Masters Theses


Sandeep Kolli


"The performance of wireless networks is dependent on a number of factors including the available energy, energy-efficiency, data processing delay, transmission delay, routing decisions, security overhead, etc. Traditionally, due to limited resources, nodes were tasked with only collecting measurements and sending them to a base station or central unit for processing. With increased capabilities of microprocessors the data processing is pushed more toward network and its more capable nodes. This thesis focuses to virtualize the processing resources of the entire network and dynamically distribute processing steps along the routing path while optimizing performance. Additionally, a new multi-key encryption (MKE) scheme is proposed to optimize efficiency while enhancing security. The main benefit of the MKE scheme is the improved resilience of the advanced encryption standard (AES) against correlation power analysis (CPA) attack by breaking the correlation between power consumption and the used secret key. The MKE security scheme is analyzed with network implementation and studied for its effects on network parameters such as network connectivity, resilience against node capture and energy efficiency of the scheme. Moreover, a new analysis methodology is proposed to quantify a resilience of a network against node capture such that the strength of the underlying security mechanisms is taken into account. Furthermore, the tradeoff between security and network performance is addressed by the proposed task-scheduling scheme. Also, the proposed methodology does not make assumption of homogenous [sic] network that is often used in literature to simplify analysis and scheme design. In contrast, the proposed formulation is generic, thus allowing heterogeneous nodes to be used while guaranteeing network performance. Consequently, 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 network resources including: available energy, processing capacity, security overhead, bandwidth etc. As a result, the online optimization of network resources is achieved"--Abstract, page iv.


Zawodniok, Maciej Jan, 1975-

Committee Member(s)

Zheng, Y. Rosa
Miller, Ann K.


Electrical and Computer Engineering

Degree Name

M.S. in Electrical Engineering


Missouri University of Science and Technology

Publication Date

Summer 2010

Journal article titles appearing in thesis/dissertation

  • Dynamic programming approach: improving performance of the wireless networks
  • Energy-efficient multi-key security scheme for wireless sensor networks


x, 81 pages


© 2010 Sandeep Chowdary Kolli, All rights reserved.

Document Type

Thesis - Open Access

File Type




Subject Headings

Data encryption (Computer science)
Dynamic programming
Wireless sensor networks -- Design

Thesis Number

T 9674

Print OCLC #


Electronic OCLC #