Barrier-Coverage for City Block Monitoring in Bandwidth Sensitive Vehicular Adhoc Networks

Abstract

Recently, vehicular ad hoc network (VANET) is receiving lots of attentions as this new networking technology is expected to improve our daily driving experience greatly and will enable a number of emerging applications. It is envisioned that the vehicles in VANETs are armed with a number of advanced technologies such as wireless transceiver, video cameras, etc. This paper investigates the potential of the advanced VANET nodes to construct an impromptu surveillance system to surround an area of interest, which can be a city block, such that any suspect of interest leaving the city block can be monitored by a VANET node participating the surveillance system. Such a system can be useful to provide an emergency response system to keep the track of suspects who are leaving the area by walk or by car after committing a crime inside the block, e.g. Boston bombing suspects. We observe that as the network bandwidth is limited, not all vehicles can participate and transmit video to the control center in real time. Therefore, we propose new scheduling algorithms for the VANET nodes, which consider the mobility of each vehicle as well as the network bandwidth and continuously provides barrier-coverage circumventing the city block over a given mission period. Via simulation, we show the efficiency of our algorithms.

Maximizing spatial–temporal coverage in mobile crowd-sensing based on public transports with predictable trajectory

“…In recent years, many researchers focus on studying the vehicular application of crowd-sensing, for example, traffic accident evidence collection, 5,13 city block monitoring, 14 bike-net for cyclist experience mapping, 15 and architectures of crowd-sensing. Authors of the literature 10,[16][17][18] proposed the participants recruitment system and formulated the recruitment of participants as a constrained coverage problem but did not consider the mobility of vehicle.…”

“…Authors of the literature 10,[16][17][18] proposed the participants recruitment system and formulated the recruitment of participants as a constrained coverage problem but did not consider the mobility of vehicle. Authors in Lee et al 14 constructed a surveillance system based on vehicle with constraint network bandwidth. Gerla et al 16 introduced a crowdsensing service based on vehicle embedded with cameras to deliver images on demand to users.…”

Ad Hoc Communication Topology Construction for Delay-Sensitive Internet of Vehicle Applications

“…en, we can choose a root node as the centre node, as shown in Figure 5. After checking (9) end for (10) EC List � make the beginning Clusters by disconnected edge; (11) (2) G List � Sort {δ(i,j), δ(k,l), . .…”

“…(2) while (S j ∈ S * ) ≠ ϕ do (3) Choose max number of set S j in the subset S * ; (4) set D * ←D * ∪ j; (5) set S * ←S * − j; (6) end while (7) find connected path between D * using shortest path; (8) c ← size of connected path; (9) if c > 2k then (10) divide connected path; (11) end if (12) if c is odd number then (13) v←(c + 1)/2; ( 14) else (15) v←c/2; (16) end if (17) �> construct the bounded k-hop tree removing cycling edge (18) while…”

“…IoVs improve the efficiency and safety of modern transportation systems. Traffic congestion detection, road condition monitoring (e.g., icy road surface), and pothole detection are a few examples demonstrating the significance of IoV and its applications [6][7][8][9][10][11][12]. In a typical setting, each IoV node is equipped with an On-Board Unit (OBU), which is an integrated electric device with various modules such as GPS and a radio transceiver.…”