PIPeR: Impact of power-awareness on social-based opportunistic advertising

Ayyat, Soumaia Al; Aly, Sherif G.; Harras, Khaled A.

doi:10.1109/wcnc.2014.6953143

Cited by 6 publications

(3 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Generally speaking, SLAW could be used for modeling the pedestrian movement behaviour in small scale social gathering events, such as train stations, malls, and theme parks due to its accuracy and realistic outlook in terms of network traffic per square meter in comparison with the random mobility models [150], [151], [152]. However, there have been a number of efforts on providing a more realistic mobility model for applications such as theme parks, airports, fairs, and festivals with prohibited or restricted use of vehicles.…”

Section: ) Self-similar Least Action Walk Model (Slaw) [70]mentioning

confidence: 99%

Impacts of Mobility Models on RPL-Based Mobile IoT Infrastructures: An Evaluative Comparison and Survey

et al. 2020

View full text Add to dashboard Cite

With the widespread use of IoT applications and the increasing trend in the number of connected smart devices, the concept of routing has become very challenging. In this regard, the IPv6 Routing Protocol for Low-power and Lossy Networks (PRL) was standardized to be adopted in IoT networks. Nevertheless, while mobile IoT domains have gained significant popularity in recent years, since RPL was fundamentally designed for stationary IoT applications, it could not well adjust with the dynamic fluctuations in mobile applications. While there have been a number of studies on tuning RPL for mobile IoT applications, but still there is a high demand for more efforts to reach a standard version of this protocol for such applications. Accordingly, in this survey, we try to conduct a precise and comprehensive experimental study on the impact of various mobility models on the performance of a mobility-aware RPL to help this process. In this regard, a complete and scrutinized survey of the mobility models has been presented to be able to fairly justify and compare the outcome results. A significant set of evaluations has been conducted via precise IoT simulation tools to monitor and compare the performance of the network and its IoT devices in mobile RPL-based IoT applications under the presence of different mobility models from different perspectives including power consumption, reliability, latency, and control packet overhead. This will pave the way for researchers in both academia and industry to be able to compare the impact of various mobility models on the functionality of RPL, and consequently to design and implement application-specific and even a standard version of this protocol, which is capable of being employed in mobile IoT applications.

show abstract

Section: ) Self-similar Least Action Walk Model (Slaw) [70]mentioning

confidence: 99%

Impacts of Mobility Models on RPL-Based Mobile IoT Infrastructures: An Evaluative Comparison and Survey

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Service discovery in highly distributed and mobile environments, similar to that of MSN, have been investigated for over a decade [7,18]. In particular, service discovery protocols addressing mobile adhoc networks [19,20], delay-tolerant networks [21], or opportunistic networks [22,23,24] are particularly relevant for our work since these networks have many similarities with MSN. In particular, [19] and [21] offer service discovery and delivery by means of a peer-to-peer model which, however, is not suitable to tolerate the frequent and prolonged disconnections typical of MSNs.…”

Section: Service Discovery Algorithmsmentioning

confidence: 99%

“…User sociality and interests are instead considered in [24,25], whose main focus however is in energy efficiency and in privacy, and in [22] that devises a strategy for discovery of resources (which are classified based on the user interests) in a delay-tolerant network. Similar to our approach, the discovery of resources in [22] is community-based, however, if the resource is not found, then the protocol reverts to a flooding-based strategy.…”

Section: Service Discovery Algorithmsmentioning

confidence: 99%

Collaborative Service Discovery in Mobile Social Networks

2018

View full text Add to dashboard Cite

Mobile social networking is a recent paradigm arisen from the wide spread of mobile and wearable devices. Based on the short-range communication interfaces of these devices it is possible to establish opportunistic communications among them and build networks independent to the global one. Challenges introduced by this new type of networks are related to the sharing of resources and services and to the exploitation of the communication opportunities among devices. Limit of existing algorithms, that have sought to fill these shortages, is the lack of attention on the main actor of this service-oriented chain, the user. To this purpose, we introduce the COllaborative seRvice DIscovery ALgorithm (CORDIAL) that leverages both mobility and sociality of the users. We evaluate the performance of CORDIAL combined with different routing protocols for opportunistic networks, and we compare it with a benchmark algorithm (S-Flood) based on flooding and another service discovery algorithm designed to leverage mobile social network features, namely, ServIce DiscovEry in Mobile sociAl Networks (SIDEMAN). Our results show that the performance of CORDIAL remains stable with the different routing algorithms and that, in function of the query forwarding strategy triggered, CORDIAL matches the performance of S-Flood in terms of Query Response Time, achieving a better proactivity score with respect S-Flood and SIDEMAN as well.

show abstract