Current Search: Distributed algorithms (x)
View All Items
- Title
- Distributed Algorithms for Energy-Efficient Data Gathering and Barrier Coverage in Wireless Sensor Networks.
- Creator
- Aranzazu-Suescun, Catalina, Cardei, Mihaela, Florida Atlantic University, College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Wireless sensor networks (WSNs) provide rapid, untethered access to information, eliminating the barriers of distance, time, and location for many applications in national security, civilian search and rescue operations, surveillance, border monitoring, and many more. Sensor nodes are resource constraint in terms of power, bandwidth, memory, and computing capabilities. Sensor nodes are typically battery powered and depending on the application, it may be impractical or even impossible to...
Show moreWireless sensor networks (WSNs) provide rapid, untethered access to information, eliminating the barriers of distance, time, and location for many applications in national security, civilian search and rescue operations, surveillance, border monitoring, and many more. Sensor nodes are resource constraint in terms of power, bandwidth, memory, and computing capabilities. Sensor nodes are typically battery powered and depending on the application, it may be impractical or even impossible to recharge them. Thus, it is important to develop mechanisms for WSN which are energy efficient, in order to reduce the energy consumption in the network. Energy efficient algorithms result in an increased network lifetime. Data gathering is an important operation in WSNs, dealing with collecting sensed data or event reporting in a timely and efficient way. There are various scenarios that have to be carefully addressed. In this dissertation we propose energy efficient algorithms for data gathering. We propose a novel event-based clustering mechanism, and propose several efficient data gathering algorithms for mobile sink WSNs and for spatio-temporal events. Border surveillance is an important application of WSNs. Typical border surveillance applications aim to detect intruders attempting to enter or exit the border of a certain region. Deploying a set of sensor nodes on a region of interest where sensors form barriers for intruders is often referred to as the barrier coverage problem. In this dissertation we propose some novel mechanisms for increasing the percentage of events detected successfully. More specifically, we propose an adaptive sensor rotation mechanism, which allow sensors to decide their orientation angle adaptively, based on the location of the incoming events. In addition, we propose an Unmanned Aerial Vehicle UAV aided mechanism, where an UAV is used to cover gaps dynamically, resulting in an increased quality of the surveillance.
Show less - Date Issued
- 2019
- PURL
- http://purl.flvc.org/fau/fd/FA00013180
- Subject Headings
- Wireless sensor networks, Distributed algorithms, Wireless sensor nodes
- Format
- Document (PDF)
- Title
- Asynchronous distributed algorithms for multi-agent supporting systems.
- Creator
- Jin, Kai., Florida Atlantic University, Larrondo-Petrie, Maria M.
- Abstract/Description
-
Based on multi-agent supporting system (MASS) structures used to investigate the synchronous algorithms in my previous work, the partially and totally asynchronous distributed algorithms are proposed in this thesis. The stability of discrete MASS with asynchronous distributed algorithms is analyzed. The partially asynchronous algorithms proposed for both 1- and 2-dimensional MASS are proven to be convergent, if the vertical disturbances vary sufficiently slower than the convergent time of the...
Show moreBased on multi-agent supporting system (MASS) structures used to investigate the synchronous algorithms in my previous work, the partially and totally asynchronous distributed algorithms are proposed in this thesis. The stability of discrete MASS with asynchronous distributed algorithms is analyzed. The partially asynchronous algorithms proposed for both 1- and 2-dimensional MASS are proven to be convergent, if the vertical disturbances vary sufficiently slower than the convergent time of the system. The adjacent error becomes zero when the system converges. It is also proven that in 1-dimensional MASS using the proposed totally asynchronous algorithm, the maximum of the absolute value of the adjacent error is non-increasing over time. Finally, the simulation results for all the above cases are presented to demonstrate the theoretical findings.
Show less - Date Issued
- 1996
- PURL
- http://purl.flvc.org/fcla/dt/15277
- Subject Headings
- Electronic data processing--Distributed processing, Computer algorithms
- Format
- Document (PDF)
- Title
- Modeling strategic resource allocation in probabilistic global supply chain system with genetic algorithm.
- Creator
- Damrongwongsiri, Montri., Florida Atlantic University, Han, Chingping (Jim), College of Engineering and Computer Science, Department of Computer and Electrical Engineering and Computer Science
- Abstract/Description
-
Effective and efficient supply chain management is essential for domestic and global organizations to compete successfully in the international market. Superior inventory control policies and product distribution strategies along with advanced information technology enable an organization to collaborate distribution and allocation of inventory to gain a competitive advantage in the world market. Our research establishes the strategic resource allocation model to capture and encapsulate the...
Show moreEffective and efficient supply chain management is essential for domestic and global organizations to compete successfully in the international market. Superior inventory control policies and product distribution strategies along with advanced information technology enable an organization to collaborate distribution and allocation of inventory to gain a competitive advantage in the world market. Our research establishes the strategic resource allocation model to capture and encapsulate the complexity of the modern global supply chain management problem. A mathematical model was constructed to depict the stochastic, multiple-period, two-echelon inventory with the many-to-many demand-supplier network problem. The model simultaneously constitutes the uncertainties of inventory control and transportation parameters as well as the varying price factors. A genetic algorithm (GA) was applied to derive optimal solutions through a two-stage optimization process. Practical examples and solutions from three sourcing strategies (single sourcing, multiple sourcing, and dedicated system) were included to illustrate the GA based solution procedure. Our model can be utilized as a collaborative supply chain strategic planning tool to efficiently determine the appropriate inventory allocation and a dynamic decision making process to effectively manage the distribution plan.
Show less - Date Issued
- 2003
- PURL
- http://purl.flvc.org/fcla/dt/12056
- Subject Headings
- Business logistics--Mathematical models, Physical distribution of goods--Management, Inventory control--Mathematical models, Genetic algorithms
- Format
- Document (PDF)