Maximize concurrent data flows in multi-radio multi-channel wireless mesh networks

Abstract

Multi-radio multi-channel (MRMC) wireless mesh networks (WMNs) have emerged as the broadband networks to provide access to the Internet for ubiquitous computing with the support for a large number of data flows. Many applications in WMNs can be abstracted as a multi-flow coexistence problem to carry out multiple concurrent data transfers. More specifically, links in different channel layers must be concatenated to compose multiple data transfer paths based on nodes? free interfaces and available channels. This is typically formulated as a combinatorial optimization problem with various stages including channel assignment, path computing, and link scheduling. This paper analyzes traffic behaviors and designs a coexisting algorithm to maximize the number of concurrent data flows. Simulations are conducted in combinatorial cases of channel and radio with various traffic requests of multiple pairs. The experimental results show the efficacy of the coexisting algorithm over a randomly generated topology. This scheme can be used to develop routing and scheduling solutions for various multi-flow network applications through prior computing.

Joint Channel Assignment and Bandwidth Reservation Using Improved FireFly Algorithm (IFA) in Wireless Mesh Networks (WMN)

“…Though the work [13], maximizes the number of concurrent data flows by minimizing the interference, it did not consider the network congestion and bandwidth utilization of flows.…”

“…Zhanmao Cao et al [13] have analyzed traffic behaviors and designs a coexisting algorithm to maximize the number of concurrent data flows. Simulations are conducted in combinatorial cases of channel and radio with various traffic requests of multiple pairs.…”

Extraction of mosaic regions through projection and filtering of features from image big data

“…Similarly, as shown in (2), the horizontal line edge LE h (x, y) is projected in the y-axis direction. Then, a set of y coordinates in which Proj(y), which is the number of pixels accumulated through the projection, is equal to or greater than TH accum is acquired as shown in (4). In (1) and 2…”

“…Recently, with the rapid development of mobile sensing, computer networks, highdefinition cameras and artificial intelligence technologies, the amount of social multimedia data available is increasing explosively [1][2][3][4][5]. In particular, as smart mobile devices and location-based services are expanded, real-time location-based video data are actively used, and such digital image data are creating large-scale big data [6][7][8][9][10].…”