Recovery in the mobile wireless environment using mobile agents

2004 ◽  
Vol 3 (2) ◽  
pp. 180-191 ◽  
Author(s):  
S. Gadiraju ◽  
V. Kumar
Keyword(s):  
Mobile Agents ◽  
Mobile Wireless ◽  
Wireless Environment

scholarly journals Data Gathering Using Mobile Agents for Reducing Traffic in Dense Mobile Wireless Sensor Networks

2013 ◽  
Vol 9 (4) ◽  
pp. 295-314 ◽  
Author(s):  
Keisuke Goto ◽  
Yuya Sasaki ◽  
Takahiro Hara ◽  
Shojiro Nishio
Keyword(s):  
Mobile Agents ◽  
Data Gathering ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Wireless Sensor ◽  
Mobile Sensor ◽  
Mobile Wireless ◽  
Sensing Coverage ◽  
Mobile Sensor Nodes ◽  
Mobile Wireless Sensor

Recently, there has been increasing interest in Mobile Wireless Sensor Networks (MWSNs) that are constructed by mobile sensor nodes held by ordinary people, and it has led to a new concept called urban sensing. In such MWSNs, mobile sensor nodes densely exist, and thus, there are basically many sensor nodes that can sense a geographical point in the entire sensing area. To reduce the communication cost for gathering sensor data, it is desirable to gather the sensor data from the minimum number of mobile sensor nodes which are necessary to guarantee the sensing coverage or the quality of services. In this paper, to achieve this, we propose a data gathering method using mobile agents in dense MWSNs. The proposed method guarantees the sensing coverage of the entire area using mobile agents that autonomously perform sensing operations, transmit sensor data, and move between sensor nodes. By gathering only sensor data generated by sensor nodes where mobile agents are running, our proposed method can achieve efficient gathering of sensor data.

scholarly journals Performance of Cooperative Time-Reversal Communication in a Mobile Wireless Environment

2007 ◽  
Vol 3 (1) ◽  
pp. 59-68 ◽  
Author(s):  
Richard J. Barton ◽  
Ji Chen ◽  
Kyle Huang ◽  
Dagang Wu ◽  
Hsiao-Chun Wu
Keyword(s):  
Time Reversal ◽  
Peak Power ◽  
Indoor Environment ◽  
Target Position ◽  
Channel Correlation ◽  
Mobile Wireless ◽  
Simulated Environment ◽  
Wireless Environment ◽  
Multipath Environment ◽  
The Relationship

In this paper, we study the performance of a technique called time reversal for cooperative communication in a mobile wireless environment. To put the work in context, a brief introduction to time-reversal communication (TRC) in general and cooperative TRC in particular is presented. Performance of a proposed cooperative TRC scheme is evaluated numerically via a simulated indoor environment containing multiple wireless communication nodes. We characterize the behavior of the peak power received at a target node as a function of the number of cooperating transmitting nodes and as a function of the distance of the target from its predicted location within the simulated environment. The results demonstrate that the performance of cooperative TRC is less sensitive to uncertainty in the target position than might be expected from standard assumptions regarding the relationship between signal wavelength and spatial channel correlation in a complex multipath environment.

Knowledge Worker Productivity

2011 ◽  
pp. 311-330 ◽  
Author(s):  
Darren B. Nicholson ◽  
Jennifer A. Nicholson ◽  
D. Veena Parboteeah ◽  
Joseph S. Valacich
Keyword(s):  
Task Performance ◽  
Task Complexity ◽  
Knowledge Worker ◽  
Conflict Theory ◽  
Mobile Technologies ◽  
Future Research ◽  
Mobile Wireless ◽  
Productivity Losses ◽  
Wireless Environment ◽  
Networked Computing

Mobile wireless computing is changing the way in which people work, allowing work to occur in a broad range of environments on tasks that previously required fixed location-based, networked computing environments. Along with this greater work flexibility, it is also likely that these mobile work environments contain various types of distractions that could potentially affect the task performance of knowledge workers. Drawing on distraction-conflict theory, this research proposes a model of knowledge worker task performance within the context of a mobile wireless work environment. To test this model, a controlled laboratory experiment was conducted that contrasted task complexity and distraction levels on the task performance of individuals within a mobile wireless environment. Results indicate that regardless of task complexity, productivity losses will occur under both lower and higher levels of distraction. The implications of these results for future research and for the deployment of mobile technologies within organizations are discussed.

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