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A Markovian analytical framework for public‐safety video sharing by device‐to‐device communications
Author(s) -
Zhao Quanxin,
Han Shuai,
Mao Yuming,
Leng Supeng,
Min Geyong,
Hu Jia,
Najjari Noushin
Publication year - 2017
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4078
Subject(s) - computer science , computer network , key (lock) , first responder , wireless , bandwidth (computing) , network packet , wireless network , real time computing , computer security , telecommunications , political science , law
Summary Monitoring video of city surveillance camera plays an important role in public security and disaster relief, which is often used by first responder teams, such as firefighters and police officers. The first responders in emergency situations require consistent connection with one another and request the remote real‐time monitoring video for effective cooperation and coordination. However, the capacity and privacy of public wireless networks fail to satisfy the requirements in many emergency scenarios, which often leads to exceptionally high traffic loads and insecurity. Device‐to‐device (D2D) communications have been deemed a key solution for this problem, as responders can use D2D links for traffic offloading and secure communications. To investigate the D2D‐based solution for public safety video sharing, this paper focuses on the Focus Geographical Area (FGA) video consisting of multiple camera streams requiring higher bandwidth consumption than that of the traditional single‐camera stream, which attracts a large number of contents delivery requests in emergency situations. This paper develops a new Traffic Burden Switching Markovian (TBSM) model to evaluate the performance of transmitting real‐time FGA video in wireless networks with D2D communications. First, a novel D2D area model is introduced to characterize link‐switching in wireless D2D communication networks. Based on the proposed D2D area model, the state and transition matrix of TBSM model are then derived by jointly considering user mobility, link‐switching, and FGA video view‐switching. Thereafter, some key performance metrics including system offloading ratio, D2D link‐switching ratio, and view‐switching ratio are derived on the basis of coverage probability and ergodic rate. The performance results show the significant varying performance among D2D areas with different geographical locations in D2D enabled wireless networks, which is referred to as multi‐D2D‐area diversity. The excellent match between simulation and model results validates the accuracy of the TBSM model, which can be used to provide guidelines for the deployment and optimization of future wireless video networks with D2D communications.