits are negated by the communication overhead involved in WDC. This paper demonstrates the application of WDC to CRNs with the help of an example CE processing task. In addition, the paper analyzes the impact of the wireless environment on WDC scalability in homogeneous and heterogeneous environments. The paper also proposes a workload allocation scheme that utilizes a combination of stochastic optimization and decision-tree search approaches. The results show limitations in the scalability of WDC networks, mainly due to the communication overhead involved in sharing raw data pertaining to delegated computational tasks.