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

Interest and social-awareness can be valuable determinants in decisions related to content delivery in mobile environments. Under certain conditions, we can deliver content with less cost and better delivery ratios, while only involving users that are interested in the type of content being delivered. However, the depletion of valuable power resources poses a deterrent to node participation in such interest-aware forwarding systems. No significant research contribution has been identified to collectively maximize the benefits of social, interest, and power awareness. In this work, we propose a new algorithm called PIPeR which integrates power awareness with an interest and socially aware forwarding algorithm called IPeR. Through simulations, we present and evaluate four modes of PIPeR. The results show that PIPeR is more fair and preserves at least 22% of the power IPeR consumes with less delay, while relying significantly on interested forwarders and with comparable cost to maintain similar delivery ratios

Social pervasive systems: the harmonization between social networking and pervasive systems

The recent advancement in mobile device sensor technology, coupled with the wealth of structured accessible data of social networks, form a very data-wealthy ecosystem. Such an ecosystem is rich in bi-directional context that can flow between the mobile and social worlds enabling the creation of an elitist breed of pervasive services and applications. We label the breed resulting from the merger as Social Pervasive Systems (SPS)

Interest aware peoplerank: towards effective social-based opportunistic advertising

Various emerging context aware social-based applications and services assume constant non-disruptive connectivity. Mobile advertisers in such environments want to reach potentially interested users in a given proximity and within a specified short duration, whether these users are connected to the network or not. While opportunistic forwarding algorithms can be leveraged for forwarding these advertisements, there is little incentive for those not interested in the ad to act as forwarders. Our goal in this paper is to leverage explicit interest, gathered from a user’s social profile, and integrate it with social-based opportunistic forwarding algorithms in order to enable soft real time opportunistic ad delivery in intermittently connected mobile networks. We propose IPeR, a fully distributed interest-aware forwarding algorithm that integrates with PeopleRank to reduce the overall cost and delay while reducing the number of contacted uninterested candidates. Our results, obtained via simulations and validated with real mobility traces coupled with user social data, are promising. In comparison to interest-oblivious socially-aware protocols such as PeopleRank, the IPeR approach reduces the cost to 70% to reach the same delivery ratio, and reduces the ratio of contacted uninterested forwarders by 23%. It also achieves an extra 70% recall and 107% accuracy with only 2% less precision

On the integration of interest and power awareness in social-aware opportunistic forwarding algorithms

Social-aware Opportunistic forwarding algorithms are much needed in environments which lack network infrastructure or in those that are susceptible to frequent disruptions. However, most of these algorithms are oblivious to both the user’s interest in the forwarded content and the limited power resources of the available mobile nodes. This paper proposes PI-SOFA, a framework for integrating the awareness of both interest and power capability of a candidate node within the forwarding decision process. Furthermore, the framework adapts its forwarding decisions to the expected contact duration between message carriers and candidate nodes. The proposed framework is applied to three state-of-the-art social-aware opportunistic forwarding algorithms that target mobile opportunistic message delivery. A simulation-based performance evaluation demonstrates the improved effectiveness, efficiency, reduction of power consumption, and fair utilization of the proposed versions in comparison to those of the original algorithms. The results show more than 500% extra f-measure, mainly by disregarding uninterested nodes while focusing on the potentially interested ones. Moreover, power awareness preserves up to 8% power with 41% less cost to attain higher utilization fairness by focusing on power-capable interested nodes. Finally, this paper analyzes the proposed algorithms’ performance across various environments. These findings can benefit message delivery in opportunistic mobile networks

Social pervasive systems: The integration of social networks and pervasive systems

Sensor technology embedded in smart mobile devices branded such devices as candidates for building innovative context-aware pervasive applications. On a parallel front, the notable evolution in the shape and form of social networking and their seamless accessibility from mobile devices founded a goldmine of contextual information. Utilizing an ecosystem that combines both mobile smart devices and a big data like environment in the form of social networks allows for the creation of an elitist set of services and applications that merge the two domains. In this paper, and following the footsteps of similar research efforts that attempted to combine both domains, we describe what we label as Social Pervasive Systems that cross-pollinate a mutually influential mobile and social world with opportunities for new breeds of applications. We present herein the evolution of the merger between both worlds for a better understanding. Above and beyond what related work achieved, we present a set of new services and potential applications that emerge from this new blend, and also describe some of the expected challenges such systems will face

SAROS: A social-aware opportunistic forwarding simulator

Many applications are being developed to leverage the popularity of mobile opportunistic networks. However, building adaptive testbeds can be costly and challenging. This challenge motivates the need for effective opportunistic network simulators to provide a variety of opportunistic environment setups, and evaluate proposed applications and protocols with a comprehensive set of metrics. This paper presents SAROS, a simulator of opportunistic networking environments with a variety of interest distributions, power consumption distributions, imported real traces, and social network integration. The simulator provides a wide variety of evaluation metrics that are not offered by comparable simulators. Finally, SAROS also implements several opportunistic forwarding algorithms ranging from social-oblivious algorithms to interest and power-aware social-based algorithms

Towards context aware opportunistic forwarding in social pervasive systems

Recent advances in mobile device sensor technology, coupled with a wealth of structured and accessible data from social networks, have together formed a data-rich ecosystem. Such an ecosystem is very wealthy in a bi-directional context that can flow between the mobile and social worlds in order to promote the creation of an elitist breed of pervasive services and applications. We label the breed resulting from the merger as Social Pervasive Systems (SPS). We review literature of the domains of social networks and mobile pervasive systems to study prior research attempts to merge both domains as detailed in Chapter 2. We begin by presenting our observations in a timeline that illustrates the progress of the merger attempts. From this study, we are able to identify a collection of services and application families that can rise as a byproduct of the merger. We also identify a set of challenges that deter the formation of systems of this kind and propose solutions for them. Although the internet access is pervasive and ubiquitous in the developed countries, it is scarce in the developing and the undeveloped economies. With the current setup in the developing countries where users own smart devices and demand access to the internet, but suffer from the poor network infrastructure, there rises the need for alternative network connectivity such as delay tolerant networks (DTNs) and opportunistic networks. Alternative technologies have been used to compensate for the scarceness of the network infrastructure and the network disconnection. In this research, we focus on a subset of the SPS applications; namely, the social-based opportunistic forwarding algorithms that are highly recommended in the domain of areas with challenged network infrastructure coinciding with pervasive mobile usage and high demand for internet access and connectivity. We focus on the challenges facing such algorithms and the drawbacks in performance as relates to efficiency, effectiveness, power awareness, and utilization fairness. From there, we propose and experiment with solutions to improve the performance of opportunistic forwarding algorithms that are much needed in environments which lack network infrastructure or those that are vulnerable to frequent disruptions. These solutions employ bi-directional context from the mobile and social worlds pertaining to user mobility, social interest, power awareness, and contact durations. Four major contributions are proposed in this research. The first and second contributions demonstrate an improvement over existing popular opportunistic forwarding algorithms, such as the People Rank algorithm, the Socialcast algorithm, and the Sensor Context-Aware Routing protocol (SCAR) by integrating interest awareness and power awareness into these algorithms. We propose the PI-SOFA framework as a framework for integrating interest and power awareness into social-aware opportunistic forwarding algorithms as detailed in Chapter 3; PI-SOFA integration implemented versions are described in detail in Chapter 5. We question the accuracy of Space syntax metrics in defining the attraction points in a given urban area and argue that this negatively affects the performance and the accuracy of forwarding decisions. This is the third proposed contribution which is presented in Section 3.2 and its proposed implemented versions are described in detail in Chapter 6. The fourth proposed contribution is proposing dynamic adaptive ranking that dynamically changes the weight of the factors controlling the node\u27s rank based on the current context. Details of the dynamic adaptive ranking are illustrated in Section 3.3, and its implemented versions are described in Chapter 7. All our contributions are empirically evaluated via our proposed simulator SAROS, our fifth contribution, which is presented in detail in Chapter 4. Throughout our research, the simulations conducted with SAROS utilize imported datasets that include both realistic and synthesized mobility traces, social profiles, social relationships, power consumption models, as well as data that are generated by the simulator itself. Detailed description of the used or generated datasets is presented in Section 4.2. The evaluation metrics that are used in the conducted experiments, along with the utilized scientific methodology are also provided. Finally, statistical analysis is conducted to produce the recommended regression model of the six main performance metrics of the dynamic adaptive ranking approach which is detailed in Section 7.7

Social pervasive systems: The harmonization between social networking and pervasive systems

The recent advancement in mobile device sensor technology, coupled with the wealth of structured accessible data of social networks, form a very data-wealthy ecosystem. Such an ecosystem is rich in bi-directional context that can flow between the mobile and social worlds enabling the creation of an elitist breed of pervasive services and applications. We label the breed resulting from the merger as Social Pervasive Systems (SPS). © 2014 IEEE

SAROS: A social-Aware opportunistic forwarding simulator

[abstract not available