Abstract
Traditional wireless networks focus on transparent data transmission where the data are processed at either the source or destination nodes. in contrast, the proposed approach aims at distributing data processing among the nodes in the network thus providing a higher processing capability than a single device. Moreover, energy consumption is balanced in the proposed scheme since the energy intensive processing will be distributed among the nodes. the performance of a wireless network is dependent on a number of factors including the available energy, energy efficiency, data processing delay, transmission delay, routing decisions, security architecture etc. Typical existing distributed processing schemes have a fixed node or node type assigned to the processing at the design phase, for example a cluster head in wireless sensor networks aggregating the data. in contrast, the proposed approach aims to virtualize the processing, energy, and communication resources of the entire heterogeneous network and dynamically distribute processing steps along the communication path while optimizing performance. Moreover, the security of the communication is considered an important factor in the decision to either process or forward the data. overall, the proposed scheme creates a wireless "computing cloud" where the processing tasks are dynamically assigned to the nodes using the Dynamic Programming (DP) methodology. the processing and transmission decisions are analytically derived from network models in order to optimize the utilization of the network resources including Available energy, processing capacity, security overhead, bandwidth etc. the proposed DP-Based scheme is mathematically derived thus guaranteeing performance. Moreover, the scheme is verified through network simulations. © 2011 Elsevier Inc. All rights reserved.
Recommended Citation
S. Kolli and M. Zawodniok, "A Dynamic Programming Approach: Improving the Performance of Wireless Networks," Journal of Parallel and Distributed Computing, vol. 71, no. 11, pp. 1447 - 1459, Elsevier, Nov 2011.
The definitive version is available at https://doi.org/10.1016/j.jpdc.2011.07.006
Department(s)
Electrical and Computer Engineering
Keywords and Phrases
Cloud computing; Dynamic programming (DP); Load balancing; Wireless sensor networks (WSN)
International Standard Serial Number (ISSN)
0743-7315
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Elsevier, All rights reserved.
Publication Date
01 Nov 2011
