دانلود رایگان مقاله انتشار محتوای فرصت طلب در شبکه های ad hoc تلفن همراه

Abstract

Opportunistic wireless content sharing via Mobile Ad hoc NETworks (MANETs) can increase throughput, lower latency, extend network coverage and reduce load on infrastructure. While the benefits of content diffusion clearly depend on the underlying movement dynamics and content demand, the impact of these factors on diffusion remains largely unexplored. We analyze content sharing potential based on device encounters inferred from a large multi-site wireless LAN trace. We explore the impact of time, location, and number of sources on diffusion, finding that contexts with higher activity generally promote faster diffusion, while additional content sources improve diffusion mainly in the short-term. We then apply real-world demand patterns from a popular campus maps application to content diffusion simulations. We find that up to 70% of map requests could theoretically be served from the peer network over the first 12 h. Finally, our analysis of the impact of trace uncertainties and individual device variation on diffusion potential reveals large differences based on the selected assumption and chosen source devices. We discuss these results and their implications for content-diffusion in MANETs.

9. Conclusion

907 Our analysis of MANET-based content diffusion reveals 908 several important factors influencing diffusion potential. 909 Firstly, the rate at which content spreads throughout a 910 network is highly site-dependent, even across sites of the 911 same type (university campuses) and even when the trace 912 collection is controlled for both network type and collec- 913 tion period. Secondly, the time at which content is in- 914 troduced into the MANET greatly influences the success 915 of information diffusion over the short-term. In particu- 916 lar, content introduced into the network over the weekend 917 suffers higher initial delay in reaching other devices than 918 content which is introduced during the working week. 919 This finding is consistent across both universal diffusion 920 and application-specific diffusion simulations. Thirdly, the 921 number of source devices used to diffuse a message can 922 greatly influence the rate of diffusion, particularly over the 923 short-term.