Analysis of optimal strategies to minimize message delay in mobile opportunistic sensor networks
Jung Hyun Peter Jun · OhioLink ETD Center (Ohio Library and Information Network) · 2011
Wireless sensor networks (WSNs) are autonomous and self-healing networks of small battery powered sensors.Besides sensing their physical environments, these sensors are capable of communicate wirelessly, store, and compute data locally.The small size and its capability attract academics as well as industry for real-time monitoring of an area for potential events like wild fire, intruders, and hazardous gas.Since multi-hop communications from sources to sink node were unavoidable in WSNs, it is hard to achieve a longer life time.To reduce multi-hop communication, the idea of using mobile nodes as relay nodes which collect data and deliver it to sink, was introduced to WSNs.In addition to life time improvement, the mobile relay nodes can also keep wireless bandwidth capacity to a constant level while the node density is high.The mobile relay nodes moves independently and random from the perspective of WSNs.Mobile Opportunistic sensor Network (MOsN) specifically denotes overlays of the mobile opportunistic network on top of a static wireless sensor network where the time taken for relay nodes to deliver the data from static sensors to sink is completely opportunistic and unbounded.However, many applications related to security, emergency, and bio-hazard cannot tolerate this unbounded message delay.So we begin by analyzing the average time taken for relay nodes to deliver the message to sink in MOsN by modelling the delivery of message as a randomly moving particle with certain biasness towards the sink.The results show this delay is a function of the message bias level and starting distance d from the sink.The i 4.3 For |R| = 100,(a) Probability of selecting the best (b) Probability of selecting one of top three . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .60 5.1 The wireless sensors layout on yellowstone national park . . . . . . . . . . .65 5.2 The decreasing of maximum detection probability with a single UAV when scale representing the relative size of network grows.Graph also shows that probability is decreasing approximately in O(1/k). . . . . . . . . . . . . . .69 5.3 The detection probability of a WSN with multiple non-collaborative UAVs are numerically computed at k = 100 for different number of UAVs. . . . .72 5.4 Linear line shows the relationship between optimum size (m * ×m * ) of a WSN with multiple non-collaborative UAVs at k = 100. . . . . . . . . . . . . . . .